279x Filetype PDF File size 0.26 MB Source: www.itqb.unl.pt
Microbial
Ecology
Metaproteomics: A New Approach for Studying Functional
Microbial Ecology
Pierre-Alain Maron, Lionel Ranjard, Christophe Mougel and Philippe Lemanceau
´ ´
UMRMicrobiologie et Geochimie des Sols, INRA/Universite de Bourgogne, CMSE, BP 86510, 17 rue de Sully, 21065, Dijon Cedex, France
Received: 17 November 2006 / Accepted: 26 November 2006 / Online publication: 13 March 2007
Abstract be an integrative science with strong interconnections
In the postgenomic era, there is a clear recognition of the between systematics, genetics, biochemistry, molecular
limitations of nucleic acid-based methods for getting biology, physiology, modeling, paleobiology, soil science,
information on functions expressed by microbial com- parasitology, epidemiology, etc., with important food,
munities in situ. In this context, the large-scale study of public health, and environmental implications. Microbial
proteins expressed by indigenous microbial communities ecology can be considered apart from Bclassical^ ecology
(metaproteome) should provide information to gain by the specifics of the organisms involved. The small size
insights into the functioning of the microbial component of microorganisms, the difficulty defining bacterial
in ecosystems. Characterization of the metaproteome is species and the huge genetic/metabolic diversity among
expected to provide data linking genetic and functional them in the various environments they colonize [50] led
diversity of microbial communities. Studies on the to the development of specific concepts and methodo-
metaproteome together with those on the metagenome logical approaches for elucidating the role of microbes in
and the metatranscriptome will contribute to progress in ecosystem functioning. Analysis of historical and recent
our knowledge of microbial communities and their advances in microbial ecology shows a Bstep-by-step^
contribution in ecosystem functioning. Effectiveness of evolution managed by methodological developments
the metaproteomic approach will be improved as ([8], Fig. 1).
increasing metagenomic information is made available In the 1960s, the most comprehensive studies
thanks to the environmental sequencing projects cur- focused on monoxenic cultures lacking interactions
rently running. More specifically, analysis of metapro- between microorganisms and between microorganisms
teome in contrasted environmental situations should and their habitat. In the 1980s, one of the first advances
allow (1) tracking new functional genes and metabolic was to take into consideration not only single organisms
pathways and (2) identifying proteins preferentially but density, diversity, and activity of microbial popula-
associated with specific stresses. These proteins consid- tions isolated from natural environments. This was
ered as functional bioindicators should contribute, in the initiated by Brock (1987) [5] who stated that the
future, to help policy makers in defining strategies for properties of an organism cultivated in the laboratory
sustainable management of our environment. may not necessary reflect its activity and physiology in
the environment where factors such as resource com-
petition, environmental heterogeneity, predation, and
other interactions are prevalent. In the 1990s, many
Past, Present, and Future Prospects studies were dedicated to this type of approach and
Microbial ecology is a scientific domain derived (40 years provided the basis for understanding the microbial
ago) from medicine and agronomy by the need to world and its role in ecosystem functioning. However,
elucidate relationships between microbes and their the statements made by Bakken (1985) [3]andAmann
natural habitats (soil, water, sediments, rhizosphere, et al. (1995) [1] that more than 90% of the micro-
alimentary canal...). Soil microbial ecology is known to organisms in the environment are not cultivable
highlighted the limit of culture-dependent approaches
to describe natural diversity and that most of the
Correspondence to: Philippe Lemanceau; E-mail: lemanceau@dijon.inra.fr microbial diversity remained unexplored. Faced with
486 DOI: 10.1007/s00248-006-9196-8 & Volume 53, 486–493 (2007) & * Springer Science + Business Media, LLC 2007
P.-A. MARON ET AL.: METAPROTEOMICS: A NEW APPROACH FOR STUDYING FUNCTIONAL MICROBIAL ECOLOGY 487
FiFirrsst st syymmppoosusuii mmooff FirFirsst mat mannuuaall ofof FirsFirst st sccieientificntific joujourrnanalsls
mmiicrcrobiaobiall eeccoolloogygy mmiicrcrobiaobiall eeccoollogyogy AAppplpl EEnnvirviroonn Micr Microbiol.obiol.
