Document [original]

Physical influence of microbial

communities on the structure and

occlusion of particulate organic

matter in a sandy agricultural soil

vorgelegt von

Dipl.-Ing.

Frederick Büks

geb. in Berlin

an der Fakultät VI – Planen Bauen Umwelt

der Technischen Universität Berlin

zur Erlangung des akademischen Grades

Doktor der Naturwissenschaften

- Dr. rer. nat. -

genehmigte Dissertation

Promotionsausschuss:

Vorsitzende: Prof. Dr. Eva Paton

Gutachter: Prof. Dr. Martin Kaupenjohann

Gutachterin: Prof. Dr. Liliane Rueß

Gutachter: Prof. Dr. Ulrich Szewzyk

Tag der wissenschaftlichen Aussprache: 3. Mai 2018

Berlin 2018

“Selbst um auf einem Stein zu sitzen – drei Jahre.”

ZEN-WEISHEIT

Table of contents
 List of figures .................................................................................................................... 8
 List of tables ...................................................................................................................... 9
 Abbreviations .................................................................................................................. 11
 Acknowledgements ........................................................................................................ 13
 Abstract ............................................................................................................................ 14
 Zusammenfassung ......................................................................................................... 15
1 General introduction ....................................................................................................... 1
1.1 A short scientific history of aggregate structure and genesis ................................ 1
1.2 Soil aggregation ..................................................................................................... 5
1.2.1 Binding mechanisms within soil aggregates ...................................................................... 5
 Physico-chemical interactions .................................................................................... 5
 Biochemical interactions I: Bacterial extracellular polymeric substances (EPS) ......... 6
 EPS and bacterial habitats ......................................................................................... 9
 Aggregates scaffolded by filamentous microorganisms ............................................ 12
 Biochemical interactions II: Fungal glomalin ............................................................. 13
1.2.2 Carbon occlusion within soil aggregates ......................................................................... 17
2 Measurement of aggregate stability and C occlusion .............................................. 21
2.1 The diversity of methods for aggregate stability measurement .......................... 21
2.2 Measuring aggregate stability by use of ultrasonication ..................................... 23
2.3 Measurement of C occlusion ............................................................................... 26
3 Aim of this work ............................................................................................................ 30
4 Enzymatic biofilm digestion in soil aggregates facilitates the release of particulate 
organic matter by sonication .......................................................................................... 31
4.1 Abstract ................................................................................................................ 31
4.2 Introduction .......................................................................................................... 32
4.3 Materials and methods ........................................................................................ 36
4.3.1 Soil properties and microbial biomass ............................................................................. 36
4.3.2 Detachment scenarios ..................................................................................................... 37
4.3.3 Release of POM carbon .................................................................................................. 39
4.3.4 Release of bacterial DNA ................................................................................................ 40
4.3.5 Statistics ..........................................................................................................................  41
4.4 Results ................................................................................................................. 41
4.4.1 Release of POM carbon .................................................................................................. 41
4.4.2 Release of bacterial DNA ................................................................................................ 43
4.5 Discussion ........................................................................................................... 44
4.6 Conclusions ......................................................................................................... 48
4.7 Acknowledgements ............................................................................................. 49
I

POM occlusion within sandy soil macroaggregates is not affected by feeding and 
motion of the nematode Acrobeloides buetschlii ........................................................ 51
1 Abstract ................................................................................................................ 51
2 Introduction .......................................................................................................... 52
3 Materials and methods ........................................................................................ 54
3.1 Soil sample ...................................................................................................................... 54
3.2 Basal respiration .............................................................................................................. 54
3.3 Preparation of the inoculum ............................................................................................ 55
3.4 Nematode population development ................................................................................. 55
3.5 Measurement of POC release ......................................................................................... 56
3.6 Phospholipid fatty acid (PLFA) extraction and analysis ................................................... 56
3.7 Mercury intrusion ............................................................................................................. 58
3.8 Statistics ..........................................................................................................................  59
4 Results ................................................................................................................. 59
4.1 Soil respiration ................................................................................................................. 59
4.2 Population development .................................................................................................. 60
4.3 POC release .................................................................................................................... 61
4.4 PLFA analysis .................................................................................................................. 62
4.5 Mercury intrusion ............................................................................................................. 64
5 Discussion ........................................................................................................... 64
6 Conclusions ......................................................................................................... 68
7 Acknowledgements ............................................................................................. 68
Two different microbial communities did not cause differences in occlusion of 
particulate organic matter in a sandy agricultural soil ................................................ 69
1 Abstract ................................................................................................................ 69
2 Introduction .......................................................................................................... 70
3 Materials and methods ........................................................................................ 73
3.1 Preparation of soil and soil extracts ................................................................................. 73
3.2 Incubation and sampling ................................................................................................. 74
3.3 DNA extraction and qPCR ............................................................................................... 75
3.4 Disaggregation of soil aggregates and quantification of POC ......................................... 77
3.5 Statistical analyses .......................................................................................................... 77
4 Results ................................................................................................................. 78
4.1 Microbial population analysis .......................................................................................... 78
4.2 POC release .................................................................................................................... 81
5 Discussion ........................................................................................................... 82
6 Conclusions ......................................................................................................... 85
7 Acknowledgements ............................................................................................. 85
Synthesis and conclusions .......................................................................................... 87
1 Single experiments .............................................................................................. 87
2 Statistical restrictions ........................................................................................... 89
3 General conclusion .............................................................................................. 90
4 Transferability to other soils ................................................................................. 92
5 Future research ................................................................................................... 92
 References ....................................................................................................................... 95
II

List of figures

Fig. 1: Idealized binding pattern of hierarchical and non-hierarchical soil aggregates ....... 4

Fig. 2: Extracellular polysaccharides, DNA, proteins and lipids within soils ....................... 8

Fig. 3: A model of soil aggregate structure on different scales ......................................... 16

Fig. 4: Proposed model of inner soil aggregate structure including EPS ......................... 33

Fig. 5: Relative POC release after enzyme treatments ..................................................... 42

Fig. 6: Relative bacterial DNA release from soil aggregates after enzyme treatments .... 43

Fig. 7: Soil respiration of samples with 0, 50, 70 and 80% water holding capacity .......... 60

Fig. 8: Population development of nematodes .................................................................. 61

Fig. 9: Relative POC release of samples with A. buetschlii and controls ......................... 62

Fig. 10: Amount of group specific PLFAs in soil aggregate samples ................................ 63

Fig. 11: Cumulative pore space diagram of macro-aggregate samples ........................... 64

Fig. 12: pF-bioreactor with its components ....................................................................... 74

Fig. 13: DNA conc. of phylogenetic classes and domains in SPsoil and SPair .................... 80

Fig. 14: Relative POC release of the variants SPsoil, SPair, SPcontrol ................................... 82

III

List of tables

Table 1: Collection of frequently used and/or promising methods for aggregate stability

measurement ........................................................................................................23

Table 2: Concentrations and molar masses of biofilm stabilizing macromolecules in

different environments ..........................................................................................35

Table 3: Variables, that are used for the calculation of enzyme units needed for biofilm

target decomposition ............................................................................................38

Table 4: Specific scenario parameters of the enzyme treatments .....................................39

Table 5: List of group specific PLFAs used in the present study .......................................58

Table 6: Target classes and domains, appropriate primer pairs, annealing temperatures

(AT) and standard organisms for qPCR ...............................................................76

Table 7: Applied primer sequences for class- and domain-specific qPCR ........................76

Table 8: Measured eubacterial class DNA of SPair and SPsoil variant in relation (%) to total

eubacterial DNA ....................................................................................................81

Abbreviations

Abbreviation Full term

Å Ångström (0.1 nm)

AMF Arbuscular mycorrhizal fungi

ANOVA One way analysis of variance

ARW Artificial rainwater

C Carbon

COM Colloidal organic matter

CPOM Co-precipitated organic matter

DNA Deoxyribonucleic acid

DOM Dissolved organic matter

eDNA Extracellular DNA

EEG Easily extractable glomalin

EPS Extracellular polymeric substances

Eub Eubacteria(l)

FID Flame ionization detector

fwd Forward (Primer)

GRSF Glomalin related soil fraction

fLF Free light fraction

GC/MS Gas chromatography/mass spectroscopy

GRSP Glomalin related soil protein

HF Heavy fraction

IREEG Immonoreactive easily extractable glomalin

LF light fraction

MOM Mineral-associated organic matter

MWD Mean weight diameter

N Nitrogen

oLF Occluded light fraction

OC Organic carbon

OM Organic matter

PCR Polymerase chain reaction

PDA Potato dextrose agar

PLFA Phospholipid-derived fatty acids

POC Particulate organic carbon

POM Particulate organic matter

qPCR Quantitative real-time PCR

R2A Reasoner's 2A growth medium

rev Reverse (Primer)

rpm Rounds per minute

SOC Soil organic carbon

SOM Soil organic matter

SPT Sodium polytungstate

Su3 Silty sand (Bodenkundliche Kartieranleitung, 2005)

TEM Transmission electron microscopy

U Enzyme unit (conversion of 1 µmol substrate per minute)

UDF Ultrasonication/density fractionation

UV Ultraviolet

WSA Water stable aggregates

Acknowledgements

I am deeply grateful to

•our laboratory assistants Claudia Kuntz, Kotan Yildiz, Maike Mai, Monika Rohrbeck,

Ruth See, Sabine Dumke and Sabine Rautenberg

•Prof. Martin Kaupenjohann, who supervised this work

•Prof. Ulrich Szewcyk for the unbureaucratic possibility to use the laboratories of the

chair of environmental microbiology

•the helpful staff of the chair of soil protection (TU Berlin)

•Prof. Liliane Rueß for her knowledge about nematodes

•Dr. Peter Lentzsch and M.Sc. Philip Rebensburg for their perseverance

•M.Sc. Patrick Reger and B.Sc. Lara Schneider for their theses and our former

students Marcus Bork, Kathrein Fischer, Christine Hellerström, Katja Jung,

Annabelle Kallähne, Paula Nitsch, Susann-Elisabeth Schütze, Anne Timm and

Karolin Woitke for their help in soil sampling, preparation and pre-trials.

•Tom Grassmann for his enthusiasm to explain me how to handle R

•the Leibnitz-Gemeinschaft who financially supported this project (SAW Pact for

Research, SAW-2012-ATB-3)

•and all the people, who have been patient with me talking again and again about

soil aggregates and bacterial slime between primary particles.

They all were responsive and kind to help me each time I had problems or need for

discussion.

Abstract

Soil aggregate stability is an integral marker of soil fertility. Well aggregated soil contributes

to high rootability, a proper water and aeration regime, resistance against compaction and

erosion as well as storage capability of organic carbon. The aggregation of soil primary

particles and microaggregates is promoted not only by a large variety of physico-chemical

but also biological interactions, that are based on e.g. the excretion of bacterial

extracellular polymeric substance (EPS) or fungal glomalin, concretion of biomineralization

products or adsorption of hydrophobic cell debris on soil particle surfaces. Hence,

microbial growth, exudation and grazing of bacterial-feeding organisms on sessile

prokaryotes – most living within a viscouse EPS matrix (biofilms) – are assumed to play a

regulating role in the occlusion of POM within soil aggregates. In consequence, microbial

communities would have physical influence on organic matter cycling e.g. in agricultural

soils.

In the present doctoral thesis, a sandy agricultural soil was treated with EPS degrading

enzymes, the bacterial feeding nematode Acrobeloides buetschlii or two different non-

converging microbial communities. After these treatments, respective changes of POM

occlusive strength were measured.

Results show no or little influence of microbial communities living in pores above the lower

mesopore scale (~10 µm) on the POM occlusive strength, whereas the applied methods

were not suitable to affect organisms within smaller pores. If there is a markable stabilizing

effect of microbial processes, it is located within the finer mesopores as indicated by

current literature. The present work highlighted this indication from a new point of view.

Future research should focus on the role of EPS as an aggregation agent within small

mesopores.

VII

Zusammenfassung

Die Aggregatstabilität in Böden ist ein integrales Merkmal von Bodenfruchtbarkeit. Gut

aggregierter Boden unterstützt Durchwurzelbarkeit, Wasser- und Luftversorgung, die

Widerstandsfähigkeit gegen Verdichtung und Erosion sowie seine Fähigkeit organischen

Kohlenstoff zu speichern. Zur Aggregierung von Primärpartikeln und Mikroaggregaten trägt

eine große Vielfalt nicht nur physico-chemischer sondern auch biologischer

Wechselwirkungen bei, die z.B. auf die Ausscheidung bakterieller extrazellulärer polymerer

Substanzen (EPS) oder pilzlichen Glomalins, auf Biomineralisationsprodukte oder die

Adsorption hydrophober Zellfragmente an Bodenpartikel zurückgehen. Daher kann

angenommen werden, dass mikrobielles Wachstum, Exsudation und die Beweidung

sessiler Prokaryoten, von denen die meisten in einer viskosen EPS-Matrix leben (Biofilm),

einen regulierenden Einfluss auf die Stärke der POM-Okklusion in Bodenaggregaten

haben. Folgerichtig hätten mikrobielle Gemeinschaften einen physikalischen Einfluss auf

den Kohlenstoffkreislauf z.B. in Ackerböden.

In dieser Arbeit wurde sandiger Ackerboden mit EPS-verdauenden Enzymen, der auf

bakteriellen Biofilmen weidenden Nematodenart Acrobeoloides buetschlii sowie

verschiedenen nicht konvergierenden mikrobiellen Gemeinschaften behandelt. Nach der

Inkubation wurde die jeweilige Veränderung der POM-Okklusionsstärke gemessen.

Die Ergebnisse zeigen wenig bis keinen Einfluss der im oberen Mesoporenbereich

(< 10 µm) lebenden microbiellen Gemeinschaften auf die POM-Okklusionsstärke, während

die verwendeten Methoden nicht geeignet waren, Organismen in feineren Poren zu

erreichen. Sofern ein bedeutender stabilisierender Effekt durch mikrobielle Prozesse

existiert, ist dieser im unteren Mesoporenbereich verortet, wie in der aktuellen Literatur

angedeutet wird. Diese Arbeit hebt jenen Effekt aus einem neuen Blickwinkel hervor.

Zukünftige Arbeiten sollten ihren Fokus auf die Rolle von EPS als Aggregierungsmittel im

unteren Mesoporenbereich legen.

VIII

Soil microbial communities and POM occlusion

1 General introduction

1.1 A short scientific history of aggregate

structure and genesis

For nearly 90 years soil structural stability gained attention in research on soil properties.

Early works concerning “soil friability”, “soil consistency” and “soil aggregate stability” were

aimed at a more precise assessment of soil plowability for the enhancement of plant

production (Russell, 1928; Christensen, 1930). In the following decades, soil aggregate

stability attained increasing importance as positive condition for plant growth and

resistance against soil compaction e.g. by large agricultural machinery (Rosenberg, 1964).

In some of the first trials focusing on aggregates, the crushing strength of dry soil

aggregates was determined by Martinson et al. (1950), and Greacen (1960) provided

evidence for increasing plastic deformation in soil aggregates with increasing water

content leading to reduced aggregate stability.

In a cutting-edge work Edwards and Bremner (1967a) postulated, that large soil

aggregates (>250 µm) are composed of smaller aggregates, which again are formed by

mineral and organic primary particles and molecules. With the underlying experiment the

authors could show, that small mechanical stress leads to disaggregation of large soil

aggregates, whereas aggregates <250 µm have a higher structural resistance, which is,

however, reduced by the removal of polyvalent cations and oxidation of water-insoluble

organic substance. Edwards and Bremner (1967a) postulated, that microaggregates are

stabilized by clay-humus interaction and are bricks of less stable macroaggregates. This

hypothesis became the foundation of later works about aggregate stability and structure.

From another point of view, based on a “theory of statistical brittle fracture”, Braunack et al.

(1979) hypothesized a decreasing stability of soil aggregates with increasing volume. If

mechanical stress reaches a critical level, the structure of a soil volume element is no

longer able to deflect forces (e.g. by plastic deformation) and thereupon cracks in its

weakest flaws. As large aggregated soil volumes statistically contain more weak points,

their stability would be reduced compared to smaller volumes. The resulting proportional

Frederick Büks (doctoral thesis 2017)

correlation between aggregate volume and susceptibility to mechanical stress was found

for soils observed in the named study.

The observations support a model of Dexter (1988), that proposes larger aggregates to be

built of interlaced even smaller aggregates down onto the level of primary particles. In this

aggregate hierarchy model aggregates of a higher order do not only contain aggregates of

lower order but also interjacent voids (and flaws) – so to speak smaller aggregates

exclude voids of the higher hierarchy level. This “porosity exclusion principle” was

supposed to lead to a lower stability of aggregates with high porosity (mostly large

aggregates) compared to such with low porosity.

Oades and Waters (1991) fortified the hypothesis of an aggregate hierarchy (Fig. 1) in face

of mechanical stress. They could show, that in one group of soil types successively

enhanced mechanical stress first leads to a fracturation of larger and than finer aggregates

(hierarchical behavior). Surprisingly, another group of soil types – mainly stabilized by

inorganic components (Tisdall, 1996) – shows an increasing fracturation of aggregates of

all size-classes with increasing mechanical stress pointing to an absence of aggregate

hierarchy. In addition, the authors could show differing structural and chemical composition

in differently sized aggregates: In hierarchical soils larger aggregates contain a higher

content of organic matter (OM) and a higher C:N ratio than small aggregates, whereas

non-hierarchical soils do not show any differences between aggregate sizes. Furthermore,

electron microscopic pictures of aggregates <200 µm in diameter show cores of plant

debris, whereas aggregates <90 µm contain increasingly degraded POM or voids instead.

Aggregates <20 µm miss nearly any POM and have a low C:N ratio.

These results motivate a classification into macro-aggregates (>250 µm), micro-

aggregates (<250 µm) and “small” microaggregates (<20 µm) (Tisdall, 1996): Smallest

sub-units <0.2 µm are composed of flocculated clay particles or associations of clay

particles, that are linked to humic substance by polyvalent cations. Those sub-units are

aggregated in association with silt particles, partly humified bacterial debris and bacterial

colonies, hyphal fragments and mineral incrustations. They contain nearly any POM but

molecular organic matter of bacterial origin. Such smaller aggregate structures can be

reasonably summarized to a class of “small” microaggregates <20 µm and are

characterized by a high stability in face of rainfall, tillage and ultrasonication. In contrast,

Soil microbial communities and POM occlusion

microaggregates of diameters between 20 and 250 µm build up another structural class.

They are composed of “small” microaggregates, that are linked and embedded by the

chemical components listed above. But in addition, occlusion of small POM, which has a

lower degree of decomposition than the molecular OM, increases the C:N ratio. These

larger microaggregates are not stable in face of ultrasound. Within these aggregates, the

grade of degradation of POM as well as water stability increase with decreasing aggregate

size. The excretion of macromolecular EPS by inhabiting bacteria is assumed to play a

role in whole microaggregate stabilization (Chenu and Stotzky, 2002).

In most agricultural soils, macroaggregates (>250 µm) consist of microaggregates.

Although physico-chemical interactions play a linking role at the contact points of

contained microaggregates, wrapping by fine roots, fungal hyphae and bacterial

pseudomycelia are supposed to be important for macroaggregate stabilization (Molope et

al., 1987; Six et al., 2004; Chenu and Cosentino, 2011). However, these aggregates are

more water-labile than microaggregates and highly prone to mechanical stress. In

contrast, non-hierarchical aggregates >250 µm react very differently: As Oades and

Waters (1991) found for Oxisols, the whole macroaggregates are stable in face of high

mechanical stress. This can be explained by both a dominance of mineral interactions

(Oades and Waters, 1991) and a statistical lack of porosity exclusion (Dexter, 1988).

Based on data of the chemical composition of hierarchical and non-hierarchical

aggregates (Oades and Waters, 1991), aggregate hierarchy gained a new level of

complexity: Like formally supposed by Edwards and Bremner (1967a) and Dexter (1988),

hierarchy in face of mechanical stress is attended by specific geometric and chemical

properties. In consequence, flaws are not randomly distributed within the aggregate but

theoretically predictable.

As, on the one hand, there is a shared understanding about aggregate structure, two

fundamentally different but not contradictory theories about aggregate genesis are under

consideration. In the first mechanistic model (Tisdall and Oades, 1982), aggregate

formation appears ascending from associations of clay particles, organic matter and

polyvalent cations, that build minor aggregates, interspersed with additional mineral

components and microbial exudates. These secundary particles aggregate to

microaggregates of 20 to 250 µm and finally form macroaggregates. In contrast to

Frederick Büks (doctoral thesis 2017)

microaggregates, which are mainly stabilized by physico-chemical interactions,

macroaggregates stick together by biological entanglement. In the second model (Jastrow,

1996), macroaggregates of mineral and organic primary particles form around an

particulate organic core. The following “consumption” of the macroaggregate, consisting of

microbial decomposition and desintegration of the core and the excretion of metabolic

products, lead to regions of stable physico-chemical bonds between organic and mineral

particles and to the formation of more stable microaggregates within the macroaggregate.

This mechanism was confirmed by Gale et al. (2000). Both the ascending and the

consuming aggregate formation most likely appear together in a dynamic soil system (Six

et al., 2000), as minor microaggregates could take part in macroaggregate formation

around organic cores and consumed macroaggregates dissociate to microaggregates

which in turn could assemble to macroaggregates by means of biotic enmeshment.

Soil microbial communities and POM occlusion

1.2 Soil aggregation

1.2.1 Binding mechanisms within soil aggregates

In conclusion of the previous chapter, most soils have an aggregate hierarchy regarding

destructive stress, which reflects the physico-chemical properties of the soil and hence soil

performance. Soil aggregates are composed of manifold components that influence these

physico-chemical properties. Silicates of the sand, silt and clay fraction, oxides and

hydroxides of Fe, Al and Mn, phosphates and – in (semi)arid soils – carbonates are the

major inorganic constituents (Bronick and Lal, 2005). Beside biological structures like

bacterial colonies, bacterial pseudomycelia, fungal hyphae and roots (Six et al., 2004), the

organic fraction within soil aggregates comprises molecular and precipitated organic

components like humins, cell exudates and decomposed products as well as particulate

organic matter including detritus and black carbon (Bronick and Lal, 2005; Brodowski et

al., 2006a; Lützow et al., 2006). The interaction of these components is supposed to play

different roles on soil aggregation depending on the hierarchical level. A current model of

aggregate geometry based on the following binding mechanisms is pictured in Fig. 3.

Physico-chemical interactions

As suggested by Edwards and Bremner (1967a), aggregation of primary particles is

mediated by organo-mineral interactions: Clay-humus complexes linked by polyvalent

cations are supposed to play a fundamental role in the formation of smallest aggregates

(<20 µm), since after oxidation of organic matter the removal of polyvalent cations leads to

a total dispersion of clay soils. However, there is a broad range of physico-chemical

mechanisms linking primary particles and molecules. Permanent and variable surface

charge of clay minerals, metal oxides and hydroxides as well as variable charge of POM

cause adsorption of charged organic and inorganic fractions. Multivalent cations with small

hydrate shells like Ca2+, Fe3+ and Al3+ increase the aggregate stability by coagulation of

clay mineral particles, whereas low charged small cations with a large shell take effect in

opposite direction. Furthermore, high charged cations mediate bindings between organic

molecules and clay, especially clay-humus complexation, or further negative charged

surfaces like those of metal oxides and hydroxides. Organo-metallic complexes of Fe3+

and Al3+ with DOM precipitate at low pH. Precipitates of slightly soluble minerals like Fe3+

Frederick Büks (doctoral thesis 2017)

and Al3+ hydroxides and Ca2+ phosphates cause cementation of primary particles and

microaggregates due to coating and increase the aggregates' shear resistance. Under

(semi-)arid conditions, readily soluble minerals like calcium or magnesium carbonates

show the same effect. (Bronick and Lal, 2005)

Although found to be an important agent of soil aggregation, humic substance is an

extensive and vague term including a broad range of organic matter coming from highly

different metabolic pathways. Among various SOM from decomposing processes,

macromolecular exudates of bacteria, archaea, fungi and plants play a major role in

aggregate stabilization (Traoré et al., 2000; Chenu and Cosentino, 2011). These exudates

and other biological binding agents are in focus of the following sections.

