George A. Kowalchuk

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Applying Environmental Genomics to Microbial
Ecology
George A. Kowalchuk
Department of Terrestrial Microbial Ecology
Netherlands Institute of Ecology (NIOO-KNAW)
Centre for Terrestrial Ecology
Royal Netherlands Academy of Arts and Sciences,
KNAW
Heteren, the Netherlands
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Whos there?
What are they doing?
How can we gain insight into, and access to, the
vast wealth of microbial functions in the soil?
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Main topics I. Can we understand the forces that
shape the structure and function of soil-borne
microbial communities to a point that we can
sensibly predict and manipulate soil
services? II. How can we gain insight into, and
access to, the vast wealth of microbial functions
in the soil?
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The Earths biodiversity The tree of life
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Consortium Partners

• BioDetection Systems B.V., Amsterdam
  (coordinator)
• Bioclear B.V., Groningen
• Vrije Universiteit, Amsterdam
• Wageningen University
• Plant Research International B.V., Wageningen
• Alterra B.V., Wageningen
• Netherlands Institute of Ecology-KNAW,
  Heteren/Nieuwersluis
• National Institute for Public Health
  Environment, Bilthoven
• Royal Haskoning B.V. Den Bosch
• Microscreen B.V., Groningen

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Bio
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Ecological
remediation
insurance
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Bio
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informatics
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Tech. development
Eco
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Disease
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toxicology
suppression
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Applications
? eco-ceuticals
? improved bioremediation
? effect-oriented bioanalysis tools
? improved agro-production systems
? other options
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Research theme 1 The bioremediation capacity of
soils WP 1.1 - Exploring microbial DNA resources
for bioremediation WP 1.2 - Design of DNA
array-based tools to detect optimal microbial
characteristics for bioremediation WP 1.3 -
Improved genomic potential for bioremediation WP
1.4 - Metagenomic analysis of microbial
ecosystems in the deep subsurface Research theme
2 Biodiversity and stress response analysis WP
2.1 - Genomic analysis of microbial community
structure WP 2.2 - Functional analysis of
nutrient cycling WP 2.3 - Genomic potential and
activity of dominantly active, non-culturable
soil bacteria WP 2.4 - Microbial diversity in
relation to sustainable agriculture WP 2.5
Stress-based expression profiling in
nematodes WP 2.6 - Stress-based expression
profiles in arthropods WP 2.7 - Stress-based
expression profiles in plants Research theme 3
Disease-suppression and production functions of
soils WP 3.1. - Metagenomic analysis of soil
health WP 3.2. - Antifungal metabolites and
fungal responses WP 3.3. - Genomic analysis of
bacterial mycoparasitism WP 3.4. - Detection of
Plant Pathogens WP 3.5. - Activities of
mycorrhizal fungi in soil systems Research Theme
4 Eco-toxicogenomics WP 4.1 - Determination of
contamination status of soils and sludge, using
existing- and genomics-based assays WP 4.2 - DNA
array systems for detection of contaminants based
upon biological responses of cultured
organisms WP 4.3 - Design of novel reporter
assays based on target gene-selection WP 4.4 -
Genomics-based eco-toxicological approach using
vertebrate model systems (e.g., Zebra fish) WP
4.5 - Identification of conserved toxicological
pathways in multiple soil organisms Research
theme 5 Overarching workpackages WP 5.1 -
Technology platform WP 5.2 - Ecological Control
Analysis (ECA) as a biocomplexity tool WP 5.3
- Bioinformatics support to genomics analysis WP
5.4 - Multidiciplinary approach to stakeholder
and societal acceptance WP 5.5 - Interactive
communication to the public

• BioDetection Systems B.V.
• Bioclear B.V.
• VU-Animal Ecology
• VU-Integrative Bioinformatics Institute
• VU-Ecology and Physiology of Plants
• VU-Innovation Transdisciplinary Res
• VU-Institute for Environmental Studies
• NIOO-KNAW
• WU-Phytopathology
• WU-Microbiology
• WU-Nematology
• WUR-Alterra B.V.
• WUR-Plant Research International B.V.
• Greenomics
• Royal Haskoning B.V.
• RIVM Nat. Inst. for Health Environment
• Microscreen B.V.

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Assessing the Living Soil An ecogenomics approach
to explore and unlock sustainable life-support
functions of soils
NIOO projects

• Genomic analysis of microbial community structure
  (Phylo-chips)
• Functional analysis of nutrient cycling
  (Functional Microarrays)
• Genomic potential and activity of dominantly
  active, non-culturable soil bacteria
  (metagenomics)
• Genomic analysis of bacterial mycophagy
  (Collimonas genome)
• Detection of Plant Pathogens (Quantitative
  detection arrays)
• Activities of mycorrhizal fungi in soil systems
  (transcriptomics)

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Assessing the
living soilTheme 2 Biodiversity and stress
response analysis

• AIMS
• Defining and understanding the normal operating
  range (NOR) of life support functions (nutrient
  cycling, maintenance of soil fertility) via an
  integrated ecogenomics approach
• Studying the interaction of internal and external
  stress factors with these functions

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WP 2.1Genomic analysis of microbial community
structure

• Main objective
• To design, test and apply comprehensive systems
  for the
• analysis of microbial community structure based
  upon
• high-density micro-array technology, in order to
  gain
• insight into the forces driving soil microbial
  community
• structure.
• Partners NIOO-KNAW, PRI, WUR, RIVM

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WP 2.1Genomic analysis of microbial community
structure
Specific goals

