15
Cite this: RSC Advances, 2013, 3, 994 Bacterial identification: from the agar plate to the mass spectrometer Received 6th September 2012, Accepted 24th October 2012 DOI: 10.1039/c2ra22063f www.rsc.org/advances Patricia Aparecida Campos Braga, a Alessandra Tata, a Vanessa Gonçalves dos Santos, a Juliana Regina Barreiro, b Nicolas Vilczaki Schwab, a Marcos Veiga dos Santos, b Marcos Nogueira Eberlin a and Christina Ramires Ferreira* a For more than a century, bacteria and fungi have been identified by isolation in culture followed by enzymatic reactions and morphological analyses. The identification of environmental microorganisms, however, remains a challenge because biochemical and staining protocols for bacteria identification are tedious, usually stepwise, can be long (days) and are prone to errors. Molecular techniques based on DNA amplification and/or sequencing provide more secure molecular identification of specific bacteria, but identification based on mass spectrometry (MS), mainly on MALDI-MS, has been shown to be an alternative accurate and fast method able to identify unknown bacteria on the genus, species and even subspecies level based profiles of proteins and peptides derived from whole bacterial cells. Breakthroughs such as non-culture-based identification of bacteria from biological fluids and MS detection of antibiotic resistance have recently been reported. This review provides an overview of the traditional bacterial and fungal identification workflow and discusses the recent introduction of MS as a powerful tool for the identification of microorganisms. Principles and applications of MS, followed by the use of high-quality databases with dedicated algorithms, are discussed for routine microbial diagnostics, mainly in human clinical settings and in veterinary medicine. Introduction If a microbiologist working in the first decades of the 20th century stepped into a current microbiology laboratory, it is likely that he would not have a hard time feeling at home. In fact, most methods for bacterial isolation and identification have remained unchanged and are still based on the use of specific culture media for isolation and on classical morpho- logical, staining and biochemical enzymatic assays for micro- organism identification. 1 Improved assays, high-throughput microbiological analysis with automated systems, molecular technologies based on DNA amplification/sequencing for microorganism identifica- tion and the detection of antimicrobial resistance are available. 2,3 However, challenges such as the urgent identifica- tion of microorganisms and their antibiotic resistances in septicemic patients and in infants, the occurrence of genetic rearrangements in microorganisms that alter their behavior in enzymatic assays, and the need to identify less frequent or rare microorganisms are difficult to tackle with classical micro- biological approaches and may lead to incorrect identifica- tions. In response to these challenges, a paradigm break for microbiology has been the introduction of mass spectrometry (MS)-based microorganism identification. This strategy emerged after the development of electrospray ionization (ESI) 4 and matrix-assisted laser desorption/ionization (MALDI) 5 at the end of the 1980s. Since the early 1990s, more than 13 000 Pubmed indexed manuscripts on microbiology associated with MS have been published. However, micro- organism identification by MS is not only performed for research purposes. Dedicated instruments equipped with automated database search functions for almost real-time microorganism identification are being installed in hospitals, clinical institutes and commercial settings, mainly in Europe. In the United States, the Food and Drug Administration has still not approved any MALDI-MS system for organism identification, which limits the widespread implementation of this approach in this country. 6 This review provides a general overview of classical microbiological approaches and the MS ionization strategies that have been mostly applied in microbiology. The most recent achievements in MS-based microorganism identifica- tion, such as the identification of uncommon pathogens and non-fermenting bacteria, non-culture identification of bacteria in biological fluids, identification of antibiotic resistance and a ThoMSon Mass Spectrometry Laboratory, Institute of Chemistry, University of Campinas, Campinas, 13083-970, SP, Brazil. E-mail: [email protected]; Fax: +55 19-3521 3073; Tel: +55 19-35213049 b University of Sa ˜o Paulo, School of Veterinary Medicine and Animal Science, Pirassununga, 13635-900, Sa ˜o Paulo, Brazil. E-mail: [email protected]; Fax: +55 19-5616215; Tel: +55 19-3565 4240 RSC Advances REVIEW 994 | RSC Adv., 2013, 3, 994–1008 This journal is ß The Royal Society of Chemistry 2013 Published on 24 October 2012. Downloaded by UNIVERSIDAD SAO PAULO on 30/04/2014 19:16:53. View Article Online View Journal | View Issue

RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

  • Upload
    others

  • View
    2

  • Download
    0

Embed Size (px)

Citation preview

Page 1: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

Cite this: RSC Advances, 2013, 3, 994

Bacterial identification: from the agar plate to the massspectrometer

Received 6th September 2012,Accepted 24th October 2012

DOI: 10.1039/c2ra22063f

www.rsc.org/advances

Patricia Aparecida Campos Braga,a Alessandra Tata,a Vanessa Gonçalves dos Santos,a

Juliana Regina Barreiro,b Nicolas Vilczaki Schwab,a Marcos Veiga dos Santos,b

Marcos Nogueira Eberlina and Christina Ramires Ferreira*a

For more than a century, bacteria and fungi have been identified by isolation in culture followed by

enzymatic reactions and morphological analyses. The identification of environmental microorganisms,

however, remains a challenge because biochemical and staining protocols for bacteria identification are

tedious, usually stepwise, can be long (days) and are prone to errors. Molecular techniques based on DNA

amplification and/or sequencing provide more secure molecular identification of specific bacteria, but

identification based on mass spectrometry (MS), mainly on MALDI-MS, has been shown to be an

alternative accurate and fast method able to identify unknown bacteria on the genus, species and even

subspecies level based profiles of proteins and peptides derived from whole bacterial cells. Breakthroughs

such as non-culture-based identification of bacteria from biological fluids and MS detection of antibiotic

resistance have recently been reported. This review provides an overview of the traditional bacterial and

fungal identification workflow and discusses the recent introduction of MS as a powerful tool for the

identification of microorganisms. Principles and applications of MS, followed by the use of high-quality

databases with dedicated algorithms, are discussed for routine microbial diagnostics, mainly in human

clinical settings and in veterinary medicine.

Introduction

If a microbiologist working in the first decades of the 20thcentury stepped into a current microbiology laboratory, it islikely that he would not have a hard time feeling at home. Infact, most methods for bacterial isolation and identificationhave remained unchanged and are still based on the use ofspecific culture media for isolation and on classical morpho-logical, staining and biochemical enzymatic assays for micro-organism identification.1

Improved assays, high-throughput microbiological analysiswith automated systems, molecular technologies based onDNA amplification/sequencing for microorganism identifica-tion and the detection of antimicrobial resistance areavailable.2,3 However, challenges such as the urgent identifica-tion of microorganisms and their antibiotic resistances insepticemic patients and in infants, the occurrence of geneticrearrangements in microorganisms that alter their behavior inenzymatic assays, and the need to identify less frequent or raremicroorganisms are difficult to tackle with classical micro-

biological approaches and may lead to incorrect identifica-tions.

