1. Analyst
MINIREVIEW
Cite this: DOI: 10.1039/c6an00131a
Received 20th January 2016,
Accepted 6th April 2016
DOI: 10.1039/c6an00131a
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Applications of MALDI-TOF MS in environmental
microbiology
Inês C. Santos,a
Zacariah L. Hildenbrandb,c
and Kevin A. Schug*a,c
Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) is an
emerging technique for microbial identification, characterization, and typing. The single colony method
can be used for obtaining a protein fingerprint or profile unique to each microorganism. This technique
has been mainly used in the clinical field, but it also has significant potential in the environmental field.
The applications of MALDI-TOF MS in environmental microbiology are discussed in this review. An over-
view on the use of MALDI-TOF MS for environmental proteomics and metabolomics is given as well as its
use for bacterial strain typing and bioremediation research. A more detailed review on the use of this
technique for the identification, differentiation, and categorization of environmental microorganisms is
given. Some of the parameters that can influence the results and reproducibility of MALDI-TOF MS are
also discussed.
Introduction
The identification of microorganisms is very important in
different fields. Usually this identification is made by morpho-
logical (e.g. cell shape), phenotypic (e.g. Gram staining), and
genetic tests (e.g. polymerase chain reaction (PCR)). The mor-
phological and phenotypic tests are time consuming, while the
genetic tests require a high level of expertise and can be quite
expensive. Therefore, these techniques are not ideally suitable
for routine identification and alternatives would be welcome
for the rapid and low cost identification of microorganisms.1
Matrix-assisted laser desorption ionization time-of-flight
(MALDI-TOF) mass spectrometry (MS) is becoming a reliable
tool for microorganism identification.2
Despite high initial
acquisition costs, this technique can identify bacteria in a few
minutes and provide a low cost per sample analysis when com-
pared to conventional methods.
To perform MALDI-TOF identification, as summarized in
Fig. 1, microorganisms are placed on a target plate where they
are overlaid with a matrix solution, which co-crystalizes with
the sample and lyses the cells. The plate is placed in the
instrument where a laser converts the bacteria constituents,
mainly ribosomal protein molecules, into gas-phase ions that
are separated and identified according to their mass/charge
ratio. The mass spectrometer gives a spectral fingerprint that
is unique to the microorganism being analyzed. The organism
is then identified by comparing its spectral profile with a refer-
ence database (fingerprint-based approach). Correlations of
peak positions and intensities between experimental and data-
base spectra are used to generate a match score. This match
score is a level of confidence that the unknown isolate is a
representative of the candidate microorganism(s) matched
from the database. Protein mass pattern spectra can be used
to identify bacteria on the genus, species, and even on the sub-
species level.1,3–5
Currently, two main identification databases are available:
Bruker BioTyper from Bruker Daltonics, Inc. and SARAMIS
from bioMérieux. The databases use the Bruker Main
Spectrum analysis (MSP) and the bioMérieux SuperSpectrum
approaches, respectively.1,2,5
These approaches differ in the
algorithms used to identify the microorganisms. The MSP
technique consists of a collection of reference spectra obtained
from single reference strains, while the SuperSpectrum
technique consists of spectra obtained from various clinical
and reference strains grown under different conditions.2
Matrix solutions used in MALDI-TOF MS analysis can affect
the quality and reproducibility of the protein fingerprints.
Sinapinic acid and α-cyano-4-hydroxycinnamic acid (CHCA) are
the most commonly reported matrix compounds used to
obtain good-quality spectra in microbial identification.6
Fur-
thermore, formic acid (0.1%) can be added to the matrix solu-
tion to suppress salt-containing adduct ions, originated from
culture media, and to improve the resolution of spectra.6
Different sample preparation methods are available for
microorganism identification.7
The simpler “whole cell”
a
Department of Chemistry and Biochemistry, The University of Texas at Arlington,
Arlington, TX, USA. E-mail: kschug@uta.edu; Fax: +1 817 272 3808;
Tel: +1 817 272 3541
b
Inform Environmental, LLC, Dallas, TX, USA
c
Affiliate of the Collaborative Laboratories for Environmental Analysis and
Remediation, The University of Texas at Arlington, Arlington, TX, USA
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2. method consists of depositing a single colony on the MALDI
plate which is consequently overlaid with matrix. The other
methods require a chemical protein extraction step before ana-
lysis using an organic acid such as trifluoroacetic acid (TFA) or
formic acid. With protein extraction methods, a more detailed
protein fingerprint can be obtained; however, these are more
time consuming when compared to the whole cell method,
which does not require any chemical treatment. Nevertheless,
the addition of ethanol or methanol has been shown to
enhance the signals of higher mass proteins.3
The identifi-
cation of microorganisms by MALDI-TOF MS requires a cell
culturing step to obtain pure cultures. Enough bacterial cells
(105
–107
bacterial cells) must be grown for extraction and ana-
lysis, and this may be considered a drawback. However, the
need for culturing is also a common step for every other con-
ventional identification method.
