genomic and proteomics

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21st Century Directions in Biology

Since the first recognition of microorganisms,scientists have devised classification schemes with thegoal of systematically identifying species in an evolutionary

or phylogenetic context (Clarke 1985). This has consistently

proved more challenging for bacteria than for macroorgan-isms. Bacteria are asexual, so the classic definition of a speciesas a group of organisms that can interbreed and produce

fertile offspring is difficult to apply. Furthermore, because of

their small size, bacteria have a limited range of morpholog-

ical attributes. They do exhibit enormous biochemical diversity in both their metabolism and cell structure; this has proved

to be a useful cue for the taxonomy of some groups, but by

no means all of them. It is important, then, that the molec-

ular revolution that has transformed all of biology has had asgreat an impact on the taxonomy and systematics of bacteria

as in any other area of biology. In the 1970s, on the basis of

molecular comparisons of evolutionarily conserved riboso-

mal genes, Carl Woese proposed the then-heretical notion thatthe bacteria actually made up two separate domains, theBacteria and the Archaea, each as distinct from one another

as they are from the Eukaryotes, the third domain that com-

prises all “higher forms” of life (Woese 1987). This classifi-

cation, supported by reams of additional molecular data, isnow the standard view among microbiologists. This is not to

say that bacterial systematics is now fully standardized; indeed,

there is a vigorous ongoing debate about what constitutes a

bacterial species (Gevers et al. 2005, Achtman and Wagner2008). Nonetheless, molecular systematics has provided the

crucial framework for building bacterial classification schemes.

Despite the lack of a coherent species definition, the timely

classification, characterization, and identification of bacteriacontinue to be critical in many areas, including public health,

clinical diagnosis, environmental monitoring, food safety

monitoring, and identification of biological threat agents.In particular, the recent advances of modern molecular tech-niques in genomics and proteomics have offered attractive

alternatives to conventional microbiological procedures for

characterizing and identifying microorganisms. These new

methods can provide a rapid, multidimensional data outputwith taxonomically relevant molecular information on both

individual strains and whole populations.

This article is primarily concerned with the identification

of individual strains of bacteria that can be grown as axenic

David Emerson is a senior research scientist at Bigelow Laboratory for Ocean

Sciences, West Boothby Harbor, Maine. He is an environmental microbiologist

who has worked on developing methods for the rapid identification of a

variety of environmentally important bacteria and archaea. Liane Agulto

is a biologist at the American Type Culture Collection (ATCC) in Manassas,

Virginia; her major interest is identifying disease-related biomarkers using

proteomics technology. Henry Liu, a graduate student at Georgetown University

School of Medicine in Washington, DC, interned at the ATCC, where he

worked on developing a diagnostic kit for rapid antimicrobial susceptibility

testing. Liping Liu (e-mail: [email protected]) was the head of proteomics at the

ATCC and is now the director of research and development at Stealth Peptides,

Inc., in Rockville, Maryland. Her major expertise is in identifying biomarkers

using proteomics technologies and in developing biotherapeutics. © 2008

American Institute of Biological Sciences.

Identifying and Characterizing

Bacteria in an Era of Genomics

and Proteomics

DAVID EMERSON, LIANE AGULTO, HENRY LIU, AND LIPING LIU

The advent of new molecular technologies in genomics and proteomics is shifting traditional techniques for bacterial classification, identification,and characterization in the 21st century toward methods based on the elucidation of specific gene sequences or molecular components of a cell. Wediscuss current genotypic and proteomics technologies for bacterial identification and characterization, and present an overview of how these new

technologies complement conventional approaches. The new methods can be rapid, offer high throughput, and produce unprecedented levels of discrimination among strains of bacteria and archaea. Remaining challenges include developing appropriate standards and methods for thesetechniques’ routine application and establishing integrated databases that can handle the large amounts of data that they generate. We conclude by discussing the impacts of rapid bacterial identification on the environment and public health, as well as directions for future development in this

field.