BrBroocckk anandd
MiMicrcrobiol.obiol. E Eccolol.. ‘o‘ommiicc eerraa’’
stst
11 ISISMMEE titimmee
19195577 19619666 11970970 1971974-4-7676 11980980 19199090 19199988 nonowwaadadayyss
InteInteggrraattioionn lleevvelel ooff st stududiesies iin mn miiccrroobbiiaall ecoecollooggyy
IIndividndividuualal lelevveell
((mmononoxoxeneniicc cucullttuure)re)
PopulatioPopulationn le levevell
CoCommmmuunniittyy lleevvelel
LinkLink be betwtweeeenn ggeenneetticic aanndd funcfunctiotionnaall divdiveerrssityity
MeMetthhooddoologilogiccaall ddeevveellopopmmeennttss
DDevelevelopmopmeenntt ofof c cuultulturre e mmeedidia fa foorr is isololatinatingg mmicricrobiobialal ororgaganisnismmss
2-2-DD ge gell MaMassss BiBioo
eleleeccttrropophhooresresiiss PCPCRR SSppececttrroommetetrryy inforinformmaatticic GenGenoomimicc
DeDevveellooppmmenentt ooff m moolleecucullaarr
bibiolologyogy aanndd bi biochocheemmiissttrryy DDNA-NA-SSIIPP
MMeetataggeenonommiicc
DDeevevelopmlopmeenntt ooff m meeththodolodologiogieess tto o extextrraacct,t, amplamplififyy,,
cclloneone an and sd seeququenencece DDNNAA f frroomm mmiiccrrobialobial ccoommummunnititiieess
MMeetatatrtraannscscrriiptptoommiicc
DDeeveloveloppmmeentnt ofof met methhododolologogiieess tto extro extracact, at, ammplipliffyy
and sand seeququencencee RRNNAA ffrromom mimiccrrobobiiaall ccoommmunimunittiieses
MeMetatapprrootteeoommiicc
DDeveevelopmlopmeenntt ooff meth methodoodollooggiieess tto o extextrracactt aandnd
chchaarraacctteeririzzee pprrooteteinsins ffroromm mmiiccrroobbiiaall cocommummunniittiieess
Figure 1. Historical and step-by-step evolution of microbial ecology.
this major limitation, Pace et al. (1985) [34]introduced evolution of uncultured microorganisms. However, indi-
a cultivation-independent approach based on the ex- cations of genetic potential does not contribute to the
traction, amplification, cloning, and characterization of elucidation of the functionality (level of expression of the
rDNA genes directly from natural environments. genetic potential) (Fig. 2) of microbial communities in
Beginning with these early works, many efforts have ecosystems [8, 45, 50, 52].
been dedicated to developing molecular methods to Different methods have been developed to discrimi-
characterizemicrobialinformationcontainedinthenucleic nate active populations from quiescent ones in natural
acids extracted from environmental samples [1, 20]. These habitats by incorporation of labeled markers in microbial
developments enabled the characterization of variations of biomass such as 13C (DNA-Stable isotope probing meth-
the microbial community structure and diversity in mul- ods [41]), or BrdU [4]. However, these approaches only
tiple situations allowing the identification of populations provide limited information on the populations associated
preferentially associated with environmental perturbations with a specific process rather than a complete description
(for review, see [44]). Further methodological progress of their functional role within a Bcommunity^. Bioinfor-
allowed the cloning and sequencing of large genome frag- matic data acquired over the last 20 years on putative
ments (about 40 kb) from microbial communities of a functional genes allows the design of primers and probes
planktonic marine archaeon [49]. This work provided the to target specific functional communities in complex
first glimpse into content and diversity of marine archae environments. The design of such primers enables
but was also the first example of the feasibility of meta- (1) the quantification of gene copy number [real time
genome characterization [collective genome from all polymerase chain reaction (PCR)] and (2) the character-
(micro-) organisms present in an ecosystem] [46]. Recent ization of polymorphism(s) of functional gene(s). These
advances in high-throughput screening and sequencing studies performed at the DNA level can be further linked
facilitate this type of study and have provided the majority to measurement of the corresponding activities [27].
