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Metabolic footprinting in
microbiology:methods and
applications in functional genomics
and biotechnology
Valeria Mapelli
,Lisbeth Olsson
and Jens Nielsen
Department of Chemical and Biological Engineering,Chalmers University of Technology,SE-412 96 Gothenburg,Sweden
Center for Microbial Biotechnology,Technical University of Denmark,DK-2800 Kgs.Lyngby,Denmark
Metabolomics embraces several strategies that aim to
quantify cell metabolites in order to increase our un-
derstanding of how metabolite levels and interactions
influence phenotypes.Metabolic footprintingrepresents
a niche within metabolomics,because it focuses on the
analysis of extracellular metabolites.Although meta-
bolic footprinting represents only a fraction of the entire
metabolome,it provides important information for func-
tional genomics and strain characterization,and it can
also provide scientists with a key understanding of cell
communication mechanisms,metabolic engineering
and industrial biotechnological processes.Due to the
tight and convoluted relationship between intracellular
metabolismand metabolic footprinting,metabolic foot-
printing can provide precious information about the
intracellular metabolic status.Hereby,we state that
integrative information from metabolic footprinting
can assist in further interpretation of metabolic net-
Metabolites are defined as low molecular weight com-
pounds that are not genetically encoded and that are
produced and modified by living organisms [1].The word
‘metabolome’ has been coined to designate the entire
ensemble of metabolites present in and derived from a
given living organism [2].Methods aimed at analyzing
metabolites were developed in the early days of biochem-
istry,but it is only recently that attempts have been made
at detecting metabolic changes by analyzing a large num-
ber of metabolites simultaneously,mainly with the help of
methods based on mass spectrometry (MS) and nuclear
magnetic resonance (NMR) [3].Within a living organism,
many metabolites participate in a large number of cellular
reactions and thus connect different pathways that med-
iate and perform several different cell functions [4,5].
Hence,the level of metabolites in a cell or tissue represents
integrative information,which is an important advantage
when biological functions are to be assessed or phenotypes
to be defined in response to genetic or environmental
changes [6,7].However,due to the integrative nature of
metabolite levels,it is generally more difficult to interpret
metabolome data than it is to interpret transcriptome and
proteome data.
The increasing interest in metabolome analysis brought
about the birth of specific definitions related to the differ-
ent approaches [8,9] aimed at extrapolating information
from cell metabolites (Box 1).Here,we will focus our
discussion on ‘metabolic footprinting’,which intends to
define the pattern of extracellular metabolites,also called
the exometabolome.
It is important to differentiate between intracellular
and extracellular metabolites because they can play differ-
ent roles.This is true both for multicellular and microbial
organisms,but the separation of the exometabolome from
complete tissue might be difficult compared to the rela-
tively easy separation of microbial cells fromextracellular
medium [10].Here,we will focus on the applications and
relevance of metabolic footprinting of microorganisms,
thus we can define the exometabolome as the entire set
of low molecular weight compounds present in the extra-
cellular medium.In particular,we will highlight how the
analysis of metabolites that are naturally released from
microorganisms can provide information useful for funda-
mental research in the field of functional genomics and
strain characterization.We also highlight some examples
in which strain characterization through metabolic foot-
printing was of critical importance at anindustrial level.In
such cases,the quality of the final product can critically
depend on the metabolic footprinting of the microorganism
the pattern of extracellular metabolites detected.Further-
more,metabolic footprinting also represents an invaluable
tool for elucidating the communication circuits within
microbial communities and for optimizing metabolic engin-
eering strategies for diverse applications (Box 2).
Knowledge coming frommetabolic footprinting analysis
will be critical for achieving a comprehensive picture of
microbial metabolism.Indeed,as we describe here,cellular
metabolism and the exometabolome are tightly coupled.
Therefore,analysis of metabolic footprinting might gen-
erate key information that will also help in optimizing
metabolic charts representing intracellular metabolic
Corresponding author:Nielsen,J.(
0167-7799/$ – see front matter ￿ 2008 Elsevier Ltd.All rights reserved.doi:10.1016/j.tibtech.2008.05.008 Available online 31 July 2008
Natural roles of extracellular metabolites
In an extracellular microbial environment,any changes in
the level of extracellular metabolites will directly reflect
any modification of the environment caused by activities of
the microorganism(s) present in the system.For example,
nutrients will be consumed and many extracellular metab-
olites are formed as byproducts fromthe activity of metab-
olism.Furthermore,the actual status of the environment
the microorganism(s) are exposed to influences their cel-
lular metabolic status and,subsequently,the metabolites
that are released into the environment (Figure 1).