Keywords: bacterial identification, bacterial characterization, genotype, proteomics, bioinformatics

www.biosciencemag.org November 2008 / Vol. 58 No. 10 • BioScience 925



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cultures in the laboratory. The discrimination and identifi-cation of bacteria within mixed natural populations is also a

rapidly developing field that utilizes some of the same tech-

niques, but it is an entirely separate subject (Liu and Stahl 2007,

Logue et al. 2008). Methods of bacterial identification can bebroadly delimited into genotypic techniques based on profiling

an organism’s genetic material (primarily its DNA) and phe-notypic techniques based on profiling either an organism’s

metabolic attributes or some aspect of its chemical compo-sition. Genotypic techniques have the advantage over pheno-

typic methods that they are independent of the physiological

state of an organism; they are not influenced by the com-

position of the growth medium or by the organism’s phaseof growth. Phenotypic techniques, however, can yield more

direct functional information that reveals what metabolic

activities are taking place to aid the survival, growth, and

development of the organism. These may be embodied, forexample, in a microbe’s adaptive ability to grow on a certain

substrate, or in the degree to which it is resistant to a cohort

of antibiotics. Because genotypic and phenotypic approaches

are complementary and use different techniques, this review is divided into two parts. However, this division is historical;

we predict that as molecular-based identification matures,

there will be more and more overlap in the information

obtained using different methodologies.

Genotypic methodsGenotypic microbial identification methods can be broken

into two broad categories: (1) pattern- or fingerprint-basedtechniques and (2) sequence-based techniques. Pattern-based

techniques typically use a systematic method to produce a

series of fragments from an organism’s chromosomal DNA.These fragments are then separated by size to generate a pro-file, or fingerprint, that is unique to that organism and its very

close relatives. With enough of this information, researchers

can create a library, or database, of fingerprints from known

organisms, to which test organisms can be compared. Whenthe profiles of two organisms match, they can be considered

very closely related, usually at the strain or species level.

Sequence-based techniques rely on determining the

sequence of a specific stretch of DNA, usually, but not always,associated with a specific gene. In general, the approach is the

same as for genotyping: a database of specific DNA sequences

is generated, and then a test sequence is compared with it.

The degree of similarity, or match, between the two sequencesis a measurement of how closely related the two organismsare to one another. A number of computer algorithms have

been created that can compare multiple sequences to one

another and build a phylogenetic tree based on the results

(Ludwig and Klenk 2001). The example cited above of usingsequence comparisons of the ribosomal RNA (rRNA) gene

to distinguish bacteria and archaea demonstrates how this

information can be applied to identify relationships among

microorganisms.Both fingerprinting techniques and sequence-based meth-

ods have strengths and weaknesses. Traditionally, sequence-

based methods, such as analysis of the 16S rRNA gene, haveproved effective in establishing broader phylogenetic rela-

tionships among bacteria at the genus, family, order, and

phylum levels, whereas fingerprinting-based methods are

good at distinguishing strain- or species-level relationships butare less reliable for establishing relatedness above the species

or genus level (Vandamme et al. 1996). When these methodsare coupled with other phenotypic tests, this creates a polypha-

sic approach that is the standard for describing new bacter-ial species (Gillis et al. 2001).

Specific genotyping methodologiesCurrent protocols for the identification of bacteria may uti-lize a variety of different fingerprinting- or sequence-based

methods, either alone or, more often, in combination. These

techniques are constantly evolving to embrace new method-

ologies that provide both greater accuracy for identificationand higher sample throughput. Examples of some of the

most widely used techniques are provided below.

Fingerprinting-based methodologies. At present, fingerprintingtechniques are the most commonly used genotypic methods

for bacterial identification. The most widely used of these

methods are shown in table 1. Repetitive element PCR (rep-

PCR), amplified fragment length polymorphism (AFLP),and random amplification of polymorphic DNA all utilize

PCR to amplify multiple copies of short DNA fragments

using defined sets of primers (Versalovic et al. 1994, Coccon-

celli et al. 1995, Vos et al. 1995, Lin et al. 1996). These meth-ods are designed to take advantage of DNA polymorphisms

in related organisms that may accrue as a result of a variety

of evolutionary mechanisms. Figure 1 provides an illustrationof the type of data obtained using rep-PCR. Multiplex PCR uses unique PCR primer sets for more than one organism;

these sets can be separated on the basis of amplicon size as a

way of rapidly identifying more than one microbe at a time

in a mixed sample (Settanni and Corsetti 2007).Riboprinting does not use PCR, but instead utilizes a sen-

sitive probing method to detect differences in gene patterns

between strains and species (Bruce 1996). DuPont’s Ribo-

Printer system (www2.dupont.com/Qualicon/en_US/ ) andthe DiversiLab system for rep-PCR (http://biomerieux-usa.

com/diversilab) have both been developed as commercial

products for bacterial identification. All of the methods de-

scribed here have been used to identify bacteria in a multitudeof different ways, many of which can be found in the scien-tific literature. These applications include source tracking

(Meays et al. 2004), authentication of isolates for archival

purposes (Cleland et al. 2008), taxonomy and systematics

(Vandamme et al. 1996, Gevers et al. 2005), and determina-tion of microbial population structures and community

studies (Savenlkoul et al. 1999), to name but a few.