In response to these challenges, a paradigm break formicrobiology has been the introduction of mass spectrometry(MS)-based microorganism identification. This strategyemerged after the development of electrospray ionization(ESI)4 and matrix-assisted laser desorption/ionization(MALDI)5 at the end of the 1980s. Since the early 1990s, morethan 13 000 Pubmed indexed manuscripts on microbiologyassociated with MS have been published. However, micro-organism identification by MS is not only performed forresearch purposes. Dedicated instruments equipped withautomated database search functions for almost real-timemicroorganism identification are being installed in hospitals,clinical institutes and commercial settings, mainly in Europe.In the United States, the Food and Drug Administration hasstill not approved any MALDI-MS system for organismidentification, which limits the widespread implementationof this approach in this country.6

This review provides a general overview of classicalmicrobiological approaches and the MS ionization strategiesthat have been mostly applied in microbiology. The mostrecent achievements in MS-based microorganism identifica-tion, such as the identification of uncommon pathogens andnon-fermenting bacteria, non-culture identification of bacteriain biological fluids, identification of antibiotic resistance and

aThoMSon Mass Spectrometry Laboratory, Institute of Chemistry, University of

Campinas, Campinas, 13083-970, SP, Brazil. E-mail: [email protected];

Fax: +55 19-3521 3073; Tel: +55 19-35213049bUniversity of Sao Paulo, School of Veterinary Medicine and Animal Science,

Pirassununga, 13635-900, Sao Paulo, Brazil. E-mail: [email protected];

Fax: +55 19-5616215; Tel: +55 19-3565 4240

RSC Advances

REVIEW

994 | RSC Adv., 2013, 3, 994–1008 This journal is � The Royal Society of Chemistry 2013

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article OnlineView Journal | View Issue

Page 2: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

mixed culture analysis, are also described and discussed.Finally, real-world perspectives on moving bacterial identifica-tion from the agar plate to the mass spectrometer arepresented.

Traditional bacterial and fungal identification based onbacterial isolation by culture and enzymatic assays

There are several methods for routine microbial identificationin clinical and research microbiology laboratories, but micro-biologists have continuously pursued efficient systems formicroorganism identification. These methods are mainlybased on morphological and biochemical characteristics ofbacterial colonies. For example, bacterial colony morphologycan be evaluated under defined growth conditions to showhemolytic capacity, by Gram staining (Fig. 1a–b), and byexamining growth performance on selective media that allowonly specific bacteria to multiply, the potential to fermentsugars, specific biochemical reactions (Fig. 1c), metaboliccharacteristics, antigenic and pathogenic capacity, and anti-biotic susceptibility.7

When determining the characteristics of a microorganism toprovide its identification, a pure culture population ofidentical cells is needed; this means that these cells originatefrom the same parental cell. However, microorganisms innature are typically found in mixed cultures with manydifferent species occupying the same environment.Therefore, in a microbiological laboratory, the first step inthe microorganism identification workflow is the isolation ofthe various species contained in a specimen. For this purpose,there is an extensive list of available commercial tools, and thechosen strategy depends on numerous factors. The mainconsiderations are the source of the sample, the species thatare expected to be present and the nutritional needs of thesemicroorganisms. For example, the isolation medium maycontain specific compounds that inhibit or prevent general

microbial growth yet simultaneously are appropriate forgrowing the species that are determined to be present(Fig. 1a).8 After isolation of the microorganism, phenotypiccharacteristics such as enzymatic profiles, sensitivity toantibiotics and chromatographic analysis of fatty acids canbe performed to characterize the strain.9

Microscopy is frequently used to characterize microorgan-isms (Fig. 1b), and there are two main microscopic techniques:light microscopy and electron microscopy. Light microscopy isroutine in the microbiology setting and can be performed withbright field, dark field, fluorescence, and phase control.Constant development and refinement of the techniques usedfor optical microscopy allow one to perform additionalspecialized functions, such as evaluating biochemical pro-cesses occurring within living cells.10

For close to a century, bacterial identification relied on theinterpretation of a skilled microbiologist using a microscope,specific media and antibiotics, but technological improve-ments over the past 50 years have allowed for both automationand simplification of analysis.2

Automated testing for bacterial identification in laboratorieshas become necessary as microbiologists attempt to answerhigher demands and the need for fast diagnoses, such as incases of patients with septicemia or neonatal infections.Automation also allows increasing numbers of specimens tobe studied.11 Usually, the microorganism cell count can bedetermined in real time by incubators equipped with a systemto measure the light absorption of liquid cultures becauseturbidity can be related to the number of cells. Anotherstrategy of an automated laboratory system is based on testingthe susceptibility of bacteria to a large number of antibiotics.10

Advances in the molecular biology field in the early 1980sresulted in novel approaches for microbial identification andcharacterization based on polymerase chain reaction (PCR) toamplify specific gene sequences of bacteria. PCR allows in vitroamplification of specific DNA or RNA sequences, the latterbeing performed following the synthesis of complementarydeoxyribonucleic acid (cDNA). PCR is a technique with highspecificity and applicability, and hundreds of methods havebeen described.12 The most important feature of PCR is itsability to exponentially amplify copies of DNA from smallamounts of material. For PCR analysis, nucleic acids must beextracted, and several protocols using specific reagents anddifferent strategies have been described for this purpose.10

Though time-consuming, costly and difficult in the case ofmultiplex assays, PCR-based bacterial identification is now acommon and often indispensable technique used in medicaland biological research for a variety of other applications,including forensic DNA typing, clinical diagnosis, DNAamplification for cloning or sequencing, paternity testing,construction of DNA libraries and detection of mutations.12–14

For example, Campylobacter, which is the most common causeof acute bacterial gastroenteritis in the world, may be detectedin pork samples using this approach. Sixty Campylobacterstrains isolated from porcine rectal swabs and from differentareas in a pork processing plant were shown by PCR analysis tobe mostly C. coli (86.9%) and C. jejuni.(13.1%).15

PCR is less prone to errors compared to traditional methodsof identifying microbes that rely exclusively on phenotypic

Fig. 1 (a) Staphylococcus aureus (left) and Staphylococcus spp. (right) on bloodagar. Note the hemolysis caused by S. aureus; (b) Bright light microscopyanalysis: Gram-positive stained cocci; (c) Biochemical tests used to identifybacteria usually include color codes.

This journal is � The Royal Society of Chemistry 2013 RSC Adv., 2013, 3, 994–1008 | 995

RSC Advances Review

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 3: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

features and some the morphological characteristics of theorganism to identify the strain, such as enzyme profiles,antibiotic sensitivity profiles, and chromatographic analyses offatty acids.9 However, the expanding and impressive capabil-ities of MS-based microorganism identification are causing arevolution in the field of microbiology.

Even though bacterial identification represents the largestinterest in routine microbiology, invasive fungal disease playsan important role in the morbidity and mortality of immuno-compromised patients.16 Approximately 60 years ago,Wickerham described a broth method that is specific formetabolic assimilation and fermentation testing of yeasts.17,18

Assimilation tests determine the ability to use varioussubstrates as the sole source of carbon (e.g., sucrose) ornitrogen (e.g., KNO3). This method is still considered apowerful tool and was used to characterize and determinethe taxonomy of yeasts. Most Wickerham media are notcommercially available and are produced in the laboratory.This process is usually long and arduous and is employed onlyby a few laboratories because basal media and varioussubstrates need to be prepared, sterilized, and dispensedprior to inoculation. Since many types of yeast can ‘‘carry-over’’nutrients from the isolation medium, one must run negativecontrols for each test type and organism. Metabolic assimila-tion tests are read for turbidity, fermentation and gasproduction for up to four weeks. Due to their time-consumingnature, these ‘‘gold standard’’ assays have been replaced bymore practical methods that are currently available.