Cells fine tune their metabolism according to the
environment to maximally exploit natural resources.
Metabolic footprinting represents the effect of a particular
cellular metabolismonthe environment,leading to a direct
and mutual relationship between the set and level of
extracellular metabolites and the intracellular metabolism
(Figure 1).An example of this is the yeast Saccharomyces
cerevisiae producing ethanol to sustain a proper redox
balance both in anaerobic conditions and in aerobic con-
ditions when there is repression of respiration.Under
anaerobic conditions,yeast cannot consume the ethanol
it produces and releases into the environment,but under
aerobic conditions,yeast can exploit ethanol as a carbon
source,resulting in the switch froma respiro-fermentative
to a fully respiratory metabolism.Similarly,the release of
metabolites that are part of the central carbon metabolism
(e.g.acetate and pyruvate) allows the cells to maintain
biochemical balance,thereby assuring the optimal oper-
ation of the metabolism.Furthermore,the presence of
metabolites that are not expected to be secreted or excreted
by cells (e.g.phosphoenolpyruvate,which is usually com-
pletely metabolized by the cells),canbe usedas a marker of
cellular lysis,thereby providing informationabout particu-
lar growth conditions,such as pH and osmolarity,that
might indicate cellular stress [11].
Nutrient sources and the chemical and physical proper-
ties of the environment are not the only factors that
influence the nature of metabolites that are produced
and released.Other cells cohabitating the same environ-
ment can induce the production and secretion of com-
pounds,such as toxins and antibiotics,that act against
competitors.These ‘switches’ inmetabolic status that occur
regardless of nutrient source are typical of many patho-
genic bacteria and fungi [12] that aimto out-compete other
living forms or to escape host defence mechanisms.Such
responses are usually not identifiable at the genomic level
and can only be detected by comprehensive metabolomics
Moreover,metabolites also play a central role in what is
referred to as quorum sensing (QS) [13],which relies on
cellular sensing of extracellular metabolites.Bacteria
employ extracellular metabolites to communicate within
Box 1.Definitions used in metabolome analysis
Metabolome:the complete set of metabolites synthesized by a cell
in association with its metabolism.The metabolome comprises the
endometabolome (all the intracellular metabolites) and the exome-
tabolome (all the extracellular metabolites).
Metabolic fingerprinting:spectra from either NMR or MS analysis
that provide an ‘imprint’ given by intracellular metabolites.Typi-
cally,the fingerprinting does not provide identification and
quantification of specific metabolites.
Metabolic footprinting:spectra fromeither NMR or MS analysis that
provide an ‘imprint’ given by extracellular metabolites.Typically,it
does not provide identification of specific metabolites,but instead
relies on the development of rules to describe trends in the data that
involve only a small number of the variables (masses).Parallel
analysis of metabolic footprinting and fingerprinting can suggest
possible mutual interconnections between intracellular and extra-
cellular metabolites,thereby helping in the identification of possible
novel cellular metabolic functions.
Metabolite profiling:analysis that provides identification and
quantification of a group of specific metabolites that share similar
physical and chemical properties or metabolic pathways.
Metabolite target analysis:the quantitative analysis of one or a few
metabolites of interest,ignoring all the non-target peaks present in
the sample.
Box 2.Analytical tools in metabolomics applications
Direct injection mass spectrometry (DIMS)
Metabolite samples are injected directly in front of the ion source,
thereby bypassing chromatography separation.Electrospray ionisa-
tion (ESI) mass spectrometers are usually employed for the
detection of polar metabolites,whereas atmospheric pressure
chemical ionization (APCI) is used to analyze less polar and non-
polar metabolites and also to improve sensitivity.DIMS allows for
high-throughput analyses of crude samples or sample extracts with
typical procedure times of 1 to 3 min per sample.The major
drawback of DIMS is the so-called ‘matrix effect’ [37],which can
compromise sensitivity and accuracy of quantification between
samples of different matrix composition.DIMS can be used in plant
and microbial non-targeted metabolomics [8,19] when matrix
composition variation is low or does not affect the comparison
between samples.