Sequence-based methodologies. The most widely usedsequence-based methods are also shown in table 1. Multilocus

sequencing is one of the newest and, to date, one of the most


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powerful methods developed to identify microbial species. In

principle, this technique is akin to 16S rRNA gene sequence

comparisons, except that, instead of one gene, the fragments

of multiple “housekeeping” genes are each sequenced, andthe combined sequences are put together, or concatenated,

into one long sequence that can be compared with other se-

quences. Housekeeping genes are generally defined as en-

coding for proteins that carry out essential cellular processes.A few examples include the gyrase B subunit ( gyrB); the

alpha and beta subunits of RNA polymerase (rpoA and rpoB);

and recA, a gene encoding for an enzyme important in DNA

repair; there are a host of others (Zeigler 2003). Housekeep-ing-gene loci are present in most cells and tend to be conservedamong different organisms. As a result, general-purpose

primers can be designed that will work using PCR to amplify

the same genes across multiple genera.

In practice, the story is a bit more complicated; in mostcases, truly universal primer sets are not possible, so primers

need to be designed for specific families or orders of bacteria.

Two multilocus sequencing strategies are currently used:

multilocus sequence typing (MLST) and multilocus sequenceanalysis (MLSA). MLST is a well-defined approach that uses

a suite of 6 to 10 genetic loci, with appropriate primers for each

locus to allow PCR amplification and sequencing of the

products (usually 400 to 600 base pairs) (Maiden et al. 1998).

The resulting concatenated sequences can then be compared

with a curated database of sequences for the same organism.The result provides a high-resolution identification of an in-

dividual strain that may reveal close evolutionary relationships

among individual strains. This technique has proved useful

in epidemiological studies, making it possible to track the out-break of virulent bacterial pathogens (Cooper and Feil 2004).

Thus far, MLST, and the robust databases that have been

created for it, has been applied only to a relatively small num-

ber of common pathogens, using highly prescribed conditionsfor each organism, both for PCR primers and for databaseanalysis.

MLSA also involves sequencing of multiple fragments of

conserved protein encoding genes, but it uses a more ad hoc

approach to choosing the genes for comparative analysis. Asmaller subset (≤ 6) of genes or loci is typically used in MLSA

than is used in MLST (Gevers et al. 2005). MLSA is typically

used to identify organisms in the broader context of probing

species relationships within genera of families, rather thantracking the history of individual strains. As typically ap-

plied, it does not have the analytical capacity to detect the very




Table 1. Genotypic methods used in identifying bacteria.

Method Technology Application Database

Common fingerprinting methods

Repetitive element polymerase Polymerase chain reaction (PCR) Identification at the species and User created; commercial individualchain reaction (rep-PCR) primers target specific repetitive strain levels database available

elements randomly distributed inthe chromosomes of bacteria andarchaea

Amplified fragment length Restriction digestion of chromosomal Identification at the species and User createdpolymorphism DNA is followed by PCR using adapters strain levels; can be used for both

coupled to the restriction sites bacteria and archaea

Riboprinting Restriction digest of chromosomal DNA Identification at the species and User created; commercial universalis followed by probing for ribosomal strain levels; often used in quality database availablegenes control and assurance

Random amplification of A set of arbitrary short primers are Comparison of strains of known User createdpolymorphic DNA used to randomly amplify short species

stretches of chromosomal DNA

Pulsed-field gel electrophoresis Chromosomal DNA is cut into large Typing of pathogenic bacteria Public universal database adminis-fragments with rare-cutting restriction tered by the Centers for Diseaseenzymes, and fragment is determined Control and Prevention (www.cdc.gov/

pulsenet)

Multiplex PCR Multiple PCR primers are used for Identif ication of multiple species in User created

diagnostic genes mixed samples such as food andclinical specimens

Common DNA sequencing methods

Small-subunit ribosomal gene Conserved primers are used to amplify The current gold standard in bacterial Public universal databases available,sequencing (SSU rDNA) and then sequence the SSU rDNA identification and determination of including the Ribosomal Database

gene; sequences are then compared evolutionary relationships; may not Project (http://rdp.cme.msu.edu) andwith a database distinguish strains or species within greengenes (http://greengenes.lbl.gov )

a genus

Multilocus sequence typing DNA sequencing of a specific subset Typing of pathogenic bacteria; Public universal database available(MLST) of conserved and semiconserved epidemiology (administered by www.mlst.net)

genes for a given species is followedby a comparison of concatenatedsequences

Multilocus sequence analysis DNA sequencing of a specific subset Provides more robust identification User created; based on BLAST (Basicof conserved genes is followed by at the species level than traditional Local Alignment Search Tool) searchesa comparison of concatenated SSU rRNA gene sequencing against GenBanksequences; this method typicallyuses fewer genes than MLST does(only two or three)


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minor changes in sequence patterns that are useful in epi-

demiologic studies. At present, MLSA is limited by a lack of standardization, and no central databases are available. For ex-ample, an analysis of eight recent papers that used MLSA to

identify a wide range of bacterial phyla found that anywhere

from two to six genes were used in the different individual

studies (Devulder et al. 2005, Lodders et al. 2005, Naser et al.2005, Paradis et al. 2005, Thompson et al. 2005, Richter et al.