MALDI-TOF MS has been extensively applied and is still
mainly used in the clinical field as shown by the number of
reviews published.8–12
In the last years, hundreds of systems
have been installed worldwide in clinical microbiology labora-
tories. The importance of rapidly identifying microorganisms
involved in human infections and consequently, applying the
right therapeutic, is unquestionable. However, MALDI-TOF MS
can also provide a significant contribution in environmental
microbiology.
In this review, the applications of MALDI-TOF MS in the
field of environmental microbiology are explored. An overview
of the works that describe the use of this technique for proteo-
mics (fingerprinting and profiling) in microbial identification,
differentiation, and categorization is given. The potential for
MALDI-TOF MS in metabolomics profiling is also discussed.
Additionally, the use of MALDI-TOF MS for bioremediation
research, mainly in identifying site-specific bacteria and
associated enzymes, is also discussed. In the end, the para-
meters that may influence the reproducibility of the mass
spectra are viewed as well as some approaches to improve the
quality of the MS results in the field of environmental
microbiology.
MALDI-TOF MS environmental
microbiology applications
Environmental microbiology is an area of research where the
use of MALDI-TOF MS remains to be comprehensively
explored. This technique is a popular tool for proteomics,
including microbial typing, but it may also be used in other
studies such as metabolomics. These two areas provide infor-
mation on the expression of proteins and on the diversity of
produced metabolites, respectively, in an organism under a
specific set of conditions.2,13
Overviews of these different
applications are given below.
Proteomics
Protein fingerprinting. The identification of microorganisms
from environmental sources is necessary to understand the
microbial community, for environmental monitoring, and to
identify possible pathogenic microorganisms. MALDI-TOF MS
has been an important advance in the field of environmental
proteomics as the protein fingerprint of each microorganism
can be used for identification. The identification can be per-
formed by comparing the unknown protein profile to a data-
Fig. 1 MALDI-TOF MS for bacterial identification. The sample colony is placed on a metal plate and overlaid with matrix. The molecules are ionized
by the laser and accelerated by an electric field. The ions are separated according to their m/z (flight time), while subjected to vacuum, until they
reach the detector, where the abundance of each signal is registered.
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3. base of reference profiles or by co-analyzing the unknown
profile with profiles of known bacteria. Table 1 presents some
examples of microorganisms identified from environmental
and clinical sources using MALDI-TOF MS. It is noteworthy
that the same microorganisms can be found in both clinical
and environmental samples. In fact, some human pathogens
derive from environmental reservoirs and are thus denomi-
nated as environmental pathogens. Nevertheless, environ-
mental microorganisms are more diverse and so their
identification and characterization pose a significant challenge
as the field grows.
Previous findings have described the application of MALDI-
TOF MS in the identification of microorganisms in environ-
mental samples such as sewage sludge, marine sponges,
water, soil, roots, and the rhizosphere.14–21
For example, in the
work by Emami et al.,15
MALDI-TOF MS was used to character-
ize bacteria in ballast water. Thirty-six isolates were identified,
at the genus-level, and the results were similar to those
obtained by 16S rRNA gene sequencing. For higher quality
spectra, the authors used cell lysates from actively growing
colonies instead of crude cells and α-cyano-4-hydroxycinnamic
acid (HCCA) as matrix, which they found to be an important
factor when trying to differentiate between closely related iso-
lates. Additionally, Ferreira et al.18
and Štursa et al.19
studied
the use of MALDI-TOF MS for the identification and character-
ization of microorganisms in the rhizosphere of plants. In the
former work, the authors built a database containing protein
profiles of 56 species of fast growing rhizobia and were able to
identify large populations of isolates from nodules with a
100% effectiveness. Furthermore, they concluded that MALDI-
TOF MS is a very useful tool for diversity and ecological
studies.
Overall, the works mentioned above describe MALDI-TOF
MS as a powerful technique in the field of environmental
microbiology for the rapid screening and identification of bac-
teria and for ecological studies. However, this technique still
presents some drawbacks.14,16,17
Kopcakova et al.16
studied the
ability of MALDI-TOF MS to identify cultivable microflora from
two waste disposal sites from the non-ferrous metal industry.
High quality mass spectra were obtained but most of the
bacteria isolates could be not identified. The overall
identification rate was lower than 20%. The authors empha-
sized the need to expand and refine the reference database
spectra to improve the ability of MALDI-TOF MS to identify
environmental bacteria, especially those acquired from
extreme environments. In the works by Lovecka et al. and
Koubek et al.,14,17
the ability of MALDI-TOF MS to identify
bacterial isolates obtained from contaminated soil was investi-
gated. They were unable to identify all the isolates and were
also unable to identify them down to the species level. These
works indicate the need of a universal sample pre-treatment
protocol and a more complete and environmentally-focused
database to improve the ability of MALDI-TOF MS to success-
fully identify environmental bacteria.