Hyphenated mass spectrometry (-MS)
This term embraces all analytical techniques in which mass
spectrometry analysis of metabolites is preceded by chromatogra-
phy separation to enable better metabolite identification and
quantification [3].In metabolomics,the most commonly used
chromatographic techniques are gas chromatography (GC-MS);
high performance liquid chromatography (HPLC-MS),which is
mostly used for targeted analysis;and capillary electophoresis
(CE-MS).Nowadays,time of flight (TOF) mass spectrometers are the
preferred instruments used in metabolomics because they provide
full mass scan abilities and complete mass spectra,therefore
enabling the detection of all metabolites with good sensitivity.
Nuclear magnetic resonance (NMR) spectroscopy
NMR has been heavily utilized in metabolomics research and
benefits from the fact that it is specific and yet nonselective
[20,40].This means that each separate resonance observed is
specific to a particular compound and provides a wealth of
structural information regarding the components of a sample.It
does not require pre-selection of analysis conditions,such as ion
sources for MS or chromatographic operating conditions.
Vibrational spectroscopy
Fourier transform-infrared (FT-IR) is currently the more widely used
technique for obtaining spectral fingerprints of biological samples
[18,41].FT-IR has the benefit of enabling the rapid,reagentless,non-
destructive analysis of complex biological samples,hence facilitat-
ing high-throughput screening and unbiased measurements.The
main drawback of FT-IR is its relatively low sensitivity,which makes
it difficult to integrate the obtained information with biological
Adapted from [8,9].
Information mainly from [3].
Trends in Biotechnology Vol.26 No.9
the population:through the secretion and subsequent
sensing of signalling molecules,the whole population can
initiate a concerted action.These communication circuits
can regulate a diverse array of physiological activities,such
as symbiosis,virulence,competence,conjugation,antibiotic
production,motility and biofilmformation,by coordinating
gene expression within a microbial community.
Applications and potential achievements of metabolic
Quorum sensing investigation via metabolic
Many pathogens use QS mechanisms to colonize and
attack their host.Chronic bacterial infections are mainly
due to the ability of bacteria to persist in biofilm commu-
nities that are often unassailable even under pressure by
antibiotics,such as in lung infections by Pseudomonas
aeruginosa [14,15].In these cases,specific targeting of
the QS molecules that induce formation of biofilms might
be a promising approach to annihilate microorganism
virulence without threatening their existence,thereby
reducing the occurrence of selective pressure leading to
drug-resistant mutants.However,due to the diverse
nature of QS molecules and their mode of action,which
can change depending on QS molecule concentration and
infection status,the design of QS antagonists might not be
that straightforward [14].
Metabolic footprinting analysis might represent an
effective approach to identifying potential QS metabolites
within a microbial community.Extracellular metabolites
that play a role in QS circuits are specifically produced and
secreted in a time- and environment-dependent manner
because microorganisms use QS to keep track of their
cellular density and of the environmental factors they
encounter.Therefore,to determine whether a metabolite
has any QS activity,metabolic footprinting analysis needs
to be performed over time and during the different growth
phases of a microbial community.It will also be necessary
to complement metabolic footprinting with morphological
and physiological analysis so that the appearance of differ-
ent mass (or NMR) peaks inthe obtained spectra at specific
time points can be associated with any phenotypical and
physiological changes in the microbial population.This
type of analysis will also provide information on exactly
Figure 1.Coupling between the environment and intracellular metabolism.The intracellular metabolism of a microbial cell or population is directly influenced by the
external environment.Metabolites that are released into the environment as a consequence of cell metabolic activity represent the cells’ so-called ‘metabolic footprint’,
which,in turn,modifies the external environment,with the consequence that cells fine tune their metabolismin response.Analysis of the metabolic footprint can therefore
give important hints on the compounds that reside in the environment and the possible microbial metabolic activities that are occurring in relation to the presence of
natural products (glucose is shown as an example) and potential xenobiotic compounds (atrazine is shown in the figure as an example).
Trends in Biotechnology Vol.26 No.9
when the administration of a QS-targeting drug might be
most effective during an infection.