The first technical progress to improve the speed andsensitivity of yeast identification from fungal blood culturesand histological practices was the development of highlysensitive and specific molecular techniques, including PCR. Atthe molecular level, genetic sequence variation offers analternative to culturing for the detection and identification offungi. For example, ribosomal genes have conserved sequenceregions that are ideal for primer targeting as well as regions ofvariability that are useful for species identification. DNAamplification techniques, with subsequent species-specificprobing of the amplicons or PCR-enzyme immunoassay, havealso been introduced to overcome the problems of sensitivity,specificity, and delay that are encountered with conventionalmethodology. These methods have already shown greatpromise in the field of diagnostics. The use of species-specificprobes, however, is not always an efficient approach inmycology, given the large number of potentially pathogenicfungi.19,20

In parallel with the development of molecular methods,there has also been an emphasis on improving commercialkits based on substrate utilization or hydrolysis. The resultsare determined by increased turbidity, the generation ofcolored products, or the detection of fluorescent products.Some colored products require the addition of reagents toreveal the color, while others are self-revealing. These kitsenable presumptive identification of the most importantetiologic agents of yeast infections. Another focus of theserapid tests has been to screen for species that are commonlyassociated with resistance to antifungal compounds.21 Somekits are read manually, while others are read automatically.

Many systems employ the aid of computer algorithms for rapidand reproducible data analysis.21

Merits of mass spectrometry in microorganism identification:time-saving and reliablity

ELECTROSPRAY-BASED BACTERIAL IDENTIFICATION (PCR-ESI-QTOF).Scientific advances in MS, such as the development of the‘‘soft’’ ionization techniques MALDI5 and ESI,4 have allowedthe ionization, detection and characterization of large intactbiomolecules. An improved understanding of the limitationsassociated with MS analysis of nucleic acids led to theionization of intact PCR products by ESI.4,22 This capabilityresulted in the development of MS analysis of nucleic acids formicroorganism identification, which was first described in2005 by Hofstadler and co-workers.23–26

This approach, previously termed TIGER (TriangulationIdentification for Genetic Evaluation of Risks) or PCR-ESI-QTOF-MS, uses broad-range primers for PCR analysis toamplify products from diverse organisms, such as viruses,bacteria, fungi and protozoa within a taxonomic group, thatare present in samples combined with PCR product calcula-tions using MS (Fig. 2).

The Ibis T5000 Universal Biosensor is an automated platformfor pathogen identification that is based on TIGER technology.In its commercial form, Ibis T5000 is capable of identifying andstrain typing a broad range of pathogens in a blinded panelfrom human or animal samples.28–30 Because the Ibis T5000provides digital signatures of identified microorganisms, thistechnology allows the collection and dissemination of epide-miological information in real-time.31–33 A major advantage ofthis methodology is the ability to characterize an organismwithout prior knowledge by the instrument operator as well asrapid sample preparation. Since rapid pathogen identificationsignificantly reduces rates of patient mortality, technologies forthe correct and timely diagnosis of bloodstream infections areurgently needed. PCR-ESI-MS has been used as a new strategyfor detecting bloodstream infections and has provided highconcordance with results from standard methods, particularlyat the genus level. The results from this technique can also beobtained in five to six hours, whereas culture and biochemicalcharacterization techniques typically require one to five days forconfirmation of microbial identification.34,35

Rapid detection and identification of Ehrlichia species, atick-borne pathogen responsible for causing Ehrlichiosisdisease, was performed by PCR-ESI-MS directly from crudeblood samples without microorganism culture. The resultsfrom an enzyme immunoassay that was also performedshowed 100% agreement with the PCR-ESI-MS results.36 Thedetection of bloodstream infections can be biased, as bloodcultures are reported to be negative in more than 50% of thecases where bacteria are believed to exist. This approachallows the detection and identification of both culturable andunculturable organisms by the same method, in addition tothe identification of mixed populations of bacteria. The PCR-ESI-MS platform not only identifies organisms that are presentin a clinical sample but is also capable of providinginformation about the strain type.37 This approach has beenapplied for the genotypic characterization of S. aureus isolatesand to detect the presence or absence of genetic elements that

996 | RSC Adv., 2013, 3, 994–1008 This journal is � The Royal Society of Chemistry 2013

Review RSC Advances

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 4: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

encode potential virulence factors and antibiotic resistanceelements. PCR-ESI-MS can also distinguish S. aureus fromother coagulase-negative staphylococci (CoNS) isolates.38,39

Members of the genus Acinetobacter, which are aerobicGram-negative organisms that are widely distributed in soiland water in the natural environment and are importantnosocomial (hospital-acquired) pathogens, were isolated frominfected soldiers and civilians involved in an outbreak in themilitary health care system associated with the conflict in Iraq.Through the PCR-ESI-MS technique, it was possible todistinguish at least 16 Acinetobacter species, and thegenotyping of A. baumannii showed a genetic relationshipbetween endemic European isolates and many of the isolatesfound in patients and in military hospitals, indicating that thisapproach provides a better understanding of the origins ofthese infections and will improve infection control andprevention measures.40

The application of this technique has also been describedfor the genotyping of pathogens related to food-borne ill-nesses, and it proved to be highly effective in differentiating C.jejuni isolates in a panel of 50 Campylobacter isolates as well asdetermining the correct classification of C. coli instead of C.jejuni (Fig. 3).41

The Ibis 5000 platform has also been applied in aquaticenvironmental analysis to identify different Vibrio speciesdirectly from natural aquatic samples. From 278 total watersamples that were screened, nine different Vibrio species weredetected, and 41% of samples were positive for V. cholerae, apathogen responsible for cholera disease. The results alsoindicated that V. mimicus could be correctly identified anddistinguished from the close species V. Cholerae.42 PCR-ESI-MS has been described as a high-throughput method tosimultaneously identify, based on genotype, a number ofbacterial species from complex mixtures in respiratorysamples taken from military recruits during respiratorydisease outbreaks and follow up surveillance at severalmilitary training facilities.43 PCR coupled to ESI-MS has alsobeen described as a powerful tool for detecting othermicroorganisms such as viruses.44–50

Use of ambient desorption/ionization techniques for directbacterial identification

Ambient desorption/ionization describes a new set of MStechniques that are performed in an open atmosphere directlyon samples in their natural environments or matrices or byusing auxiliary surfaces. Ambient MS has greatly simplified

Fig. 2 An overview schematic of the traditional bacterial identification workflow and the recent integration of mass spectrometry techniques. Figure adapted fromDrake et al., 201127 with permission from John Wiley and Sons.

This journal is � The Royal Society of Chemistry 2013 RSC Adv., 2013, 3, 994–1008 | 997

RSC Advances Review

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 5: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

and increased the speed of MS analysis, and especially after2004, this approach has experienced a large trend towards real-world rapid chemical analysis of untreated samples inambient conditions.51,52 Recently, several new high-through-put ambient desorption/ionization methods have beenreported. One of the most studied ambient ionization methodsis desorption electrospray ionization (DESI), which wasintroduced by Cooks and co-workers in 2004.53 DESI involvesspraying untreated samples with ionized solvent droplets froma pneumatically-assisted electrospray. Desorption and ioniza-tion of analytes occurs through interactions of the chargeddroplets with the surface from which they pick up organicmolecules, and they are delivered as desolvated ions into themass spectrometer (Fig. 4a).