2006, Chelo et al. 2007, Richert et al. 2007). Furthermore, no

single gene was common to all studies, and most studies

used completely different sets of genes. Although the techniqueproved useful for each individual study, the lack of cohesive-

ness makes comprehensive comparative analyses impossible.

The genomic future. The genomes of approximately 2000

strains of bacteria and archaea have now been sequenced orare in the process of being sequenced. This has led to theadvent of using whole-genome comparisons between related

species to determine the average nucleotide identity between

two genomes (Goris et al. 2007). This technique currently de-

fines a species at the genomic level as having 95% averagenucleotide identity between two strains. This corresponds to

an estimate of at least 70% reassociation for DNA-DNA

hybridization, which has been the traditional standard for

defining bacterial species (Vandamme et al. 1996). Completegenome comparisons have proved to be more accurate than

DNA-DNA hybridization, which requires very stringent



Figure 1. An example of genotyping archaea from extreme environments using repetitive element poly-

merase chain reaction. The dendrogram compares the barcodes derived from four genera of extremely thermophilic archaea ( Methanocaldococcus, Methanotorris, Sulfolobus , and Thermococcus ) associ-

ated with high-temperature environments like the hydrothermal vent shown in the photograph on the

left, and four genera of halophilic archaea ( Halobacterium, Haloferax, Haloarcula,and Halorubrum )

associated with high-salt environments like the solar saltern shown on the right. This analysis providesa highly specific method for strain identification of these unique organisms, but it does not provide in-

formation regarding their phylogenetic relatedness. Photographs: David Clelann.


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protocols and is often difficult to reproduce precisely be-

tween laboratories. The rapid advent of the next generation

of sequencing technologies is likely to make sequence-based

methods more cost-effective and more readily available for use

at all levels of bacterial classification and identification.

This raises the question of whether it will soon be possi-

ble to simply sequence the genome of an isolate to determinewhat it is and what it does. Can this be done for roughly the

same cost as a standard battery of biochemical identification

tests and a genotype analysis? Can it be done with the same

or better speed and efficiency as current methods? These are

the challenges faced by researchers who are developing and

using genomics-based identification methods. It is difficult to

predict how soon, if ever, whole-genome sequencing will be

used as a routine means of bacterial identification; however,

it is certain that the multilocus sequencing approaches de-

scribed above will expand and mature rapidly. While we ap-

preciate the technological challenges of DNA sequencing per

se, perhaps an even greater challenge will be the establishmentof large, integrated databases that allow for the rapid assem-

bly of sequence data to help researchers make robust com-

parisons among sequences and predict identifications between

bacteria with a high degree of confidence. The lack of stan-

dardization for MLSA analysis needs to be addressed so that

standards can be developed for comparisons of multiple

taxa. Once these are in place, it will become progressively

easier to develop MLSA- or MLST-type sequence-based

strategies that accurately target multiple genes and can be used

to provide a full range of genotypic information for all

bacteria and archaea.

Microarrays are another technology that shows promise asa means of simultaneously identifying specific microbes and

providing ecological context for the population structure

and functional structure of a given microbial community. Mi-

croarrays work on the general principle of spotting probes for

hundreds or thousands of genes onto a substrate (e.g., a glass

slide) and then hybridizing sample DNA or RNA to it. The

sample DNA or RNA is labeled with a fluorescent reporter

molecule so that samples that hybridize with probes on the

microarray can be detected rapidly. In terms of bacterial

identification, several iterations of a “phylochip” that utilizes

the small-subunit ribosomal gene as a target have been de-

veloped, both for specific and for very broad groups of envi-ronmental bacteria (Liu et al. 2001, Wilson et al. 2002).

Another example is the geochip, which has been developed

to identify microbes involved in essential biogeochemical

processes such as metal transformations, contaminant degra-

dation, and primary carbon cycling (He et al. 2007). In the clin-

ical realm, the use of microarrays is moving forward rapidly,

both for diagnostic purposes and for understanding the fun-

damentals of disease pathology (Frye et al. 2006, Richter et al.