Therefore,metabolic footprinting could significantly
accelerate the identification of QS molecules as potential
drug targets [8] because certain peaks within a spectrum
that might be part of intercellular communication net-
works can be pinpointed.These peaks need to be further
characterized for their chemical and physical identity,and
the corresponding metabolites need to be tested for their
actual effects on the microbial community.
Metabolites that play a role in QS can also be potential
drugs.Microorganisms in their natural environment often
face direct competition with other microorganisms for
resources.The fact that a homogeneous microbial com-
munity is able to sense,evenat a distance,the presence of a
different microbial population that might threaten nutri-
ent availability,implies that diffusible compounds are
released and recognized.Such compounds might induce
defensive changes in the morphology of the producing
microorganisms and also inhibit the growth of the ‘enemy’
population.Such interactions between different microbial
populations are often combined under the term ‘socio-
biology’ [16].A recent proof of principle study conducted
metabolic footprinting analysis of interacting mycelia [17]
and related the morphological changes that occurred
during their interaction.Many of the metabolites detected
in this study are still unidentified,but further analysis
could lead to the discovery of novel natural products that
might have different applications:from anti-fungal drugs
to natural pigments possibly produced as natural defence
against a cohabiting microbial population.Metabolic foot-
printing of interacting cultures also has the advantage that
the biosynthesis of certain metabolites might be upregu-
lated;therefore,such metabolites might be present in
much larger and hence detectable quantities than would
be the case for isolated cultures,leading to the possible
discovery of novel compounds.
Therefore,even though the metabolic footprinting of a
certain biological system,according to the definition (Box
1),refers merely to the ‘shape’ of obtained mass (or NMR)
spectra,without implying the identification of detected
peaks,it certainly represents the first step towards the
discovery of novel natural molecules that might find
important applications.
Functional genomics and strain classification
Thanks to the continuous development of spectroscopic
techniques towards high-throughput applications com-
bined with the relative ease of obtaining metabolic foot-
prints compared to metabolic fingerprints,metabolic
footprinting has established itself as an effective and
robust method for functional genomics studies.Different
yeast and Escherichia coli strains with mutations in genes
that are closely related within the metabolism [8,18,19],
couldbesuccessfullydiscriminatedonthe basis of metabolic
footprinting.This approach relies on the identification of a
Figure 2.Metabolic footprinting can result in important biological information.Different yeast strains are schematically represented by the different colours (a),and their
metabolic footprinting analysis by direct injection mass spectrometry (DIMS) is shown in (b).DIMS analysis of total extracellular metabolites of the different mutants results
in different mass spectra that can be further analysed by statistical techniques (c),such as principal components analysis (PCA),which helps to reduce multidimensional
datasets to lower dimensions for analysis.In this way,the different strains can be differentiated on the basis of their metabolic footprinting.Discriminant analysis (d) can
then be used to create a new variable by combining the original variables in such a way that the differences between the predefined groups are maximized,resulting in
information on biological functions (e).
Trends in Biotechnology Vol.26 No.9
small number of variables (mass peaks) whose changes
define a rule that is linked to a particular mutation.There-
fore,metabolic footprinting can be exploited for first-round
analyses,confining the identification to mass peaks contri-
buting to the discrimination of mutants [8] (Figure 2).
Additionally,in mutations that are silent with regard to
observable phenotypic parameters (e.g.specific growth
rate),metabolite levels might nevertheless change substan-
tially to compensate for the effect of mutations and metab-
olite analysis might therefore be the preferred approach to
detecting any genotypic alterations [20].
Fast discrimination between microbial strains is not
only relevant in functional genomics but also in industrial
biotechnology,where the identification of novel and better-
producing strains is of great importance.For example,
discrimination and classification of brewing yeasts by
metabolic footprinting revealed [21] that it was possible
to classify strains that could not be discriminated at
genetic level owing to the inherent genetic complexity of
yeast brewing species.Because exometabolites strongly
affect the product quality in this and similar cases,meta-
bolic classification can directly reflect commercially
important traits,thereby confirming its potential for
industrial biotechnology.