Another well-explored ambient ionization technique is thedirect analysis in real time (DART) method, first described byCody and co-workers in 200554 (Fig. 4b). Due to the increasingimportance of rapid identification of bacteria for food,biosafety and medical analysis, ambient desorption/ionizationmethods are of substantial interest.55 Both the DESI and DARTtechniques allow direct and rapid analysis of condensed phasesamples without any sample preparation or the need tointroduce the samples into the vacuum system of the massspectrometer. DESI and DART have been widely utilized inmany different applications, including bacterial analysis andidentification.51 The most important characteristic of DESIand DART-MS approaches is the absence of sample prepara-tion, so the real-time identification of microorganisms bythese approaches appears to be feasible.56,57

Cooks and co-workers were the first to recognize thepotential of these ambient desorption/ionization methods formicroorganism identification when they performed DESI-MS

on freshly harvested cells from untreated E. coli andPseudomonas aeruginosa samples deposited on a polytetra-fluoroethylene (PTFE) target. The characteristic DESI massspectra for each microorganism that was analyzed demon-

Fig. 3 Deconvoluted ESI-TOF mass spectra of PCR amplicons of the tkthousekeeping genes from six different C. jejuni strains. Both the forward (e) andthe reverse (#) strands of the PCR amplicons from each strain are clearly evidentin the spectra (e.g., for strain RM4197, the forward strand is A49, G22, C26 andT45 and the reverse strand is A45, G26, C22 and T49). As can be observed in thestacked spectra, differences due to variations in the sequence (and thus the basecomposition) are readily discernible. Note that any mass differences resultingfrom changes in the number of guanosines are enhanced by the use of 13Cguanosine (G*). The T5000 software automatically determines the basecomposition of each strain and provides a strain association by using a set ofeight primer pairs. Reproduced from ref. 41 with permission from the AmericanSociety for Microbiology.

Fig. 4 Schematic of ambient MS techniques used for direct microorganismanalysis. These approaches usually make use of untreated samples, which aredesorbed and ionized from surfaces or solutions under normal atmosphericconditions. (a) For DESI, an ionized solvent is pneumatically sprayed onto thesample, forming a thin film in which the sample molecules are dissolved.Secondary droplets containing ionized analytes are then delivered in thedirection of the mass spectrometer inlet. (b) DART uses an electrical potentialapplied to a gas with a high ionization potential (typically nitrogen or helium) toform a plasma of excited-state atoms and ions, which desorbs low-molecularweight molecules from the surface of a sample. (c) In LTP-MS, there is no needfor any solvent. The ion source consists of a glass tube with an internalgrounded electrode centered axially and an outer electrode of copper tapesurrounding the outside of the glass tube. An alternating voltage is applied tothe outer electrode with the center electrode grounded to generate thedielectric barrier discharge. The discharge AC voltage is provided by a custom-built power supply with total power consumption below 3W. Helium is used asthe discharge gas, and it is fed through the glass tube to facilitate the dischargeto direct the plasma onto the sample surface and to transport analyte ions tothe mass spectrometer.

998 | RSC Adv., 2013, 3, 994–1008 This journal is � The Royal Society of Chemistry 2013

Review RSC Advances

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 6: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

strated the potential of the technique for microbiologicalapplication.58

The similarity of the spectra for different samples of thesame culture or for E. coli different cultures was evaluated andindicated that DESI-MS for microorganisms was reproducible.The characteristic constituents of bacteria were observedwithout chemical derivatization; in particular, acylium ionsof fatty acids were observed directly, not as the usual methylesters. Principal component analysis (PCA) was performed onthe DESI-MS data to differentiate the bacteria studied into twowell-separated groups that could be identified based on thefirst principal component (PC1), which corresponds to thedifferentiation between E. coli and S. typhimurium. Because themass spectra were recorded directly from freshly harvestedmicroorganisms, and no chemical reagent or other processingstep was used to disrupt the cells before MS analysis, anyvariations in the final spectra associated with samplepretreatment were eliminated in collaboration with theseparation. Although only two different species were evalu-ated, this study demonstrated the possibility of performing insitu identification using DESI-MS, including sub-speciesdifferentiation of microbiological agents.56

Meetani et al. (2007) also applied DESI-MS to bacterialidentification for a larger number of different samples. In thisstudy, seven different bacterial species were evaluated on thebasis of their spectra profiles. Incubated bacterial cells weretransferred from agar plates, washed to remove mediacomponents, applied on glass slides and directly subjectedto DESI-MS analysis. The mass range from 50–500 was used,and the observed ions in the mass spectra revealed thepresence of free fatty acids, such as palmitic acid (16:0) at m/z257 for the protonated molecule and m/z 279 for the sodiumadduct. Further comparisons of the mass spectra with low-mass matrix-assisted laser/desorption ionization (MALDI)mass spectra of bacteria did not show common ion signals,indicating the likely complementary nature of DESI-MS andMALDI-MS for whole-bacteria identification. The mass spectraof negative ions were also evaluated, showing a greaternumber of detected ions than their counterpart positive ionspectra throughout the measured m/z range.57

In vivo recognition of bacteria was evaluated in anotherstudy from the Cooks group that examined direct profiles ofintact biofilms of Bacillus subtilis by DESI-MS, noting that thebiofilms were still viable after the experiment. The authorsreported that the DESI plume primarily desorbs materialsfrom the bacterial cell envelopes outer layers together withexcreted metabolites. Bacteria with a rigid cell wall canwithstand the impinging sprayed droplets. This assumptionwas corroborated by experimental results from Gram-negativeand Gram-positive bacteria. The outermost layer of Gram-negative bacteria is the cell outer membrane, while theoutermost layer of Gram-positive bacteria is a thicker cellwall. For Gram-negative species, the outer membrane isrelatively easy to break, and its major phospholipids (PL) canbe readily ionized, which leads to PL dominance in theresulting DESI mass spectra. However, the thicker cell walls ofGram-positive species are more difficult to break, and theirmajor components, which correspond to 90% of glycans, aremuch more easily ionized than PL. Consequently, the excreted

metabolites are observed as the dominant species in theresulting DESI mass spectra, especially those lipopeptides thatare produced in large quantities, are surface-active and ionizewith high efficiency, such as the surfactins.59

Fernandez and co-workers have also applied DART-MS totwo different bacterial samples.60 They describe the detectionof fatty acid methyl ester (FAME) ions from whole bacterial cellsuspensions and their identification by accurate-mass ortho-gonal TOF-MS. This study is interesting because the ‘‘goldstandard’’ methods routinely used in bacterial taxonomy andclassification are based on the determination of microbialFAME composition after culturing, a process that forms thebasis of the commercial Sherlock microbial identificationsystem (MIDI Inc., Newark, Delaware, US). Routine FAMEanalysis involves lengthy sample preparation, starting with thehydrolysis of bacteria cells followed by fatty acid methylation.Gas chromatography coupled to mass spectrometry (GC-MS) isthen used for separation and the detection of FAME composi-tion. Each GC-MS run generally takes 20 to 30 min, whereasthe total DART-MS analysis takes less than 10 min.55,61 FAMEwere generated from approximately 107 cell mL21 Streptococcuspyogenes and E. coli. After incubation, cells were washed withTRIS-sucrose buffer, suspended in water, and diluted with asolution of tetramethylammonium hydroxide (TMAH) toproduce thermal hydrolysis and methylation of bacteriallipids. An aliquot of the whole bacterial cell suspension mixedwith TMAH was deposited in the bottom of the capillary tube.The capillary was positioned so that the bottom of the tubecame in contact with the DART He stream directly in front ofthe mass spectrometer inlet orifice after sliding the sampleholder arm. The protonated FAME C9:0, C10:0, C11:0, C12:0,C14:0, C15:0, C17:1/cycloC17:0, and C19:1/cycloC19:0 werefound to be present only in E. coli, while C11:1 was uniquelydetected in S. pyogenes. C17:1/cycloC17:0 and C19:1/cycloC19:0were found in E. coli at relatively high abundances but werenot detected in the S. pyogenes spectrum, which is inaccordance with the membrane characteristics of Gram-negative bacteria. Some FAME ions were common to E. coliand S. pyogenes; however, clear differences existed in therelative abundances of these ions in the mass spectra.Differences among samples were thus observed in the spectraltemporal and intensity domains.60