2006). However, because of their inherent complexity and rel-

ative expense, microarrays have yet to be used as standard

methods in microbial identification.

Proteomics technologies in bacterialidentification and characterizationAlthough genotypic information is valuable in identifying an

organism and determining how it is related to others, meth-

ods that probe an organism’s phenotypic properties remaincritical for understanding the physiological and functional

activities of an organism at the protein level. Phenotypicmethods that determine the activity of specific enzymes,

such as catalase or oxidase, or metabolic functions, such as theability to degrade lactose, have long been a mainstay of bac-

terial identification. The advent of new proteomics tools that

are based primarily on mass spectrometry and allow rapid in-

terrogation of biomolecules produced by an organism offersan excellent complement to classical microbiological and

genomics-based techniques for bacterial classification, iden-

tification, and phenotypic characterization. What is also in-

teresting is that some of these techniques are integratinggenotypic and proteomic data to provide more complete

information. The predominant proteomic technologies that

have been explored for bacterial identification and charac-

terization include matrix-assisted laser desorption/ionizationtime-of-flight mass spectrometry (MALDI-TOF-MS); elec-

trospray ionization mass spectrometry (ESI-MS); surface-

enhanced laser desorption/ionization (SELDI) mass

spectrometry; one- or two-dimensional sodium dodecylsulfate–polyacrylamide gel electrophoresis (SDS-PAGE); or

the combination of mass spectrometry, gel electrophoresis, and

bioinformatics. (See figure 2 for a general integrated proteo-

mics flowchart.) In addition to the above-mentioned classi-cal proteomics approaches, Fourier-transform infrared

spectroscopy (FT-IR) has been used to classify and identify

bacterial samples (see, e.g., Al-Qadiri et al. 2006).

Mass spectrometry–based bacterial characterization and

identification. Mass spectrometry is a powerful analytical

technique that has been used to identify unknown com-

pounds, quantify known compounds, and elucidate the struc-ture and chemical properties of molecules. The development

of mass spectrometry can be traced back to the late 19th

century, when it was first used by J. J. Thomson (1899) to

measure the mass-to-charge ratio of electrons. With the re-finement of this technology throughout the 20th century,

mass-spectrometry applications have been expanded to

include physical measurement, chemical characterization,

and biological identification.One of the major breakthroughs in mass spectrometry

for the analysis of biological molecules was the soft ionization

method (i.e., MALDI-TOF-MS and ESI-MS; see figure 3 for

a simplified schematic representation). Until the develop-

ment of the soft ionization method, the application of massspectrometry to biological materials was limited by the re-

quirement that the sample be in vapor phase before ioniza-

tion. Soft ionization has made it possible to study larger

biological molecules and perform analyte sampling and ion-ization directly from native samples, including whole cells,

using mass spectrometry (Fenn et al. 1989). Since its initial




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MALDI-TOF-MS is rapidly becoming an accepted tech-

nology for bacterial identification, so we will cite only one

example of its use. Staphylococcus aureus, a bacterium com-

monly found on human skin, causes infection during timesof uncontrolled growth. Improper use of antibiotics has

rendered S. aureus resistant to the methicillin class of anti-

biotics. The first outbreak of methicillin-resistant S. aureus(MRSA) was recorded in a European hospital in the early 1960s. Since then, the threat of MRSA has spread from

hospitals and clinical settings to schools and public commu-

nities, thus necessitating the use of techniques that can rapidly

identify and discriminate MRSA from methicillin-sensitive S.aureus (MSSA). Edward-Jones and colleagues (2000) developeda MALDI-TOF-MS method for the identification, typing,

and discrimination of MRSA and MSSA. In this method, a

sample is taken from a single bacterial colony and smeared

onto a sample slide. The appropriate matrix is applied to thesample, which is then analyzed using MALDI-TOF-MS.

MALDI-TOF-MS analysis shows that MRSA and MSSA yield

distinct spectral peaks that allow for rapid distinction between

the two and therefore, hypothetically, for appropriate treat-ment of S. aureus infections with respect to their resistance

to antibiotics.

To serve market needs, severalinstrument systems based on

MALDI-TOF-MS have been

developed for bacterial identi-

fication and characterization.For instance, Bruker Daltonics’

MALDI BioTyper is a systembased on the measurement of

high-abundance proteins, includ-ing many ribosomal proteins in

a microorganism (Mellmann et

al. 2008). The system is equipped

with bioinformatics tools (clus-tering and phylogenetic dendro-

gram construction) that allow

for the rapid identification and

characterization of a known orunknown bacterial culture on the

basis of proteomics signatures.