Biochemical interactions I: Bacterial extracellular polymeric substances (EPS)

Slipping on stones on a river bank, complaining about mucus of a severe cold, marveling

about colorful microbial mats in volcanic hot springs and being pleased about the efficacy

of biological waste water treatment – we are faced to the wide abundance of bacterial

biofilms (Costerton et al., 1995). Bacteria represents approximately 1/3 of the biomass in

soil ecosystems (Foster, 1988). It is supposed, that most of these bacteria live on surfaces,

protected by a matrix of homemade extracellular polymeric substance (EPS), making

these so called biofilms an ubiquitous mode of procaryotic life (Davey and O'toole, 2000).

Using histochemical staining, Foster (1988) showed intra-aggregate bacteria in soil

protected within an EPS capsula. But also archaea, fungi and algae are able to produce

extracellular polymers (Lewin, 1956; Rillig, 2004; Fröls, 2013) and partly live in – also

syntrophic – communities with sessile bacteria (Riding, 2000; Wargo and Hogan, 2006;

Stams and Plugge, 2009).

Prokaryotic biofilms consist of up to 97% water (Zhang et al., 1998; Schmitt and Flemming,

1999; Pal and Paul, 2008). The dry mass is composed of 10 to 50% cell biomass and

50-90% EPS matrix components comprising polysaccarides, extracellular DNA (eDNA),

lipids, proteins, humic and low-molecular substances (Flemming and Wingender, 2010;

More et al., 2014). Especially polysaccharides and eDNA have a large influence on biofilm

viscosity and stability, but also proteins are known as stabilizing agent, while lipids show

hydrophobic interface effects (Flemming and Wingender, 2010).

Soil microbial communities and POM occlusion

Early works describe extracellular macromolecules with focus on capsule or slime

polysacchrides of bacteria (Stacey, 1947; Wilkinson, 1958). As investigated in recent

works, these extracellular polysaccharides comprise 40 to 95% of the EPS dry mass

(Flemming and Wingender, 2001), concentrations of about 169 to 401 µg g-1 dry soil with

high variations between soil types (Redmile-Gordon et al., 2014) and molecular masses

between 0.5x106 and 2x106 Da. They contribute to the viscosity of the moist extracellular

matrix by entanglement and mediate attachment of EPS and cells to surfaces. This effect

is enhanced by polyvalent cations (e.g. Ca2+), which link polysaccharide strands by

bilateral binding to hydroxy groups (-OH). (Flemming and Wingender, 2010)

Similar mechanisms underly the stabilizing effect of extracellular DNA (eDNA) on EPS

matrix viscosity (Flemming and Wingender, 2010; Das et al., 2013; Das et al., 2014).

Extracellular DNA appears both exudated and released from lysed cells, is not

distinguishable from genomic DNA (Das et al., 2013) and has typical contents of 1 to 10%

of the dry EPS matrix (More et al., 2014), molar masses of 7.75x104 to 2.32x107 Da

(DeFlaun et al., 1987) and highly variable concentrations between 0.03 and 200 µg g-1 dry

soil depending on soil type and extraction method (Frostegård et al., 1991; Niemeyer and

Gessler, 2002; Agnelli et al., 2004; Pietramellara et al., 2009).

Extracellular proteins comprise two well known functional classes regarding biofilm

viscosity and structure. (1) Structural proteins provide specific binding sites and build

linkages among macromolecules (e.g. polysaccharides and eDNA) and with surfaces

(Flemming and Wingender, 2010). (2) Extracellular enzymes, on the other hand, work as

agents against other microorganisms, as metabolic enzymes or as instrument for

restructuring the biofilm matrix e.g. when adverse chemical gradients or a lack of nutrients

appeared (Donlan, 2002; Stewart and Franklin, 2008; Flemming and Wingender, 2010). As

it is impossible to extract these functional classes selectively, molecular data – e.g. the

average share of 60% on the EPS dry mass with extrema of 75% (Jahn et al., 1999; More

et al., 2014) and concentrations in different soils of 43 to 163 µg g-1 dry soil (Redmile-

Gordon et al., 2014) – are potentially more widespread than only for extracellular structural

proteins.

Extracellular lipids are mainly biosurfactants and contribute to the attachment and

adhesion of cells to surfaces (Flemming and Wingender, 2010). Actually, lipids are not

Frederick Büks (doctoral thesis 2017)

numbered among macromolecules, since their molecular mass spans 750 to 1500 Da

(Abröll et al., 2008). However, lipids are major constituents of EPS dry mass (10%) (More

et al., 2014), whereas concentration data in soils were not found in the actual literature.

In contrast to polyvalent cations, polysaccharides, eDNA, proteins and lipids, little is known

about the function of humic substances within biofilms (Flemming and Wingender, 2010).

Furthermore, the collected data of extracellular macromolecules are rare (Fig. 2), partly

from non-soil ecosystems, contradictory and highly dependent on the extraction method

(Redmile-Gordon et al., 2014). Therefore they only allow rough estimations about the

abundance of EPS components in soil ecosystems.

The viscose biofilm habitat provides a bunch of protective, genetical and community

services for its inhabitants. In addition to adhesion and cohesion on surfaces, which is in

focus of the present work, manifold other functions are achieved by EPS capsulae. The

supply of a dehydration barrier, storage for organic and inorganic nutrients and an

extended extracellular space for catabolic activity, protection against disinfectants,

Fig. 2: Extracellular polysaccharides, DNA, proteins and lipids in soils with spans of molar masses,

concentrations in soil and shares in dry EPS. Data are yet rare and have to be specified to soil type and

extraction method in future research. (CCL by-nc-sa, Frederick Büks 2017)

Soil microbial communities and POM occlusion

biocides, antibiotics, oxidation stress, UV radiation, grazing organisms and immune

system cells as well as the fostered inter-cell communication, syntrophy and horizontal

gene transfer are just outstanding examples (Flemming and Wingender, 2010).

Mathematical modeling and foregoing investigations showed the biofilm matrix to be an

viscoelastic fluid, that is able to withstand mechanical forces (Klapper et al., 2002). Strong

adhesion of biofilm-occluded bacteria on surfaces in face of mechanical stress was

demonstrated by Böckelmann et al. (2003). As the growing biofilm within the narrow pore

space is connected to surfaces of different particles, interconnection between soil particles

most likely fosters soil aggregation. The direct mechanical contribution of biofilms to

aggregate coherence was shown in laboratory trials with artificial (Czarnes et al., 2000)

and native EPS (Geoghegan and Brian, 1948). However, a general and direct influence of

EPS on soil aggregation and the underlying regulatory processes are controversial. For

example, Martens and Frankenberger Jr (1992) and Tang et al. (2011) found aggregate

stability influenced by bacterial growth, but without direct attribution to microbial

polysaccharide production. Furthermore, the rheological properties of EPS strongly

depend on its chemical composition, which in turn is a result of microbial composition and

environmental conditions (Marty et al., 1992; Béjar et al., 1998; Steinberger and Holden,

2005; Simoes et al., 2007; Ayala-Hernández et al., 2008; Celik et al., 2008). However, in

cases of direct aggregate stabilization due to EPS, fixation of small organic particles within

microaggregates is conceivable. Even coarse POM might be occluded within attached

microaggregates and primary particles, leading to the assumption, that effective influence

of EPS on aggregate formation also have influence on POM occlusion.

EPS and bacterial habitats

Within the soil matrix bacteria appear in preferred habitats. As shown by Hissett and Gray

(1976), a majority of bacteria from sandy soils is located in or on POM with similar

abundances in further soils (Kerek et al., 2002). Kanazawa and Filip (1986) found, that

bacteria are highly abundant in coarse organic particles and the silt and clay fraction

<50 µm. In contrast, Chenu and Stotzky (2002) also reported dense bacterial growth and

attachment even on sand grains, which underpins the bacterial potential to colonize

surfaces of particles with various size and composition. However, Ranjard and Richaume

(2001) reviewed, that the majority of soil bacteria is located in the inner part of soil

Frederick Büks (doctoral thesis 2017)

aggregates, mainly in micropores <9 µm within microaggregates <100 µm in sandy soils

and within microaggregates <20 µm in clayey soils. Within these pores, single cells or

microcolonies normally do not fill the whole porespace to allow gas, water and nutrient

exchange (Foster, 1988). Probably as a result of mechanically induced reshaping of soil

structure, also micropores <1 µm were colonized by bacteria (Foster, 1988). Also Nunan et

al. (2003) analyzed porosity, bacterial population density and distribution in 30 to 40 µm

thin-cuts of cropped topsoil, fallowed topsoil and subsoil of a sandy agricultural soil. The

population density is reduced on the surface of inter-aggregate pores (>30 µm) and rises

towards the inner aggregate with increasing organic nutrient support. In addition to Foster

(1988), the authors found, that a decreasing nutrient support (cropped

topsoil > fallowed topsoil > subsoil) leads to a retreat of bacteria from the aggregate's core.

Higher population densities point to higher rates of growth due to increased nutrition, but

are very low, leading the author to assume a general lack of biofilms within sandy arable

soils. This interpretation could also be gathered from TEM pictures (Foster, 1988), but

strongly conflicts to established suppositions.

Beside surface properties of soil particles and taxonomic properties of the colonizers, the

spatial differentiation of bacterial densities is influenced by different factors as there are

accessibility of water, gradients of oxygen and nutrients as well as grazing pressure. Being

aquatic organisms, bacteria are restricted to saturated pores or water films on particle

surfaces (Chenu and Stotzky, 2002). Saturation is more likely given in smaller pores within

microaggregates than in draining mesopores. On the other hand, diffusion of nutrients and

metabolites is decreasing with pore size diameter, leading to low nutrient supply and

metabolite removal and hence decreased microbial growth rates within microaggregates

compared to larger mesopores (Chenu et al., 2001). Furthermore, within small pores

bacteria are protected against grazing. Predators such as large protozoa and grazers like

certain soil Nematodes are restricted to accessible pore space (Wallace, 1958), whereas

small predators such as amoebae, flagellates and small ciliates are able to enter the inner

pore space of soil aggregates (Vargas and Hattori, 1991). In consequence, bacterial-

feeding protozoa mediate a nutrient flow from the inner pore space to larger predators

(Bonkowski, 2004). In addition to spatial inaccessibility and EPS encapsulation, Hattori

(1970) showed strong adhesion of clay particles on E. coli in laboratory cultures. Thus,

Soil microbial communities and POM occlusion

bacterial cells and microcolonies can be surrounded by a coating of clay particles that

hinders predation and grazing (Chenu, 1995).

In consequence, soil bacteria basically show two different ways of interaction with

predators and grazers, which explain higher bacterial densities in microaggregates: (1) A

life in small pores around 10 µm within soil microaggregates, protected against drought

and feeding by spatial exclusion, clay-coating, EPS and taxonomic inedibility, but limited

by low diffusion of nutrients and metabolic products and therefore slowly growing in

established mature and stable biofilms. And (2) a life in larger pores, on surfaces of

aggregates and non-aggregated particles, with sufficient nutrient supply, able to dispose

metabolic waste, but highly susceptible to grazing, what results in high growth rates and

young biofilms (Chenu et al., 2001).

The composition of bacterial communities in different soil compartments is often analyzed

by use of ecotyping, performed with quantitative real-time PCR (qPCR). The taxonomic

level of class/phylum is assumed to be sufficient to depict changes of relevant ecological

processes and qualities in the soil, e.g. SOM cycling. (Von Mering et al., 2007; Fraser et

al., 2009; Philippot et al., 2010; Rousk et al., 2010)

Of known bacterial phyla, Gemmatimonadetes, Actinobacteria and Verrucomicrobia are

found to be mainly present in inner micro-aggregates (Kanazawa and Filip, 1986;

Drążkiewicz, 1994; Ranjard and Richaume, 2001; Mummey and Stahl, 2004; Mummey et

al., 2006). Other data show that Actinobacteria are also abundant or preferentially live in

outer parts of soil aggregates or on coarse organic particles (Kanazawa and Filip, 1986;

Drążkiewicz, 1994; Ranjard and Richaume, 2001; Mummey et al., 2006). Depending on

soil type, representatives of Firmicutes and Proteobacteria (e.g. α- and γ-Proteobacteria)

are suggested to prefer settling at the border between micro- and macroaggregates – just

like Cyanobacteria – or within the inner microaggregates (Ranjard and Richaume, 2001;

Mummey and Stahl, 2004; Mummey et al., 2006). Nitrifyers – taken as a metabolic but not

a taxoniomic group – are mainly found in the <20 µm fraction, but are hardly present in

macroaggregates (Lensi et al., 1995; Ranjard and Richaume, 2001), whereas Drążkiewicz

(1994) also found them to be abundant in macroaggregates. In contrast, Acidobacteria are

enriched within macroaggregates with decreasing abundance towards inner

microaggregates. This leads to the assumption, that they are loosely attached and play a

Frederick Büks (doctoral thesis 2017)

minor role in aggregate stabilization. Data on Bacteroidetes and Chloroflexi were too

sparse for evaluation (Mummey et al., 2006) and data on the distribution of other bacterial

phyla (Tenericutes, Chlorobi, Fusobacteria, Nitrospirae, Spirochaetes, Synergistetes,

Chrysiogenetes, Deferribacteres) as well as Archaea were not found. Furthermore, the

transfer of these single-moment results to the assessment of field trials has to be done

carefully, since the distribution of bacteria in soil is not static but changing with

environmental conditions (Fierer et al., 2003; Griffiths et al., 2003). However, due to a lack

of sufficient data about specific taxa and soil types, the relation of certain taxa to soil

aggregation processes and levels of the aggregate hierarchy is not sufficiently understood.

Aggregates scaffolded by filamentous microorganisms

On the macroaggregate scale, fine roots and hyphae grow into accessible pores and

thereby wrap microaggregates and primary particles. Both types of filaments produce a

coating of macromolecular exudates and cell wall components, e.g. polysaccharides, that

establish sticky links to the surfaces of adjacent particles. As a result, microaggregates

and primary particles are interconnected to macroaggregates by a sticky string bag of

roots and hyphae. The attachment of fine particles and precipitates cause an incrustation

of this bag. As physico-chemical links between microaggregates are weaker than such

within, this filamentous network significantly provides the formation of water-stable

macroaggregates and, in turn, disturbance of fungi and roots by tillage or chemical agents,

e.g. pesticides, lowers macroaggregate stability (Bossuyt et al., 2001).

As an additional mechanism, the growth-related pressure of hyphae and roots supports

aggregation of soil particles by relocation and compaction. Furthermore, especially

arbuscular mycorrhizal fungi (AMF) positively influence aggregation not only directly, but

also provides root growth due to fungi-plant symbioses (Miller and Jastrow, 1990). In

addition, fine roots and hyphae take up water and dry the adjacent soil, which enhance the

mechanical stability of soil aggregates. (Tisdall, 1996)

Compared to fungi, filamentous bacteria have 10-fold smaller hyphal diameters, but also

connect soil particles (Tiessen and Stewart, 1988). Actinobacteria are suggested to play a

role in microaggregate formation (Mummey et al., 2006). However, their influence on

aggregate stability and POM occlusion is unknown.

Soil microbial communities and POM occlusion

Biochemical interactions II: Fungal glomalin

In the last two decades, a macromolecular substance of fungal origin became a focus of

research on soil structure. This substance, Glomalin related soil protein (GRSP),

comprises a group of highly hydrophobic, strongly adhering and persistent glycoproteins

primarily produced by AMF (Wright et al., 1996; Rillig, 2004). Originally isolated as a target

of monoclonal antibodies for immunofluorescence detection of specific growing AMF

hyphae on roots (Wright et al., 1996), it shaped up as an only operationally defined group

of proteinaceous soil organic matter, that is coextracted with large excess of humic acids

(Schindler et al., 2007). A lack of knowledge about the relation of GRSP components and

functions recommends a broader denotation, e.g. glomalin related soil fraction (GRSF)

(Rillig, 2004).

The GRSF is suspected to play a role in soil aggregation. In an experimental study on a

variety of 37 soils across the United States and Scotland, Wright and Upadhyaya (1998)

demonstrated a correlation of glomalin concentration and stability of soil aggregates, that

saturates at >80% water stable aggregates (WSA). This relation was confirmed by other

surveys in different climate zones (Rillig et al., 2002; Bedini et al., 2009; Hontoria et al.,

2009; Spohn and Giani, 2010; Fokom et al., 2012; Wu et al., 2014). Furthermore, in a

comparison of different crop rotation systems, Wright et al. (1999), Wright and Anderson

(2000) and Fokom et al. (2012) found linear correlation between glomalin and aggregate

stability as well as a positive effect of non-tillage management on aggregate stability

compared to classical tillage. Wright et al. (2007) showed that the major part of GRSF in a

non-tillage agricultural ultisol is concentrated in the macro-aggregate fraction, whereas

treated soils contain most of their GRSF in the microaggregate and fine fraction. It was

also demonstrated that tillage decreases GRSF concentration in macro-, microaggregates

and fine material of agricultural ultisols compared with untreated soils (Wright et al., 2007).

This implies a correlation depending on agricultural practice. Deviating from that, in

samples of arid sandy/silty loam with stability mainly caused by high carbonate contents of

average 71%, positive correlation between glomalin and aggregate stability could not be

observed (Rillig et al., 2003).

These results imply that glomalin is preferentially accumulated in intact macro-aggregates

and AMF glomalin productivity is somehow related to aggregate stability. That could reveal

Frederick Büks (doctoral thesis 2017)

glomalin as a proxy but not necessarily as an agent of soil aggregation. Likewise

undisturbed fungal hyphae systems could produce more glomalin than those in tilled soils,

while merely stabilizing soil aggregates physically by entanglement and enmeshment

(Miller and Jastrow, 2000).

Results of Driver et al. (2005) showing >80% of GRSF (1.4 µg mg-1 mycelium) tightly

bound within the hyphal cell wall confirm glomalin as not being exudated, but rather being

integral part of AMF cell walls. Yet unexplored, its local function could encompass easing

of hyphal surface binding by increased hydrophobicity, decreased digestibility in face of

grazers or accumulation of cations (Gonzalez-Chavez et al., 2004; Driver et al., 2005).

Glomalin distribution in the soil matrix mainly appears by hyphal decay producing

fragments of approximately <5 µm (Wright and Upadhyaya, 1998). With given

concentrations of only 0.03 to 0.5 mg extraradical hyphae g-1 soil and hyphal average

turnover time of 5 to 7 days in pot experiments and laboratory cultures (Friese and Allen,

1991; Staddon et al., 2003; Zhu and Miller, 2003), GRSF concentrations of 1 to

21 mg g-1 soil amounting 3 to 10-fold the hot water extractable soil carbohydrates can only

be explained by high persistence and accumulation within the soil matrix (Wright et al.,

1996; Wright and Upadhyaya, 1998; Steinberg and Rillig, 2003; Zhu and Miller, 2003).

Although interactions of hydrophobic SOC with the soil matrix are expected to enhance

aggregate stability (Piccolo and Mbagwu, 1999), high aromatic and carboxyl as well as low

aliphatic group concentration measured by (Schindler et al., 2007) challenge the position

of glomalin as a hydrophobic substance. However, attached to hydrophobic chitin cell wall

fragments it could be immobilized and somehow act as hydrophobic aggregant.

Hydrophobe chitin-glomalin traces on particle surfaces could therefore support soil

aggregation by decreasing soil wettability and, in consequence, decrease decomposability

of organic surfaces, enhance aeration and cell attachment and provide sticking between

surfaces (Wright and Upadhyaya, 1998).

Previous results provide informations about the distribution of GRSF within soil

aggregates: The smaller proportion is located in AMF cell walls possibly playing a role in

hyphae-soil particle interaction (Driver et al., 2005). A distinctly higher concentration is

found in the soil matrix as a recalcitrant remain of hyphal turnover (Wright and Upadhyaya,

Soil microbial communities and POM occlusion

1998). Whether the latter is located around actual and former hyphal positions or evenly

distributed within the meso- and macropores of macro-aggregates is still unbeknown.

However, whereas GRSP is assumed to be hydrophobic and probably immobile, hyphal

wall fragments could be mobile or change their position relative to aggregate surfaces by

long-term reorganization of soil aggregates. In this case, an increasing equality of

distribution within the macro-aggregate can be assumed with increasing sequestration

time. After destructive soil treatment, GRSF is necessarily found in the micro-aggregate

fraction. Should the agglutinative effect of glomalin be proved, this pattern could elucidate

the high correlation of GRSF concentration and macroaggregate stability.

Frederick Büks (doctoral thesis 2017)

Soil microbial communities and POM occlusion

1.2.2 Carbon occlusion within soil aggregates

Nearly 1,500 Gt of organic carbon are stored in the first meter of global soils, which is

twice the atmospheric carbon stock (Lal, 2008a; Stockmann et al., 2013). Owing to this

enormous pool, the knowledge of decomposition and turnover rates of SOC is essential for

future predictions about the atmospheric CO2 content and SOC loss in consequence of

degradation due to land use or climate change.

The turnover rates of organic matter are strongly influenced by its stability in face of

chemical and biological decomposition (Schmidt et al., 2011). Although there are obvious

differences in the metabolization rate of different SOM under normalized conditions (e.g.

glucose versus lignin), fast decomposition of recalcitrant (Knežević et al., 2013) and

persistence of easily decomposable organic matter (Sollins et al., 1996) show that

degradability is not only an inherent factor of matter, but also depends on environmental

conditions like the metabolic capability of the grasping microbial populations (McGuire and

Treseder, 2010) or protection within the soil matrix (Six et al., 2002).

Soil aggregates contain approximately 90% of the total SOC, and up to 40% are located in

microaggregates (Lützow et al., 2007). Beside inherent recalcitrance of SOM, two

mechanisms are assumed to control the stabilization of SOM within the soil matrix: (1)

Molecular SOM is protected against microbial decomposition by the adsorption to charged

surfaces of silt and clay particles. (2) The occlusion within soil aggregates protects

particulate and molecular SOM against decomposition due to physical inaccessibility as

well as hindrance of nutrient and waste diffusion, which reduces microbial metabolic

activity. (Six et al., 2002)

The tremendous number of feedstocks and degradative pathways causes manifold soil

organic final and interstage products. However, physical pools of organic carbon - less

complex than chemical classifications – comprise carbon from particulate organic matter

(POM), dissolved organic matter (DOM), mineral-organic associations (MOM) as well as

the minor researched fractions of co-precipitated organic matter (CPOM) and colloidal

organic matter (COM). These physical carbon pools represent different functions in the soil

ecosystem. Particulate organic matter mainly originates from above and belowground

plant debris and further fungal and animal fragments (Blume et al., 2015). It provides

Frederick Büks (doctoral thesis 2017)

surface for microbial colonization, nutrient source and structural function in soils (Bronick

and Lal, 2005). Molecular organic matter, which appears dissolved or adsorbed on

surfaces, is produced by bacteria, archaea, fungi and plants and enters the soil matrix via

exudation, cell break down, external input or extracellular enzymatic decomposition. It

appears to be an in part mobile microbial nutrient source (Marschner and Kalbitz, 2003),

but bound in mineral-organic complexes it shows reduced biodegradability and enhanced

contribution to soil microaggregation (Tisdall, 1996; Six et al., 2002; Edwards and

Bremner, 1967a). In addition, little is known about the appearance and behavior of

colloidal organic matter like bacterial cell wall debris, which is assumed to influence

hydrophobicity of soil mineral particles (Achtenhagen et al., 2015), and organic matter,

which is occluded within precipitated minerals (Eusterhues et al., 2008). These last two

classes are therefore excluded from further discussion in the present work.

Total SOM can be further subdivided into different C pools by means of its persistence,

which are linked to physical C pools (von Lützow et al., 2008): The active pool comprises

non-occluded residues, microbial biomass and other free SOM with turnover times

<10 years. The intermediate pool includes imperfectly decomposed POM from plant

residues and is protected by the occlusion within soil aggregates with turnover times of 10

to 100 years. Finally, the passive SOM pool mainly comprises decomposed molecular OM

strongly adsorbed to mineral surfaces and charred POM, which are thus protected for a

span extrapolated to >100 years.