Recently, a new ambient ionization technique termed lowtemperature plasma mass spectrometry (LTP-MS) was appliedfor bacterial identification.60 This ambient ionization methodwas introduced in 2008 by Cooks and co-workers, and theabsence of any solvent is the distinguishing feature of thisplasma-based method (Fig. 4c).55 LTP-MS was employed todetect fatty acid ethyl esters (FAEE) from bacterial samples in adirect way. Positive ion mode FAEE mass spectrometricprofiles for 16 different bacterial samples were obtainedwithout extraction or other sample preparation. Data wereexamined by PCA to determine the degree of possibledifferentiation among the bacterial species. Growth mediaeffects were observed, but in this case, they did not interferewith species recognition based on the PCA results.55

Ambient desorption/ionization techniques can therefore beapplied to bacterial identification, but in some cases, such asfor DESI that uses a high velocity nebulizing gas, it is necessary

This journal is � The Royal Society of Chemistry 2013 RSC Adv., 2013, 3, 994–1008 | 999

RSC Advances Review

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 7: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

to secure or fix bacterial cells onto the DESI probe surface toprevent sample dispersion and/or aerosolization duringanalysis. This procedure is required for the analysis ofpathogenic bacteria, and heating (for example, at 220 uC for30 s) or long-term drying (.1 h at room temperature) ofbacterial cells are effective means of fixing the sample onto aglass slide surface.57 Different groups using the same ambientionization technique have presented different results due tothe dependence of mass spectral profiles of intact bacteria onthe experimental design and the way in which growth mediawas used and/or prepared. Future investigations in this areaappear to require detailed evaluation of the experimentaldesign and its influence on the data output.57 However, thesuccessful demonstration of identification by ion compositionfrom whole bacterial cells via ambient MS analysis, mainly forsegregating bacterial strains according to Gram status,constitutes the first step that could in the future lead to thesuccessful development of new approaches for high-through-put microbial identification from a variety of biological, food,and water samples in the open air with minimum samplepreparation.57

MALDI-MS based platforms: real-world breakthroughs inmicrobiology

PROTEOMIC STUDIES FOR THE IDENTIFICATION OF BIOMARKERS.Approaches that use proteomics as a tool for studyingexpressed proteins are increasingly being utilized to addressdiverse biomedical questions. Via the identification ofspecific and conserved biomarkers, such as ribosomalproteins, peptides and lipids, it is possible to provide cancerdiagnoses, study inflammatory and degenerative diseases andto determinate pathogens responsible for a broad range ofdiseases.62–66

Protein profiles obtained from direct MALDI-MS analysis ofintact microorganisms or protein extracts have revealed robustbiomarkers that are mostly related to conserved and specificribosomal proteins. Currently, bacterial species identificationby MALDI-MS is the MS approach that has the highest impactin the field of microbiology.67,68 This approach is based on theacquisition of ribosomal protein fingerprints directly fromprotein extracts from intact organisms. Interestingly, theseprotein profiles, which primarily contain ribosomal proteins,have been found to vary considerably and allow the propercharacterization of different microorganisms. These proteinmarkers are rapidly being incorporated into human clinicalmicrobiology routines due to the availability of bioinformaticstools for databank searches, allowing secure identification andhigh laboratory reproducibility.67,68 MALDI-MS has beenproved by many reports to be easier, faster and sometimesmore reliable than classical protocols even when compared tomore sophisticated DNA analysis-based technologies.69,70

MALDI-MS-based microorganism identification has rapidlybeen introduced in laboratory and clinical settings anddelivers fast and reliable diagnostic results, not only for genuslevel identification but also at the species level for bac-teria,63,70–81 fungi,16,82–91 algae,92 viruses93–96 and protozoa.97

An essential step in the identification of microorganisms atthe species level by MALDI-MS has been the use of dedicateddatabases with rigorous data quality control and powerful

algorithms for comparison with mass fingerprinting. Thesedatabases can be run in parallel with MS acquisition data,giving almost real-time bacterial identification results.33,98,99

Because much effort has focused on MALDI-TOF-MS, thisapproach is already in use in clinical diagnostic labora-tories.68,100–107 The observed biomarkers in the mass spectrumenable not only the detection of pathogenic bacteria but alsothe ability to distinguish them from corresponding non-pathogenic species.108

Many Campylobacter species and Helicobacter strains causegastrointestinal diseases and can be discriminated via proteinprofiles observed by MALDI-MS.109–113 Biomarker assignmentalso makes it possible to distinguish subspecies of members ofthe Enterobacteriaceae family so that their fingerprints can beused as family-specific biomarkers for accelerated bacterialidentification via database searches.114

Biomarker monitoring by MALDI-MS can also be used toidentify environmental toxin producers. MS analyses ofpeptides and polyketides from intact cyanobacteria were usedto identify toxic and nontoxic water blooms115–117 andpathogens isolated from seafood, which are associated withfood-borne diseases. This approach was also used to furtherstudy the different protein profiles of azaspiracid toxinbiomarkers in contaminated and non-contaminated bluemussels (Mytilus edulis).118

Burkholderia cepacia, which are important agents of chronicpulmonary disease in cystic fibrosis patients and are proble-matic to accurately identify due to their complex taxonomy,have been successfully discriminated by MALDI-MS.119–122

Mycobacterial species, which are responsible for causingsignificant morbidity in humans by diseases such as tubercu-losis, and Haemophilus spp., which are well known etiologicalagents of pneumonia, meningitis and conjunctivitis, havebeen identified by MALDI-MS via their protein profilespectra.123–125

In the veterinary field, bacteria isolated from cows present-ing subclinical mastitis, a common and easily disseminateddisease in dairy herds, were diagnosed in a few minutesthrough the analysis of ribosomal protein biomarkers isolatedfrom microorganisms present in milk samples by MALDI-MSwith the use of the Biotyper database, a commercial softwarefor MALDI-MS-based microorganism identification that allowsearlier treatment with appropriate antibiotics.126

Immunoproteomic analyses of Mannheimia haemolytica, themost important bacterial pathogen associated with bovinepneumonia, have been performed by MALDI-MS to search forand identify biomarkers from outer membrane proteins thatmay hold potential as candidate vaccine antigens.127