of DNA sequences now found in databases. Metagenomic However, this integrated approach is restricted to a
approaches provide new insights into genetic diversity and limited number of functions (denitrification, nitrification,
488 P.-A. MARON ET AL.: METAPROTEOMICS: A NEW APPROACH FOR STUDYING FUNCTIONAL MICROBIAL ECOLOGY
Figure 2. Schematic representation of the FMeta_ levels in the ecology of microbial communities.
and methane oxidation) for which genes involved in each which represents the last and crucial step toward our
step of the metabolic pathway are known and sufficiently understanding of metabolome regulation (collective
conserved to allow the design of consensus primers. metabolites from all microorganisms present in an
Furthermore, the presence of a gene within populations ecosystem [12]) (Fig. 2). The aim of this position paper
of a given Bfunctional community^ does not necessarily is to stress the relevance of metaproteome analysis in
mean that it is expressed in the habitat. (1) describing new functional genes and (2) relating
In the postgenomic era, a major challenge is to genetic and taxonomic diversity to the functionality of
elucidate the functional role of the metagenome by microbial communities in complex environments.
linking genetic structure and diversity of microbial
communities with their functions. To fulfill this chal-
lenge, advances in the understanding of the evolution of Onthe Track of Metaproteomics?
microorganisms must be achieved by developing new
approaches(Fig.1). Databases also include putative func- Proteomics, Bthe large-scale study of proteins expressed
tional gene sequences from microbial groups which have by an organism^ [54], truly emerged in the middle of the
yet to be cultivated in isolation in the laboratory. Until 1970s, when scientists started to map protein expression
we manage to grow them, progress in our knowledge of using the newly developed two-dimensional (2-D) gel
their functions in complex environments can only be electrophoresis [29]. By applying the 2-D technique, it
achieved by untargeted culture-independent character- became possible to separate proteins from complex
ization of their functionality. As shown in Fig. 2, mixtures of cellular extracts into individual polypeptides,
microbial functionality can be characterized either by thus, allowing the analysis of bacterial response to
the analysis of transcripts (metranscriptome: collective various growth conditions [38]. However, protein iden-
RNA from all microorganisms present in an ecosystem) tification was time consuming and tedious due to the
and/or proteins (metaproteome: collective proteins from lack of sensitive and fast sequencing technologies for
all microorganisms present in an ecosystem [45]). So far, protein analysis. From the 1990s, proteomics has been
major limitations related to the short half-life of RNA, made advanced, thanks to the development of high-
difficulty in eliminating humic acids during the extrac- efficiency peptide ionization methods in mass spectrom-
tion process, differential transcription kinetics of similar etry (MS), allowing rapid and highly sensitive protein
genes in different populations, low correlation between identification [36, 56]. In parallel, progress was made in
RNA levels and synthesis of the corresponding proteins bioinformatic tools and in their adaptation to the
have hampered the study of the metatranscriptome of analysis of information from 2-D gels and MS, making
indigenous microbial communities [17, 58]. possible (1) the identification of proteins by database
These limitations, together with progress in protein searching with MS information [35], (2) the character-
analysis (see below), have stimulated interest in meta- ization of the corresponding genes by reverse genetics
proteome characterization. The term Bmetaproteomics^ [22], and(3)thedeterminationofproteinposttranslational
was first proposed by Wilmes and Bond (2004) [55]as modifications [2]. Over the last decade, the advances in
Bthe large-scale characterization of the entire protein proteomic technologies, together with the sequencing of
complement of environmental microbiota at a given an increasing number of complete genomes of different
point in time^. As proteins, and more precisely enzymes, microorganisms, provide the opportunity to link phylog-
are involved in biotransformation processes, metapro- eny with the function of microorganisms. In this context,
teome analysis constitutes a suitable way to characterize the proteomic characterization of model organisms
the dynamics of microbial function in a holistic way, currently being sequenced further facilitates the descrip-
P.-A. MARON ET AL.: METAPROTEOMICS: A NEW APPROACH FOR STUDYING FUNCTIONAL MICROBIAL ECOLOGY 489
tion of those physiological pathways involved in various environmental matrix to the resolution of their diversity
functions and interactions within and between organisms and their identification (Fig. 3).