Novel metabolic pathway discovery and metabolic
Currently,considerable industrial interest is focused on
the degradationof plant fibres [22] usedas rawmaterial for
the production of ethanol or other fuels and chemicals by
fermentation.One of the major goals of research in this
area is to achieve a complete degradation of plant fibre
polysaccharides (cellulose and hemicellulose) into fermen-
table monosaccharides (e.g.xylose and arabinose),ideally
without chemical or enzymatic hydrolysis.The optimal
combination of microorganism and process conditions for
this reaction remains to be determined,but metabolic
footprinting might provide key information by allowing
us to measure the degree of degradation via the detection
of degradation products that are present in the extracellu-
lar medium.The identification and,importantly,quanti-
fication of extracellular metabolites deriving from fibre-
degrading microorganisms [23,24] can provide important
clues on bottlenecks,as well as on previously unidentified
pathways in microbial metabolism.This information can
then be combined with transcriptomics and proteomics
data to further characterize the genes involved in fibre
degradation or other relevant pathways.The use of meta-
bolomics for obtaining integrative information and to dis-
cover novel metabolic pathways has been demonstrated for
the filamentous fungus Aspergillus nidulans [25].Analysis
of metabolic footprinting of A.nidulans grown under a
range of conditions significantly contributed to the identi-
fication of a novel fungal metabolic pathway,the phospho-
ketolase pathway,which is involved in xylose metabolism.
Metabolic footprinting can also be employed in biore-
mediation.Here,metabolic footprinting of polluted soils
and waters might indicate whether a polluting compound
has undergone a complete mineralization (i.e.has been
entirely degraded to CO
and water) or whether the biode-
gradation process has led to the production of hazardous
compounds,possibly due to metabolic bottlenecks that
hindered full biodegradation.In the area of bioremedia-
tion,the detection and characterization of catabolic path-
ways,as well as of possible metabolic constraints,might be
further improved by using isotope-labelled substrates
[26,27] that will allow us to follow the different biodegra-
dation steps of xenobiotic compounds [10].Once microor-
ganisms that can partially or completely degrade a
particular pollutant compound have been detected,meta-
bolic engineering can be employed to bypass apparent
bottlenecks or to improve the catabolic capacity of these
microorganisms.However,it might be necessary to trans-
fer an entire catabolic pathway that is able to mineralize a
compound in one species to a different and more-suitable
microorganism.This has been demonstrated for the decon-
tamination of soils polluted with 2,4-dinitrotoluene (2,4-
DNT) [28].Some microbial species belonging to the Bur-
kholderia genus have beenfound able to efficiently degrade
2,4-DNT.However,the fact that Burkholderia toxic
for plants and is also an opportunistic human pathogen
impaired the possibility of an in situ bioremediation
approach.To overcome this limitation,the entire degra-
dation pathway was transferred to a non-pathogenic and
plant-growth-promoting bacterium:Pseudomonas fluores-
cens.This kind of approach has great potential for improv-
ing bioremediation,where metabolic footprinting
combined with metabolic engineering will play a key role.
Bioprocess monitoring and development
Metabolic footprinting canyield a multitude of biochemical
information,which,together with the development of
advanced automatable analytical techniques,makes it
an attractive method for monitoring bioprocesses at indus-
trial scale.The microbial exometabolome substantially
changes throughout the different microbial growth phases
[8],which are each characterized by a specific footprinting,
meaning that a culture’s status can be determined simply
by ‘reading’ the corresponding MS spectra.This approach
is particularly useful when the target is the product of one
or more specific compounds whose biosynthesis is coupled
with growth,as has been shown in cyanobacteria [29].
In some bioprocesses it is very important to gain specific
knowledge about the presence of specific extracellular
metabolites,especially when exometabolites are the
essence of the final product,as in,for example,beer and
wine production.So-called ‘metabolic interactions’ have
been discovered during wine fermentation processes
[30,31],where the simultaneous presence of different yeast
species andstrains (mixedculture) resultedinanensemble
of flavour-active metabolites that was different from the
mix of compounds found in blended wines and,more
importantly,not just a sum of compounds produced by
the respective monocultures.This effect was a consequence
of interactions between the different yeasts and their
sharing of metabolites.Therefore,metabolic footprinting
could be developed as a direct and rapid quality control
method able to monitor the specific aroma generated
during wine fermentations.