Electrospray ionization mass

spectrometry. ESI-MS also has

the potential to play an impor-

tant role in bacterial character-

ization, especially for the analysisof cellular components. Proteins

expressed by the bacteria can be

extracted from the lysed cells

and analyzed using ESI-MS.This technique allows for the

analysis of both intracellular and

extracellular proteins, carbo-hydrates, and lipids. A major ad-

vantage of ESI-MS is its ability to perform tandem mass

spectrometry, in which the protein of interest can be frag-

mented for a second mass analysis that provides protein frag-

ment sequence information, or a peptide fragmentationfingerprint, that can then be applied to a database search to

identify that specific protein. This has significantly increased

the accuracy of protein identification compared with identi-

fication using only molecular weight information from asingle MALDI-TOF-MS analysis. A study by Krishnamurthy

and Ross (1996) reported that the total analysis time leading

to unambiguous bacterial identification in samples is less

than 10 minutes, with reproducible results. A system recently developed by Ibis Biosciences (the T5000 Biosensor System)can identify and characterize bacterial strains rapidly and

effectively using a combination of PCR and ESI-MS tech-

nology (Sampath et al. 2007). Another example of the use of

mass spectrometry to analyze nucleic acids for bacterial iden-tification is the combination of MALDI-TOF-MS with MLST

analysis using Neisseria meningitidis (Honisch et al. 2007).

These efforts exemplify how the integrated genotypic and pro-

teomics technologies provide an even more powerful tool forbacterial identification. Additional descriptions of the ESI-MS

technique and its applications for bacterial characterization



Figure 3. Schematic representation of soft ionization techniques used in mass spectrome-

try. (a) Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass

spectrometry. The sample to be analyzed (the analyte) is mixed with organic matrices

and deposited on the sample plate in the form of a small spot. The mixture is ionizedby the laser beam. The resulting ions move toward the mass analyzer, and the mass is

detected to obtain the mass spectrum. (b) Electrospray ionization mass spectrometry

(ESI-MS). The analyte is mixed with a solvent and sprayed from a narrow tube.

Positively charged droplets in the spray move toward the mass-spectrometersampling orifice under the influence of electrostatic forces and pressure differentials.

As the droplets move to the orifice, the solvent evaporates, causing the analyte

ions to move toward the analyzer for mass analysis.


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may be found in a review article by Bons and colleagues(2005).

Another advantage of ESI-MS is its ability to identify

target bacteria in mixed samples. The resolution of ESI-MS

is such that specific intracellular biomarkers for individual mi-croorganisms can be distinguished with enough confidence

that they can be identified in unknown samples. For the pro-tein analysis, comparing the experimentally obtained protein

profile of an unknown bacterial species with the profile in-formation found in a proteomics database will allow for the

identification and characterization of the unknown species.

Identifying the virulence factors of pathogenic bacteria is

one of the major applications of liquid chromatography withtandem mass spectrometry (LC/MS/MS) (Chao et al. 2007).

Once the putative virulence factors are identified, their func-

tions and mechanism can be further characterized by pheno-

typic analyses such as mutagenesis, conventional biochemicalmethods, and structural biology.

Surface-enhanced laser desorption/ionization. SELDI is a

relatively new technology, designed to perform mass spec-trometric analysis of protein mixtures retained on chemically

(e.g., cationic, ionic, hydrophobic) or biologically (e.g.,

antibody, ligand) modified chromatographic chip surfaces.

These varied chemical and biochemical surfaces allow dif-ferential capture of proteins based on the intrinsic properties

of the proteins themselves. The SELDI mass spectrometer

produces spectra of complex protein mixtures based on the

mass-to-charge ratio of the proteins in the mixture and theirbinding affinity to the chip surface. Differentially expressed

proteins may then be determined from these protein profilesby comparing peak intensity. Figure 4 illustrates the general

procedure.

SELDI technology has been applied extensively to bio-

marker and protein profiling studies in the field of oncology (Yip and Lomas 2002). By contrast, only a limited number of

reports have investigated the applicability of SELDI for de-tecting and identifying bacterial pathogens (Seo et al. 2004)

and virulence factors. However, these limited study resultsdemonstrate that SELDI technology offers an alternative

approach to the other techniques for exploring bacterial pro-

teomes, ultimately permitting bacterial identification based

on a comparison of protein profiles and patterns. An exam-ple of how SELDI technology has been applied is its use in dis-

tinguishing between four subspecies of Francisella tularensis,the causative agent of tularemia in humans. Of the four sub-

species of F. tularensis, tularensis is the most infectious andthe only subspecies found in North America. Lundquist and

colleagues (2005) showed that SELDI time-of-flight mass

spectrometry is capable of generating unique and repro-

ducible protein profiles for each subspecies, allowing thesubspecies to be distinguished from one another.