Pigments and proteins from chlorosomes, the light-harvest-ing organelles from the photosynthetic green sulfur bacteriumChlorobium tepidum, were characterized directly from orga-nelles and bacteriochlorophyll, and homologs were detected toprovide fingerprints for these biomarkers.128

MALDI-MS analysis was used to detect the increasedexpression of cold shock proteins in bacteria collected fromthe Siberian permafrost, and distinct proteins and peptideprofiles were observed as a function of temperature. Therecent capability of MALDI-MS imaging has been used to studysynergism and antagonism in microbial communities in the

1000 | RSC Adv., 2013, 3, 994–1008 This journal is � The Royal Society of Chemistry 2013

Review RSC Advances

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 8: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

nests of leaf-cutting ants through the identification ofantimicrobial and antifungal compounds that are producedto defend a symbiotic fungus, which is a major food source forant species.129

These numerous examples of MALDI-MS applications aresupported by the availability of dedicated instrumentation andsoftware containing fingerprinting databases for bacterialidentification. Such instruments are operator-friendly, andtechnicians can operate them in microbiological settings andhospitals with diagnostic purposes with minimal specializa-tion in MS or microbiology and with high-throughput, efficientand trustworthy results. As a result, diverse human clinicalsettings start by comparing the results of traditional methodsversus MALDI-MS-based bacterial identification, and, aftersome time, they move to a solely MALDI-MS-based approachbecause of the many advantages and the desire to avoidnumerous time-consuming and tedious assays.

Identification of uncommon bacterial pathogens, fungi andyeast by MALDI-MS

Microorganisms still represent the largest reservoir of biodi-versity yet to be studied. It has been estimated that onlybetween 1 and 10% of bacteria have been properly described.Correct microorganism identification is essential for appro-priate classification, and the criteria for the identification ofdiverse microorganism species are still equivocal. Somestrains can be misidentified as closely related species. Thisis the case, for example, for Cronobacter spp.130 that can easilybe misidentified as apathogenic Enterobacter turices, E.helveticus and E. pulveris. Cronobacter spp. are Gram-negativeopportunistic food-borne pathogens and are known as rare butimportant causes of neonatal infections. To overcome thisproblem, MALDI-MS was successfully used for rapid genus andspecies-specific identification. Moreover, multi-isotope ima-ging mass spectrometry is contributing to understanding thebacterial diversity of bacterioplankton and helping to linkmicrobial diversity to the biogeochemistry of the pelagic zoneof the aquatic system.131

The marine environment has also been proven to be asource of diverse arrays of bioactive metabolites with greatpotential for pharmaceutical and other applications. In fact,MALDI-MS was applied to classify environmentalSphingomonadaceae using ribosomal subunit proteins codedin the S10-spc-alpha operon as biomarkers.132 In particular,sponges have a largely unexplored biosynthetic potential. Setsof bacteria were cultured from marine sponges (Isops phlegraei,Haliclona sp., Phakellia ventilabrum and Plakortis sp. growingon the Norwegian coast). Intact cell MALDI-MS was used forthe rapid screening and proteometric clustering of a subset ofthe strain collection comprising 456 isolates. The 11 resolvedgroups were also verified by 16S rDNA analyses. The resultsindicated that MALDI-MS is effective for the rapid identifica-tion of isolates, for the selection of strains representing rarespecies and for their dereplication, i.e., rapid grouping ofbacterial isolates for subsequent characterization.133

Screening for microbial population complexity and diversityin the sediment of contaminated environments has alsoreceived increased interest, particularly due to the significanceof these microbes for environmental protection. The taxono-

mical identification of microbial isolates obtained fromsediment samples contaminated with polychlorinated biphe-nyls was successfully performed with MALDI-MS with minimaltime demand and reduced costs.134

The contribution of MS to worldwide biodefence has alsobeen substantial.135,136 In fact, some potential agents forbiological attacks are microorganisms and biotoxins. MS wasdemonstrated to be a valid tool for the rapid identification ofpotential bioagents. Confident identification of an organismcan be achieved by top-down proteomics following identifica-tion of individual protein biomarkers from their tandem massspectra. In bottom-up proteomics, the rapid digestion of intactprotein biomarkers is again followed by MS to provideunambiguous bioagent identification and characteriza-tion.133,134

Accurate discrimination between species of filamentousfungi is also essential because some species have specificantifungal susceptibility patterns, and misidentification mayresult in inappropriate therapy. Direct surface analysis offungal cultures90,137,138 and yeasts139 by MALDI-MS has beenevaluated for species identification. The protein profiles ofintact fungal spores83,140 such as Aspergillus, Fusarium andMucorales demonstrated that MALDI-MS is appropriate for theroutine identification of filamentous fungi in medical micro-biology laboratories.73,138

Culture collection strains representing 55 species ofAspergillus, Fusarium and Mucorales were used to establishone reference database for MALDI-MS-based species identifi-cation with the MALDI BioTyper 2.0 software. To evaluate thedatabase, 103 blind-coded fungal isolates collected in aroutine clinical microbiology laboratory were tested, and96.8% of the isolates were correctly identified to the specieslevel in agreement with reference methods. Eight technicalreplicates of 15 strains were also obtained to study thevariation of mass spectra. Little variation was observed foreach spectrum, whereas enough MS variation could beobserved to separate each strain (Fig. 5).90

Yeast infections cause significant mortality in critically illand immunocompromised patients. In particular, Candidaspp. are the 4th most common cause of nosocomial blood-stream infections in the United States, and Cryptococcusneoformans is the most common cause of fungal meningitisworldwide.141,142 Candida species were reliably identified byMALDI-MS, which had superior performance over conven-tional methods, and it was possible to discriminate betweendifferent molecular types of Cryptococcus neoformans andCryptococcus gattii with the same technique.143,144

Non-fermenting bacteria

Non-fermenting bacteria are a taxonomically heterogeneousgroup of bacteria of the Proteobacteria division, which cannotcatabolize glucose. The genera Pseudomonas, Burkholderia,Stenotrophomonas and others belong to this large group. Theyare ubiquitous environmental opportunists, and some speciescan cause severe infections,145 particularly in immunocom-promised or cystic fibrosis (CF) patients.146 It has beendemonstrated that classical phenotypic methods can fre-quently misidentify non-fermenters.147,148

This journal is � The Royal Society of Chemistry 2013 RSC Adv., 2013, 3, 994–1008 | 1001

RSC Advances Review

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 9: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

For this class of bacteria, molecular tools such as 16S rDNAgene sequencing provide reliable results, but less accurateresults have been obtained at the species level. Therefore, areference database for MALDI-MS based on the identificationof non-fermenters was established by Mellmann et al.149,150

and 16S rRNA gene sequencing was used for comparison.Different cultivation conditions and mass spectrometerinstruments were used, and the methodology was evaluatedwith 80 blind-coded clinical non-fermenter strains. The studydemonstrated that the MALDI-MS method provides fast andthorough identification of non-fermenting bacteria, even moreaccurately than partial 16S rRNA gene sequencing for speciesidentification of members of the Burkholderia cepacia complex.A large international multicenter study has also demonstratedthe high reproducibility of the identification of non-ferment-ing bacteria by MALDI-MS, with 98.75% correct speciesidentification. This study demonstrated the suitability of thetechnique as an alternative to partial 16S rRNA platforms. Avery recent study also evaluated the ability of the technique toidentify non-fermenting bacteria from among a total of 182isolates from 70 CF patients because non-fermenters are themain cause of mortality in this type of patient.151 MALDI- MSwas found to improve routine identification, particularly byenlarging the Biotyper 2.0 database to include the rare andinfrequent microorganisms recovered from CF patients.152