A further aspect of metabolic footprinting important for
bioprocesses is its use for the monitoring of the physiologi-
cal status of cells and of conditions that could induce
Trends in Biotechnology Vol.26 No.9
cellular stress.Metabolic footprinting might help to
identify the most suitable strain and growth condition
for a given bioprocess [11].Furthermore,cells’ particular
responses to the presence of environmental stresses and
biomarkers could be revealed by metabolic footprinting,
and these responses might indicate the presence of toxic
chemicals in the environment.For example,metabolic
footprinting of sludge cultures during biological treatment
of wastewater [32] allowed the discrimination of different
types of chemical stress elements present in the treated
water,such as cadmium,2,4-DNT and N-ethyl-maleimide,
and this approach might pave the way to the development
of microbial biosensors for environmental monitoring.
Although lipids are usually not included in the meta-
bolome realm [10],biosurfactants are a significant part of
the molecules excreted by a variety of microorganisms.
Biosurfactants are amphiphilic molecules able to lower
interfacial energy and tension,and they are naturally
produced by pathogenic and non-pathogenic microorgan-
isms [33,34] with the main purpose of pseudosolubilizing
hydrocarbons and facilitating their uptake as a carbon
source.Surfactants are used in industry in a variety of
processes and,moreover,have recently been discovered to
have several properties of biomedical and therapeutic
importance,such as antibacterial and antiadhesive
actions,against several pathogenic microorganisms [35].
Due to their physical and chemical properties,surfactants
belong to the most important classes of industrial chemi-
cals,but their production is mainly petroleum-based and
therefore has a substantial environmental footprint.Bio-
surfactants are commercially promising alternatives to
chemical surfactants owing to their lower toxicity,higher
biodegradability and higher stability at extreme conditions
(i.e.extremes of pHand temperature).Metabolic footprint-
ing represents a valuable approach for the discovery and
characterization of novel biosurfactants,and it can also
help to determine ideal production processes through the
identification of the best natural and/or recombinant pro-
ducers and the optimal growth conditions [35].
Common procedures and databases for high-
throughput applications
One of the major advantages of metabolic footprinting is its
potential for being used in a high-throughput method that
can be easily used in research laboratories as well as on-
site during industrial bioprocesses.Furthermore,com-
pared with metabolic fingerprinting,metabolic footprint-
ing does not require any complex procedures,such as the
quenching (i.e.rapid stopping) of cellular metabolism,the
extraction of metabolites from cells and the subsequent
processing of metabolites for analysis [36].The number of
steps required before the actual analysis of intracellular
metabolites,in addition to being time consuming and
costly,can also affect the reliability and reproducibility
of results owing to an over-manipulation of samples,so the
low number of steps in metabolic footprinting gives it an
Furthermore,using direct injection mass spectrometry
(DIMS) [3] results in a short protocol (Figure 2) that can
yield significant results in determining target peaks as
specific markers (e.g.using defined metabolites to identify
a bioprocess status) and in functional genomics analysis
[8],which aims to discriminate between strains on the
basis of their entire metabolic footprints (Figure 2).How-
ever,a major drawback of DIMS is the so-called ‘matrix
effect’ [37],which is especially pronounced when chemical
interactions between extracellular components (sugars,
proteins and salts) interfere with the ionization process
in DIMS,thus affecting the pattern of peaks in the spectra.
In such cases,other techniques,such as liquid chromatog-
raphy coupled to mass spectrometry (LC/MS),should be
considered for the obtainment of reliable spectra in which
isomers of a single compound can be distinguished.
A detailed discussion of the technical considerations
that are associated with the identification of metabolites
is outside the scope of this review.Nevertheless,to develop
metabolic footprinting into a metabolomics technique that
is suitable for high-throughput application,benchmark
spectra with identified peaks are needed so that peak
patterns obtained fromMSor NMRanalysis can be rapidly
translated into relevant biological information.For this
reason,the establishment of detailed spectra databases is
of great importance for any metabolomics analysis,but it is
particularly useful for high-throughput metabolic foot-
printing.Furthermore,because all steps of a metabolite
analysis procedure are crucial in determining the features
of an MS or NMR spectrum,common experimental pro-
cedures should ideally be established for metabolite
analysis.However,the diversity among metabolites often
necessitates the use of several techniques to obtain a
complete and exact picture.This fact is being taken into
consideration by the scientific community,and efforts are
being undertaken to compile databases that will contain
very detailed informationonthe technical steps inaddition
to the obtained spectra [38].This will hopefully allow for
specific benchmark spectra to be used for peak identifi-
cation if specific analytical procedures have been adopted.