The underlying model, that links persistence of different physical C pools and their status

within the soil matrix was supposed with varying accentuation by different authors and

includes different mechanisms of chemical longevity and protection (von Lützow et al.,

2008; Schrumpf et al., 2013; Lehmann and Kleber, 2015): Decomposition of plant and

animal residues result in a wide range of molecules with low to high molar masses as well

as POM, that have different decomposabilities depending on molecular structure and

surrounding microbial metabolisms, but no inherent, static recalcitrance. Stepwise

degradation towards smaller biopolymers, monomers and final mineralization – with

reaction constants depending on the type of matter and biochemical steps to total

decomposition – leads to a steady state equilibrium between more and less persistent

organic matter. The equilibrium is shifted towards longevity by the adsorption of both

Soil microbial communities and POM occlusion

particles and molecules of any size to mineral surfaces and occlusion within soil

aggregates. However, this protection is enhanced with decreasing particle and molecule

size, resulting in a high longevity of SOM in occluded mineral-organic associations.

Following Kalbitz et al. (2005), organo-mineral association is – next to occlusion within soil

aggregates – the main protection mechanism against mineralization.

The persistence of organic matter from different functional pools is linked to specific

properties: High C:N ratios of 30.9±11.9 and 32.1±15.5 are related to free and occluded

particulate plant debris, respectively (Wagai et al., 2009; Cerli et al., 2012), whereas a low

C:N ratio of 13.5±4.6 found on the soil mineral matrix is more similar to C:N ratios around

9 related to microbial biomass (Cleveland and Liptzin, 2007; Wagai et al., 2009). In

consequence, a low C:N ratio indicates OM that is metabolized by fungi, bacteria or

archaea (OM of autotrophic prokaryotes excluded). Wagai et al. (2009) reviewed that the

C:N ratio of POM is positively related to the particle size and microbial activity as well as

negatively related to the grade of mineral coating, which underpins both an increased

degree of microbial decomposition of smaller particles and the protective function of

occlusion. High concentrations of carbohydrates represent both a very early state of

degradation of plant and animal debris as well as extensive storage of microbial

metabolites after OM decomposition (Poirier et al., 2005). This bipolarity can be solved by

analysis of polymerized monosaccharides: A decrease in the ratio of xylose (a mainly plant

derived sugar) to mannose (mainly microbial) indicates a microbial origin of OM (Oades,

1984). Likewise, increased aliphaticity points to increased degradation of SOM (Wagai et

al., 2009).

In conclusion, type and degree of SOM protection within soil aggregates are important

criteria for SOC storage and cycling. As particulate debris is the most important SOM feed,

the occlusion of POM as a first step of protection in an early stage of decomposition is an

important marker of turnover rates and C storage in soils.

Frederick Büks (doctoral thesis 2017)

Soil microbial communities and POM occlusion

2 Measurement of aggregate stability

and C occlusion

2.1 The diversity of methods for aggregate

stability measurement

Earliest measurements of soil aggregation were largely performed using standardized dry-

and wet-sieving procedures (Yoder, 1936; Chepil and Bisal, 1943), which were frequently

adapted for the analysis of aggregate stability (Bissonnais, 1996; Wright and Upadhyaya,

1998; Seybold and Herrick, 2001). The underlying rationale of aggregate stability

measurement is to apply a distinct level of mechanical stress to a soil sample by shaking

in a sieve. The stress leads to disconnection of particles within the soil aggregate, that

depends on the strength of intra-aggregate binding forces. Weakly aggregated soils suffer

more reduction in secondary particle size, measured as mesh aperture, than stronger

aggregates. (Kemper and Rosenau, 1986)

Newer methods including water-dropping and ultrasonication share this principle of using

disaggregating forces (Farres and Cousen, 1985; Edwards and Bremner, 1967a).

However, both sieving and more recent methods require reference values to derive

aggregate stability from the post-treatment aggregation, e.g. the pre-treatment state, a

reference sample of a different or differently treated soil or the exact amount of applied

energy. Some frequently used and/or promising methods shall be shortly described in the

following (Table 1).

Dry-sieving in rotary sieves (Chepil and Bisal, 1943) and stacked sieves (Singh, 1952) is a

simple time- and material-saving method, which is used to date (Zhang, 1994; Rajaram

and Erbach, 1999). The human factor, which e.g. affects constant mechanical stress

generation, can be avoided by using machined sieving, but some important disadvantages

remain: The lab worker is not able to distinguish water-stable from water-labile aggregates,

which form during air-drying and increase the content of coarser aggregates (Beare and

Bruce, 1993). In addition, the analysis of fresh soil is restricted to lower water content to

avoid luting within the sieve. Furthermore, aggregate stability negatively correlates with

Frederick Büks (doctoral thesis 2017)

water content (Francis and Cruse, 1983; Beare and Bruce, 1993). Hence, compared to air-

dried aggregates fresh ones are reduced in their stability, and the reduced stability span

between stable and labile aggregates could therefore reduce the resolution of dispersion

measurement.

In contrast to dry-sieving, wet-sieving is conducted submerged. Although varying in mesh

size, number of sieves, amount of soil as well as movement axis, range and speed of

shaking (Kemper and Rosenau, 1986; Seybold and Herrick, 2001), all wet-sieving

procedures base on a scheme described by Yoder (1936). However, different re-wetting

methods affect the aggregate size distributions after wet-sieving (Beare and Bruce, 1993).

Some dry- and wet-sieving procedures are proposed by Kemper and Rosenau (1986),

Nimmo and Perkins (2002) and standardized in DIN/ISO (2002).

Alternatives to wet-sieving mainly used in early trials are the disaggregation by end-over-

end shaking (Oades and Waters, 1991) as well as the elutriation of soil aggregates within

a shaking tube and the further determination of aggregate sizes on the basis of

sedimentation layers and sedimentation time (Baver and Rhoades, 1932). Although this

method is simple, it provides dysfunctionality e.g. in face of fast-depositing particles

coarser than silt-size and is blind for differences in the bulk density of different aggregates.

However, it is functional for analyzing the disaggregation of microaggregates (Oades and

Waters, 1991).

Another class of methods comprises water-dropping on single soil aggregates in an

apparatus (Farres and Cousen, 1985) and artificial raining on soil beds (Barthes and

Roose, 2002) with measurement of the dispersive effects. Thereby, the quantification of

the applied energy was tried by integrating the kinetic energy of water drops with known

mass and height of fall (Marshall and Quirk, 1950).

The rupture-threshold approach, applied to single soil aggregates by Perfect and Kay

(1994), uses two parallel plates to provide a defined compression force to the interjacent

aggregate. This method allows to derive single aggregate stability from deformation up to

the point of rupture.

Strongly differing from methods involving mechanical stress is the estimation of aggregate

stability by means of a substance, which strongly correlates with aggregate stability in its

Soil microbial communities and POM occlusion

concentration. Wright and Upadhyaya (1998) found a correlation to aggregate stability

measured by mean weight diameter after wet-sieving for (freshly produced)

immonoreactive easily extractable glomalin (IREEG) and also easily extractable glomalin

(EEG) after autoclavation with 50 mM sodium citrate solution. Further experiments confirm

this relation (Wright et al., 1999; Wright and Anderson, 2000; Rillig et al., 2002; Wu et al.,

2014). Although this finding is not matured to a serviceable method, it has potential to be

used in qualitative comparison studies. However, it is most probably restricted to soils

getting their stability from organic compounds.

Table 1: Collection of frequently used and/or promising methods for aggregate stability measurement.

Method Restrictions Quantitative Exemplary reference

dry-sieving

(rotary sieves) no dist. between water-labile and -stabile

aggregates; restricted to lower water

content; susceptible to water content;

particles > silt size

no Chepil and Bisal (1943)

dry-sieving

(stacked sieves) no Singh (1952)

wet-sieving particles > silt size no Kemper and Rosenau (1986)

elutriation particles ≤ silt size no Baver and Rhoades (1932)

water-dropping applicable to single aggregates and

aggregates on surfaces yes Farres and Cousen (1985)

rupture-threshold

approach single or spatially separated aggregates yes Perfect and Kay (1994)

sonication needs calibration per each soil; needs

subsequent classification yes Edwards and Bremner (1967b)

glomalin only in soils with aggregate stability

dominated by organic agents no not yet applied

However, another currently preferred method for the mechanical disaggregation of soil

aggregates is the ultrasonication.

2.2 Measuring aggregate stability by use of

ultrasonication

Ultrasonication is a widely used method for the disaggregation of soil samples (Oades and

Waters, 1991; Lehtinen et al., 2014; Edwards and Bremner, 1967a). In the common

procedure (Kaiser and Berhe, 2014; Edwards and Bremner, 1967b), a pieco-electric

Frederick Büks (doctoral thesis 2017)

converter uses electric energy to generate axial vibration of a sonotrode, that is dipped into

a flask containing a submerged soil sample. The oscillating sonotrode emits shock-waves

within the aqueous medium. In front of the wave the medium is compressed, and the

increased pressure causes an increased gas solubility. Behind the wave the medium

relaxes below the normal pressure conditions leading to an explosive outgassing. This so

called cavitation effect produces lots of exploding micro-bubbles within the soil matrix

generating local pressure peaks of 200 to 500 atm accompanied by 4200 to 5000 K (Ince

et al., 2001), that provoke detachment of bondings within soil aggregates. Depending on

device type and settings, the vibration frequency can vary up to 10,000 kHz, but it is

recommended to use low frequencies around 20-100 kHz for soil aggregate dispersion

without influencing chemical composition of OM (Kaiser and Berhe, 2014).

In contrast to the methods mentioned above, ultrasonication allows semi-quantification of

aggregate stability without a reference sample, if the power output of the sonotrode (P) is

known. Its quantification take place by heating a known amount of water (mH20) in a Dewar

vessel with application of ultrasound for a certain time (t), represented by equation (1).

P=(mH20·cH20+CDewar)·ΔT

t+H

(1)

The increase in temperature (ΔT) is proportional to the heating time. As the Dewar vessel

is nearly thermally isolated (enthalpy flux H≈0) (North, 1976), has a heat capacity

CDewar<<(mH20·cH20) and the specific heat capacity of water is nearly constant between 298

and 318 K, equation (1) can be simplified to equation (2).

P=(mH20·cH20)·ΔT

(2)

However, in case of sonifying soils, this equation only describes the energy transmission to

the bulk of aqueous solution and soil, but not the ratio of heating the water, heating the soil

and stressing the soil by mechanical cavitation forces. This leads to an overestimation of

binding forces within the soil aggregates, when applied energy is claimed to work

Soil microbial communities and POM occlusion

completely cavitational. To reduce this overestimation, the specific dispersive power output

has to be distinguished from heating energy. If the same calibration is performed with an

additional amount of soil (ms) with a specific heat capacity (cs), the amount of dispersive

power (ms·L) is marked by a reduction in the heating rate of the solution and described by

equation (3).

P=(mH20·cH20+CDewar)·ΔT

t+ms·cs·ΔT

t+ms·L

t+H

(3)

As the specific heat capacity of the soil is also negligible (ms·cs <<mH20·cH20), the equation

can be simplified in accordance to equation (2) to

P=(mH20·cH20)·ΔT

t+ms·L

(4).

The ΔP between equations (2) and (4) relates to the effectively used cavitational energy.

Using this second calibration, a full-qualitative measurement of mechanical forces applied

to the soil matrix is possible (North, 1976). However, measurement of binding forces within

the soil aggregates remain semi-quantitative, as it is impossible to distinguish micro-

explosions treating particle links or surfaces.

Knowing the effective cavitational power, defined amounts of energy can be applied to soil

samples and the percentage of weight fraction smaller than a specific mean weight

diameter (MWD) can be plotted as a function of the applied energy, whereby steeper

gradients represent less stable soil aggregates (North, 1976). As cavitation bubbles have

diameters of maximum 100 µm (Crum, 1995) and expand in even the smallest soil pores,

ultrasonication is suitable for the disaggregation of both micro- and macroaggregates with

a broad span of stabilities. The resulting size-class distribution after treatment can be

determined e.g. by sieving and elutriation. In contrast to different wet-sieving methods,

using this method Graf-Rosenfellner (unpublished data) showed no significant differences

in disaggregation between different sonotrode types, which is known to be more effective

than a sonication bath (Edwards and Bremner, 1967a).

Frederick Büks (doctoral thesis 2017)

2.3 Measurement of C occlusion

Effective methods for the measurment of SOC functional pools comprise those of physical

fractionation by means of particle size or density as well as chemical extraction and

decomposition methods (Lützow et al., 2007). The present work focus on ultrasonication

with a subsequent density fractionation (UDF) to separate particulate non-occluded and

occluded as well as mineral-organic associated SOM.

The UDF is a frequently used method to analyze these soil carbon pools (Golchin et al.,

1994). For this purpose, soil samples are added to water or denser aqueous liquids to

perform floating of unbound organic matter, whereby centrifugation is used to accelerate

and improve the fractionation. Sodium polytungstate solution as a non-polluting, non-toxic

and reusable liquid facilitating a wide range of density cut-offs (1.0 to 3.1 g cm-³) is often

used for this separation (Six et al., 1999). The floating matter, that is separated without

mechanical destruction of aggregates, is operationally named free light fraction (fLF). The

sampling of fLF is followed by ultrasonication of the remaining soil leading to a

detachment, subsequent floating and separation of aggregate-occluded POM (oLF).

Repeating this procedure with constant or increasing energy leads to separation of organic

matter with increasing bonding strength to the mineral matrix. The OM remaining within the

sedimented after separation of all particulate organic matter is named the heavy fraction

(HF) and comprises mineral-associated organic matter. (Kaiser and Berhe, 2014)

The underlying method invented by Golchin et al. (1994) is used as a blue-print for diverse

surveys regarding e.g. organic carbon storage and SOM turnover (Baisden et al., 2002;

Crow et al., 2007), influence of land-use on carbon stocks (Tiessen and Stewart, 1983;

Meyer et al., 2012), carbon indicative or functional studies (Leifeld and Kögel-Knabner,

2005; Lützow et al., 2007) or further analyses of organo-mineral associations (Basile-

Doelsch et al., 2007). Those examinations often varied methodologically in the chosen

density cut-off, dispersion intensity, soil/liquid ratio, immersion depth of the sonotrode's tip

and other parameters and therefore lack comparability, as e.g. liquids of different densities

provide largely different fractionation of POM.

Soil microbial communities and POM occlusion

As UDF often plays a major role in studies about the ecological functionality of SOM

fractions, standardized parameters have to be chosen in a way, that operational fractions

match the functional C pools as accurate as possible:

In a first attempt to standardize this method for a wide range of soils, Cerli et al. (2012)

recommended a density cut-off of 1.6 g cm-³ even for the treatment of weakly aggregated

soils with low C content. SPT concentration <1.6 g cm-³ resulted in a decrease of OM in

the fLF, whereas concentrations >1.6 g cm-³ caused a sharp increase of the mineral

content. That characterizes ρ=1.6 g cm-³ as the cut-off avoiding both incomplete floating of

unbounded OM and contamination by OM from other functional pools, e.g. organic-mineral

associations.

However, in contrast to a density cut-off, a general energetic dispersion cut-off (J ml-1) for

the total dispersion of soil aggregates could not be specified as it strongly depends on the

soil type. This cut-off is theoretically bounded below by insufficient release of oLF and

above by disruption and floating of organic-mineral associations from the HF. Kaiser and

Berhe (2014) reviewed 15 studies using ultrasonication of soil aggregates in terms of

energy level for total dispersion of soil aggregates and avoidance of primary particle

destruction. They found destruction of POM at applied energy levels >60 J ml-1, destruction

of sand-sized primary particles at >710 J ml-1 and of coarse silt-size particles at

>1500 J ml-1, whereas clay-sized primary particles gain damage at energy levels

>12.000 J ml-1. The over-application of ultrasound not only causes rupture of mineral and

organic matter, but also chemical transformation of OM due to very local heat and

pressure peaks (Ince et al., 2001). These peaks result in ●OH and ●H reactions leading to a

decrease in amount, molar mass and aliphaticity of OM. This mechanism mainly

influences more volatile OM, whereas a change in chemical composition of mineral-

associated organic matter was not found (Kaiser and Berhe, 2014).

Based on these findings it is recommended to prove every examined soil in pre-trials with

increasing dispersion energy for the point of depletion of oLF to distinguish between

occluded POM and mineral-associated OM. Only in best cases these do not overlap with

the disruption of parts of the soil matrix (Cerli et al., 2012). This results in a trade-off

between complete extraction of oLF-POM and the avoidance of an intermixture of

functional C pools by destruction and redistribution of soil primary particles. As a reaction

Frederick Büks (doctoral thesis 2017)

to this trade-off, e.g. Kaiser and Berhe (2014) recommended a treatment to reduce those

artefacts, that uses stepwise ultrasonication with a cumulated energy density of 1000 J ml-1

at <40°C and low frequency ultrasound (20 to 100 kHz).

Beside these standardization problems, UDF exhibit some fundamental problems

regarding the identity of operational and functional C pools and the representation of the

latter by binding patterns and decomposition state. In a comparative study of 36 soils with

different vegetation and site characteristics, Wagai et al. (2009) found an oLF C:N ratio

increased compared to the fLF, which contradicts to the theory of occlusion accompanied

by biotic degradation. This is explained e.g. by the distribution of recalcitrant POM like

biochar particles, spores and pollen to both the fLF and the oLF. As ultrasonication is also

used to detach bacterial cells from surfaces (Böckelmann et al., 2003), it is further

possible, that the C:N ratio of the oLF is an artefact, as it is increased by the removal of

bacterial biomass, whereas mineral-associated OM of the HF is not affected by this

method.

Furthermore, Wagai et al. (2009) suggest, that also the surface/volume ratio of the POM

determines the classification as fLF or oLF: Small POM with a mineral coating could have

a bulk density of >1.6 g cm-³ rather than larger particles with a coating of the same material

and exemplary thickness. Thus, a sharp separation of both the fresh POM and the

colonized plus degraded POM is not possible due to an intermixture between fLF and oLF.

Soil dispersion using UDF is also affected by SPT. As sodium acts as dispersive agent on

negatively charged surfaces, dispersion efficacy depends on soil mineral composition and

decrease comparability of different soil types.

Anyway, the use of 1.6 g cm-³ and an appropriate dispersion cut-off allows a rough

separation of functional carbon pools along the bulk light and heavy fraction and a less

precise separation of free and occluded light fractions. Making a complete C balance of

functional pools does not only require a predetermined dispersion cut-off, but also the

measurement of water/SPT solution-extractable DOM when extracting the fLF (Kaiser and

Berhe, 2014). Furthermore, a standardized pre-treatment has to be used, as e.g. drying

and further pre-treatment steps shift the OC content from oLF to fLF compared to field-

fresh soil aggregates (Kölbl et al., 2005).

Soil microbial communities and POM occlusion

In contrast, the analysis of POM occlusive strength of one soil type after different

treatments can be executed by use of an arbitrary dispersion cut-off. Differing POM

release as reaction on mechanical stress can be interpreted as a change in occlusive

strength, but the explanatory power about functional pools is thereby omitted. However,

Cerli et al. (2012) demonstrated that the release of occluded POM caused by cavitational

forces strongly depends on content, composition and binding patterns of POM as well as

soil mineralogy. In consequence, the comparison of POM occlusive strength is restricted to

very similar soils, if soil specific dispersion cut-offs for the total and exclusive oLF

detachment are not determined or determinable.

Frederick Büks (doctoral thesis 2017)

3 Aim of this work

As most of the SOM is located in soil aggregates, its physical protection has large

influence on decomposition, turnover rates and the soil carbon budget of landscapes. The

present work was conducted on a plowed sandy topsoil (Su3) from a cropland near Berge

(Brandenburg, Germany) and focus on POM occlusion, since this protective mechanism

represents initial stages of SOM decomposition. Due to their influence on soil structure,

microbial nutrition and metabolic diversity in soils, the grade and strength of POM

occlusion could be a proxy for soil properties like soil fertility and soil health. The

interaction of soil microorganisms and soil particles, which is an important factor of soil

aggregation, is assumed to have significant influence on the occlusion of POM within soil

aggregates. This overall aussumption is tested in the present thesis.

In a first experiment, the influence of bacterial EPS on the occlusive strength of POM

within soil aggregates was examined. I hypothesized that POM is fixed to the mineral

phase by EPS. This hypothesis was tested by a treatment of soil aggregates with

increasing concentrations of EPS degrading enzymes, that should result in an additional

release of POM after mechanical treatment.

The second experiment focus on the influence of grazing organisms on POM occlusion. I

hypothesized, that feeding on EPS by the bacterial-feeding nematode Acrobeloides

buetschlii would result in an additional release of occluded POM compared to a control

without nematodes, when grazed bacterial biofilms and EPS remains lose their cohering

function between soil particles.

In a third work, I investigated the influence of structurally different microbial populations on

the POM occlusion. Based on the assumtion, that different communities provide different

sets of biochemical and physical mechanisms for aggregate stabilization, we expected

differing POM occlusion in two variants with strongly unequal microbial populations.

The overall aim of this work is to elucidate different aspects of the contribution of

microorganisms to the POM occlusion within sandy agricultural soils (stabilization,

variability with changing populations and feeding influence).

Soil microbial communities and POM occlusion

4 Enzymatic biofilm digestion in soil

aggregates facilitates the release of

particulate organic matter by sonication

4.1 Abstract

The stability of soil aggregates against shearing and compressive forces as well as water

caused dispersion is an integral marker of soil quality. High stability results in less

compaction and erosion and has been linked to enhanced water retention, dynamic water

transport and aeration regimes, increased rooting depth and protection of soil organic

matter (SOM) against microbial degradation. In turn, particulate organic matter is

supposed to support soil aggregate stabilization. For decades the importance of biofilm

extracellular polymeric substances (EPS) regarding particulate organic matter (POM)

occlusion and aggregate stability has been canonical because of its distribution, geometric

structure and ability to link primary particles. However, experimental proof is still missing.

This lack is mainly due to methodological reasons. Thus, the objective of this work is to

develop a method of enzymatic biofilm detachment for studying the effects of EPS on

POM occlusion. The method combines an enzymatic pre-treatment with different activities

of α-glucosidase, β-galactosidase, DNAse and lipase with a subsequent sequential

ultrasonic treatment for disaggregation and density-fractioning of soils. Particulate organic

matter releases of treated samples were compared to an enzyme-free control. To test the

efficacy of biofilm detachment the ratio of bacterial DNA from suspended cells and the

remaining biofilm after enzymatic treatment were measured by quantitative real-time PCR.

Although the enzyme treatment was not sufficient for total biofilm removal, my results

indicate that EPS may attach particulate organic matter (POM) within soil aggregates. The

tendency to additional POM release with increased application of enzymes was attributed

to a slight loss in aggregate stability. This suggests that an effect of agricultural practices

on soil microbial populations could influence POM occlusion/aggregate stability and

thereby carbon cycle/soil quality.

Frederick Büks (doctoral thesis 2017)

4.2 Introduction

Soil organic matter (SOM) comprises 50% (~1,700 Gt, including peat) of the near-surface

terrestrial carbon budget, compared to ~813 Gt bound in the atmosphere (Lal, 2008b).

Beside carbon storage and its influence on the atmospheric CO2 balance, manifold

ecological soil functions are mediated by different SOM types like dissolved organic matter

(DOM), particulate organic matter (POM), molecular organic matter of organo-mineral

associations, colloidal organic matter and coprecipitated molecular organic matter (Kalbitz

et al., 2000; Weng et al., 2002; Pokrovsky et al., 2005; Eusterhues et al., 2008). For

example, POM is a structural component of soil aggregates, a nutrient source and

provides surfaces for microbial growth (Chenu and Stotzky, 2002; Bronick and Lal, 2005).

Parts of the POM are occluded within soil aggregates (Six et al., 2002). Physical isolation

protects POM against microbial degradation (Six et al., 2002; Lützow et al., 2006) and

maintains its ecological functions, while on the other hand this POM is thought to promote

soil aggregation (Bronick and Lal, 2005). Therefore, many benefits of soil POM are linked

to soil aggregate stability.