To overcome these limitations, researchers have attempted
to identify microorganisms by detecting and identifying
specific protein markers (biomarkers) in the protein finger-
print.24
A biomarker is a particular molecule that is specific to
a microorganism and confirms its detection and/or identifi-
cation.1
Peptides and proteins are the molecules most used as
biomarkers in MS-based microorganism identification, due to
their high abundance compared to other classes of molecules
and their relatively high ionization efficiencies. Furthermore,
proteins represent the genetic status of a bacteria and are,
therefore, more informative and characteristic than lipids and
metabolites. These protein biomarkers can be, for example,
virulence factors, toxins, and other strain-specific proteins that
are uniquely indicative of a certain microorganism and can be
used to facilitate the identification. For instance, by knowing
the molecular weight of a toxin, targeted searches for signals
at the corresponding m/z ratio can be made to aid the identifi-
cation of the microorganism.12
In fact, when studying MALDI-
TOF MS reproducibility, Wang et al.25
found a number of
signals that were conserved under different experimental con-
ditions and that have the highest potential for use as bio-
markers for bacterial identification. Therefore, these and other
authors proposed the use of specific conserved biomarker pro-
teins for bacterial identification as they are not altered by exter-
nal conditions. For example, in the work by Ruelle et al.,20
bacterial identification was based on the observation of a set
of biomarkers as shown in Fig. 2. Furthermore, the authors
studied the conditions that led to good-quality and reproduci-
ble spectra for the rapid identification of environmental bac-
teria. A protocol using a matrix solution composed of α-cyano-
4-hydroxycinnamic acid and an ethanol treatment for the
Table 1 Examples of bacteria identified by MALDI-TOF MS in environ-
mental and clinical fields
Environmental14–22
Clinical5,22,23
Achromobacter sp. Acinetobacter baumannii
Acinetobacter sp. Campylobacter spp.
Aeromonas sp. Enterohemorrhagic
Escherichia coli
Arthrobacter sp. Enterococcus faecium,
Enterococcus faecalis
Bacillus mycoide Haemophilus influenza
Burkholderia xenovorans Klebsiella pneumonia,
Klebsiella oxytoca
Escherichia coli Listeria spp.
Enterococcus faecium, Enterococcus
faecalis
Neisseria spp.
Microbacterium sp. Nocardia spp.
Pseudoalteromonas sp. Proteus mirabilis
Pseudomonas aeruginosa,
Pseudomonas stutzeri, Pseudomonas
putida, Pseudomonas gessardii
Pseudomonas aeruginosa
Rhizobium Salmonella thyphimurium,
Salmonella enterica
Rhodococcus sp. Shigella spp.
Salmonella spp. Staphylococcus aureus,
Staphylococcus epidermidis
Serratia fonticola Streptococcus pneumoniae
Stenotrophomonas sp. Vibrio parahemolyticus
Vibrio spp. Yersinia enterocolitica
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4. extraction of more and higher mass cell compounds was
adopted. With this standardized protocol, environmental bac-
terial strains of Escherichia coli, Salmonella, and Acinetobacter
were identified from sewage sludge using MALDI-TOF MS. As
another example, Dieckmann et al.,21
performed the strain-
level identification of diverse strains isolated from marine
sponges by implementing weighted pattern matching, where
the peaks with higher importance for discriminating strains
were given more weight in the analysis.
When compared to conventional identification methods,
MALDI-TOF MS provides higher throughput and a lower cost
of analysis. However, only cultivable bacteria are identified
by this technique. As it is known, less than 1% of microbial
species in the environment are able to grow in rich growth
media under laboratory conditions.26
This may be seen as a
major drawback of this technique when applied in the study
of environmental communities. Nevertheless, recent new
approaches to cultivate previously uncultivated bacteria have
been studied by using dilute nutrient media or simulated
natural environments,27
which may help overcome limit-
ations for identifying the limited number of cultivable
bacteria.
Protein profiling. Nowadays, two approaches for bacterial
identification through protein identification and discovery of
new biomarkers are used: top-down28
and bottom-up29
proteo-
mics. In the former approach, intact proteins are identified by
analyzing their primary structure, while in the latter approach,
the proteins are enzymatically digested and their peptides
used for identification. Traditionally, these approaches are per-
formed by gel electrophoresis and immunoassays such as
western blot, ELISA, immunohistochemistry, and protein
microarrays.30
In immunoassays, protein identification is per-
formed by using specific antibodies that are labeled with an
enzyme or tagged to a fluorophore for detection. Nevertheless,
these techniques present some drawbacks such as being labor
intensive and they can sometimes provide poor reproducibility
and resolution. Mass spectrometry is now considered to be the
most powerful tool in proteomics, as it provides higher
throughput and it is very sensitive and reproducible. In the
top-down approach, intact proteins are separated and intro-
duced in the mass spectrometer where they are fragmented
(MS/MS). The proteins can be identified by comparing MS/MS
spectra with fragmentations predicted from protein sequences
in existing proteome databases. In the bottom-up approach,
the proteins are first separated by chromatography or gel elec-
trophoresis, then digested into constituent peptides by specific
enzymes. The peptide mixtures are then introduced in the
mass spectrometer for further interrogation.31,32
Peptide
identification is performed by comparing the masses of pep-
tides and MS/MS fragment ions with theoretical sequences
derived from genome sequence data. When using MS, top-
down proteomics presents some limitations compared to
bottom-up proteomics as peptides are more easily fractionated,
ionized, and fragmented compared to intact proteins.33
Bio-
informatics approaches for automated protein identification
using mass spectral data are important tools to support top-
down and bottom-up proteomics. The informatics approaches
for protein identification have already been extensively
reviewed by Johnson et al. and Zhang et al.32,34
and so will not
be further discussed here.