Non-culture-based identification of bacteria from blood andmilk

In addition to being increasingly used for the rapid identifica-tion of bacteria and fungi, MALDI-MS also holds promise forbacterial identification from blood culture (BC) broths inhospital laboratories153–155 and bacterial identification directlyfrom milk samples.156

A MALDI-MS-based approach has been shown to performrapid (,20 min) bacterial identification directly from positiveBCs with high accuracy. Positive predictive values for the directidentification of both Gram-positive and Gram-negativebacteria from monomicrobial blood culture broths were100% to the genus level. A diagnostic algorithm for positiveblood culture broths that incorporates Gram staining andMALDI-MS should be able to identify the majority ofpathogens, particularly at the genus level.153,154

The routine identification of microorganisms that contam-inate milk is mostly based on phenotypic characteristics suchas colony morphology, hemolytic potential and severalbiochemical reactions, which are time-consuming andcostly.157 Additionally, these tests may fail to correctly identifyall agents, and even though methods based on PCR aredeveloping rapidly, there may be no agreement among thetechniques that phenotypically and genotypically differentiatebacterial species, resulting in the false identification of agents.Non-culture MALDI-MS identification based on protein finger-printing from bacteria (E. coli, S. aureus and E. faecalis)inoculated and recovered directly from milk samples has beensuccessful (Fig. 6). Although relatively high bacterial loads (106

to 107 bacteria mL21 of milk) must be present, the simpleincubation of an initial load of 104 bacteria mL21 of milk canbe used to facilitate bacterial replication and successful

Fig. 5 Three-dimensional principal component analysis (PCA) plot of the technical replicates of selected reference strains of (a) Aspergillus (seven strains), (b) Fusarium(four strains) and (c) Mucorales (four strains). Reproduced from ref. 90 with permission from John Wiley and Sons.

Fig. 6 MALDI-MS ribosomal protein fingerprints for the identification ofbacteria in whole milk. Data were collected in the m/z 4000–22 000 range afterprocessing 900 mL of whole milk that had been experimentally contaminatedwith E. coli at (a) 103, (b) 104, (c) 105, (d) 106, (e) 107, (f) 108, or (g) 109 cfu ml21.Reproduced from Proteomics ref. 156 with permission from John Wiley andSons.

1002 | RSC Adv., 2013, 3, 994–1008 This journal is � The Royal Society of Chemistry 2013

Review RSC Advances

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 10: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

identification. Fast, reliable and sensitive protocols for theanalysis of relatively low concentrations of bacteria present inmilk could be of great value for the dairy industry.

Testing for antibiotic resistance with MS and polymicrobialculture analysis

Antibiotic resistance is the ability of a microorganism towithstand the effects of an antibiotic drug, and this abilityrepresents a huge health concern in the medical andveterinary fields. Recent studies have shown that individualsare at risk of carrying antibiotic-resistant bacteria after a seriesof antibiotic treatments due to the resulting selection forantibiotic-resistant microorganisms. The most commonmechanisms of antibiotic resistance can be divided in threeclasses: alteration of the antibiotic target, restriction ofantibiotic access to the target and inactivation of theantibiotic.158–160

Recently, the ability of MALDI MS to effectively discriminatebacteria strains which have acquired resistance to a variety ofantibiotics has been demonstrated, indicating that thistechnique has the potential to differentiate bacterial strainswith varying degrees of antibiotic resistance.161

The rapid detection of resistance type is necessary to selectthe best antibiotic therapy. b-Lactam antibiotics represent abroad class of antibiotics that contain a b-lactam nucleus intheir molecular structure. These antibiotics include penicillinderivatives (penams), cephalosporins (cephems), monobac-tams, and carbapenems. b-Lactam antibiotics act by inhibitingthe synthesis of the peptidoglycan layer of bacterial cell walls,

which is important for cell wall structural integrity. b-Lactamantibiotics mainly affect Gram-positive organisms becausepeptidoglycan is the outermost and primary component oftheir cell wall. This antibiotic class binds in the active site ofpenicillin-binding proteins (PBPs), preventing the final cross-linking (transpeptidation) of the nascent peptidoglycan layerand disrupting cell wall synthesis.162 Since these antibioticsare widely administered to treat infections in human anddomestic animals, many Gram-positive bacteria have alreadydeveloped resistance mechanisms.

Antimicrobial susceptibility has classically been determinedusing a variety of in vitro methods such as disk diffusion andbroth microdilution as well as automated instrument-basedmethods. These methods may require from a few hours, suchas for the antimicrobial susceptibility test (AST), to 24–96 h fora pure culture of the suspected pathogen to be obtained andsubjected to disk diffusion assays.3,163 A novel MALDI-MSmethod for the detection of b-lactamase resistance hasrecently been reported. Resistance to b-lactam antibioticscan be easily monitored by MS because hydrolysis of thecentral b-lactam ring by b-lactamases results in the disap-pearance of the original ion, which is shifted 18 m/z unitshigher in the spectrum of the antibiotic. In many cases,hydrolysis is directly followed by a decarboxylation of thehydrolyzed product, resulting in a further shift of 244 m/zunits due to detection of the hydrolyzed form. Because MSeasily monitors such m/z shifts, a MALDI-MS assay was set upto analyze the hydrolysis reactions of different b-lactamantibiotics (Fig. 7).164

MALDI-MS can also be applied to study bacterial resistanceto antibiotics or antimicrobial compounds secreted by otherbacterial species.68,165,166 Reportedly, antibiotic-resistant andnon-resistant strains of an important human pathogen, S.aureus, can be differentiated by MALDI-MS by rapid andaccurate discrimination between methicillin-sensitive andmethicillin-resistant strains of this organism, which can couldlead to major improvements in the treatment strategies forinfected patients.167 The same microorganism has beenidentified via biomarker analysis as one of the main pathogensresponsible for prosthetic joint infections, indicating reliabledifferentiation between S. aureus and coagulase-negativestaphylococci.168

The resistance mechanism of colistin-resistant variants ofAcinetobacter baumannii was elucidated by MALDI-MS169 bydetermining the phosphoethanolamine modification of lipidA. For Bacteroides fragilis, it was recently shown that thedifferentiation of cfiA gene-encoded class B metallo-b-lacta-mase was possible by direct MALDI-MS.170,171 The carbapenemresistance of B. fragilis is due to a species-specific metallo-b-lactamase, which is encoded by the cfiA (ccrA) gene of theorganism. Almost 100% of the carbapenem-resistant bacteroidstrains were cfiA-positive B. fragilis isolates. However, suchclonal differentiation for resistant and susceptible clonescannot be expected for the majority of bacteria. Antibioticresistance in Gram-negative rods, particularlyEnterobacteriaceae, Pseudomonas spp. and Acinetobacter spp.,has been an increasing problem worldwide. Infections bymultidrug-resistant Gram-negative bacteria are usually treatedwith carbapenems. This resistance is caused by an alteration

Fig. 7 (A and B) MALDI-MS of ampicillin after incubation with a b-lactamase-producing strain (B). (C) Inhibition of hydrolysis by a b-lactamase-producingstrain was performed in the presence of clavulanic acid. Peaks corresponding tothe non-hydrolyzed form of ampicillin are highlighted in gray. Peakscorresponding to the hydrolyzed form of ampicillin are indicated with an arrow.Reproduced from ref. 164 with permission from the American Society forMicrobiology.