The stability of soil aggregates against shear and compression forces (Skidmore and

Powers, 1982) as well as disaggregation caused by water (Tisdall and Oades, 1982) is an

integral marker of soil quality (Bronick and Lal, 2005). Since aggregate stability implies

pore stability, it results in less soil compactibility (Baumgartl and Horn, 1991; Alaoui et al.,

2011) and a more dynamic water transport regime in the macropores that reduces erosion

caused by surface runoff (Barthes and Roose, 2002). Other benefits in comparison to

compacted soils are a higher aeration (Ball and Robertson, 1994) and lower penetration

resistance (Bennie and Burger, 1988) causing increased rootability and rooting depth

(Bengough and Mullins, 1990; Taylor and Brar, 1991). In addition, micropores within the

aggregates enhance water retention.

The occlusion of POM within soil aggregates depends on the properties of the aggregated

components. The mineral part of the solid soil matrix is composed of siliceous sand, silt

and clay particles, oxides and hydroxides of Fe, Al and Mn as well as diverse minor

minerals. Sticking together, pervaded and coated with multivalent cations and organic

constituents (like soluble metabolic products, humic substances, black carbon and other

POM) macro-aggregates (>250 µm) are formed by direct coagulation or built of micro-

Soil microbial communities and POM occlusion

aggregates (<250 µm). (Bronick and Lal, 2005; Brodowski et al., 2006b; Lützow et al.,

2006)

The structure-bearing primary particles, precipitates and adsorbed molecules cohere by

physico-chemical interactions between (i) permanent charge of mainly the clay mineral

fraction, (ii) multivalent cations with small hydrate shells such as Ca2+, Fe3+ and Al3+, (iii)

variable charges of various minerals and SOM and (IV) variable and permanent dipoles of

different soil components. Also carbonates, phosphates and other microbial precipitates

force up aggregation and occlusion of POM. (Jastrow and Miller, 1997; Bronick and Lal,

2005)

In addition, since a few decades biological structures like bacterial colonies, bacterial

pseudomycelia, algae, fungal hyphae and their exudates (e.g. glomalin), roots as well as

soil fauna are accepted as a major factor of soil aggregation (Tisdall, 1991; Oades, 1993;

Wright and Upadhyaya, 1998; Brown et al., 2000; Chenu and Stotzky, 2002; Rillig, 2004;

Bronick and Lal, 2005). Furthermore the role of extracellular polymeric substance (EPS) of

bacterial biofilms as an adhesive between soil particles is seen to be of importance

(Baldock, 2002; Ashman et al., 2009).

Physical and chemical properties of

soil mineral and organic matter allow

to hypothesize a simple spacial

model of the inner geometry of soil

aggregates, that includes biofilms as

links between primary particles

(Fig. 4). The biofilm itself is a viscous

microenvironment mainly built up of

90 to 97% water (Zhang et al., 1998;

Schmitt and Flemming, 1999; Pal

and Paul, 2008). The remaining dry

mass contains differing ratios of

polysaccharides, extracellular DNA

(eDNA), proteins and lipids besides

10 to 50% cell biomass (More et al.,

2014). In contrast to 'biofilm', EPS

Fig. 4: Proposed model of inner soil aggregate structure

including EPS: Sand and silt (both grey) and organic

particles (black) stick together by physico-chemical

interactions and are bridged by EPS (striped), which

additionally stabilizes the soil aggregate structure and

the pore space (white). (Büks and Kaupenjohann, 2016)

Frederick Büks (doctoral thesis 2017)

terms the extracellular polymeric matrix excluding cells. Extracellular polysaccharides

cause the EPS structural stability by means of entanglement and Ca2+ bridging between

molecules. So does eDNA (Das et al., 2014). Proteins function as enzymes and structural

links stabilizing the polysaccharide matrix, while lipids act as biosurfactants for bacterial

attachment on surfaces. (Flemming and Wingender, 2010)

The composition of EPS is highly variable depending on community composition and

environmental cues (Table 2): Redmile-Gordon et al. (2014) measured a natural habitat

extracellular polysaccharide concentration of 401 µg g-1 dry soil in grassland and

169 µg g-1 in fallows. Diverse single- and multi-species biofilms show a proportion of

polysaccharides on dry EPS of up to 95% (Pal and Paul, 2008; More et al., 2014).

Different single- and multi-species biofilms in laboratory cultures and natural soils have a

dry EPS eDNA content up to 10% (More et al., 2014). For forest soils values of 1.95 up to

41.1 µg g-1 dry soil are known (Niemeyer and Gessler, 2002; Agnelli et al., 2004).

Extracellular DNA concentration of other diverse soils ranges between 0.03 and 200 µg g-1

dry soil (Niemeyer and Gessler, 2002; Pietramellara et al., 2009), whereas concentrations

in soils explicitly used for agriculture are unknown. Extracellular matrix protein

concentration was measured at 163 µg g-1 dry soil in grassland and 43 µg g-1 dry soil in

fallow (Redmile-Gordon et al., 2014), but can contribute the largest fraction of EPS dry

mass, e.g. 60% (More et al., 2014), and even up to 75% in P. putida biofilms in laboratory

cultures (Jahn et al., 1999). The typical proportion of lipids in the EPS dry-mass of different

non-soil biofilms amounts up to 10% (More et al., 2014). Sparse molar mass data from

different environments comprise 0.5x106 to 2x106 Da for polysaccharides (Flemming and

Wingender, 2010), 7.75x104 to 2.32x107 Da for eDNA (DeFlaun et al., 1987) and 750 to

1,500 Da for lipids (Munk, 2008).

The extracellular matrix is not only exuded by soil bacteria and archaea, but also by fungi

and algae. It is engineered by grazing protozoa and small metazoa as well as microbial

extracellular enzymes. (Battin et al., 2007; Flemming and Wingender, 2010)

The activity of EPS degrading enzymes in natural soils spans up to two orders of

magnitude: The α-glucosidase and β-galactosidase activity of various soils ranges from

0.00011 U g-1 to 0.0011 U g-1 and from 0.00017 to 0.0094 U g-1, respectively (Eivazi and

Tabatabai, 1988; Acosta-Martinez and Tabatabai, 2000). The lipase activity in coarse

mineral soils shows values from 0.3 U g-1 in a sandy soil (Cooper and Morgan, 1981) to

Soil microbial communities and POM occlusion

Table 2: Concentrations and molar masses of biofilm stabilizing macromolecules (polysaccharides=PS,

eDNA, lipids and proteins) in different environments.

Conc. Proportion Molar mass Comment Reference

µg (g soil)-1 µg (100 µg EPS)-1 Da

169 µg g-1 bare fallow Redmile-Gordon et al. (2014)

401 µg g-1 grassland Redmile-Gordon et al. (2014)

95% % of EPS dry-mass More et al. (2014)

40-95% % of EPS dry-mass Pal and Paul (2008)

2x106Chenu and Roberson (1996)

0.5-2x106Flemming and Wingender (2010)

eDNA

2.2-41.1 µg g-1 forest soil Agnelli et al. (2004)

0.08 µg g-1 Luvisol Niemeyer and Gessler (2002)

1.95 µg g-1 forest podzol Niemeyer and Gessler (2002)

0.03-200 µg g-1 unnamed soil Pietramellara et al. (2009)

10% % EPS dry-mass More et al. (2014)

7.75x104-2.32x107estuarine and oceanic

environments

DeFlaun et al. (1987)

Lipids

10% % of EPS dry-mass More et al. (2014)

750-1500 Abröll et al. (2008)

Proteins

43 µg g-1 bare fallow Redmile-Gordon et al. (2014)

163 µg g-1 grassland Redmile-Gordon et al. (2014)

< 75% % of Ps. Putida biofilm Jahn et al. (1999)

60% % EPS dry-mass More et al. (2014)

2.09 U g-1 in a Luvisol (Margesin et al., 2000) and up to 5 U g-1 in a Leptosol (Margesin et

al., 1999). Data for eDNAse activity in soils are not available.

Not much is known about the contribution of EPS to POM occlusion and aggregate

stability in relation to other aggregate stabilizing factors. That is mainly due to

methodological reasons: Though e.g. Tang et al. (2011) showed a significant contribution

of bacterial growth on aggregate stability, the observations could not definitely be

attributed to soil microbial exopolysaccharide production. Redmile-Gordon et al. (2014)

subsequently found that the techniques previously used to measure extracellular

polysaccharides in soil co-extracted large quantities of ’random’ soil organic matter which

confounded estimates of EPS production. Owing to the widespread interest in the role of

biofilms on soil fertility, the objectives of this work are (i) to design a selective method for

Frederick Büks (doctoral thesis 2017)

enzymatic biofilm detachment with minor impact on other types of aggregate bonds and (ii)

to apply the method to an agricultural soil to provide indications of the influence of biofilm

cohesion on POM fixation, which is expected to contribute to aggregate stability (Six et al.,

2004).

The method combines a modified enzymatic pre-treatment (Böckelmann et al., 2003) with

α-glucosidase, β-galactosidase, DNAse and lipase, a determination of the DNA ratio of

sessile to suspended cells after enzymatic treatment and an ultrasonication of soil

aggregates followed by density-fractioning and soil organic carbon (SOC) measurement

(Kaiser and Berhe, 2014). The ultrasonication/density-fractionation separates SOC into

three operational solid fractions: non-occluded free light fraction SOC (fLF-SOC),

aggregate-embedded occluded light fraction SOC (oLF-SOC) and colloidal as well as

(macro)molecular SOC, which is not detachable from mineral surfaces by the chosen

fractioning method and subsumed under heavy fraction (HF-SOC) (Kaiser and Berhe,

2014).

We hypothesize that a destabilization of the EPS matrix occurs during enzymatic

treatment. This should result in an increased cell detachment from aggregates. We also

expect an increased fLF-SOC release from destabilized aggregates compared to the

control and a shift of the oLF-SOC ratio from higher to lower binding strength (represented

by ultrasonic energy levels) that is interpretable as alteration of soil aggregate stability.

4.3 Materials and methods

4.3.1 Soil properties and microbial biomass

Well aggregated silty sand (Su3) of a plowed topsoil from a cropland near Berge

(Brandenburg/Germany) was air-dried and sieved to obtain a particle size of 0.63 to

2.0 mm containing mainly macro-aggregates. The aggregates have a pHCaCl2 of 6.9, Corg of

8.7 mg g-1 dry soil and a carbonate concentration of 0.2 mg g-1.

To estimate the soil microbial biomass, first 8 x 10 g of soil aggregates have been adjusted

to 70 %vol soil water content and incubated for 70 h at 20°C in the dark to attain basal

Soil microbial communities and POM occlusion

respiration. Then, based on DIN EN ISO 14240-2 half of the samples were fumigated with

ethanol-free chloroform in an evacuated desiccator for 24 h, whereas the other half

remained untreated. Afterwards chloroform was removed and both halves were extracted

with 40 ml of 0.5 M K2SO4 solution by 30 min of horizontal shaking and filtered through

0.7 µm glass fiber filters. The DOC concentrations of all filtrates were measured by a TOC

Analyzer (TOC-5050A, Shimadzu). 176±22 µg microbial carbon g-1 dry soil (Cmic) were

derived from the difference between DOC concentrations of fumigated and non-fumigated

samples multiplied by a conversion factor of 2.22 (Joergensen, 1996). Soil bacterial

biomass was derived from Cmic as 352±44 mg kg-1 assuming 0.5 as a ratio of Cmic to total

cell dry mass (Bratbak and Dundas, 1984).

4.3.2 Detachment scenarios

Four degradative enzymes were selected on the basis of soil pH and the temperature used

for definition of the catalytic unit (Tdef): a-glucosidase from S. cerevisiae (Sigma-Aldrich,

pHopt 6 to 6.5, Tdef=37°C, product number G0660) hydrolyzes terminal a-1,4-glycosidic

linkages in polysaccharides as b-galactosidase from E. coli (Sigma-Aldrich, pHopt 6 to 8,

Tdef=37°C, product number G5635) does with b-glycosidic bonds. Lipase from porcine

pancreas (Sigma-Aldrich, pHdef 7.7, Tdef=37°C, product number L0382) splits fatty acids

from lipids via hydrolysis, but do not digest phospholipids, which are part of bacterial

membranes. DNAse I from bovine pancreas (pHdef 5, Tdef=25°C, product number D5025)

breaks the phosphodiester linkages between nucleotides of DNA as an endonuclease.

Proteases were not used because of their promiscuity and therefore incalculable influence

on the other applied enzymes.

Literature shows a wide range of target concentrations related to these enzymes in

different soils. As we do not know target concentrations of our soil (due to a lack of

extraction methods), we considered the largest published values (Table 2) of EPS content

(ξEPS

max )

and enzyme target dry mass contents

(ξtarget

max )

from literature. Further, as bacterial

dry mass

(ξcell

min)

and target molar masses

(Mtarget

min )

vary as well, here we choose the

minimum percentage and the smallest mass, respectively. These values conduce to a

“worst-case” point of view with a maximum of enzyme targets. Any other boundary

Frederick Büks (doctoral thesis 2017)

conditions such as ion activity, diffusion rates or metabolization of enzymes by soil

organisms were disregarded.

Calculated by Eq. (1)

Unittarget=ccell

⋅q⋅ξEPS

max⋅ξtarget

max ⋅msample

ξcell

min

⋅Mtarget

min ⋅t

(1)

with variables listed in Table 3 and Table 4, sufficient enzymes were provided to digest the

expected EPS concentration in five scenarios: In the E1 scenario ccell was given by the

results of fumigation-extraction. In the E2 scenario a bacterial dry mass of 500 g m-2 in the

upper 30 cm is considered, which is assumed to be the maximum for middle and northern

European soils (Brauns, 1968). Supposing a soil bulk density of 1.4 g cm-3, a ccell of

1190.5 µg g-1 dry soil is given. Although the soil bulk density of the soil aggregate samples

is ~1.15 g cm-3, we decided to use the soil bulk density of the original soil, which is in the

normal range of sandy silk soil (~1.40 g cm-3) (Chaudhari et al., 2013). This is due to the

fact that biofilm populations are mentioned to be mainly located in soil aggregates (Nunan

et al., 2003) and accords to the “worst-case”-approach. The E3 scenario uses a 100-fold

excess (q=100, Table 4) of the enzyme activities applied in the E2 scenario, whereas the

E4 scenario contained the 2,820-fold, which is slightly higher than activities used in

Böckelmann et al. (2003). Enzyme-free samples (E0) were used as a control.

Table 3: Variables, that are used for the calculation of enzyme units needed for biofilm target decomposition

and scenario parameters, [a] More et al., 2014; [b] Pal and Paul, 2008; [c] Flemming and Wingender, 2010;

[d] Abröll and Munk, 2008; [e] DeFlaun et al., 1987.

ccell

[µg g-1] bacterial dry mass per g dry soil

[-] enzyme concentration multiplier

ξEPS

max

[-] maximum ratio of EPS dry mass per total biofilm dry mass

(

ξEPS

max=0.9[a]

)

ξtarget

max

[-] maximum ratio of enzyme target per EPS dry mass

(

ξpolysaccharides

max =0.95[b]

ξlipids

max =0.1[a]

and

ξeDNA

max =0.1[a]

)

msample

[g] sample mass

ξcell

min

[-] minimum ratio of bacterial dry mass per total biofilm dry mass (

ξcell

min=0.1[a]

)

Mtarget

min

[µg µmol-1] minimum molar mass of enzyme target

(

Mpolysaccharides

min =0.5 x106[c]

Mpolysaccharides

min =700[d]

MeDNA

min =7.75 x104[e]

)

[min] incubation time

Soil microbial communities and POM occlusion

Table 4: Specific scenario parameters of the variants E0, E1, E2, E3 and E4.

E0 E1 E2 E3 E4

ccell

[µg g-1 dry soil] 352 352 1191 1191 1191

[-] 1 1 1 100 2,820

Ualpha−glucosidase

max

[U g-1 dry soil] 0.00000 0.00010 0.00034 0.03393 0.95683

[µg g-1 dry soil] 0.00000 0.00080 0.00272 0.27144 7.65464

Ubeta−galactosidase

max

[U g-1 dry soil] 0.00000 0.00010 0.00034 0.03393 0.95683

[µg g-1 dry soil] 0.00000 0.00020 0.00068 0.06786 1.91366

Ulipids

max

[U g-1 dry soil] 0.00000 0.00754 0.02551 2.55102 71.93876

[µg g-1 dry soil] 0.00000 0.00038 0.00126 0.12551 3.59694

UeDNA

max

[U g-1 dry soil] 0.00000 0.00007 0.00023 0.02304 0.64973

[µg g-1 dry soil] 0.00000 0.00004 0.00012 0.01152 0.32487

4.3.3 Release of POM carbon

Fifteen g of air-dried soil aggregates were incubated in 5 replicates per scenario with

3.4 ml of highly concentrated artificial rainwater (ARW: 0.2 mM NH4NO3, 0.3 mM

MgSO4x7H2O, 0.5 mM CaCl2 x 2H2O, 0.5 mM Na2SO4, 15 mM KCl, pH 5.7) for 3 days at

20°C in the dark to establish basal respiration and avoid slaking in the following

preparation steps. After incubation 2.5 ml of ARW containing enzymatic units according to

Table 4 were added to the samples. By means of a following incubation at 37°C, enzymes

were let to work near their catalytic optimum for 1 h, which is proven to be sufficient for

biofilm degradation (Böckelmann et al., 2003). After this enzymatic pretreatment, 67.2 ml

of 1.67 g cm-3 dense sodium polytungstate (SPT) solution were added resulting in a

density cut-off of 1.6 g cm-3, and samples were stored for 30 min to allow SPT diffusion into

the aggregates. Then samples were centrifuged for 26 min with 3,569 G. Sodium

polytungstate solution with floating fLF was filtered through an 1.5 µm pore size glass fibre

filter to capture LF particles. Afterwards following Golchin et al. (1994) aggregate samples

were consecutively disaggregated in four steps by application of each 50 J ml-1 of

ultrasonic energy (Branson© Sonifier 250) for 1 min 15 sec. The energy output was

determined by measuring the heating rate of water inside a dewar vessel (Schmidt et al.,

1999). Every treatment cycle consisted of ultrasonication, centrifugation for 26 min with

3,569 G and filtering of SPT solution through an 1.5 µm pore size glass fibre filter to

capture the LF. Afterwards the LFs and the remaining soil matrix ('sediment', consisting of

oLF bonded >150 J ml-1 and the HF) were frozen, lyophilized, ground and dried at 105°C.

Frederick Büks (doctoral thesis 2017)

Total amount of fraction carbon was determined using an Elementar Vario EL III CNS

Analyzer and the absence of carbonates was proved, respectively.

4.3.4 Release of bacterial DNA

The release of bacterial cells into the solution was estimated by use of DNA extraction

using a FastDNATM SPIN Kit for Soil and quantitative real-time PCR.

Therefore 45 µl of ARW were added directly to 0.1 g of air-dried aggregates. The samples

were sterilely incubated in duplicate at 20°C for 3 days in the dark in a closed FastPrep

Lysing Matrix E tube during run to basal respiration. Then 30 µl of ARW containing

enzymatic units according to Table 4 were distributed equally to the aggregates' surfaces.

The samples were incubated for 1 h at 37°C in a heating block, cooled down on ice to

decrease enzyme activity and washed three times in 1 ml of ARW not by shaking but

gently rotating along the tube's longitudinal axis to separate detached and planktonic cells

from the soil matrix. Supernatants of all three washing steps were removed carefully with a

pipette, pooled and centrifuged at 13.000 G for 15 min at 4°C. Then the supernatant was

discarded, the pallet resuspended in 200 µl ARW and transfered to another FastPrep

Lysing Matrix E tube. Both soil and washing ARW samples were extracted and purified at

4°C following the FastDNATM SPIN Kit for Soil manual. All DNA samples were stored at

-20°C for further use. A direct subsampling from the aggregate stability experiment was

rejected due to its destructive capability regarding aggregates. Temperature, substrate, pH

and water content of the DNA experiment were similar to the incubation of samples for the

measurement of aggregate stability. Further differences (e.g. soil volume) were

disregarded.

Amplification of 10-fold diluted DNA samples was performed using a C1000 Touch Thermal

Cycler (BioRad). According to the reference for SG qPCR Master Mix (Roboklon)

thermocycling comprised an initial denaturation at 95°C for 10 min as well as 55 cycles of

15 sec of denaturation at 95°C, 20 sec of annealing at 49°C and 30 sec of elongation at

72°C. The reaction mix contained 1 µl PCR-H2O, 12.5 µl SG qPCR MasterMix, each

0.75 µl of a 20 µmol l-1 solution of the universal bacterial primers 63f

(5'-CAGGCCTAACACATGCAAGTC-3') and 341r (5‘-CTGCTGCCTCCCGTAGG-3‘)

(Muyzer et al., 1993; Marchesi et al., 1998) and 10 µl template DNA. Escherichia coli 16s

Soil microbial communities and POM occlusion

DNA solution containing 10,000 copies µl-1 was used as qPCR standard in steps of tenfold

diluted concentration from 106 to 102 copies µl-1.

4.3.5 Statistics

For evaluation of the light fraction SOC (LF-SOC) release, mean values as well as

standard deviations were calculated. Parallels of each variant were positively tested to

provide normal distribution and evidence of variance homogeneity (Shapiro Wilk test,

Levene test, both p>0.05, data not shown). One way analysis of variance (ANOVA) was

applied followed by Tukey test to clarify significant (p<0.05) differences in LF-SOC release

between variants of each energy level. Results of bacterial DNA release were presented

as duplicates.

4.4 Results

4.4.1 Release of POM carbon

The relative LF carbon release from soil aggregate samples after different enzymatic

treatments is shown in Fig. 5. The proportionate C of each captured fraction is defined as

Cfrac CΣ-1, in which Cfrac is the release of LF-SOC per energy level or – in case of the

sediment – the organic carbon remaining in the soil matrix. CΣ is the total SOC of all

separated LFs and the sediment. Averaging all treatments, around 79% of CΣ remain in the

sediment, whereas the bulk of LF-SOC is released as weakly bound oLF (50 J ml-1) and

fLF. Only around 4.5% of CΣ is detached at 100 J ml-1 and 150 J ml-1.

None of the enzymatic treatments altered the quantity of fLF-SOC released in the absence

of sonication (0 J ml-1). In contrast, visible differences to the control were shown for E1

(decrease, p=0.34) and E4 (increase, p=0.42) at mild sonication (50 J ml-1), whereas E2

(p=1.00) and E3 (p=1.00) are very similar to the control. The difference between E1 and

E4 was statistically significant (p=0.01) as indicated by the Tukey test, and the addition of

the highest enzyme concentration (E4) caused the release of about 63% more oLF-SOC

than occurred with the addition of the lowest concentration (E1). Released LF-SOC at 100

and 150 J ml-1 is not different among treatments. Only the E2 scenario shows any

Frederick Büks (doctoral thesis 2017)

tendency of increased oLF-SOC release at 100 J ml-1 compared to the other treatments

(p=0.07 compared to E3).

The sediment represents the SOC remaining unextractable at ≤150 J ml-1 and accordingly

shows a trend to decrease with increasing enzyme activity. In relation to the control, nearly

the whole alteration in the oLF-SOC releases of E1 and E4 at 50 J ml-1 as well as E2 at

100 J ml-1 comes from the sediment fraction, but hardly from the other LFs. However,

opposite reallocation of SOC between fractions due to converse physico-chemical effects

can only be observed in sum. Therefore alterations must be considered as net C transfer

between stability fractions.

Cumulating LF-SOC releases of all energy levels, E1 shows a reduction by 16% compared

to the control (3.3% of CΣ), whereas E4 was increased by 10% (2.2% of CΣ). The strongest

enzymatic treatment (E4) caused the release of about 58% (0.49 mg/g dry soil) more

cumulated LF-SOC than occurred with scenario E1.