Although the use of mass spectrometry has great potential

for identifying bacteria by their spectral profile, many factors

affect the reproducibility of bacterial spectra. Sample pre-paration, matrix selection, and differences in instrument

quality and performance can all have an impact on the re-

producibility of protein profiles (Wunschel et al. 2005). Just

as important, the physiological state of the cell may also in-fluence the results of mass spectral analysis, and thus both the

growth medium and the growth

stage of the cells must be takeninto account. Using MALDI-TOF-MS technology to analyze

and discriminate foodborne mi-

croorganisms, Mazzeo and col-

leagues (2006) concluded thatthe growth time did not affect

the bacterial protein profile, but

that different growth media did

affect the mass spectra of Es-

cherichia coli. Similarly, Walker

and associates (2002) showed

that culture medium—especially

with the addition of blood, as inColumbia blood agar—will causevariation in mass spectra profiles.

With so many variables, many

scientists have introduced stan-

dardized techniques for MALDI-TOF-MS of whole cells. Liu and

colleagues (2007) developed a

universal sample preparation

method for characterizing gram-positive and gram-negative bac-

teria using MALDI-TOF-MS.



Figure 4. Schematic representation of the surface-enhanced laser desorption/ionization

technique. This technique utilizes aluminum-based chips, engineered with chemically

or biologically modified surfaces. These varied surfaces allow the differential captureof proteins based on the intrinsic properties of the proteins themselves. Bacterial lysates

are applied directly to the surfaces, where proteins with affinities to the surface will bind.

Following a series of washes to remove nonspecifically bound proteins, the bound proteins

are profiled using the integrated mass analyzer to generate a mass spectrum for further analysis. Abbreviations: MS, mass spectrometry; m/z, mass-to-charge ratio.


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These results emphasize the need to develop standardized tech-

niques for preparing samples to use in the creation of mass

spectra databases for bacterial identification.

Gel-based bacterial characterization and identification. Bac-

teria may also be differentiated on the basis of their cellular

protein contents. The most established technique for exam-ining cellular protein content is to lyse cells and separate

their entire protein complement using SDS-PAGE. This results

in a migration pattern of the protein bands that is character-

istic for a given bacterial strain (Vandamme et al. 1996). Re-

searchers can identify bacteria by comparing their migration

patterns with reference gel patterns in an established database.

However, because SDS-PAGE analysis is slow and labor-

intensive, and because the application necessitates precise

culture conditions that yield fairly large amounts of sample

material, it is not particularly useful for rapid identification

of bacteria, particularly for field and point-of-care applications.

Two-dimensional gel electrophoresis (2DE)—the combi-nation of isoelectric focusing (IEF) and SDS-PAGE—affords

a high-resolution separation of up to several thousand

spots in a single gel analysis. In 1975, O’Farrell (1975) intro-

duced 2DE as a method for separating complex mixtures of

cellular proteins. In 2DE, proteins are separated by IEF elec-

trophoresis in a pH gradient according to each protein’s

isoelectric point in the first dimension, followed by the

second-dimension SDS-PAGE separation according to the

relative molecular weight of each protein. After the second-

dimension separation, the gel can be stained with standard or

sensitive staining solutions so that protein spots can be visu-

alized and analyzed. Protein gel patterns or 2DE maps from

known bacteria can be further scanned, analyzed, and stored

in a reference database. To identify an unknown species, a 2DE

map from the unknown sample is generated by running a 2DE

gel and then comparing it with 2DE maps in the reference

database for identification.

When used as a stand-alone technique, 2DE is most often

used for analyzing protein mixtures, isolating proteins of in-

terest for identification, and comparing differential expression

patterns of different types of samples. For more complex

proteomics analysis, 2DE is greatly enhanced when com-

bined with mass spectrometry. For example, Redmond and

associates (2004) analyzed the exosporium of Bacillus anthracis

spores by isolating the proteins from the outer casing of thespore using SDS-PAGE and analyzing the isolated protein

using delayed-extraction MALDI-TOF-MS. The team iden-

tified several proteins associated with the exosporium of

B. anthracis. Using these same methods, the whole proteome

or subproteome (or both) has also been made available for

many other bacteria, including E. coli, Bacillus subtilis, S.

aureus, Pseudomonas aeruginosa, and Helicobacter pylori

(Nouwens et al. 2000, Hecker et al. 2003, Peng et al. 2005,

Pieper et al. 2006). A collective proteomics database with

complete 2DE maps and mass spectra of known bacteria

will allow investigators to compare and identify unknown bac-

teria with great efficiency. However, building such a database

will not be an easy undertaking.