Both MALDI and electrospray ionization (ESI) have been
extensively used for proteomic analyses. However, MALDI pro-
vides some advantages, such as simple sample preparation
and formation of singly charged ions. Therefore, MALDI-TOF
MS can be an important tool in the identification of proteins
for microorganism identification.35,36
Demirev et al.,35
demon-
strated the ability of MALDI-TOF/TOF MS to rapidly identify
intact Bacillus spore species using a top-down approach.
Protein spore biomarkers were fragmented and identified by
comparing their spectra with a proteome database. Fragment
ion spectra of whole protein biomarkers were obtained
Fig. 2 MALDI spectra of (A) Salmonella 2B5, (B) Acinetobacter 14B5 and
(C) Escherichia coli 1B1 showing the potential genus- (.) and strain- (*)
specific biomarkers. (Reprinted from Ruelle et al.20
with permission from
Wiley. Copyright 2004.)
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5. without the need for digestion, separation, and cleanup. The
identification of protein spore biomarkers allowed the identifi-
cation of Bacillus spore species such as Bacillus globigii and
Bacillus cereus. Bacillus spores were also identified in a bottom-
up approach using MALDI-TOF MS in work by Warscheid and
Fenselau.36
Spore proteins were enzymatically digested and
analyzed by MALDI-TOF MS using a curved-field reflectron
instrument. Proteins were identified by partial sequencing of
distinctive tryptic peptides from Bacillus spores via post-source
decay analysis combined with genome-based database
searches by Mascot Sequence Query. Various spore proteins
were identified which allowed the characterization of Bacillus
species. By performing the protein identification, microorgan-
isms were also identified. As shown, when using MALDI-TOF
MS, top-down and bottom-up approaches provide a much
higher level of identification specificity for individual micro-
organisms when compared to the identification of micro-
organisms using their protein fingerprint.
Top-down and bottom-up proteomics are used not only for
bacterial identification, but also in microbial ecology for
different applications,37
where the bottom-up approach, in
spite of being more laborious, is more commonly used than
the top-down approach. MALDI-TOF MS can be used to track
new functional genes and metabolic pathways. For example,
Kurian et al.38
used two-dimensional electrophoresis (2-DE)
and MALDI-TOF MS to provide insight into the heterotrophic
metabolism of Synechocystis sp. PCC 6803. They were able to
characterize the cellular metabolic shift due to a trophic
change in Synechocystis by identifying the proteins produced
in autotrophic and heterotrophic conditions.
MALDI-TOF MS can also be used to map the proteins of an
ecosystem in a time-resolved fashion. Kan et al.39
used proteo-
mic approaches to study time-dependent protein expression
profiles of Chesapeake Bay microbial communities. The
authors reported that the MALDI-TOF MS analysis of highly
expressed proteins produced no significant matches to known
proteins. They conjectured that it is unlikely that many pro-
teins in environmental samples will share a high level of iden-
tity with proteins in sequence databases derived from cultured
organisms. De Vriendt et al.40
used 2-DE and MALDI-TOF/TOF
MS to describe the changes in protein expression of Shewanella
oneidensis MR-1 when growing as a biofilm.
Additionally, MALDI-TOF MS can be used in the identifi-
cation of proteins associated with specific stresses. When
subjected to changes in environmental parameters, micro-
organisms change their protein expression profiles, as a
response to overcome these changes. These differences in the
protein expression profiles can be used as an indicator of
environmental pollution. In the work by Heim et al.,41
MALDI-
TOF MS was used to identify proteins produced by Pseudo-
monas putida due to iron limitation stress. The authors were able
to identify 25 proteins that were up- and downregulated due to
iron deprivation. Lacerda et al.42
used 2-DE, MALDI-TOF MS/
MS, and de novo sequencing to identify proteins differentially
expressed over time following exposure of a bacterial commu-
nity to an inhibitory level of cadmium.
Clearly, MALDI-TOF MS is an important tool in microbial
ecology, allowing the identification of stress-related proteins
and an insight into the microbial community proteome. Never-
theless, an improvement in proteome databases is needed to
drive this application forward.