Fig. 5: Relative POC release after treatments (E0, E1, E2, E3,

E4) at different energy levels (0, 50, 100, 150 J ml-1, sediment),

illustrated by Tukey test characters (a, ab, b). Data are shown as

mean values and standard deviations (n=5). (Büks and

Kaupenjohann, 2016)

Soil microbial communities and POM occlusion

4.4.2 Release of bacterial DNA

The relative DNA release after enzymatic treatment, as pictured with the treatments E0, E1

and E4 in Fig. 6, is defined as the ratio of extracted DNA from suspended bacterial cells

(DNAsusp) to the sum of DNA extracted from suspended and sessile bacterial cells and the

remaining EPS (DNAΣ) multiplied by 100. While there was no difference in relative DNA

release in the wash of control and low enzyme additions, treatment E4 caused an increase

to more than double the DNA content of either E0 or E1, which amounts to 5.6% of total

DNA. This increase is caused by both an increase in released bacterial DNA from

suspended bacterial cells and a decrease in eDNA remaining on washed soil particles.

Fig. 6: Relative bacterial DNA release from

soil aggregates after treatments E0, E1, and

E4 defined as 100x ratio of bacterial DNA

from suspended cells (DNAsusp) to total

bacterial DNA from suspended cells, sessile

cells (DNAΣ) and the EPS remaining upon the

soil matrix. (Büks and Kaupenjohann, 2016)

Frederick Büks (doctoral thesis 2017)

4.5 Discussion

We found that increasing the quantity of enzymes applied to aggregates led to increased

release of LF-SOC when aggregates were sonicated. This detachment is explained by the

following mechanism: The enzyme mix flows into the unsaturated pore space. From there

α-glucosidase, β-galactosidase, DNAse and lipase diffuse into the biofilm matrix, where

structural components like polysaccharides, eDNA and lipids are digested as approved for

diverse enzymes and enzyme targets in ecological and medical studies (Böckelmann et

al., 2003; Walker et al., 2007). We propose a simple spatial model to explain the observed

findings: The biofilm bridges gaps between organic and mineral primary particles,

connects them in addition to other physico-chemical bondings and builds a restructured

pore system inside the aggregate (Fig. 4). As macromolecular biofilm components yield

EPS as a viscoelastic structure (Sutherland, 2001), their digestion causes a loss in EPS

viscosity and thereby should reduce forces involved in the occlusion of POM. The effect is

expected to grow with increasing enzyme activity until the whole EPS matrix is dispersed.

In the following, LF-SOC is interpreted as SOC from released POM, since the share of

both adsorbed DOM and colloids on captured dry mass is considered to be negligible after

SPT treatment. Furthermore, LF-SOC transferred from the sediment fraction to light

fractions due to enzymatic treatment is also interpreted as POM, as in contrast mineral

associated organic matter of the HF is not assumed to be extractable at the applied

energies (Cerli et al., 2012).

In accordance with the model, measured oLF-SOC releases indicate a trend for increased

POM release with increasing enzyme addition (Fig. 5). The E4 scenario shows that relative

oLF-SOC release increased by 63% (5% of CΣ) compared to E1 at 50 J ml-1, but its release

is similar to the mean of the other treatments at 0 J ml-1, 100 J ml-1 and 150 J ml-1.

Noticeable deviations of E1 and E4 from the control do not match the usual significance

criteria (p<0.05). However, the increase of the relative oLF-SOC release in the E4 scenario

compared to the control is predominantly related to an equally lower C content of the

sediment but no decrease in the 100 J ml-1 and 150 J ml-1 fractions. That points to a strong

(oLF >150 J ml-1) intra-aggregate fixation of POM due to enzyme targets, which is

weakened by enzymatic treatment.

Soil microbial communities and POM occlusion

The relation of LF-SOC release with enzymatic biofilm digestion is supported by the

comparison of bacterial DNA releases between the treatments (Fig. 6). This indicates that

applied enzymes are targeting biofilm components and release bacterial cells: The E4

scenario shows EPS digestion and additional cell release leading to a doubled relative

DNA release compared with the control and E1. However, considering that most of the soil

bacteria are expected to live in biofilms (Davey and O'toole, 2000), the total DNA release

of only 5.6% in the E4 scenario is too low for total biofilm digestion. Hence, biofilm

detachment caused by E4 is still likely to be incomplete and the increased oLF-SOC

release of E4 only results from a partial soil biofilm detachment. We conclude a slight

influence of enzymatic treatment on the occlusion of POM at enzyme concentrations

exceeding natural concentrations. This conforms to results of Böckelmann et al. (2003),

which indicate that a treatment with enzyme concentrations of near that of E4 is sufficient

to destabilize biofilms within 1 hour.

The incomplete biofilm detachment can be explained by the reduction of enzyme activity

due to interaction with the soil matrix. Based on our calculations enzyme concentrations of

mix E1 should have been sufficient for total biofilm digestion within time of application (1 h)

– as far as there are no other factors reducing enzyme efficiency. As surveys of natural

soils show enzyme concentrations up to mix E3 (Cooper and Morgan, 1981; Eivazi and

Tabatabai, 1988; Margesin et al., 1999; Acosta-Martinez and Tabatabai, 2000; Margesin et

al., 2000), such factors might be reasonably assumed. After addition to the soil sample,

enzymes must enter the EPS matrix by diffusion. Therefore parts of the enzymes probably

do not reach the biofilm due to inhibited diffusion. Beside diffusion, sorption and

decomposition could play a major role in reducing enzyme efficiency. Whereas turn-over

rates of soil enzymes are not yet assessed, extended stabilization of active enzymes over

time on soil mineral and organic surfaces is reported (Burns et al., 2013). This mechanism

could explain immobilization of enzymes off the biofilm and high measured soil enzyme

concentrations from literature in face of still existing biofilms. After penetration of biofilms

(macro)molecules interfere with EPS components depending on molecular size, charge

and biofilm structure (Stewart, 1998; Lieleg and Ribbeck, 2011) which is strongly

influencing decay rates of enzymes. Due to these boundary conditions, quantification of

the relation of enzyme concentration and POM carbon release was not possible in this

work.

Frederick Büks (doctoral thesis 2017)

The trend for increased POM release with increasing enzyme addition was only broken by

the control treatment. Probably this could be explained by pre-incubation of soil

aggregates given 0.2 mM NH4NO3 and further addition of NH4NO3 with enzyme

application: Redmile-Gordon et al. (2015) proposed that low C/N ratios of substrates

available to soil microorganisms reduce cell specific EPS production rates, and may trigger

microbial consumption of EPS to acquire C for cell-growth, which could weaken the

biofilm. The observations leading to this proposed dynamic were also found by addition of

NH4NO3. In the present study, NH4NO3 was applied with all treatments including the control

(which also received no C from enzyme provision). The lowest C/N ratio in the control soils

may itself have sustained EPS consumption and repressed reconstruction of the EPS,

contributing to the higher than expected release of POM from the control soil with

sonication at 50 J ml-1 and the break in the trend for increasing POM release with

increasing enzyme addition.

Enzyme C in E1 to E4 could be used as microbial C source. The addition of C increases

the C/N ratio and has been shown to lead to soil aggregate stabilization (Watts et al.,

2005; Tang et al., 2011). Decay rates of enzymes in soil are unknown but needed for a

more accurate estimation of enzyme C as a fast energy and carbon source.

Under certain conditions POM carbon release is indicative for soil aggregate stability.

Generally, aggregate stability is characterized by determining the reduction in aggregate

size after application of mechanical force. The commonly used methods are dry and wet

sieving. However, the destruction of soil aggregates by ultrasonication has an advantage

over these methods, which is the quantification of the applied energy (North, 1976). It is

used for studying reduction of aggregate size (Imeson and Vis, 1984) as well as

detachment of occluded POM carbon (Golchin et al., 1994). Kaiser and Berhe (2014)

reviewed 15 studies using ultrasonication of soil aggregates in consideration of its

destructiveness to the soil mineral matrix and occluded POM. They found destruction of

POM at applied energy levels >60 J ml-1, destruction of sand-sized primary particles at

>710 J ml-1 and of smaller mineral particles at even higher energy levels. We used this

method of gentle POM detachment from soil aggregates to measure the oLF-SOC release

as a result of mechanical force and linked it to aggregate stability. Since Cerli et al. (2012)

have shown that the release of free and occluded light fractions strongly depends on soil

properties like mineralogy, POM content, composition and distribution, this method is

Soil microbial communities and POM occlusion

restricted to comparison of soils being similar in these properties. Having regard to this

restriction, the trend for increase of oLF-SOC release over increasing enzyme additions

demonstrates an alteration of soil aggregate stability.

Although our results give a slight evidence for the influence of biofilms on aggregate

stability, they have to be recognized with restrictions to full quantifiability: (1) The enzyme

concentration hypothetically needed to disperse the whole soil sample EPS matrix

depends on diverse boundary conditions like the concentration of enzyme targets,

environmental conditions such as pH, temperature as well as ion activity and delay factors

such as low diffusion, kinetic influence or metabolization of enzymes by soil organisms. (2)

Underlying enzyme kinetics were measured by the producer using pure targets for unit

definition, while biofilm targets are much more diverse and soil matrix could interfere. (3)

Alternative enzyme targets might be reasonably assumed within the complex chemism of

the soil matrix. Released organic cytoplasm molecules of lysed cells can be excluded to be

an additional enzyme target due to their low concentration. On the other hand, enzyme

specificity to EPS targets in face of the organic soil matrix is unbeknown. (4) The decrease

of extracted POM mass due to biofilm erasement from surfaces is suggested to be low, but

could cause underestimation of POM release especially in scenario E4. In contrast, a

direct contribution of enzyme C to the POM carbon release can be refused. Even in case

of complete adsorption to the POM of only one fraction, the highest enzyme concentration

(E4) would result in additional 13.5 µg enzyme g-1 dry soil being <0.4% of the smallest

extracted POM fraction (Table 4). (5) Regarding DNA release measurement as well, data

are semi-quantitative, since quantification of the detachment effect is limited by a potential

adherence of detached cells to soil particles after washing (Absolom et al., 1983; Li and

Logan, 2004). Thus, cell release could be underestimated as biofilm detachment

increases.

Many of these uncertainties are owed to the high complexity of the soil system. Enzymes

were applied in concentrations four orders of magnitude higher than calculated from actual

Cmic and even 1 to 2 orders of magnitude higher than values from literature. Incomplete

biofilm removal indicated by the release of maximum 5.5% DNA from the soil matrix may

suggest that the pooled influence of the disregarded boundary conditions on enzymatic

detachment efficiency is large.

Frederick Büks (doctoral thesis 2017)

However, these results give a first though still vague insight in fundamental processes

underlying POM occlusion. A slight release of occluded POM coupled with increased

bacterial DNA release after treatment with high enzyme concentrations underpin the

assumption that biofilm is involved in POM occlusion being a stabilizing agent of soil

aggregates as proposed in a review by Or et al. (2007). The apparent increase of POM

carbon release caused by the digestion of EPS components suggests biofilm relevance in

soil ecosystems e.g. in terms of soil-aggregate related functions like soil water and C

dynamics, mechanical stability as well as rootability. However, the statistical power of this

introductory work is low and a more quantitative analysis of the relation of enzymatic EPS

detachment and POM release would require deeper knowledge of enzyme dynamics in

soil, more replicate samples, additional enzyme concentrations and probably inclusion of

soils from different land use. However, this was beyond the scope of the present study.

4.6 Conclusions

Extracellular polymeric substance (EPS) was shown to be a promising candidate factor of

aggregate stability. Our experimental results suggest that EPS contributes to occlusion

and attachment of particulate organic matter (POM) in sandy soil aggregates. The

application of a highly concentrated mix of α-glucosidase, β-galactosidase, DNAse and

lipase is related to a slight detachment of POM from a stable to a more fragile binding

structure, but not to an increase in POM release without physical disruption of aggregates

by sonication. The pattern of measured light fraction soil organic carbon (LF-SOC) release

and additional bacterial DNA release points to an intra-aggregate fixation of POM by

enzyme targets. A loss of EPS integrity could therefore cause a detachment of soil organic

matter, not only in the laboratory but also in tilled soils. Our results further suggest that a

change of the biofilm composition probably due to a shift in microbial population structure

may alter soil aggregate stability. On macro-scale this could affect soil compactibility,

erodibility, water transport, retention and aeration regime, rooting depth and the occlusion

of soil organic carbon. This, in conclusion, invites to behold soil EPS dynamics as a factor

of sustainable land use.

Soil microbial communities and POM occlusion

4.7 Acknowledgements

This project was financially supported by the Leibnitz-Gemeinschaft (SAW Pact for

Research, SAW-2012-ATB-3). We also are grateful to Prof. Dr. Ulrich Szewzyk and the

helpful staff of the Chair of Environmental Microbiology (Department of Environmental

Technology, TU Berlin) for the unbureaucratic possibility to use their laboratories. In

addition our thanks go out to Lara Schneider. Her bachelor thesis helped us to get an

overview in the early phase of this experiment. And thanx both to Dennis Prieß for initiating

a good idea during a very good Taiji training and to Tom Grassmann for his help to handle

R coding.

Frederick Büks (doctoral thesis 2017)

Soil microbial communities and POM occlusion

5 POM occlusion within sandy soil

macroaggregates is not affected by

feeding and motion of the nematode

Acrobeloides buetschlii

5.1 Abstract

To protect in a harsh environment, bacteria gather in a viscose biofilm, which also forms a

food source for the soil fauna such as bacterial-feeding nematodes. In addition to its

protective and nutritive function, biofilm is supposed to provide the aggregation of soil

particles, which is attended by the occlusion of particulate organic matter (POM). In the

present work we hypothesized, that grazing of the nematode A. buetschlii on bacteria in a

sandy agricultural soil affects the occlusion of POM. Soil aggregate samples from a

cropland near Berge (Germany) were inoculated with on average 370 individuals g-1 of A.

buetschlii and incubated for 14 days. The population development was monitored and the

POM occlusion as well as the amount and pattern of phospholipid fatty acids (PLFAs) were

measured at day 0, 1 and 14. Although the population of A. buetschlii remained stable

across the experimental period, neither a changing microbial biomass and composition nor

a variation of POM release was observed compared to a nematode-free control. As about

41% of the mesopores within the aggregate sample did not provide enough space for

nematode migration, this suggests an inaccessibility of intra-aggregate biofilms and

therefore protection against faunal grazing. These spacially protected microaggregates

likely have a key role in POM occlusion.

Frederick Büks (doctoral thesis 2017)

5.2 Introduction

Biofilms represent a bacterial strategy to withstand ecological stressors, e.g. toxics and

antibiotics, radiation, drought and grazing pressure (Flemming and Wingender, 2010).

They consist of 90 to 97% water (Zhang et al., 1998; Schmitt and Flemming, 1999; Pal and

Paul, 2008), differing ratios of polysaccharides, extracellular DNA (eDNA), proteins and

lipids as well as microbial cells, which accounts for 10 to 50% of the biofilm dry mass

(More et al., 2014). The viscous biofilm matrix not only functions as protective clothing for

microorganisms living within, it is also a genetic cross-over hotspot and collective digestive

system, which plays a role in nutrient cycling and soil aggregation. (Baldock, 2002;

Ashman et al., 2009; Flemming and Wingender, 2010)

As soil bacteria are known to colonize particulate organic matter (POM), their biofilms are

suggested to play a role in POM occlusion due to soil aggregate formation (Jastrow and

Miller, 1997; Baldock, 2002; Chenu and Stotzky, 2002). Compared to unaggregated soils,

well aggregated soils show an increased water holding capacity in micropores, drainage,

aeration and rootability as well as less compactibility and erodability (Baumgartl and Horn,

1991; Taylor and Brar, 1991; Ball and Robertson, 1994; Barthes and Roose, 2002; Alaoui

et al., 2011). These are parameters that affect soil fertility. Consequently, influences of

agricultural praxis or natural soil processes on soil biofilms are important in sustainable

land use.

Grazing soil biota, e.g. protozoa and nematodes, are assumed to affect the bacterial

community and the soil nutrient cycling (Ingham et al., 1985; Bonkowski, 2004). Nematode

grazing maintains bacterial populations in a youthful state and thereby enhances

decomposition activity (Neher, 2010). It is therefore conceivable, that soil biofilm structure

is engineered by these organisms. As part of the microfauna, the phylum Nematoda is an

ecologically important branch containing >25,000 species (Zhang, 2013) in freshwater,

marine, endobiontic and soil habitats. Nematodes are ubiquitary abundant even in

stressed or disturbed soils (Neher, 2010) and show different feeding habits as there are

plant parasites, fungal feeders, predators, unicellular eukaryote feeders as well as

bacterial grazers (Yeates et al., 1993). Due to these diverse trophic interactions

nematodes hold a central position in both bottom-up and top-down controlled food webs

(Ferris, 2010; Yeates, 2010).

Soil microbial communities and POM occlusion

A well examined, cosmopolitic, robust and easily cultivable representative, Acrobeloides

buetschlii, is used in this study (Nicholas, 1962; Frey, 1971). This opportunistic species is

common in many soils and its ecology is well examined in studies of e.g. forest, subarctic

and agricultural soils (Ruess, 1995a; Korthals et al., 1996; Ruess et al., 2002; Kästner and

Germershausen, 2014). Female adults, predominant in soils, have a length between 300

and 500 µm and a diameter of 12.5 to 41.7 µm (Bongers, 1994). In pure culture A.

buetschlii showed its highest population growth rate at 26.6°C and a slightly reduced

growth rate at an incubation temperature of 20°C (Venette and Ferris, 1997). Its metabolic

rate is the highest at 35°C (8.5 ng CO2 µg-1 Nematode h-1) and has a second local optimum

(7 ng CO2 µg-1 Nematode h-1) at 20°C (Ferris et al., 1995). 20°C also lead to a generation

time of 13 to 14 days (Nicholas, 1962). As other nematodes are known to use chemotaxis

when foraging for food, A. buetschlii is also assumed to migrate this way (Zuckerman and

Jansson, 1984). The nematode develops well at a soil pH of 6 (Frey, 1971; Korthals et al.,

1996) and 60% field capacity in sandy soils (Ackermann et al., 2016). Nematodes swim in

water-filled pores and water films on particle surfaces (Juarez et al., 2010) and migrate

with 52 to 718 µm sec-1 as measured for various taxa (Gray and Lissmann, 1964; Wallace,

1968). A. buetschlii was shown to move randomly in the soil without bacteria present, and

cover distances of at least 6.6 cm within 8 days (Ackermann et al., 2016). With a bacterial

trigger A. buetschlii moves towards the resource, which may be located even at several

centimeter distance.

By feeding on soil bacteria, digesting and excreting easily available nutrients e.g. NH4+, A.

buetschlii functions as an interlink in soil elemental cycling and thereby strongly affects

bacterial growth (Freckman, 1988). Given that the bulk of soil bacteria is living in biofilms

(Davey and O'toole, 2000), it seems obvious, that bacterial feeders, whose feeding habit is

influenced by preference and food accessibility, influence this small-scale habitat (De

Mesel et al., 2004) and thus biofilm related POM occlusion within soil aggregates.

Furthermore, Ghanbari et al. (2012) showed a maximum level of mechanical force

generation for C. elegans of about 61.94 µN. As also A. buetschlii releases mechanical

forces to its surrounding, it possibly could manipulate soil structure, e.g. by displacing

primary particles within soil aggregates.

Based on this trophic and mechanical potential, we hypothesized that a dense population

of A. buetschlii given on a habitable, nematode-free soil would affect microbial community

Frederick Büks (doctoral thesis 2017)

and POM release. Expected changes in the occlusion of POM within soil aggregates are

attributed to a combined impact of both, mechanical displacement of soil particles and

biofilm grazing, and can be negative (destabilization) or positive (adaptive reaction of the

biofilm community). To prove our hypothesis, soil aggregates from an agricultural site near

Berge (Germany) were incubated for 14 days with A. buetschlii at densities similar to

common field populations of bacterial-feeding nematodes. The POM occlusion was

determined after 0, 1 and 14 days by ultrasonic treatment of soil aggregates, density-

fractioning and measurement of released particulate light fraction carbon (POC) following

Golchin et al. (1994) and compared to a nematode-free control. In addition, the microbial

biomass and community composition was determined by analysis of soil phospholipid fatty

acids (PLFAs) at each sampling date, and the nematode population was counted.

Separately, also the soil pore size distribution was measured by mercury intrusion to check

the accessibility of the intra-aggregate pore space for nematodes.

5.3 Materials and methods

5.3.1 Soil sample

Soil aggregates with a size of 630 to 2,000 µm were collected from an air-dried sandy

topsoil (Su3) (Sponagel et al., 2005) of an agricultural site near Berge (Brandenburg,

Germany). The resulting sample had a pHCaCl2 of 6.9, Corg=8.7 g kg-1, Cmin=200 mg kg-1 and

Cmic=352 mg kg-1.

5.3.2 Basal respiration

Following Nordgren (1988), 20 g of air-dried soil aggregates were incubated in 9-fold

replication at 20°C for 72 hours in a respiration device (CarbO2Bot, PRW Electronics) to

determine dry baseline CO2 emission. Afterwards the 9 replicates were divided into

triplicates and three different water contents were set (50, 70 and 80%vol field capacity;

addition of sterile tap water: 3.2 ml, 4.5 ml and 5.2 ml, respectively). Incubation was

conducted at 20°C for 95 hours to detect the water content of highest soil respiration and

the point of beginning basal respiration.

Soil microbial communities and POM occlusion

5.3.3 Preparation of the inoculum

Breeding of A. buetschlii was performed on colonies of the fungus Chaetomium globosum.

Sterile incubation of C. globosum took place on potato dextrose agar (39 g PDA, 1 l dest.

Water, sterilized at 121°C for 20 min) for 4 weeks. Afterwards, Petri dishes with C.

globosum were infected with A. buetschlii and sterilely incubated at 18°C in the dark until

dense population. A modified Baermann's funnel extraction (Ruess, 1995b) was applied for

3 days at 20°C to segregate living Nematodes from the agar plate and collect them in

45 ml flasks. Subsequently a washing procedure was applied to clean nematodes from

protozoa and bacteria: The Nematode suspension was centrifuged for 8 min at 700 rpm

and 8°C in a Thermo Scientific Heraeus Multifuge 3SR+ and the supernatant was

removed. The nematode pallet was resuspended in sterile tap water and washed again.

Then the received pallet was resuspended in 3 ml 0.01% HgCl2 solution, exposed for

3 min, subsequently washed another 2 times and resuspended in sterile tap water. The

Nematode concentration was determined by brightfield microscopic counting (100x

magnification) in 125 µl suspension. Afterwards the suspension was adjusted to 5,500

individuals ml-1 by addition of sterile tap water.

5.3.4 Nematode population development

18x15 g of dry soil aggregates were filled in 250 ml PE-bottles, adjusted to 70% field

capacity with sterile tap water (3.4 ml) and incubated for 4 days at 20°C in the dark to

reach basal respiration. Afterwards the evaporated water was refilled and half of the

samples were inoculated with 1 ml of A.buetschlii suspension containing

5,500 individuals ml-1 (Nem), which results in an density of 370 individuals g-1 dry soil

aggregates. The water volume added via nematodes thereby set soil aggregates on 90%

field capacity. The other half, used as control (Con), got 1 ml of sterile tap water instead.

Each 3 replicates per variant where incubated for 1, 6 and 14 days at 20°C in the dark.

Afterwards living Nematodes were extracted from the soil following Ruess (1995b) and

fixated with 4% formaldehyde solution. Collected Nematodes were counted using

brightfield microscopy with 100x magnification.

Frederick Büks (doctoral thesis 2017)

5.3.5 Measurement of POC release

25 soil aggregate samples à 15 g were moistened with sterile tap water to get 70% field

capacity (3.4 ml) and incubated at 20°C for 4 days in the dark. Afterwards, evaporated

water was refilled. Nematode samples were incubated in 5-fold replication for 1 day

(Nem1) and 14 days (Nem14) with addition of 1 ml of the above inoculum. Three further

controls without Nematodes (Con0, Con1 and Con14) were established comparably. After

incubation and refill to 90% field capacity, POC release was estimated by successive

ultrasonication, density fractioning and C/N-analysis (Kaiser and Berhe, 2014): In

consideration of the contained amount of water, 70.6 ml of 1.64 g cm-3 dense sodium

polytungstate solution (SPT) were added to the sample for the adjustment of 1.6 g cm-3.