• Comparison of different phylogenetic microarray
  platforms
• Comparison with conventional molecular survey
  data
• Determination of NOR across Dutch agro-ecosystems
  and semi-natural ecosystems
• Detection of alterations in community structure
  upon stress

0.0
1217
3142
Tree of OTU list, based on hybridization
similarity measurement (Pearson Correlation) and
the average linkage cluster algorithm.
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WP 2.2Functional analysis of nutrient cycling

• Main objective
• To apply functional gene arrays, focussed on
  crucial steps of key nutrient cycles, to
  determine the natural variation, responses to
  stressors and resilience of soil-borne microbial
  activities
• Partners NIOO-KNAW, Alterra, WUR, PRI

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WP 2.2Functional analysis of nutrient cycling
Specific goals
50-mer functional genes array (FGA II)in
collaboration with J. Zhou

• Determination of NOR of gene presence, diversity
  and activity across Dutch agro-ecosystems and
  semi-natural ecosystems
• Detection of alterations in functional gene
  distribution, density, diversity and activity in
  response to stresses
• Confirmation with other quantitative methods for
  select gene activities

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WP 2.3Genomics potential and activity of
dominantly active, non-culturable soil bacteria

• Main objective
• To determine the genomic potential and functional
  importance of uncultured bacteria that are
  dominantly present and active in the rhizosphere.
• Partners NIOO-KNAW, WUR, PRI

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WP 2.3Genomics potential and functionality of
dominantly active, non-culturable soil bacteria
Specific goals

• Identify dominant microbial populations in the
  rhizosphere that cannot yet be cultured (Acidos
  and Verrucos)
• Construct large-insert meta-genomic libraries
  from rhizosphere soil
• Improve methodologies for high molecular weight
  DNA isolation, as well as genetic and functional
  screening of soil meta-genome libraries
• Determine the partial genomic potential of
  dominant rhizosphere bacteria
• Detect novel microbial activities
• Amplify micro-scale samples for (meta-) genomic
  analysis at relevant scales
• Apply meta-transcriptomic approach

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Soil Heterogeneity
pore
fungal hypha
root
bacteria
clay
mite
soil particle
nematode
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Are soil-borne microbes living on islands?
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environmental genome sequencing
(inter)activities of players may be deduced from
their individual genome sequences
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environmental genome sequencing
Why not piece together your community one genome
at a time?
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reducing the complexity
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Environmental transcriptomics /
Meta-transcriptomics

• Sample
• Total RNA extraction DNA
  extraction
• rRNA subtraction (degradation)
• cDNA synthesis polyA-tail addition
• (RT-PCR w/ short primers)
• ligation of RNA oligo
• cDNA synthesis cDNA synthesis
• (polyT-based RACE ) with FAME label

• Microbial community analysis
• broad PCR-DGGE (Bact. Fungi, Archea
• PCR-DGGE of specific bacterial groups, AOB,
  pseudomonads, etc.)
• Functional gene analyses (Q-PCR)
• PLFA / NLFA or FAME
• Phylogenetic microarray

cDNA community profile
Cloning into E. coli High throughput
processing and sequence analysis
Annotation and Data analysis
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Theme 3 Disease suppression and production
function of soils

• Symbionts/mutualists
• Antagonists
• Pathogens
• Culturables
• Unculturables

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WP 3.3 Analysis of bacterial mycophagy
Collimonas fungivorans as a model for the study
of bacterial mycophagy
C. fungivorans with Fusarium culmorum on
water-agar
C. fungivorans with Mucor hiemalis or Chaetomium
globosum in purified sand
de Boer et al (2001) Appl. Environ. Microbiol.
673358-3362
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A genomics approach to mycophagy using C.
fungivorans as a model
Leveau et al, in preparation
Nimblegen custom microarray
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Complete genome sequence of Collimonas
fungivorans Ter331 a model organism for
bacterial mycophagy
accelerates the discovery of genes, enzymes,
and regulatory networks that are the basis for
the ability to use living fungi as growth
substrate.
5.2 Mbp
4508 ORFs
will prove to be a valuable resource for
assessing the role of bacterial mycophagy in soil
health.
Collimonas fungivorans Ter331
underlies future application or commercial
exploitation of bacterial mycophagy, Collimonas
fungivorans, or its genes and gene products.
GC 59.54
GC-skew
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WP 3.4 Quantitative Multiplex Detection of Plant
Pathogens
BioTrove system for high throughput,
quantitative detection
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WP 3.5 Activities of mycorrhizal fungi in soil
systems
Problem We currently lack reliable indicators of
mycorrhizal functionality or potential.

• Directed at field sites varying in the intensity
  of agricultural management
• Conventional and molecular determinations of AMF
  community structure
• Functional analyses via reciprocal soil and spore
  inoculation experiments
• PCR-based studies targeting specific gene
  families involved in nutrient uptake and
  translocation
• cDNA libraries from root-organ cultures under
  varying conditions of nutrient stress
• combined phylogenetic and functional micro-array
  for AMF structure and functionality

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We are now in a position to generate huge
quantities of sequence (and other) information
but are we traveling efficiently?
Data generation capacity
Screening bioinformatic strategies
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• Some of the bioinformatic challenges stemming
  from the Dutch EcoGenomics Program
• Determining informative patterns within a
  background of dynamic variation
• Dealing with highly incomplete metagenomic data
• Unraveling novel physiological pathways and
  phenotypes
• Linking different types of data

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