Microbial typing. Another interesting application of MALDI-
TOF MS is for the typing of bacteria, to identify microorgan-
isms at the strain level.43
The methods most commonly used
for microbial typing are 16S rRNA sequencing, pulsed field gel
electrophoresis (PFGE), multilocus sequence typing (MLST),
and repetitive extragenic palindromic-polymerase chain reac-
tion (rep-PCR).43–45
Brief descriptions and the main advan-
tages and disadvantages of the methods often used for
identification and typing are presented in Table 2. In spite of
their recognized resolution, many of these approaches are
expensive, laborious, and time consuming. These are certainly
undesirable attributes, specifically in the identification of con-
tamination sources as is, for example, described in the works
by Giebel et al. and Siegrist et al.46,47
When dealing with patho-
gens, a rapid identification of the contamination source is
necessary to rapidly resolve the problem. Due to these reasons,
MALDI-TOF MS is gaining more attention in this field as it
requires less sample preparation and provides higher analysis
throughput.
When using MALDI-TOF MS, microbial typing can be per-
formed either for taxonomy, bacterial differentiation, or categ-
orization.43
In taxonomy, the microorganisms are classified
into genera, species, or strains, based on their protein finger-
print or profile similarities, as explained previously. For bac-
terial differentiation and also identification, MALDI-TOF MS
can be used to cluster, in the form of a dendrogram, the
protein profiles according to their similarities. By comparing
the percentage of similarity of an unknown profile with
known bacteria profiles, the taxonomy of the unknown bac-
teria can be deduced. Furthermore, strain-specific differences
can be determined and used to study taxonomic and inter-
and intra-species diversity. Several works have been described
that use MALDI-TOF MS for bacterial differentiation and
identification and some are discussed in this manuscript. In
the work by Dieckmann et al.,21
Pseudoalteromonas sp. iso-
lated from marine sponges and differing in only 1 bp out of
400 bp or by 3–4 bp out of 1500 bp of their 16S rRNA gene
sequences, were readily discriminated by their MALDI-TOF
MS spectra. In fact, the authors described considerable intra-
and inter-species classification problems, which 16S rRNA
sequencing failed to resolve. MALDI-TOF MS, by introducing
additional phenotypic markers, was able to discriminate very
closely related species with high reliability. In another
study,48
MALDI-TOF MS was used to characterize seven pet-
roleum microorganisms. The authors showed the discrimi-
nation power of this technique as these seven petroleum
strains were clustered into three groups, consistent with the
molecular identification using the gyrB gene sequence as the
phylogenetic marker. MALDI-TOF MS was able to discriminate
strains that, due to their similarities, were not discriminated
by 16S rRNA.
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6. Additionally, Munoz et al.49
verified that MALDI-TOF MS
analysis of whole cells is a powerful tool for studying the culti-
vable fraction of hypersaline environments. The authors used
MALDI-TOF MS to classify bacterial isolates into 25 phenotypic
clusters at 52% similarity, which was validated by 16S rRNA
sequencing to indicate that each phenotypic cluster consisted
of a homogeneous set of strains. In the work by Donohue
et al.,50
MALDI-TOF MS was used for the speciation of
unknown environmental water isolates of Aeromonas using the
m/z signature of known strains of that microorganism. Due to
its analysis speed and its capability for handling a large
number of samples, the authors proffered that this technique
could be useful for environmental monitoring.
Eddabra et al.51
described the use of MALDI-TOF MS to dis-
criminate 30 Vibrio strains isolated from two wastewater treat-
ment plants. The dendrogram obtained by MALDI-TOF MS
was different from the one obtained by PFGE which could be
explained by the different targets analyzed by the two
methods. Nevertheless, the results showed the ability of
MALDI-TOF MS to differentiate closely related Vibrio spp.,
which presented a high congruence of strain grouping. In
another work, Stets et al.52
were able to identify and group bac-
terial isolates from wheat roots. By comparing the dendro-
grams obtained with whole-cell MALDI-TOF MS analysis and
16S rRNA gene sequence phylogeny, they observed that the
former had a higher resolution within the genus level than the
latter, as it was able to separate the isolates sharing high 16S
rRNA sequence identity in different clusters. Therefore, the
authors concluded that whole-cell MALDI-TOF MS analysis can
be used as a rapid and efficient screening method for grouping
bacterial isolates from environmental samples, independently
of databases. Furthermore, they determined that this tech-
nique may have the potential to differentiate bacterial isolates
at the strain level.
All the above works described the successful application of
MALDI-TOF MS in grouping bacterial isolates. Nevertheless,
the ability of this technique to differentiate at the strain level
does not always overcome the ability of conventional methods
as shown by Ghyselinck et al.53
The authors examined the taxo-
nomic resolution of MALDI-TOF MS profiling for bacteria iso-
lated from the rhizosphere of potato plants. In fact, this
technique was able to differentiate bacterial strains but the
conventional technique, rep-PCR, facilitated strain differen-
tiation more readily than MALDI-TOF MS when members of
the genera Rhizobium, Streptomyces, Paenibacillus, Arthrobacter,
and Pseudomonas were considered.