Afterwards, the samples rested for 30 min to enable SPT distribution within the pore

space. Thereafter, the free light fraction (fLF) was captured using centrifugation at 3,569 G

for 26 min and filtering of supernatant trough a glass fibre filter with 1.5 µm pore size. For

the following ultrasonic treatment, energy output of the ultrasonication device (Branson©

Sonifier 250) was derived from the heating rate of water inside a dewar vessel (North,

1976). The remaining soil was refilled to 75 ml 1.6 g cm-3 dense SPT, treated with 50 J ml-1

and again centrifuged and filtered to capture the weakly bond occluded light fraction

(oLF50). After further refill, soil samples were ultrasonicated twice with each additional

50 J ml-1 and again centrifuged and fractionated (oLF100 and oLF150). Light fractions (LF)

and the remaining sediment (heavy fraction HF plus strongly bond POM) were froze at

20°C, lyophilized, ground, dried at 105°C and analyzed for organic C concentration by use

of an Elementar Vario EL III CNS Analyzer. As the soil aggregates do not contain

carbonates (data not shown) and dissolved organic matter (DOM) was removed during

density fractionation, collected soil organic carbon (SOC) can be interpreted as POC.

5.3.6 Phospholipid fatty acid (PLFA) extraction and analysis

Similar to the measurement of POM release, 5 variants (Con0, Con1, Con14, Nem1 and

Nem14) with 5 replications were prepared. After incubation, samples were directly stored

at -20°C for later PLFA analysis.

Extraction of PLFAs from soil aggregates was performed following Frostegård et al.

(1993). Briefly, 2 to 3 g of soil substrate (wet weight) were extracted with Bligh/Dyer

Soil microbial communities and POM occlusion

solvent (chloroform:methanol:citrate buffer ratio of 1:2:0.8, ph 4). Lipids were fractionated

into neutral lipids, glycolipids and PLFAs on a silica column (HF BOND ELUT – SI, Varian

Inc.) by elution with chloroform, acetone and methanol, respectively. PLFAs were

subjected to mild alkaline methanolysis, resulting in fatty acid methyl esters (FAMEs),

which were extracted with hexane-chloroform. Methylnonadecanoate (19:0) was used as

internal standard. FAMEs were dissolved in isooctane and stored at -20ºC until analysis.

PLFAs were analyzed by gas chromatography using an Agilent 7890 gas chromatograph

(GC) and flame ionization detector (FID) equipped with an HP Ultra 2 capillary column

(25 m x 0.2 mm i.d., film thickness 0.33 µm) and a computer associated software

(Sherlock Pattern Recognition Software, MIDI®). The system was operated in split mode

(1:40) with hydrogen as carrier gas. The oven temperature program started with 170°C

and increased by 28°C min-1 to 288°C, followed by 60°C min-1 to 310°C (hold time 1.3 min).

FAMEs were identified on the basis of their retention times in comparison to a standard

mixture. Correct identification, i.e. chain length and saturation, was verified by GC-mass

spectrometry (GC-MS). Representative samples were analysed with an Agilent Series

7890A GC connected to a Mass Selective Detector (Agilent 7000 Triplequadrupole)

equipped with HP5MS capillary column (30 m x 0.25 mm i.d., film thickness 0.25 µm),

operated in splitless mode with helium as carrier gas. Oven temperature program sated at

40°C and increased by 46°C min-1 to 200°C, followed by 5°C min-1 to 238°C, 120°C min-1

to 295°C and 2°C min-1 to 300°C, held for 2 min. A mass range of 40 to 400 m z-1 was

monitored in scan mode.

The microbial community was assigned using the PLFA 18:2ω6 for saprotrophic fungi, and

i15:0, a15:0, i16:0, i17:0, a17:0, cy17:0, 17:0 10-meth, cy19:0, 16:1ω7, 17:1ω8 and

18:1ω7 for bacteria according to Frostegård et al. (1993), Frostegård and Bååth (1996)

and Zelles (1999). The total amount of PLFAs represents a mean for microbial biomass

(Zelles, 1999). For more details see Table 5.

Frederick Büks (doctoral thesis 2017)

Table 5: List of group specific PLFAs used in the present study.

Target group PLFA References

Actinobacteria 10-meth16:0 Kroppenstedt (1985); Vestal and White (1989); Mirza et al. (1991)

10-meth-17:0

10-meth-18:0

gram(+) Eubacteria 14:0 iso O’Leary and Wilkinson (1988); Vestal and White (1989); Zelles

(1997); Zelles (1999)

15:0 anteiso

15:0 iso

16:0 iso

17:0 anteiso

17:0 iso

gram(-) Eubacteria 17:0 cyclo O’Leary and Wilkinson (1988); Zelles (1997); Zelles (1999)

19:0 cyclo

Eubacteria 15:1 ω9c iso Bowman (2015)

16:1 ω9c iso Bowman (2015)

16:1 ω5c Nichols et al. (1986); Zelles (1997)

16:1 ω7c Guckert et al. (1991); Zelles (1999)

16:1 ω9c Zelles (1997)

16:1 ω11c Zelles (1997)

17:1 ω7c anteiso Bowman (2015)

17:1 ω9c anteiso Bowman (2015)

17:1 ω8c Kaneda (1991); Bühring et al. (2014)

18:1 ω7c Zelles (1999)

Fungi 18:2 ω6c Federle (1986); Frostegård and Bååth (1996); Stahl and Klug

(1996); Zelles (1999)

Plants 22:0 Zelles (1999); Ruess et al. (2007)

24:0 Zelles (1999); Ruess et al. (2007)

Animals 20:3 ω6c Hutzell and Krusberg (1982); Ringelberg et al. (1997); Watts

(2009); Buyer et al. (2010)

20:4 ω6c Lechevalier and Lechevalier (1988); Stanley and Nelson (1993);

Chen et al. (2001)

Miscellaneous origin 14:0 Balasooriya et al. (2014); Lange et al. (2014)

15:0

16:0

17:0

18:0

20:0

23:0

18:1 ω5c Hutzell and Krusberg (1982); O’Leary and Wilkinson (1988);

Zelles (1997)

18:1 ω9c Vestal and White (1989); Zelles (1999); Bååth (2003); Ruess et al.

(2007)

5.3.7 Mercury intrusion

The measurement of the pore size distribution within the soil aggregate sample was

performed using mercury intrusion (Porosimeter 2000 WS, Carlo Erba Instruments). The

soil aggregate sample (0.51 g) was air-dried for 24 hours at 40°C and measured using a

maximum test pressure of 200 MPa and a pressure decrease of 3.6 MPa min-1 at 26.1°C

(find additional data in the supplements). Data are given for pore sizes between 0.005 and

Soil microbial communities and POM occlusion

50 µm representing the non-draining intra-aggregate pore space, which is filled with water

at field capacity (Blume et al., 2015).

5.3.8 Statistics

Data of Nematode density, POC release and PLFA composition analyzed with Shapiro and

Wilk's test as well as Levene's test are assumed to be normal distributed (Shapiro and

Wilk, 1965) and have homogeneity of variance (Lim and Loh, 1996), respectively. Basal

respiration was expressed as simple moving average with a span of 4 adjacent sampling

times. The characteristics of the triplicate with the largest ratio of CO2 emission to soil

water content was chosen for later incubation. A repeated measurement design (two-

factorial ANOVA, p≤0.05) was used to test for differences between Nematode and control

samples in both nematode density and PLFA composition (von Ende, 2001). Data of POM

release were analyzed using one-way analysis of variance (ANOVA, p≤0.05) followed by

Tukey's test (Christensen, 1996).

5.4 Results

5.4.1 Soil respiration

As dry soils showed nearly no CO2 emission, wetting resulted in a respiration maximum

around 6 µg CO2 g-1 h-1 after 17 hours and a basal respiration of about 2.7 µg CO2 g-1 h-1

after 60 hours in all samples. In the first 20 hours after wetting, samples of 50% water

holding capacity exhibit a lower basal respiration compared to samples of 70% and 80%,

which had quiet similar CO2 emissions. (Fig. 7)

On the basis of these data, a water holding capacity of 70% was chosen for pre-incubation

in all experiments, for it provides highest bacterial metabolic activity and sufficient air

capacity after application of Nematodes.

Frederick Büks (doctoral thesis 2017)

5.4.2 Population development

On average 367 nematodes g-1 dry soil were added to each inoculated sample. Nematode

counting after 1, 6 and 14 days points to a stable population with numbers between 187

and 239 nematodes g-1 soil (Fig. 8). In control soils few endogenous nematodes were

recorded with densities below 1 individual g-1 dry soil until day 6, which slightly increased

to 5 and 18 individuals g-1 dry soil at day 14 in two of the six replicate samples. Overall,

control samples comprised very few to no nematodes, whereas inoculated aggregate

samples function as habitat for a significantly higher and nearly stable nematode

population (p=0.0026) containing a large number of young nematodes at day 14 (not

counted).

Fig. 7: Soil respiration of dry samples (day -72 to 0) and samples with 50%, 70% and 80% (day 0 to 72)

water holding capacity. Data are presented as simple moving average. Peaks at -72 and 0 h are caused by

opening the device and have to be ignored.

-72 -60 -48 -36 -24 -12 0 12 24 36 48 60 72 84 96

0,00

2,00

4,00

6,00

8,00

10,00

12,00

14,00

16,00 50% water holding capacity

70% water holding capacity

80% water holding capacity

time [h]

respiration [µg CO g-¹ h-¹]

Soil microbial communities and POM occlusion

5.4.3 POC release

A comparison of the POC release – defined as ratio of the organic carbon release per

energy level (Cfrac) to the sum of organic carbon of all light fractions and the sediment (CΣ)

– shows a high similarity between the variants (Fig. 9): Tukey's test does not show

significant differences for 0, 50 and 100 J ml-1, neither between sampling dates of one

variant nor between variants for a fixed point in time. However, at day 14 the oLF150

release of the Nematode samples is reduced compared to day 1, amounting to 1.6% of CΣ

or 0.13 mg C g-1, respectively. The average relative POC release amounts to 5.9% in the

fLF, 9.4% in the oLF50, 2.8% in the oLF100 and 1.9% in the oLF150, whereas 80% of the POC

remain in the soil matrix. The absolute POC releases in mg POC g-1 dry soil show very

similar relations and significances (see supplements).

The cumulative POC release of both treatments shows a tendency (p=0.08 for Nem and

p=0.06 for Con) to decrease from day 0 (2.0 mg C g-1) to day 1 (1.8 C g-1) and further to

day 14 (1.6 C g-1) after stepwise application of 3x50 J ml-1.

Fig. 8: Population development of nematodes (individuals g-1 dry soil)

in 9 soil aggregate samples with (■) and 9 without (x) amendment of

Acrobeloides buetschlii after 1, 6 and 14 days of incubation at 20°C.

0 2 4 6 8 10 12 14

100

150

200

250

300

350

400

450

500

Con

Nem

incubation time [d]

abundance [individuals/g soil]

Frederick Büks (doctoral thesis 2017)

5.4.4 PLFA analysis

The total amount of PLFAs, as measure for microbial biomass, ranged from 28.0 to

42.5 nmol g-1 dry soil. No significant differences between samples colonized by A.

buetschlii and control samples were detected, and also no significant variation of microbial

biomass over time (Fig. 10). Both inoculated and control samples have total PLFA

concentrations of 17.4 to 28.3 nmol g-1 for Eubacteria, 6.0 to 9.0 nmol g-1 for gram positive

bacteria, 1.7 to 4.7 nmol g-1 for gram negative bacteria, 2.3 to 4.6 for Actinobacteria and

0.6 to 2.1 nmol g-1 for fungi, but do also not show different concentrations neither within the

phylogenetic groups nor regarding single PLFAs. The fungal population is surprisingly low.

From the 35 assessed individual PLFAs, only 20:4ω6c, a marker for soil animals,

significantly increases with the application of nematodes (p=0.05 at day 14).

Fig. 9: Relative POC release (mean values with standard deviations) of

samples with A. buetschlii and controls at different incubation times (0, 1 and

14 days) and applied ultrasonciation levels (0, 50, 100 and 150 J ml-1).

Significances are illustrated by Tukey test characters a, b and c.

0 50 100 150

0,02

0,04

0,06

0,08

0,1

0,12

0,14

control (day 0)

control (day 1)

nematodes (day 1)

control (day 14)

nematodes (day 14)

energy level [J/ml]

POC release [Cfrac/CΣ]

a a a a a

Soil microbial communities and POM occlusion

Fig. 10: Amount of group specific PLFAs in soil aggregate samples with (■) and without amendment of A.

buetschlii (x) at day 0, 1 and 14.

0 2 4 6 8 10 12 14

total eubacteria

t [d]

PLFA [nmol/g]

0 2 4 6 8 10 12 14

gram(-) eubacteria

t [d]

PLFA [nmol/g]

0 2 4 6 8 10 12 14

actinobacteria

t [d]

PLFA [nmol/g]

0 2 4 6 8 10 12 14

fungi

t [d]

PLFA [nmol/g]

0 2 4 6 8 10 12 14

total PLFA

control

nematode sample

t [d]

PLFA [nmol/g]

0 2 4 6 8 10 12 14

gram(+) eubacteria

t [d]

PLFA [nmol/g]

Frederick Büks (doctoral thesis 2017)

5.4.5 Mercury intrusion

The pore size distribution within the range of 0.005 to 50 µm is plotted in Fig. 11. At 90%

field capacity, pores <40 µm are filled with water. If the water content drops below 63%,

only pores of an equivalent diameter of 12.5 μm are completely filled with water, which

corresponds to the smallest known diameter of adult female A. buetschlii.

5.5 Discussion

The experimental setting featured environmental conditions that match the requirements of

soil-born grazing nematodes: Cultivation temperature and pH conform to literature and are

related to metabolic optima of A. buetschlii (Frey, 1971; Korthals et al., 1996; Venette and

Ferris, 1997). The measured nematode-free soil basal respiration of about

2.7 µg CO2 g-1 h-1 exceeds data reported from a regional-scale survey in Northeastern

Germany by the 2-fold (Wirth, 1999), with corresponding values in microbial carbon

(Cmic=352±44 mg kg-1 soil). Furthermore, the bacterial PLFA amount with an average

22.7 nmol g-1 dry soil aggregates during the experimental period conforms to literature

Fig. 11: Cumulative pore space diagram of macro-aggregates from a sandy

agricultural soil. The dotted line marks the body diameter of adult A. buetschlii.

0 5 10 15 20 25 30 35 40 45 50

100

mean pore diameter [µm]

pore space [%]

Soil microbial communities and POM occlusion

values (Bååth and Anderson, 2003). This implies a normal microbial activity and

abundance provided by the experimental soil substrate. As in addition sandy agricultural

soils in temperate regions are proved to be a habitat for A. buetschlii (Korthals et al.,

1996), an adequate bacterial food source can be reasonably assumed. This is supported

by the stable A. buetschlii population, which amounts ~1.4 times the Cephalobidae

density of a comparable agricultural soil (Scharroba et al., 2012). Nematode densities of

further soils from field and laboratory experiments show this density as above-avarage

(Yeates and Brid, 1994; Dmowska and Ilieva, 1995; Bouwman et al., 1996; Yeates et al.,

1999; Kästner and Germershausen, 2014). Additionally, the increased proportion of

juvenile nematodes occurring in the inoculated samples of day 14 (data not shown)

underpin the existence of a feasible environment to support nematode development and

accords to generation times found by Nicholas (1962). Furthermore, Ackermann et al.

(2016) reported a chemotactic perception of food sources by A. buetschlii within 6.6 cm.

This points to perceptibility of food sources at every point within the PET flask and a

potential migration of A. buetschlii within the whole soil sample. The soil moisture was

adjusted to high values that most probably provide connectivity between habitable pores.

Sufficient oxygen supply is expected, as anaerobic conditions appear as a shift in

abundance towards anaerobic bacterial taxa, e.g. represented by vaccenic type fatty acids

(e.g. ω7 type) (Zelles, 1999). Measured PLFAs do not show such a shift, pointing to

constant aerobic conditions during the whole incubation period.

However, no influence of the inoculum on POM occlusion and PLFA composition was

observed: The tendency of both variants to increase POM occlusion over time suggests a

rebuilding of aggregate structure after slaking induced by the initial wetting (Beare and

Bruce, 1993), but the occlusion of POM is not influenced by the application of nematodes.

This might be due to minor influence of nematode grazing on the abundance and

composition of the microbial community: The bacterial groups, represented by cumulated

amounts of specific PLFA markers, do not show any differences between nematode

samples and the control. This suggests no shift within major bacterial groups, e.g. gram

positive forms or acidobacteria. Also 34 of 35 individual PLFAs do not show significant

differences of amount and proportion between the variants. Only 20:4ω6c, a marker for

soil animals (Ruess and Chamberlain, 2010), is significantly enriched after nematode

application. This PLFA was most likely derived from the inoculated nematodes, yet

Frederick Büks (doctoral thesis 2017)

Protozoa developing in the soil may be an additional source. The PLFA 16:1ω5c showed a

tendency to decline in the presence of nematodes, suggesting nematode feeding on

bacteria. However, as 16:1ω5c is a general bacterial marker (Ngosong et al., 2012), no

specific group as nematode prey can be assigned. In sum, the limited shift between

aggregate soil with/without nematodes indicates only a small influence of grazing on the

soil microbial community.

Different reasons can be considered for the lack in hypothesized grazing effects:

1) The Nematodes do not feed upon the given microbial community. Although this is not

directly tested, refusing food seems implausible in the present study due to proper habitat

quality and observed nematode reproduction. Moreover, A. buetschlii is an opportunistic

bacterial feeder with a broad feeding range (Nicholas, 1962; Bird and Ryder, 1993; Venette

and Ferris, 1998).

2) Extracellular polymeric substance is known to be a hindrance against grazing. However,

whether this barrier is highly protective against certain grazers leading to preservation of

nearly the whole biofilm population or incompletely effective depends on various factors

such as biofilm architecture, toxicity or signaling and cannot be estimated in the present

study. (Höckelmann et al., 2004; Matz et al., 2004; Weitere et al., 2005)

3) Biofilms might be ineffectual for POM occlusion in sandy soils. The influence of biofilms

on aggregate formation is assumed to be weaker in sandy than in clayey soils, as mainly

silt, clay and small organic particles are bound by the biofilm extracellular matrix (EPS)

and protection of bacteria against grazers is enhanced by a fine pored, hardly accessible

habitat (Chenu, 1995; Chenu and Stotzky, 2002; Six et al., 2004). However, work on the

same sandy soil indicates a slight influence of EPS on the occlusion of POM (Büks and

Kaupenjohann, 2016).

4) Grazing Nematodes might be restricted to zones, whose bacterial population do not

contribute to the POM occlusion: At field capacity, soil pores <50 µm are water-saturated.

In the present study the soil water content reaches up to 90% field capacity, which allows

free swimming of Nematodes within the non-draining pore space <40 µm as well as gliding

even in thin water films within larger pores (Wallace, 1968). However, the motility of A.

buetschlii is restricted to pores larger than its body diameter, here 12.5 µm equal to ~37%

of the non-draining pore space of the present soil. Further ~22% of the non-draining pore

space have diameters <0.3 µm and are therefore not colonized by bacteria (Foster, 1988),

Soil microbial communities and POM occlusion

whereas all larger pore size classes, aggregate surfaces and the inter-aggregate space

are inhabited by bacterial communities. As a result, 41% of the non-draining pore space

comprise pores between 0.3 and 12.5 µm, that contain bacteria, which are spatially

protected against nematode grazing. This is in accordance with data of Ranjard and

Richaume (2001), who found that in sandy soils the majority of the bacterial population is

located in the inner part of soil aggregates, mainly in micropores <9 µm within aggregates

<100 µm, and also matches data of Winding et al. (1997). This undisturbed bacterial

community might be the agent for soil aggregation: Following a comprehensive review of

Tisdall (1996), the hierarchical structure of soil aggregates base upon “minor”

microaggregates (<20 µm), which are built of clay-humus-complexes associated with silt

particles, partly humified bacterial debris and exudates, mineral incrustations and even on

this level bacterial colonies. Larger microaggregates (<250 µm) consist of these elements

and further POM. Considering the function of bacterial macromolecular exudates on soil

aggregation (Chenu and Stotzky, 2002), spatially protected intra-aggregate bacteria could

play a role in POM occlusion, whereas grazed bacteria in large pores are subject to a

higher turnover rate and not able to establish a permanent structure for sticking primary

particles. Referring to the similar POM release in both treatment variants, also the

mechanical force generation of A. buetschlii does not suffice to overcome physico-

chemical bonds and to move/separate soil particles to reach new grazing sites within

microaggregates.

We propose to explain the missing effect of A. buetschlii on POM occlusion in the following

way. A. buetschlii most probably feed on EPS within the accessible pore space, but is not

able to reach bacteria in smaller mesopores. On its grazing sites, feeding is non-selective

and maintains a growing bacterial population resulting in an equilibrium and hence

constant PLFA amounts comparable to the control (Ingham et al., 1985). The bacterial

community of smaller mesopores, which is supposed to provide POM occlusion within soil

aggregates, remain protected against grazing. In consequence, A. buetschlii is not able to

influence the POM occlusion. However, deeper investigations are necessary to prove this

explanation. Long-term effects on soil structure, e.g. due to acclimatization of A. buetschlii

or mineral N exudation (Ferris et al., 1997), were excluded from this work. Further

experiments with different soils and nematode taxa as well as longer incubation time are

necessary.

Frederick Büks (doctoral thesis 2017)

5.6 Conclusions

We hypothesized a grazing influence of an excess population of A. buetschlii on soil PLFA

composition concomitant with a change of POM occlusion. This hypothesis has to be

refused, as a large, stable and fertile population of A. buetschlii only marginally affected

the soil PLFA composition and had no influence on POM occlusion in aggregates of a

sandy agricultural soil. This is explained by a majority of inadequate pore diameters

hindering A. buetschlii to access the finer pore space of microaggregates. However, the

bacterial communities in those microaggregates are assumed to contribute to aggregation

and POM occlusion.

5.7 Acknowledgements

This project was financially supported by the Leibnitz-Gemeinschaft (SAW Pact for

Research, SAW-2012-ATB-3). Our thanks go out to the Department of Building Materials

and Construction Chemistry (TU Berlin) for the possibility to use their Mercury Intrusion

Porosimeter and to it's helpful staff.

Soil microbial communities and POM occlusion

6 Two different microbial communities

did not cause differences in occlusion

of particulate organic matter in a sandy

agricultural soil

6.1 Abstract

Apart from physico-chemical interactions between soil components, microbial life is

assumed to be an important factor of soil structure forming processes. Bacterial exudates,

the entanglement by fungal hypae and bacterial pseudomycelia as well as fungal glomalin

are supposed to provide the occlusion of particulate organic matter (POM) through

aggregation of soil particles.

This work investigates the resilience of POM occlusion in face of different microbial

communities under controlled environmental conditions. We hypothesized that the formation

of different communities would cause different grades of POM occlusion. For this purpose

samples of a sterile sandy agricultural soil were incubated for 76 days in bioreactors.

Particles of pyrochar from pine wood were added as POM analogue. One variant was

inoculated with a native soil extract, whereas the control was infected by airborne microbes.

A second control soil remained non-incubated. During the incubation, soil samples were

taken for taxon-specific qPCR to determine the abundance of Eubacteria, Fungi, Archaea,

Acidobacteria, Actinobacteria, α-Proteobacteria and β-Proteobacteria. After the incubation

soil aggregates (100 to 2000 µm) were collected by sieving and disaggregated using

ultrasound to subject the released POM to an analysis of organic carbon (OC).

Our results show, that the eubacterial DNA of both incubated variants reached a similar

concentration after 51 days. However, the structural composition of the two communities

was completely different. The soil-born variant was dominated by Acidobacteria,

Actinobacteria and an additional fungal population, whereas the air-born variant mainly

contained β-Proteobacteria. Both variants showed a strong occlusion of POM into

aggregates during the incubation. Yet, despite the different population structure, there were

only marginal differences in the release of POM along with the successive destruction of soil

aggregates by ultrasonication. This leads to the tentative assumption that POM occlusion in

agricultural soils could be resilient in face of changing microbial communities.