Concluding remarks
In a microbial system,extracellular metabolites include
metabolites that are excreted and secreted by cells into
their living environment,as well as metabolites left and
discharged into the environment as byproducts of natural
environmental resources.The entire ensemble of extra-
cellular metabolites released by a certain microbial com-
munity represents the metabolic footprinting of that
community.As we discussed in this review,crucial infor-
mation about a microbial system can be obtained from
metabolic footprinting analysis,and bothfundamental and
applied research can benefit fromthis knowledge.Already,
metabolic footprinting analysis has been demonstrated to
be a fast and reliable tool for discriminating between
different strains [8,18,19] that are often not otherwise
distinguishable.Furthermore,because some extracellular
metabolites are the basis of intercellular communication
circuits,referred to as QS,information obtained from
metabolic footprinting is of critical importance for elucidat-
ing QS circuits when combined with metabolite identifi-
cation and integrated with physiological and phenotypical
observations [17].Identification of QS metabolites might
contribute to the discovery of novel natural drugs [17] and,
furthermore,might help in the development of novel drugs
Trends in Biotechnology Vol.26 No.9
targeting QS molecules [14].Such drugs would have the
major advantage that they would not encourage the occur-
rence of resistant microorganisms because they would only
interfere with inter-cell communication and not with via-
bility,thereby avoiding the evocation of any selective
pressure to counteract the drug [14].We also highlighted
the potential of metabolic footprinting for high-throughput
applications [8],industrial bioprocess monitoring,product
quality control [30,31] and for monitoring the physiological
status of a cell culture [11,32].
Even though metabolic footprinting is the metabolomics
approach with the best fit for high-throughput appli-
cations,some obstacles are still present where fast metab-
olite identification is required.This problem could be
overcome by the establishment of detailed spectra data-
bases that could be used as benchmarks once metabolic
footprint spectra have been obtained.Establishing such
databases is a complex matter due to the complexity of
metabolite analysis,and several research groups are com-
bining their efforts [38] to define solid and reliable data-
bases.Such databases will be crucial for speeding up
spectra analysis and eliminating the current rate-deter-
mining step in metabolomics approaches.
Metabolic footprinting analysis has great potential for
biotechnology and industrial applications,but it can also
benefit fundamental biology applications.It is possible to
define a certain metabolic cell status through metabolic
footprinting owing to the tight relationship between
intracellular metabolism and the environment.The
relationship between intracellular metabolismand exome-
tabolome is not univocal;indeed,cells can tune their
metabolismaccording to the external environment,which
includes both natural resources and the metabolites
released by organisms living in the same environment
(Figure 1).This convoluted relationship indicates that
the way in which cells tune their metabolism according
to the extracellular environment has a direct effect on the
extracellular environment itself.Therefore,metabolic foot-
printing gives us indirect or direct information about the
intracellular metabolic status.Furthermore,according to
evolutionary laws,organisms that better manage to adapt
to the actual environment are the ones that survive.In this
regard,flexibility and plasticity of cellular metabolismare
needed,and this is achieved through the adaptation of
cellular enzymes to novel substrates,which can be
exploited as nutrient source.Even though detailed meta-
bolic maps are available for some microorganisms,they
have been designed on the basis of genome-scale models
[39] and of intracellular metabolic profiles without con-
sidering the possibility that certain enzymes might adapt
to different substrates.Therefore,these metabolic maps
represent usable scaffolds that need to be further refined
by integrating metabolic fingerprinting of the entire meta-
bolome with metabolic footprinting.This might make it
possible to infer new potential functions to previously
annotated enzymes,thus allowing the identification of
novel metabolic pathways that are ‘activated’ by cells when
they evolve.Therefore,including metabolic footprinting
and its influence on cell metabolism in the definition of
metabolic maps might account for the ‘plasticity’ and evol-
ution of metabolic networks.Current metabolic maps and
databases could be further updated by exploiting infor-
mation frommetabolic footprinting,leading to better defi-
nitions of biological systems and,in turn,advantages for
biotechnological applications.
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