Bacterial strain typing by MALDI-TOF MS can be used to
determine the origin of a specific strain by grouping the iso-
late’s protein profile by source. This information can be used
to determine the source of, for example, a microbial contami-
nant. This is an approach termed bacterial source-tracking
(BST). The works by Giebel et al. and Siegrist et al.46,47
describe
the potential use of MALDI-TOF MS to identify the sources
of pathogenic bacteria (fecal contamination) found in re-
creational and surface water, respectively. Siegrist et al.47
used
MALDI-TOF MS-based fingerprinting and the Dice similarity
coefficient to cluster several E. coli isolates from canine,
bovine, and avian sources. Using six avian, three bovine, two
canine, and four human E. coli isolates, the authors observed
that only the human isolates did not group completely by
source. In the work by Giebel et al.,46
the Pearson product-
moment correlation coefficient was used. As with the Dice
Table 2 Review of the methods often used for bacterial identification and typing43–45
Method Description Pros Cons
Pulsed field gel
electrophoresis (PFGE)
Gel electrophoresis technique where the
polarity of the current changes for
separation of very large DNA fragments
High discriminatory
ability and reproducibility
Relatively costly and time
consuming
Amplified fragment length
polymorphism (AFLP)
PCR amplification of a subset of DNA
fragments generated by restriction
enzyme digestion
Reproducible Labor-intensive and costly
Random amplification of
polymorphic DNA (RAPD)
PCR amplification of random DNA. The
amplification is followed by electrophoresis
Cheap, rapid, and easy to
perform
Lack of reproducibility
Variable-number tandem
repeat (VNTR)
PCR amplification of polymorphic regions of
DNA containing the VNTRs
High discriminatory
ability
Lack of reproducibility
Repetitive extragenic
palindromic PCR (rep-PCR)
PCR amplification of repetitive DNA
elements
Easy to perform Discriminatory power and
reproducibility is lower compared
to PFGE and MLST
16S rRNA sequencing PCR amplification and sequencing of 16S
rRNA gene sequences
Useful for the
discrimination until the
Genus level
Relatively costly and limited
discriminatory power
Multilocus sequence analysis
and multilocus sequence
typing (MLST)
PCR amplification and sequencing of
multiple housekeeping genes
Good discriminatory
ability
Time consuming and costly
MALDI-TOF MS Molecular weights of proteins are used to
identify microorganisms
High throughput, easy to
perform, low cost per
analysis
High initial instrumentation cost,
limited resolution, and database
discordances
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7. similarity coefficient, they found intrareplicate repeatability to
be lower than that of the former software. Fig. 3 shows the
cluster analysis of 21 Enterococcus isolates from seven sources
(human, bovine, canine, chicken, duck, goose, and gull). All
21 isolates were not grouped by source, but the gull and
chicken isolates composed their own discrete cluster, and two
out of the three human (human77 and human80) isolates
grouped together. Overall, both works recognize the ability of
MALDI-TOF MS to group isolates by source and the potential
of this technique to fingerprint environmental isolates and
therefore be applied as a rapid and accurate BST tool.
In spite of its recognized benefits in bacterial strain typing,
MALDI-TOF MS still needs to be further explored in the field
of environmental chemistry. The identification at the strain
level requires higher resolution which may be more challen-
ging as strains of the same species are quite similar.43
Also,
some factors may influence the reproducibility of the tech-
nique, as explained below, which is very critical when the
identification of a bacterium’s strain is intended.
Applications in bioremediation. Environmental pollution is
of great concern and environmentally friendly alternatives for
remediation are necessary. The use of microorganisms to
reduce or eliminate hazardous compounds from the environ-
ment, so called bioremediation, is a promising approach.54
MALDI-TOF MS can be used for the rapid screening and
identification of site-specific microorganisms present in
contaminated environments using their global protein
expression.24
This allows researchers then to focus on specific
microorganism species to evaluate their potential for degra-
dation of chemical hazards. After evaluating their capability,
the isolated microorganisms can be used for bioremediation
of contaminated and polluted sites. As an example, in the
works by Lovecka et al. and Uhlik et al.,14,55
the identification
of bacteria isolated from contaminated soil for bioremediation
purposes was performed using MALDI-TOF MS. In both works,
the bacteria were isolated from contaminated soil by using
their ability to grow on solid mineral medium with the chemi-
cal hazards, pesticides or biphenyl, as a sole carbon source.
Afterwards, the isolates were identified, some to the strain-
level, using MALDI-TOF MS. The results obtained were in
agreement with the results of 16S rRNA sequencing. However,
in both works there were additional microorganisms that were
not successfully identified by MALDI-TOF MS, which the
authors believe may be due to their absence in the database.
Nevertheless, the authors believe that MALDI-TOF MS is an
important tool for bioremediation research as it allows the
rapid and accurate identification of site-specific microorgan-
isms. As the isolated microorganisms have the ability to grow
using the hazardous exogenous compounds as sole carbon
source, they can act as potential degraders and therefore be
Fig. 3 Cluster analysis of mass spectra from Enterococcus isolates from seven sources. Similarity coefficients were calculated using the method of
Pearson, and the dendrogram was constructed using the UPGMA approach. (Reprinted from Giebel et al.46
with permission from Elsevier. Copyright
2008.)