Frederick Büks (doctoral thesis 2017)

6.2 Introduction

Microbial communities play an irreplaceable role in soil ecosystems. Due to their metabolic

diversity and abundance, especially bacteria and Fungi have considerable influence on

mineral and organic matter transformation (Torsvik and Øvreås, 2002; Gianfreda and Rao,

2004; Uroz et al., 2009; Madigan et al., 2015) and often represent the first element in

manifold faunal food webs. They also release a broad variety of molecules involved in

nutritional or functional cell-plant symbioses supporting plant growth and health (Pühler et

al., 2004; Van Der Heijden et al., 2008).

This work focus on a further ecological function of microbial communities: There is

evidence, that the soil microbial community takes part in soil aggregate formation, which is

supposed to be positively related to the occlusion of particulate organic matter (POM)

within soil aggregates. The grade of occlusion influences the carbon cycle, as occluded

POM is superior protected against microbial degradation compared to free POM and

mutually promotes development of stable macroaggregates. (Jastrow and Miller, 1997;

Bronick and Lal, 2005; Brodowski et al., 2006a; Lützow et al., 2006)

The physico-chemical mechanisms underlying aggregate formation comprise interactions

between permanent and variable charges of silicates, (hydr)oxides of Fe, Al and Mn,

phosphates, carbonates, DOM and POM, which are meditated by multivalent cations with

small hydrate shells (e.g. Ca2+, Fe3+ and Al3+), and also hydrophobic interactions (Bronick

and Lal, 2005). Fine roots form a physical stabilizing network in and around soil

macroaggregates and release cementing root exudates (Bronick and Lal, 2005). The

microbial influence is supposed to be achieved by the following mechanisms:

(1) Hyphal Fungi and possibly Actinobacteria as well as filamentous colonies of

Cyanobacteria wrap and pervade soil aggregates and increase their mechanical strength

(Chenu and Cosentino, 2011). Length, strength, surface adherence and geometry of the

mycelia determine the contribution to the bulk stability (Chenu and Cosentino, 2011).

When disturbed e.g. by tillage, mycelia were found to be less contributive to the formation

of water stable aggregates than intact ones (Beare et al., 1997). Whereas fungal hyphae

are assumed to mainly stabilize macroaggregates by formation of a sticky string bag

(Gupta and Germida, 1988; Miller and Jastrow, 2000), actinobacterial pseudomycelia were

Soil microbial communities and POM occlusion

found both within and around soil microaggregates (Kanazawa and Filip, 1986; Ranjard

and Richaume, 2001; Mummey and Stahl, 2004).

(2) Microbial exudates and debris adsorb to soil particles and alter their surface properties,

e.g. increase the hydrophobicity which decrease water-caused dispersion of soil

aggregates (Chenu and Cosentino, 2011; Achtenhagen et al., 2015).

(3) Microbial biomineralization could cement or block soil particles at their contact regions

(Bronick and Lal, 2005). However, little is known about the influence on POM occlusion.

(4) Arbuscular Mycorrhizal Fungi (AMF) are able to produce a proteinaceous substance

opperationally defined as Glomalin Related Soil Fraction (GRSF) or – shortly – glomalin

(Wright et al., 1996; Rillig, 2004). It appears in large quantities in various soils (Wright and

Upadhyaya, 1998), but is most probably not an exudate, since Driver et al. (2005) showed

that >80% of the soil glomalin are strongly bond within hyphal cell walls even after harsh

extraction. Soil aggregates rich in glomalin showed a high mechanical stability. However,

the frequently found correlation between soil aggregate stability and glomalin

concentration (Rillig et al., 2002; Bedini et al., 2009; Hontoria et al., 2009; Spohn and

Giani, 2010; Fokom et al., 2012; Wu et al., 2014) does not necessarily imply glomalin as

an agent of soil aggregation, as for example undisturbed AMF populations could produce a

lot of glomalin while in effect aggregate soil particles by wrapping. Therefore the influence

of glomalin concentration on POM occlusion is hypothetical.

(5) In contrast to Fungi, the bulk of bacteria is assumed to encapsulate within a viscose

matrix of extracellular polymeric substance (EPS) as a reaction to diverse ecological

stressors (Roberson and Firestone, 1992; Davey and O'toole, 2000; Mah and O'Toole,

2001; Weitere et al., 2005; Chang et al., 2007; Flemming and Wingender, 2010; Ozturk

and Aslim, 2010). This biofilm contains in average 90% water (Zhang et al., 1998; Schmitt

and Flemming, 1999; Pal and Paul, 2008). Only 10% to 50% of the remaining dry mass

are microbial biomass, whereas the bulk mainly consists of extracellular macromolecules

like polysaccharides, extracellular DNA, proteins, lipids and humic substance (Flemming

and Wingender, 2010; More et al., 2014). As a result of the ubiquity (Davey and O'toole,

2000), mechanical strength (viscosity) (Möhle et al., 2007; Flemming and Wingender,

2010), structure (Van Loosdrecht et al., 2002) and distribution across the soil aggregate

(Nunan et al., 2003), biofilms are supposed to be an important factor of soil aggregation

(Baldock, 2002). However, the viscosity of EPS is affected by its molecular composition

Frederick Büks (doctoral thesis 2017)

(Ayala-Hernández et al., 2008), which strongly depends on species and environmental

conditions: For example, different single-species biofilms cultivated under similar

conditions have a strongly differing EPS composition (Béjar et al., 1998; Steinberger and

Holden, 2005; Celik et al., 2008). But also similar single-species biofilms show differently

composed EPS under varying environmental conditions as demonstrated for

Pseudomonas aeruginosa (Marty et al., 1992; Ayala-Hernández et al., 2008). Little is

known about the capability of different bacterial taxa to produce EPS. For example,

Rhizibia species are considered to be strong EPS producers within the phylum of α-

Proteobacteria (Rinaudi and Giordano, 2010), and the genetic ability to produce large

amounts of high-molecular polysaccharides and proteins was found in different

Acidobacteria (Ward et al., 2009). However, these sparse data do not allow predictions

about the potential of specific microbial communities to take part in POM occlusion.

The five above specified mechanisms are all supposed to affect POM occlusion, and all of

them are obviously influenced by the composition of the soil microbial community. The aim

of this work is to test the resilience of POM occlusion in face of the development of two

fundamentally different microbial communities in a sandy agricultural soil. In this case

study, a gamma-sterilized sandy soil with pyrogenic biochar amendment from pine wood

was inoculated in two variants with microbial and sterile soil extract and incubated for 76

days in a bioreactor at field capacity. The second variant was routinely exposed to room air

during sampling to initiate the development of an air-born bacterial population. We chose

this inoculation, to receive two complex populations that have no potential to converge

their taxonomic abundances, as Delmont et al. (2014) recently found that the development

of microbial communities is controlled by physical-chemical properties of soils rather than

the initial population: E.g. a population taken from a forest soil was given on a sterile

grassland soil and there developed like the original grassland population. The biochar was

used as a POM analogue, but also represents an upcoming class of soil amendments

(Lehmann and Joseph, 2015). During incubation the DNA of Eubacteria, Fungi, Archaea,

Acidobacteria, Actinobacteria, α- and β-Proteobacteria in soil samples from both variants

was quantified using taxon-specific qPCR. After incubation, soil aggregates of a size

between 0.1 and 2 mm were separated by sieving. Following the method of Golchin et al.

(1994), aggregates were treated with ultrasound, and the release of intra-aggregate

particulate organic carbon (POC) was quantified by use of POM density fractionation and

Soil microbial communities and POM occlusion

carbon analysis. The amount of released POC depends on the destruction of soil

aggregates, which is a function of applied energy, and gives information about the binding

strength of POM within the aggregates.

We hypothesized that the establishment of different microbial communities will lead to a

different occlusion of POM. A lower occlusion strength is attended by an increased POC

release when applying a specific amount of mechanical stress to soil aggregates under

further similar conditions.

6.3 Materials and methods

6.3.1 Preparation of soil and soil extracts

Air-dried soil from a sandy A-horizon (Su3) of an agricultural experimental site in Berge

(Germany) was sieved to <2 mm particle size and mechanically disaggregated in a mortar

to create an macroaggregate-free soil sample with Corg=8.7 mg g-1 dry soil. The soil sample

was amended with 5%vol of pyrogenic biochar (pine wood, PYREG® GmbH,

Dörth/Germany) with a particle size <0.1 mm (71% <40 µm, see supplements) and

homogenized by end-over end shaking. Subsequently, the biochar-soil-mixture was

sterilized with 40.000 Gy using a Cobalt-60 γ-radiation source and an exposure time of

2 weeks following McNamara et al. (2003). The resulting soil had a pH of 7.1 in

0.01 M CaCl2 solution, a four times increased Corg concentration of 36.2 mg g-1 and a grain

gross density of 2.54 g cm-3.

In addition, 1200 g of untreated fresh soil were extracted with 1560 ml of 10-fold diluted

modified R2A broth (0.1 g l-1 NH4NO3, 0.05 g l-1 yeast extract, 0.05 g l-1 soy peptone,

0.05 g l-1 casamino acids, 0.05 g l-1 glucose, 0.05 g l-1 soluble starch, 0.03 g l-1 K2HPO4,

0.0024 g l-1 MgSO4, pH 7.2±0.2, autoclaved at 121°C for 20 min) (Atlas, 2010) by end-over

end shaking for 3 h. The extract was filtered twice through two layers of laboratory tissue

paper and afterwards split into two halves. One half was autoclaved at 120°C for 20 min,

whereas the other half remained untreated to provide an inoculum with a soil-born

microbial population.

Frederick Büks (doctoral thesis 2017)

6.3.2 Incubation and sampling

Under sterile conditions, two triplicates of each 300 g sterile soil

were filled into pF-bioreactors (Fig. 12) and packed to get a

bulk density of 1.36 g cm-3. When closed and connected to a

hydrostatic head, the reactors provide constant matrix potential,

similar evaporation rates and sterile air supply for soil microbial

containment experiments. In the present study, the headspace

was continually replaced with a flow rate of 0.4 l min-1 by room

air filtered with an 0.2 µm membrane filter. The hydrostatic head

was 120 cm (pF 2.08) and thus provided a soil water content of

about 35.0%vol and a soil air content of 11.5%vol. The water

content of 35%vol equates to 77 ml soil solution. For example,

giving 100 ml soil extract to the dry sample, hence 23 ml are

subsequently removed by the hydrostatic head when water

tension is adjusted. The adjustment of soil water content was

tested in pre-trials with addition of 100 ml of tap water to 300 g

of dry soil sample – here the impounded water was rejected

within 15 min and the adjustment to 37%vol soil water content at

pF=2 took place within 4 days (data not shown). These

characteristics were also assumed for the main experiment.

The first triplicate (SPsoil) was inoculated with each 100 ml of

the non-autoclaved inoculum to reestablish the native microbial

population. The sterilized inoculate was given to the second

triplicate to start with an abiotic environment, that is susceptible

for infection by air-born microorganisms (SPair) when exposed

to unsterile air. Soil extract exceeding the adjusted soil water content was removed by the

hydrostatic head and discarded.

The soil columns were incubated for a total of 76 days. During the incubation, a stress

factor setting was established that includes warm-humid conditions from day 1 to 24, warm

and drying-out conditions between day 25 and 50 as well as cold-humid conditions from

day 51 to 76. This setting is supposed to promote EPS production and fungal growth

Fig. 12: pF-bioreactor

with its components A)

air supply composed of

diaphragm pump and

membrane filter, B) filter

column with soil sample

(dark grey) and filter

plate (dotted), C)

hydrostatic head (pale

grey) and D) liquid waste

container.

Soil microbial communities and POM occlusion

(Roberson and Firestone, 1992; Di Bonaventura et al., 2008; Borowik and Wyszkowska,

2016). Therefore, incubation took place at room temperature between 24.5°C and 32.5°C

until day 50 and at 8°C from day 51 to 76. Hanging water columns were disconnected at

day 24 and reconnected after addition of 100 ml of 10-fold diluted modified R2A broth at

day 50.

Soil sampling for DNA analysis was performed with sterile plastic pipes used as sampling

rings. About 500 mg composite sample compounded of soil from 3 evenly distributed

sampling points was taken from each column 18 and 29 h as well as 3, 5, 16, 49, 51 and

76 days after inoculation. The samples were filled in 2 ml reaction tubes and stored at

-20°C for later DNA extraction and quantification. During each sampling the bioreactors

with air-born cultures were exposed for 15 min to the unsterile room air to enforce

infection, whereas the soil-born variant was sampled in a cleanbench. After each

sampling, both variants were reconnected to sterile air supply.

After day 76, the soil was removed from the reactors and air-dried for 2 weeks in a laminar

flow hood. A pH of 6.8±0.3 was measured for all variants. Afterwards soil aggregates

between 0.1 and 2.0 mm in diameter were used for analysis of POM occlusion. In addition,

a non-incubated third triplicate (SPcontrol) was analyzed in the same way.

6.3.3 DNA extraction and qPCR

DNA was extracted from 370 mg dry soil equivalent by use of a NucleoSpin® Soil Kit

(MACHEREY-NAGEL GmbH & Co. KG, Düren/Germany) following the manual

instructions. DNA sample purity, represented by 260/230 nm and 260/280 nm extinction

ratios, was determined with a NanoDrop1000 spectrophotometer (NanoDrop Products,

Wilmington, DE, USA) and assessed as free of contamination (NanoDrop, 2008).

For quantification of different phylogenetic classes (Acidobacteria, Actinobacteria, α- and

β-Proteobacteria) and domains (Archaea, Eubacteria, Fungi), a quantitative real-time PCR

with specific primer pairs (Table 6) was performed using a QuantStudio™ 12K Flex Real-

Time PCR System (Life Technologies, Grand Island, NY/USA). The reaction mix per

sample contained 4 µl of 5x HOT FIREPol® EvaGreen® HRM Mix ROX (Solis Biodyne,

Tartu/Estonia), each 0.25 µl of the proper 10 pM fwd and rev primer solution (biomers.net,

Ulm, Germany; Table 7), 14.5 µl of PCR-H2O and 1 µl of template DNA solution.

Frederick Büks (doctoral thesis 2017)

Amplification of DNA templates was executed having an initial denaturation at 95°C for

15 min followed by 40 thermocycles consisting of a denaturation at 95°C for 15 sec,

annealing for 20 sec at primer-specific temperatures listed in Table 6 and elongation at

72°C for 30 sec. PCR was checked for consistency by melting curve analysis implemented

in the QuantStudio™ 12K Flex Real-Time PCR System. Extracted DNA from standard

organisms named in Table 6 was used as DNA standard for the relevant taxa, whereas

DNA of non-target organisms from soil samples in return functioned as negative control.

Sample-DNA dilution ranged between 1:1 and 1:100 in steps of 1:10.

Table 6: Target classes and domains, appropriate primer pairs, annealing temperatures (AT) and standard

organisms for qPCR. (AWI=Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research;

DSM=German Collection of Microorganisms and Cell Cultures; ZALF=Leibniz Center for Agricultural

Landscape Research)

Target organism Primer pair AT Standard organism (origin)

Archaea Ar109f / Ar915r 57°C Methanosarcina mazei (AWI)

Acidobacteria Acido31 / Eub518 50°C Acidobacterium capsulatum (DSM11244)

Actinobacteria Actino235 / Eub518 60°C Streptomyces avermitis (DSM46492)

α-Proteobacteria Eub338 / Alf685 60°C Agrobacterium tumefaciens pGV2260 (ZALF)

β-Proteobacteria Eub338 / Bet680 60°C Burkholderia phymatum (DSM17167)

Eubacteria Eub338 / Eub518 53°C Pseudomonas putida F1 (ZALF)

Fungi ITS1f / 5.8s 52°C Verticillium dahliae EP806 (ZALF)

Table 7: Applied primer sequences for class- and domain-specific qPCR.

Primer Primer sequence Reference

5.8s 5'–CGCTGCGTTCTTCATCG–3' Fierer et al. (2005)

Acido31 5'–GATCCTGGCTCAGAATC–3' Fierer et al. (2005)

Actino235 5'–CGCGGCCTATCAGCTTGTTG–3' Stach et al. (2003)

Alf685 5'–TCTACGRATTTCACCYCTAC–3' Lane (1991)

Ar109f 5'–ACKGCTCAGTAACACGT–3' Lueders and Friedrich (2003)

Ar915r 5'–GTGCTCCCCCGCCAATTCCT–3' Lueders and Friedrich (2003)

Bet680 5'–TCACTGCTACACGYG–3' Overmann et al. (1999)

Eub338 5'–ACTCCTACGGGAGGCAGCAG–3' Lane (1991)

Eub518 5'–ATTACCGCGGCTGCTGG–3' Muyzer et al. (1993)

ITS1f 5'–TCCGTAGGTGAACCTGCGG–3' Fierer et al. (2005)

Soil microbial communities and POM occlusion

6.3.4 Disaggregation of soil aggregates and quantification of POC

Successive destruction of soil aggregates by ultrasonication was used to release occluded

POM from its bonding sites (Kaiser and Berhe, 2014). Therefore, in a first step, 75 ml of

1.6 g cm-3 dense sodium polytungstate solution (SPT) were added to 15 g of air-dried

SPsoil, SPair and SPcontrol soil samples. After 30 min of SPT infiltration into the soil matrix and

centrifugation at 3,569 G for 26 min, the floating free light fraction (fLF) comprising non-

occluded POM was collected by filtering the SPT solution through an 1.5 μm pore size

glass fibre filter. In a following step, the remaining soil was filled up to 75 ml SPT solution

and ultrasonicated with 50 J ml-1 using a sonotrode (Branson© Sonifier 250) to destroy

weaker aggregate bonds and release occluded POM. After centrifugation, the floating

occluded light fraction (oLF50) was collected. For this purpose, the energy output of the

sonotrode was determined by measuring the heating rate of water inside a dewar vessel

(Schmidt et al., 1999). Then again the SPT solution was filled up to 75 ml and the sample

was treated with an additional energy of 450 J ml-1. After centrifugation, the floating

occluded light fraction (oLF500) and the “sediment”, which contains stronger bound POM as

well as molecular OM adsorbed to the mineral matrix, were separated and all separated

light fractions (LFs) and sediment samples were frozen at -20°C, lyophilized, ground and

analyzed for organic carbon concentration using an Elementar Vario EL III CNS Analyzer.

As dissolved organic matter (DOM) were leached by SPT solution during the first step of

density fractionation, extracted light fraction OC is interpreted as light fraction POC.

6.3.5 Statistical analyses

The statistical analysis of microbial populations and POC release comprised the

calculation of mean values, standard deviations and analysis of variance (p<0.05). After

application of the Shapiro-Wilk test (Shapiro and Wilk, 1965) and Levene test (Lim and

Loh, 1996) samples were assumed to be normally distributed and to have variance

homogeneity. Total bacterial populations were assumed to be similar in a sample, if the

absolute difference between the DNA mean values of both variants is smaller than the

averaged standard deviation. A repeated measurement design (two-factorial ANOVA) was

used to test for significant differences of class, domain and total DNA concentrations and

shares between SPsoil and SPair within the final period (von Ende, 2001). Particulate organic

Frederick Büks (doctoral thesis 2017)

matter releases of SPsoil, SPair and SPcontrol were analyzed using one way ANOVA followed

by Tukey's test (Christensen, 1996).

6.4 Results

6.4.1 Microbial population analysis

The DNA extracted from both incubated variants shows qualitative differences in the

composition of eubacterial populations and further quantitative differences in the fungal

population. It is expressed as ng DNA per mg dry soil (ng mg-1) and includes intra- and

extracellular DNA. (Fig. 13)

The sum of total measured DNA (DNAtot=DNAEUB+DNAFUNG+DNAARCH) in SPair averages

2 ng mg-1 until day 6, increases to 13.6 ng mg-1 at day 49 and decreases again to

6.8 ng mg-1 until day 76. In contrast, SPsoil quickly increases from 2.4 ng mg-1 at the

beginning to 19.6 ng mg-1 at day 6 and then decreases to 11.4 ng mg-1. Between day 51

and 76 (final period) both variants show a parallel development, but a significant difference

in DNA abundance (p=0.049), which is mainly due to fungal DNA. However, both variants

have similar total eubacterial populations (DNAEUB, amplified with Eub338/Eub518 primer

pair) within the final period with growth curves similar to DNAtot. From day 49 to day 76 the

population densities of both variants converge. Within the final period their difference fall

below the threshold for similarity.

Fungi (DNAFUNG) show nearly no growth in SPair and remain at DNA concentrations below

0.2 ng mg-1, whereas the fungal population of SPsoil grows from 1.11 ng mg-1 at day 0 to 5.6

at day 49 and then decreases to 4.7 ng mg-1. Fungal populations of SPsoil and SPair differ

significantly within the final periode (p=0.001). In contrast, the amount of archaeal DNA

(DNAARCH) remains <0,002 ng mg-1 in both variants and does not show a significant

difference.

Some eubacterial classes show significant differences between the variants. The amount

of acidobacterial DNA differs significantly within the final period (p=0.003). While SPair does

not exceed values of 0.3 ng mg-1, the DNA concentration in SPsoil increases from

Soil microbial communities and POM occlusion

0.4 ng mg-1 to values between 2.19 and 3.2 ng mg-1. Actinobacteria in SPair exhibit a nearly

constant DNA concentration <0.5 ng mg-1. In contrast, the SPsoil population quickly rises to

1.7 ng mg-1 at day 6 and then decreases to 1.0 ng mg-1 at day 76. Although SPsoil shows an

in tendency higher population then SPair, differences of both variants within the final period

are not significant (p=0.067). The concentration of α-proteobacterial DNA in SPsoil quickly

rises from 0.1 ng mg-1 to 1.0 within 6 days and then decreases continuously to 0.4 ng mg-1,

whereas SPair does not exceed 0.2 ng mg-1. Within the final period there are no significant

differences between the variants (p=0.237). Among the examined eubacterial classes, only

β-Proteobacteria show a significantly higher population in SPair than in SPsoil: Until day 16

the DNA concentration in SPair remains smaller than 0.1 ng mg-1, but increases to

5.9 ng mg-1 at the end. In contrast, SPsoil quickly increases to 2.8 ng mg-1 at day 6 and then

stabilizes at around 0.9 ng mg-1.

The DNA of eubacterial taxa as a percentage of the total eubacterial DNA (Table 8) shows

a dominance of Acidobacteria in SPsoil reaching shares of 32.7% (day 51) and 36.8% (day

76), whereas values in SPair stay below 0.9% (p=0.002). Actinobacteria show a 3-fold

higher percentage of around 14.6% in SPsoil compared to SPair within the final period

(p=0.057). In SPair and SPsoil, α-Proteobacteria show percentages of around 2.4% and

5.2%, respectively, and therefore do not represent a dominant class (p=0.27). In strong

contrast, β-Proteobacteria hold increasing percentages of 79.8% and 88.1% in SPair

compared to 8.8% and 12.3% in SPsoil (p=0.023). Cumulation shows that these classes

cover 88.9% to 96.6% in SPair, mainly dominated by β-Proteobacteria, and 60.9% to 69.1%

in SPsoil, that is dominated by Acidobacteria, Actinobacteria and also Fungi. In both variants

these classes hold an increasing percentage of the total DNA over time.