such as symbiosis [14], pathogenicity [28], antibiotic As with in situ nucleic acid-based studies, the most
resistance [6], and adaptation to stresses [16, 51]. crucial step in the metaproteome analysis is ensuring that
These studies stress the relevance of proteome the quality and quantity of the proteins extracted are
analysis for investigating global modifications in genome representative of the sample. This is particularly true for
expression of prokaryotic organisms and to progress in environmental proteomic studies because of the com-
our knowledge of those processes that regulate gene plexity of indigenous microbial communities, the het-
expression. However, these investigations have largely erogeneity of natural environments, especially soil, and
been performed under laboratory conditions, at the the presence of interfering compounds (phenolic com-
organism level, without taking into account the biotic pounds, humic acids...) making difficult the extraction of
(among microorganisms) and abiotic (microorganisms a suitable protein fraction for analysis. The extraction
with their natural habitat) interactions governing the strategy varies according to the targeted protein fraction
ecology of microbial communities in situ. Therefore, new (i.e., procaryota/eucaryota, extracellular/cell associated)
approaches are needed for in situ characterization of the and by the subsequent methods of protein analysis
global protein expression at the population, or more (i.e., 2-D comparative protein maps or measurement/
widely, at the community level. The main challenge of detection of specific polypeptides or enzymatic activities).
environmental proteomics is to map proteins (proteo- Recently, Schulze et al. (2004) [47] characterized extra-
typing) extracted from indigenous microbial communi- cellular proteins isolated from dissolved organic matter
ties and identify in an untargeted way new physiological in different environments and showed that the relative
pathways and their associated coding genes. proportion of the proteins originating from bacteria
varied from 78% in lake water to less than 50% in a
forest soil solution.
HowtoDoIt? For an exhaustive recovery of environmental pro-
teins (cellular + extracellular), organisms may be lyzed
Metaproteome analysis of soil microbial communities directly in the environmental matrix before purification,
implies the development of different technical steps, quantification, and analysis [30–32, 48, 55]. This strate-
from the extraction of microbial proteins from the gy, based on direct lysis, was applied by several authors
EnEnvironmvironmeenntaltal ExtExtrractactiion of on of mmiicrobcrobiiaall pprotroteeiicc poolpool ProtProteieinn ssepeparataratiioonn
sasammppleless
2D2D-gel-gel e ellectectrroopphhororesiesiss 1D1D-gel-gel el eleeccttrrophorophoresiesiss
PPrrototeieinn
ssttatatisisticticaall aanalynalyssiiss prprofiofillee
LLiink tnk too ModiModiffiiccaattiionsons of of ooff en encodcodeedd pprofrofiillee ==
genetgenetiicc ssttrucructturure e funcfuncttiionalonal ssttrruuccttuurree FFiingerpingerpintntiinngg ooff
funcfuncttiionalonal ststruruccttuurree
IInn si situ spot ditu spot digestgestionion
IIddententiiffiicatcatiioonn reverse reverse
FunctFunctiiononalal of newof new funct functiiononalal gegenneettiicc ProtProteieinn iidendenttiiffiiccatatiion bon byy
comcommmuniunittiieess gegenneess MaMassss sp speecctrtroommeettrryy
FFunctunctiiononalal PPhhyyssioiolologgiiccaall
bibioioindindiccaattoror responseresponse
Figure 3. Experimental strategy and expected outcomes of the metaproteome characterization.
no reviews yet
Please Login to review.