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8. used for on-site bioremediation. However, only the work by
Lovecka et al.14
specifically studied the capability for the
identified bacteria to degrade the contaminants by measuring
the degradation of pesticides and the formation of degradation
products.
Top-down and bottom-up proteomics can also be used in
bioremediation studies to identify the proteins and enzymes
that catalyze the mineralization of chemical hazards. These
enzymes can be used as catalysts for cell-free remediation.24
Tomás-Gallardo et al.,56
used MALDI-TOF MS(/MS) for the
identification of proteins specifically involved in phthalate and
protocatechuic acid (PCA) degradation by Rhodococcus sp.
through de novo peptide sequencing. In the work by Kim
et al.,57
eighty unique proteins were identified by 2-DE/MALDI-
TOF MS from Pseudomonas putida KT 2440 cultured in the
presence of six different organic compounds. The authors
refer that the proteomics analysis was laborious and accurate
quantification was not easy to perform. To overcome this draw-
back, cleavable isotope-coded affinity tag (ICAT) analysis was
performed. The information gained from this experiment com-
plemented the results, confirming some proteins ID and
revealing additional ones. In another work,58
the Acinetobacter
radioresistens S13 membrane proteome was profiled during
aromatic exposure using 2-DE/MALDI-TOF MS. The developed
method allowed the identification of proteins that were only
expressed in the presence of aromatic substrates.
Furthermore, bottom-up proteomics has also been used to
monitor bioremediation. In work by Wilmes et al.,59
2-DE and
MALDI-TOF MS were used to identify highly expressed proteins
during microbial transformations from a mixed culture acti-
vated sludge system important for phosphorus removal. The
authors were able to identify proteins related to the chemical
transformations.
MALDI-TOF MS, as a high-throughput technique, is an
interesting tool for bioremediation studies. This technique
allows the rapid identification of site-specific microorganisms
present in contaminated environments. Additionally, the
identification of enzymes for the mineralization of chemical
hazards is also possible without the need of cultivation.
MALDI-TOF MS can also be used to monitor the bioremedia-
tion strategy in situ. Undoubtedly, this is a technique for which
much more can be explored.
Metabolomics
Metabolomics involves the investigation of all metabolites pro-
duced and liberated by an organism under certain conditions.
Fig. 4 Metabolite analysis E. coli extract by MALDI-TOF-MS. Top: Mass spectrum of methanol lysed E. coli strain DH5-R. Bottom: Magnification
from 700 to 800 m/z. Lower trace is blank. Upper trace is E. coli sample, offset 10% for clarity. * indicates peaks in matrix or blank. (Reprinted from
Edwards and Kennedy,62
with permission from the American Chemical Society. Copyright 2005.)
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9. MALDI-TOF MS has been extensively used for proteomic fin-
gerprinting but it is also a sensitive tool for untargeted meta-
bolomics, more specifically in metabolic profiling and
fingerprinting.60
Metabolic profiling consists of studying a
specific group of metabolites related to a specific metabolic
pathway. This approach can be an important tool for bioreme-
diation studies. In bioremediation, it is important to deter-
mine if the isolated bacteria from contaminated sites are able
to degrade chemical hazards into less hazardous, and ulti-
mately, completely innocuous byproducts. Mass spectrometry
can be used to follow the biodegradation pathways either in
the environment or in laboratory assays by identifying the cata-
bolic products, therefore determining the bacteria’s capability
for degrading toxic compounds.24
In laboratory assays, the
microorganism is incubated in mineral media with the pollu-
tant, and MALDI-TOF MS can be used to identify the expected
metabolites that are formed as a result of the biodegradation.
Due to its high sensitivity, MALDI-TOF MS can be used as a
tool to predict environmental contaminations as the metab-
olite fingerprint may change when the microorganism is
exposed to such types of stress.61
This approach is usually per-
formed by direct injection mass spectrometry (DIMS) but the
use of MALDI-TOF MS could be explored for metabolic finger-
printing as it allows minimal sample preparation and high-
throughput analysis. In fact, in the work by Edwards and
Kennedy,62
MALDI-TOF MS was used for metabolomics where
over 100 metabolites from E. coli were detected as shown in
Fig. 4. The same authors acknowledged that MALDI-TOF MS
has been less commonly used for the characterization of small
molecules. In fact, when analyzed by this technique, small
molecules suffer from matrix ion interferences and detector
saturation in the low mass range. However, Edwards and
Kennedy62
demonstrated that negative ionization mode
MALDI-TOF MS with 9-aminoacridine (9-AA) as the matrix
appears to be a promising tool for metabolic profiling. For
future work, the authors propose the use of separations to
improve the number of compounds detected and detection
limits by minimizing competitive ionization.