Frederick Büks (doctoral thesis 2017)

Fig. 13: DNA concentrations of phylogenetic classes and domains in soil with natural inoculate (SPsoil) and

air-born infection (SPair) (values in ng DNA per mg dry soil; * marks samples with p<0.05; n=3)

0 10 20 30 40 50 60 70 80

0,5

1,5

2α-proteobacterial DNA

t [d]

DNA [ng/mg dry soil]

0 10 20 30 40 50 60 70 80

0,5

1,5

2archaeal DNA

SPair

SPsoil

t [d]

DNA [ng/mg dry soil]

0 10 20 30 40 50 60 70 80

5acidobacterial DNA*

t [d]

DNA [ng/mg dry soil]

0 10 20 30 40 50 60 70 80

5actinobacterial DNA

t [d]

DNA [ng/mg dry soil]

0 10 20 30 40 50 60 70 80

14 fungal DNA*

t [d]

DNA [ng/mg dry soil]

0 10 20 30 40 50 60 70 80

14 β-proteobacterial DNA*

t [d]

DNA [ng/mg dry soil]

0 10 20 30 40 50 60 70 80

25 total DNA

t [d]

DNA [ng/mg dry soil]

0 10 20 30 40 50 60 70 80

25 eubacterial DNA

t [d]

DNA [ng/mg dry soil]

Soil microbial communities and POM occlusion

Table 8: Measured eubacterial class DNA of SPair and SPsoil in relation (%)

to the total eubacterial DNA at days 49, 51 and 76. Within the final period

(day 51 to 76) the total eubacterial population is assumed to be similar

between both variants. P-values are given for comparison of shares within

the final period. (n=3)

Eubacterial class SPair SPsoil

at day 51 76 51 76 p-value

Acidobacteria 0.79 0.86 32.69 36.77 0.002

Actinobacteria 5.97 5.51 14.94 14.23 0.057

α-Proteobacteria 2.37 2.51 4.55 5.85 0.270

β-Proteobacteria 79.75 88.10 8.83 12.27 0.023

sum 88.88 96.57 60.88 69.12

6.4.2 POC release

The relative light fraction POC release Crel is defined as the ratio of the POC release at the

respective energy level (Cfrac) to the cumulative POC release of all collected light fractions

plus the sediment (Ctot), expressed by Cre=Cfrac·Ctot-1.

SPsoil and SPair do not differ in their relative fLF release, which is around 4.6% of the Ctot. In

contrast, the fLF release of SPcontrol amounts to 44.7% (Fig. 14). SPsoil releases 2.4% of the

Ctot within the oLF50, whereas SPcontrol releases 10.3% (p=0.051). SPair lies in between

releasing 6.3% without a significant difference to both. At 500 J ml-1, all variants release

similar percentages of Ctot. The POC release of SPsoil and SPair is similar to the amount

released at 50 J ml-1, whereas SPcontrol is reduced to 1.3%. SPair shows a tendency to

exceed SPsoil and SPcontrol.

The carbon content of each sediment corresponds to the sum of the respective light

fraction POC release and amounts to 92.3% (29.9 mg g-1) in SPsoil, 83.9% (26.5 mg g-1) in

SPair and 43.8% (15.8 mg g-1) in SPcontrol. Thus, only SPcontrol shows a significantly reduced

carbon content remaining in the soil matrix. In consequence, the C-release from SPsoil and

SPair does not differ significantly in any fraction (although SPair shows a tendency to

release more POC than SPsoil in both occluded light fractions). In contrast, SPcontrol loses

nearly half of its Ctot in the fLF and additional 10% after application of 50 J ml-1.

Frederick Büks (doctoral thesis 2017)

6.5 Discussion

The total eubacterial DNA in SPsoil und SPair converge between day 6 and day 49 and

match the condition for similarity between day 51 and day 76 (the final period). Also the

observed eubacterial classes in both variants seem to be established until day 51 and

show a stable or slightly decreasing population development within the final period (Fig. 8).

This development lead to a cumulative percentage of Acidobacteria, Actinobacteria, α-

Proteobacteria and β-Proteobacteria on total eubacterial DNA, that increases from 88.9%

to 96.6% in SPair and from 60.9% to 69.1% in SPsoil. It can be seen that this bundle of

eubacterial classes holds the majority in both variants and becomes increasingly

dominant. For these three reasons, the effect of named eubacterial as well as fungal and

archaeal populations on POM occlusion is discussed based on the final period.

Although there is a similar total eubacterial DNA amount, the population structure is

strongly varying between the variants: Acidobacteria and β-Proteobacteria show a

significant and Actinobacteria an in tendency but not significant difference between

variants, whereas α-Proteobacteria, which have low abundances (<6%) in both variants,

did not develop differently. Beside Eubacteria, a fungal population developed in SPsoil,

Fig. 14: Relative POC release of the variants SPsoil, SPair, SPcontrol at different energy

levels (0, 50, 500 J ml-1). The highest carbon release is associated with the lowest

occlusive strength of POM at the respective energy level. (n=3)

fLF oLF(50) oLF(500)

0,00

10,00

20,00

30,00

40,00

50,00

60,00 SPsoil

SPair

SPcontrol

energy level [J/ml]

POC release [Cfrac/CΣ]

Soil microbial communities and POM occlusion

whose DNA spans 27.2% to 41.4% of the total measured population (DNAtot), whereas

only very small amounts of fungal DNA were found in SPair samples. Hence, ecosystems of

both variants were dominated by strongly different microbial classes: During the final

period Acidobacteria, Actinobacteria and Fungi together hold 61.9% to 71.3% of the total

measured DNA in SPsoil. In contrast, SPair is strongly dominated by β-Proteobacteria, which

provide 79.4% to 87.3% of the total measured DNA. We conclude, that both variants differ

in their community structure within the final period. Following our hypothesis, this implies a

different POM occlusion in SPsoil and SPair.

A strong occlusion of POM during incubation becomes apparent comparing the incubated

variants with SPcontrol: The carbon content in the fLFs of SPsoil and SPair decreased, while

increased in the sediment. However, contrary to our hypothesis SPsoil and SPair do not

show a significant (p<0.05) difference of POM occlusion in any fraction, although SPsoil has

a tendency to release less POC. Even considering a relation of microbial development and

POM occlusion in single parallels, no correlation of the growth of a specific taxon and POM

occlusion was observed (data not shown). The occlusion in both variants is extensive:

Total occluded POC amounts to ~30 mg g-1 dry soil in both variants and therefore exceed

occlusion in comparable soils by four-fold (Büks and Kaupenjohann, 2016). Our POM

mainly consists of pyrochar particles <20 µm. Since Kaiser and Berhe (2014) reviewed,

that microaggregates <63 µm are stable in face of ultrasonication levels >500 J ml-1, an

occlusion within very stable microaggregates of the sediment is expected. The main

biological agent for this occlusion is most likely bacterial EPS (Six et al., 2004). Thus, in

the present study POM occlusion exceeds that of a native soil, but is most probably not

affected by the community composition.

However, triplicates usually do not provide sufficient test power to avoid type 1 and 2

errors. Therefore the convention of p<0.05 only gives a weak statement. If instead

discussing the in tendency increased POM occlusion in SPsoil as a fact, fungal glomalin

and archaeal EPS can be refused as relevant mechanisms: As AMFs are obligatory

symbionts of plant roots (Bago and Bécard, 2002), remains of glomalin might exist in the

soil sample as a remain from the field, but neither are expected to differ between the

variants nor could be enriched by fungal growth. Also archaeal EPS (Fröls, 2013) could be

excluded, since Archaea hardly exist in both variants. Low-molecular weight exudates and

biomineralization could play a role in physico-chemical POM occlusion, but chemical

Frederick Büks (doctoral thesis 2017)

diversity and unknown effect levels do not allow an estimation of their influence in the

present study.

Fungi are highly abundant in SPsoil. Therefore, wrapping of macroaggregates by fungal

hyphae is expected to enhance POM occlusion. In contrast, Actinobacteria, which are

assumed to have the capability to form microaggregates, show only slight differences

between the variants and are therefore not supposed to contribute to the occlusion of

POM. (Aspiras et al., 1971; Gasperi-Mago and Troeh, 1979; Tisdall, 1991; Bossuyt et al.,

2001)

As the broad molecular diversity of EPS (Leigh and Coplin, 1992; Votselko et al., 1993;

Allison, 1998; Al-Halbouni et al., 2009; Flemming and Wingender, 2010; Ras et al., 2011)

develops in dependency of species and environmental factors and affects viscosity, it

seems self-evident that two different complex multi-species biofilms should show different

binding strength of POM within soil aggregates. However, even assuming no influence of

other microbial binding mechanisms, the bacterial community composition seems to be

less relevant in the present study. What are the explanations?

First, relicts of the original EPS could endured drying, mechanical dispersion, γ-sterilization

and recolonization along the whole soil treatment and form a background load, which

overlays the effect of the newly built EPS on POM occlusion. This explanation for similar

POM occlusion of SPsoil and SPair seems improbable due to γ-degradation and

metabolization (Kitamikado et al., 1990; Wasikiewicz et al., 2005), but cannot finally be

ruled out in this work. More likely, the different microbial development in both incubated

variants (1) causes only a little difference in EPS molecular composition, that is not

sufficient to affect POM occlusion in large extent, or (2) the span of possible molecular EPS

compositions has in general no significant influence on the mechanical characteristics of

EPS. Furthermore, (3) despite a broad acceptance of EPS as agents of soil aggregation, its

influence could be of minor importance under certain conditions (e.g. in sandy soils). (4)

Probably, but also not tested, similar POM occlusions in both variants can be caused by a

multi-species balancing mechanisms, in which a loss of coherence due to the dominance

of one group of taxa is compensated by another group.

Our results only give a first insight to the relation of microbial community composition and

POM occlusion. A more quantitative analysis would require more replicate samples,

manifold microbial communities and probably soils from different land use. This was

Soil microbial communities and POM occlusion

beyond the scope of the present study. Our findings show that soil-microbial ecosystems

with vastly different community structures can develop a nearly similar grade of POM

occlusion. This implies that soil ecosystems could be able to compensate the influence of

population shifts on POM occlusion.

6.6 Conclusions

Our incubation experiment demonstrated the possibility to breed stable soil aggregates in

the laboratory within 3 month. However, our hypothesis was not supported by the data.

After 76 days of incubation, two variants of the same sandy agricultural soil (Su3)

established a similar total eubacterial abundance, but different community structures – one

strongly dominated by β-Proteobacteria, the other one by Acidobacteria, Actinobacteria

and Fungi. Structural differences between these microbial communities did not cause

significant differences in the occlusion of POM. This leads to the tentative assumption that

POM occlusion in agricultural soils could be resilient in face of changing microbial

communities. Nonetheless, a population shift can affect e.g. soil metabolic characteristics.

Therefore, the state of the soil microbial community should remain in focus of agricultural

practice.

6.7 Acknowledgements

This project was financially supported by the Leibnitz-Gemeinschaft (SAW Pact for

Research, SAW-2012-ATB-3). We are also grateful to our students Kathrein Fischer,

Christine Hellerström, Annabelle Kallähne, Paula Nitsch, Susann-Elisabeth Schütze, Anne

Timm and Karolin Woitke for pre-trials and soil preparation.

Frederick Büks (doctoral thesis 2017)

Soil microbial communities and POM occlusion

7 Synthesis and conclusions

7.1 Single experiments

The present experiments show only little or even no significant effects of microbial binding

factors on the POM occlusion in a sandy agricultural soil.

Enzymatic treatment. The treatment of aggregate samples with a highly concentrated

enzymatic solution shows no significantly (p<0.05) enhanced POM release compared to

the control. But, there is a tendency for the reduction of POM occlusive strength. This

POM detachment is attributed to the enzymatic digestion of bacterial EPS. However, the

concomitant low additional release of DNA from intact bacterial cells confirms an

incomplete detachment and/or that the majority of cells within aggregates is not fixed by

EPS, but e.g. by occlusion. Following Ranjard and Richaume (2001), a majority of soil

bacteria is located in pores <9 µm in microaggregates <100 µm. Also Monrozier et al.

(1991) found 39 to 60% of the microbial biomass associated with microaggregates

<30 µm. This could explain the lack of POM release by the inaccessibility of bacterial EPS

for diffusing enzyme molecules: After pre-incubation, smaller mesopores are already filled

with soil solution, so that – in contrast to macropores and larger mesopores – enzymes do

not reach via convection, but only diffusively. In consequence, enzyme migration into small

mesopores is hindered, whereas larger pores are easily accessible for enzymes and

susceptible for instant enzymatic digestion of EPS components. By comparison, enzymatic

plus mechanical treatment led to accessibility of inner aggregate EPS and a significantly

higher cell release compared to pure mechanical and my enzymatic detachment

(Böckelmann et al., 2003).

In conclusion, the enzymatic treatment of extracellular polymers within the larger meso-

and macropore space has little effect on POM occlusion. This indicates little influence of

EPS on POM occlusive strength within the aggregate-hierarchical level of

macroaggregates and matches current assumtions (Chenu and Stotzky, 2002). The slight

additional POM release after application of the highest enzyme concentration mainly

originates from strongly bound POM (>150 J ml-1) of the sediment fraction and points to

the destabilization of stable macroaggregates (Kaiser and Berhe, 2014). However, the

Frederick Büks (doctoral thesis 2017)

effect on small mesopores could not be determinded due to little diffusive accessibility and

additionally depends on the amount of POM occluded in these aggregate regions.

Nematode grazing. The missing influence of a stable, fertile and grazing population of the

bacterial-feeding Nematode Acrobeloides buetschlii on the composition and abundance of

the bacterial community as well as on POM release conflicts with the initial hypothesis,

that grazing on bacterial biofilms and EPS would reduce the strength of POM bonds with

mineral particles. Like in the former experiment, this lack of effect might be caused by the

inaccessibility of the finer mesopore space. Restricted by its body diameter, A. buetschlii is

not able to enter small mesopores. In consequence, grazing is restricted to larger pores,

where the influence of bacterial biofilms and EPS on POM occlusive strength is assumed

to be insignificant (Chenu and Stotzky, 2002). As all samples showed a natural bacterial

population density derived from the PLFA concentrations, the results underpin the idea of

small mesopores as relevant retreat habitat for soil bacteria. However, the results give no

information if micropore-protected bacterial colonies are a relevant factor of aggregate

formation and POM occlusion within microaggregates. In addition, this experiment gives

no information about long-term influences of bacterial-feeding on POM occlusion, e.g. by

nematodal excretion and microbial population shifts.

Microbial communities. After incubation with two different microbial populations the

inoculated variants showed a significant increase of occluded biochar particles (POM

analogue), which is, however, not affected by the composition of the microbial community.

Tendencies of decreased POM release in the soil-born variant can be explained with the

high abundance of fungi, which are assumed to be an important biological factor of

macroaggregate formation. This, on the other hand, points to a negligible influence of the

bacterial community composition on POM occlusion in any pore size class, especially

within microaggregates, that are inaccessible for fungal hyphae (Chenu and Stotzky,

2002).

Soil microbial communities and POM occlusion

7.2 Statistical restrictions

Due to the little number of replicates within each variant, the analysis of these data suffer

from restrictions regarding the perceptibility of significance of the observed results:

Originally p-values were intended to support the estimation of statistical significance by

ranking given results on a scale of probability for the rejection of an actually true null

hypothesis (H0) (Fisher, 1925). Later p-values were conventionalized by means of

accepting p<0.05 and p<0.01 as sharp threshold values to distinguish between

insignificance, significance and strong significance, respectively (Biau et al., 2010). Beside

the obvious disutility of accepting data with – for instance – p=0.049 as statistically

insignificant and such of p=0.051 as significant, solely use of p-values hold insufficiencies

not only in the analysis of variants with little parallels. Nonsignificance never means a lack

of difference between variants (Goodman, 2008): For example, high variance between

parallels can result in p>0.05, although compared means are largely different and the

effect size is large (Zhu, 2016). Higher validity of statistical analyses can be reached by

use of further statistical markers. Whereas, on one hand, the p-value indicates the type-I

error, the probability of erroneously accepting the null hypothesis (also known as type-II

error) is given by the test power (1-β) (Biau et al., 2010). The test power increases with

decreasing variance within each variant as well as increasing |μA-μB| (the difference

between the means of the compared variants) and number of samples. Furthermore, even

in cases of few parallels, the effect size give information about the importance of the

difference between the compared variants in face of their amount and and give substantial

information about the relevance of found data even in case of p>0.05 (Cohen, 1988; Zhu,

2016).

In the present thesis, the released POM fractions of the enzymatic treatment and microbial

community experiments show a broad variance within samples of each variant.

Differences between the variants of these experiments are not significant (p>0.05), but

show a high effect size comparing E0 and E4 (d=0.98) as well as SPsoil and SPair (d=1.25)

at 50 J ml-1 applying Cohens d-test for single comparison (Cohen, 1988). The test power

for one way analysis of variance (ANOVA) was not calculated, but is most probably low

due to few parallels, high variance and small differences between the means of the

variants. In conclusion, the present results show tendencies with increased probability of

Frederick Büks (doctoral thesis 2017)

type-I errors. Hence, on the statistical level this work represents the standard problem of

environmental research: little money, little time, little parallels, little explanatory power by

applied statistics.

7.3 General conclusion

In soils there is no fundamental hindrance for bacteria or fungi to colonize any surface,

which is not in a pore smaller than the cell's size or fully covert by other particles.

Therefore, biofilms, EPS residues and further microbial binding factors are expected to

appear both in smaller mesopores and on particle surfaces within larger pores and could

therefore potentially be effective in both micro- and macroaggregates.

The distribution of bacterial biomass between these smaller and larger pore size ranges

most probably depends on factors such as soil texture, chemical and biological

composition, that affect the appearance of niches, predators and nutrient supply. Sandy

soils contain 30±10% of pores >10 µm (Blume et al., 2015), which allow free motion of

nematodes within the soil pore volume, whereas finer texture hinders nematode motion

and less likely provide a network of accessible pores for unhindered grazing (Wallace,

1968). The microbial biomass of a sandy soil is therefore prone to grazing and assumed to

be concentrated in small protective mesopores.

Soil respiration, PLFA concentrations and DNA amounts point to a microbial population

density, which is in the normal range of sandy soils. As biofilms and EPS residues of larger

pores are accessible and susceptible to enzymatic and trophic treatments, an influence on

POM occlusive strength should be measurable, if these substances have influence on

POM occlusion within the named pore size range. By reason that this is not the case, my

results can be interpreted in two ways:

(1) The enzymatic detachment, grazing and population changes in the upper mesopore

scale and beyond are of minor relevance for the strength of POM occlusion. The part of

the bacterial population, which is important for soil aggregation and POM occlusion, might

live in smaller mesopores <10 µm of microaggregates, where microbial binding factors

Soil microbial communities and POM occlusion

play a relevant role for aggregation, as assumed by different authors (Tisdall, 1994; Six et

al., 2004; Bronick and Lal, 2005).

(2) Within the probed sandy soil biofilms, EPS, bacterial exudates and residues have no

influence at all neither in smaller mesopores nor in the pore space above. This

interpretation conflicts with the established model but matches data of Foster (1988), who

did not find any biofilms within sandy soils.

However, the influence of microbial binding factors in smaller mesopores remained non-

proven in the present work due to methodological reasons and have to be part of future

research.

The third experiment furthermore shows the minor influence of microbial aggregation

factors resulting from different populations within the whole pore size range. This most

likely results from little differences in the rheological properties of EPSs with different

composition as well as other binding factors and do not affect POM occlusive strength.

Different soils – varying in content, composition, distribution and physico-chemical

properties of their OM and mineral phase – most likely do not release the same amount or

share of OM when treated with the same mechanical stress. Cerli et al. (2012) addressed

this problem in their comprehensive work about separation of operational OM fractions.

However, in the present study aggregate samples do not differ in their chemical

composition, while the applied treatments are used to selectively alter the influence of the

microbial community on physico-chemical binding properties. For that reason, the POM

occlusive strength is interpretable as proportional to aggregate stability when restricted to

soils with the same structural abilities. In consequence, enzymatic and trophic treatment of

biofilms/EPS as well as the two different microbial populations are assumed to have no

influence on aggregate stability.

The results of the present thesis underpin the future focus on microaggregates. Precise

differentiation of specific intra-microaggregate POM from other occluded POM and

mineral-associated OM is a challenging task, some authors estimated this fraction to

comprise 10 to 30% of the total POM in different soils (Besnard et al., 1996; O'Brien and

Jastrow, 2013) and up to 90% of the occluded POM in aggregates (Six et al., 2000). Given

this high proportion, to understand the contribution of microbial communities to the intra-

microaggregate occlusion of POM with all its ecological functions is an important task for

the research and practice on soil fertility in agriculture.

Frederick Büks (doctoral thesis 2017)

7.4 Transferability to other soils

Silty sand (Su3) from the topsoil of the agricultural test site was used in all three

experiments. The samples showed a high sand and a low clay content (~72% and ~4%,

respectively), a low organic carbon content (~0.9%, with exception of the microbial

community experiment) and a low microbial carbon content of about 176 mg C kg-1 soil,

which is on the bottom of Cmic values for agricultural soils (Blume et al., 2015). Compared

to soils with larger silt, clay and OM content, the soil samples contain less than half of the

microbial population density (Anderson and Domsch, 1989; Anderson and Domsch, 2010),

hence with lower capability of EPS production. Microbial biomass correlates to the organic

matter and the clay content of soils (Schnürer et al., 1985; Anderson and Domsch, 1989)

and benefits from the amount of protective niches (Chenu et al., 2001), which is increased

in soils with finer texture. Therefore it could be argued, that microbial binding factors have

minor effect on aggregate stability and POM occlusion in soils, which are poor in clay and

OM. Assuming higher occlusive strength of POM in soil types with higher content of those

aggregation agents, future investigation on agricultural topsoils such as from Cambisols,

Luvisols or Chernozems might be proper to get more general insight into the function of

microbial communities in POM occlusion (Zech et al., 2014).

7.5 Future research

Aggregated soils with increased silt and clay content show a shift of the pore size

distribution towards smaller pores (Blume et al., 2015) leading to enhance the effect of

diffusion hindrance of macromolecules. In consequence, both the evaluation of the results

from the enzymatic experiment on the basis of statistically significant re-measurements

and the analyses of further soil types for micro- and macroaggregate occlusion of POM

require a preceding test procedure to optimize the application time of enzymes. The object

is to reach a preferably complete diffusion of enzymes into the whole pore space >0.3 µm

without significant reduction of POM mass by enzymatic digestion of organic surfaces.

Soil microbial communities and POM occlusion

Just like the diffusion behavior of macromolecules, the development of the microbial

community strongly depends on the soil type (Bossio et al., 1998; Buyer et al., 2002).

However, there is a lack of comprehensive studies both on the composition and

distribution of bacterial, archaeal and fungal phyla within aggregates of different soils.

Ecotyping on microbial phyla, their metabolic and physical properties (such as EPS

excretion, production of hydrophobic substances, entangling abilities and

biomineralization), their localization within the aggregate structure (inside

microaggregates, between microaggregates, on macroaggregate surfaces and outside of

aggregates) and knowledge about specific microbial community compositions at different

surfaces (POM, mineral surfaces, pyrochar, microplastic) could give insights in the

influence of microorganisms on the binding of soil particles, the aggregation processes

and the occlusion of POM.

In addition, grazing organisms might influence the potential of microbial phyla in accessible

pore space by depleting target populations and hold them in equilibrated permanent

growth. Results of the present work showed, that even small Nematodes like A. buetschlii

might be unable to influence bacterial populations within pores of 0.3 to 12.5 µm in

diameter. Following Griffiths et al. (1999), smaller protozoal grazers are able to reach

bacterial populations within microaggregates and could be used for further investigation on

the relation of biofilm/EPS grazing and aggregation of soil particles. Furthermore, selective

grazing of different protozoal taxa might give information about special roles of bacterial,

fungal and archaeal prays on the stabilization of aggregates.

At the instrumental level, the water content has large influence on aggregate stability and

in consequence on POM occlusive strength. Extensive analyses of various samples often

require storage of air-dried soil samples. To avoid slaking and further mechanical damage

by fast re-wetting, a device is needed to slowly increase the water content of soil

aggregates to a constant value (e.g. via filter plates) and directly perform

ultrasonication/density fractionation without destructive transfer to other tubes. This gentle

treatment is assumed to reduce variability of POM releases caused by undesired

mechanical disruption.

Future knowledge about the role of microorganisms in soil aggregate stabilization will

contribute to predictions about related soil fertility factors as a consequence of e.g. land-

use changes, application of biocides, climatic or seasonal changes. Future agriculturalists

Frederick Büks (doctoral thesis 2017)

might be enabled to optimize their food production allowing for microbial communities and

their effects on the soil-plant system.

Soil microbial communities and POM occlusion

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