The database challenge. One thing modern genomic and pro-

teomic approaches share is the generation of large data sets

for any individual sample that is analyzed. These present a real

challenge in terms of archiving the data, processing and in-tegrating data from many samples so that it can be used

for comparative purposes in the broadest way possible, and

developing robust quality control and quality assurance

practices. All this should be done in an environment that isaccessible and easy to use for a broad group of scientists,

many of whom may have little experience with a particular

method of analysis. At present there are no comprehensive ge-

nomic or proteomic databases for bacterial identification.There are, however, a great number of databases and tools

available for both genomic and proteomic analysis that are

essential for providing integrated data for specific types of

analysis. Two examples of databases that provide excellentanalysis for identification based on 16S rRNA gene sequence

analysis are the Ribosomal Database Project (Cole et al. 2007)

and greengenes (DeSantis et al. 2006). On the proteomics side,

LC/MS/MS data analysis has improved by several means andcontinues to complement 2DE gel analysis, which is still

limited by the inability of the pattern recognition software to

resolve overlapping protein spots (Palagi et al. 2006). Protein

identification and characterization has been carried out withmore depth since the development of predictive tools such as

GlycoMod and databases such as PhosphoSite, which can

reveal possible posttranslational modifications not other-

wise accounted for in databases consisting simply of theoretical

spectra (Barrett et al. 2005, Witze et al. 2007).More important, algorithms are evolving to adapt to actual

experimental occurrences and parameters. One example of

such adaptation is the development of a recent algorithm thatpredicts missed cleavage sites as they typically occur during

protein digests, in order to ease the return of, and render

greater confidence to, mass spectra probability matches

(Siepen et al. 2007). The goal of the ProDB platform proposedby Wilke and colleagues (2003) is not only to integrate data

derived from various databases to enrich a protein profile but

also to archive experimental conditions and parameters, such

as growth and culture conditions as they might apply to bac-teria, to account for the subsequent effects on mass-spectra

profile generation. Archiving and integrating specific exper-imental conditions as part of the proteomic bioinformatics

may alleviate the need for stringent culturing standards whenattempting to identify proteins that aid the characterization

and identification of clinically important bacteria. For a more

comprehensive review on proteomic data analysis, see Lisacek

and colleagues (2006).

ConclusionsAdvanced genomics and proteomics technologies will continueto play a critical role in bacterial identification and charac-

terization in the 21st century. Bacterial characterization has




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a number of practical applications, aside from being funda-

mental to questions of bacterial systematics, taxonomy,

and evolution. Rapid identification and discrimination of

pathogenic microbes has a major impact on public health in

terms of correct diagnosis and timely disease treatment.

The ability to identify specific indicator organisms is also

important for determining water quality, and an enhancedunderstanding of the population structure of these organisms

can allow researchers to identify the source of a particular

contaminant. For example, methods are being developed

to determine whether fecal bacteria found in public water

supplies are from humans, mammals, or birds. This kind of

information has a significant impact for treatment options.

As researchers learn more about the community fabric of

microbial ecosystems, it is likely that we will come to recog-

nize sentinel microbes that will tell us, by their presence (or

absence) and abundance, important information about

the state of that ecosystem. For example, the identification of

microbes that carry out specific transformations of nitrogenor phosphorus might indicate the status of these important

nutrients in aquatic or soil ecosystems. Likewise, the presence

of microorganisms with certain biodegradative capacities

could be an indicator of specific pollutants in an environment.

The ability to rapidly identify these individual organisms

within populations of thousands of different species is

essential for understanding how they will affect our eco-

systems. Bacterial characterization will also assist in elucidating

the mechanisms that govern microbial pathogenesis, and

allow for the discovery of important protein targets essential

to the development of vaccines, diagnostic kits, and thera-

peutics for infectious diseases. It is these kinds of applicationsthat make the continued development of techniques for bac-

terial identification important both for basic science and for

the maintenance of human and environmental health.

Acknowledgments

The authors would like to thank Raymond Cypess (chief

executive officer, American Type Culture Collection [ATCC])

and Cohava Gelber (chief scientific and technology officer,

ATCC) for their unconditional support in preparing this

manuscript. We thank Scott Jenkins for his help in editing

the manuscript and David Cleland for his help in preparing

figure 1. We also acknowledge that many excellent papers,

particularly those providing examples of the use of the tech-

nologies described herein, could not be cited because of space

limitations.

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