Furthermore, MALDI-TOF MS can be used for metabolic
profiling by detecting specific metabolic biomarkers that are
an indicator of the presence of a particular microorganism.4
For example, Persson et al.63
were able to detect bacteriochloro-
phyll a and homologs of bacteriochlorophyll c that are
characteristic of the bacteria Chlorobium tepidum. The authors
suggested that MALDI-TOF MS can provide taxonomic infor-
mation by studying the pigment composition of photo-
synthetic bacteria.
Improving MALDI-TOF MS
reproducibility
Applications of MALDI-TOF MS in environmental micro-
biology, either for identification or typing, still present some
limitations as different factors can influence the reproducibil-
ity of the method or lead to the misidentification of bacteria.25
These limitations may be due to different reasons such as the
composition of the bacteria’s cell wall or the choice of the
appropriate sample pre-treatment method. According to Wang
et al. and Valentine et al.,25,64
the same species can produce
different mass spectra if different chemical extraction methods
or growth conditions are used. Furthermore, Toh-Boyo et al.,65
demonstrated that matrix surface morphology heterogeneity is
an important factor contributing to mass spectra profile repro-
ducibility in bacteria MALDI-TOF MS analysis. The authors
point out the importance of the sample preparation strategy to
reduce or eliminate the MALDI matrix morphology heterogen-
eity, thereby reducing the variability of the bacteria mass spec-
tral profiles. Also, the growth age can have an influence on
MALDI-TOF MS results. At early stages, bacteria produce
increased amounts of proteins as these are needed for growth.
Therefore, the quantity of proteins varies with age. Due to
these reasons, it is very important to identify bacteria grown
under similar conditions and, when performing comparative
studies, it is important to use bacteria that have entered the
same growth phase.7
As previously discussed and according to Havlicek et al.,2
there are different databases available in the market for micro-
organism identification using MALDI-TOF MS. The identifi-
cation of bacteria is performed with the aid of a protein
database, where the unknown protein spectrum is compared
to reference spectra. Therefore, this database must be, as
much as possible, complete. However, these platforms do not
currently include the broad range of microorganisms found in
the environment.14
The protein databases are biased towards
clinical organisms. In fact, some of the previously described
works that use MALDI-TOF MS for microorganism identifi-
cation in environmental samples argue that a more environ-
mentally-oriented database should be a priority.14,52
Moreover,
if a microorganism is exposed to a stressful environment, its
protein profile can change due to the production of stress-
related proteins which may lead to its misidentification. Thus,
the way in which the databases are populated with spectra for
matching purposes may require special considerations relative
to clinical databases, since the range of environmental stresses
can be quite a bit more variable.
Conclusions
MALDI-TOF MS can be a powerful tool in the field of environ-
mental microbiology and bioremediation research. This
technique has already been proven to be a workhorse in
proteomics. A significant number of papers describe the use of
this technique for the identification and differentiation of
environmental microorganisms through their protein profile.
In fact, MALDI-TOF MS can be used, not only for microorgan-
ism identification and differentiation but also for detection of
protein or metabolite biomarkers that can be used as an indi-
cator of the presence of a specific bacterium. This identifi-
cation is important to detect possible microbial pathogens, to
study the bacterial community within the environment, or to
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10. identify contaminant-degrading bacteria. The application of
MALDI-TOF MS for metabolomics still has room for improve-
ment specifically when applied to bioremediation studies to
confirm the bacteria’s capacity to degrade toxic pollutants.
Furthermore, this technique can be used as an important tool
for bacterial source-tracking as identification to the strain level
is possible.
In spite of its recognized advantages, MALDI-TOF MS repro-
ducibility is influenced by culture conditions and instrumental
parameters. Therefore, it is very important to use the same
sample preparation protocol and to ensure that the analyzed
bacteria are all at the same growth stage. Additionally,
improvements in the protein database should be made to
include more environmental microorganisms and to take into
account different protein profiles that can be obtained due to
environmental stress.
We believe that the potential of MALDI-TOF MS in the field
of environmental microbiology has yet much to be explored.
Currently, MALDI-TOF MS methods for bacterial identification
still require validation from molecular methods due to the
limitations described. Additionally, challenges are encoun-
tered due to the complexity of environmental samples and due
to the diversity of environmental microorganisms. However,
future advancements such as the improvement of the protein
databases and sample preparation will allow this technique to
be implemented as a routine method for environmental micro-
biology, eventually replacing conventional methods. In fact,
MALDI-TOF MS is simple to perform allowing a low cost and
fast analysis. This technique can be further explored in bio-
remediation research as an important tool for the rapid identi-
fication of site-specific bacteria present in a contaminated
environment or the identification of enzymes responsible for
the production or removal of chemical hazards.
Acknowledgements
Support for this work is acknowledged from the Collaborative
Laboratories for Environmental Analysis and Remediation at
The University of Texas at Arlington. This consortium is largely
supported by philanthropic contributions by landowners and
citizens concerned about the potential environmental impact
of industrial processes.
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