This journal is � The Royal Society of Chemistry 2013 RSC Adv., 2013, 3, 994–1008 | 1003

RSC Advances Review

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 11: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

in the outer membrane of the cell wall and by the productionof carbapenemases.172 Carbapenamase activity was detected in124 strains following comparison between well-typed bacterialcarbapenem non-susceptible isolates and clinical isolatessusceptible to carbapenems. Antibiotic resistance was demon-strated by detecting the disrupted amide bond and itscationized forms.173

Although the microbiological methods of microorganismculture and isolation are successful, mixed cultures orpolymicrobial cultures may occur. For example, one bacterialisolate from subclinical bovine mastitis was identified asStaphylococcus aureus by an enzymatic assay, and yet the samesample, when analyzed by Biotyper software after MALDI-MS,displayed a signature of Enterococcus faecalis mixed with S.aureus, which was confirmed by 16S RNA sequencing.174

When bacterial identification of human clinical isolates wasperformed by MALDI-MS directly on 500 blood broth cultures,there were 27 polymicrobial cultures, and 25 (92.6%) had atleast one species correctly identified by the instrumentdatabase. Using the same instrument and software platform,similar results have been observed by Moussaoui et al.175 andChristner et al.,176 who reported that 80.9% and 81.2%,respectively, of at least one of the species present wereidentified in polymicrobial cultures obtained directly fromblood culture vials.175,176

Conclusions and real-world perspectives

Diverse ionization methods and MS techniques can besuccessfully used for microorganism identification andresearch. MALDI-MS is the leading MS technique for clinicaland commercial microbiological use, and there are consistentreports demonstrating the confidence of this approach incomparison to other non-MS based gold-standard approachesto identify a large range of microorganisms. The broad use ofthis technique now appears to only be dependent onregulatory issues in various countries, including the UnitedStates.

Limitations of MS-based microorganism identification aredependent on the initial cost of the technology, which isrelated to the instrument configurations. Also, most labora-tories will need an internal validation period in which thetransition between the traditional methods to MS-basedmicroorganism identification and staff training is performed.Since one instrument is sufficient for a high number ofsamples/day, technical problems can interrupt the routine andimpact clinical decisions, especially in septicemic conditions.These issues should be managed with appropriate planningsuch as the long-term benefits related to the cost/sample. Theidentification of bacteria isolated from 928 human clinicalsamples in a routine microbiology setting has been recentlycompared using the BD Phoenix, API panels and otherrecommended procedures and MALDI-MS using a TOFanalyzer and the Biotyper software. Besides the velocity ofthe diagnosis, MALDI-MS showed substantial savings of

around U$ 2–3 per isolate, depending on the cost of theinstrument.

Therefore, microbiology is ready to enter into a new era inwhich molecular rather than morphological or biochemicalcharacteristics of microorganisms will be rapidly assessed(directly from biological fluids) by MS for identification. Theuse of this technique is not only limited to clinical diagnosis,but it has been shown to have successful application fordetecting antibiotic resistance, characterizing microorganismsthat are difficult to isolate and culture and exploring thebiodiversity of microorganisms present in the environmentand in the digestive tracts of animals and humans. Massspectrometry-based proteomics approaches have also beenapplied to gain a greater understanding of the pathophysiol-ogy and virulence of microorganisms. This approach isproviding key insights to better understand the molecularprocesses involved in protein secretion, modification, synth-esis and degradation.177–179

A new era has indeed emerged in which bacterialidentification seems fully prepared to make the transitionfrom the agar plate and visual inspection to the massspectrometer for characterization at the more accuratemolecular level.

References

1 C. B. Talaro, Foundations in Microbiology: Basic Principles,McGraw-Hill Science/Engineering/Math, New York, 2011.

2 W. P. Olson, Automated Microbial Identification andQuantitation: Technologies for the 2000s, CRC Press, BocaRaton, FL, 1996.

3 J. H. Jorgensen, J. D. Turnidge and J. A. Washington,Antimicrobial Susceptibility Tests: Dilution and DiskDiffusion Methods, ASM Press, Washington, DC, 2007.

4 J. B. Fenn, M. Mann, C. K. Meng, S. F. Wong and C.M. Whitehouse, Science, 1989, 246, 64–71.

5 M. Karas and F. Hillenkamp, Anal. Chem., 1988, 60,2299–2301.

6 P. R. Murray, J. Mol. Diagn., 2012, 14, 419–423.7 M. M. Read, Trends in DNA Fingerprinting Research, 2005.8 N. M. C. NMC, 2004.9 V. Thurm and B. Gericke, J. Appl. Microbiol., 1994, 76,

553–558.10 M. J. Pelczar, 1993.11 A. Galar, J. Leiva, M. Espinosa, F. Guillen-Grima,

S. Hernaez and J. R. Yuste, J. Infect., 2012, 65, 302–309.12 Y. W. Tang, G. W. Procop and D. H. Persing, Clin. Chem.,

1997, 43, 2021–2038.13 K. B. Mullis and F. A. Faloona, Methods Enzymol., 1987,

155, 335–350.14 J. M. Bartlett and D. Stirling, Methods Mol. Biol., 2003, 226,

3–6.15 O. M. Cloak and P. M. Fratamico, J. Food Prot., 2002, 65,

266–273.16 G. Marklein, M. Josten, U. Klanke, E. Muller, R. Horre,

T. Maier, T. Wenzel, M. Kostrzewa, G. Bierbaum,A. Hoerauf and H. G. Sahl, J. Clin. Microbiol., 2009, 47,2912–2917.

1004 | RSC Adv., 2013, 3, 994–1008 This journal is � The Royal Society of Chemistry 2013

Review RSC Advances

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 12: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

17 L. J. Wickerham, J. Bacteriol., 1943, 46, 501–505.18 L. J. Wickerham and K. A. Burton, J. Bacteriol., 1948, 56,

363–371.19 C. Y. Turenne, S. E. Sanche, D. J. Hoban, J. A. Karlowsky

and A. M. Kabani, J. Clin. Microbiol., 1999, 37, 1846–1851.20 M. D. Lindsley, S. F. Hurst, N. J. Iqbal and C. J. Morrison,

J. Clin. Microbiol., 2001, 39, 3505–3511.21 D. H. Pincus, S. Orenga and S. Chatellier, Med. Mycol.,

2007, 45, 97–121.22 J. B. Fenn, M. Mann, C. K. Meng, S. F. Wong and C.

M. Whitehouse, Mass Spectrom. Rev., 1990, 9, 37–70.23 S. A. Hofstadler, R. Sampath, L. B. Blyn, M. W. Eshoo, T.

A. Hall, Y. Jiang, J. J. Drader, J. C. Hannis, K. A. Sannes-Lowery, L. L. Cummins, B. Libby, D. J. Walcott, A. Schink,C. Massire, R. Ranken, J. Gutierrez, S. Manalili, C. Ivy,R. Melton, H. Levene, G. Barrett-Wilt, F. Li, V. Zapp,N. White, V. Samant, J. A. McNeil, D. Knize, D. Robbins,K. Rudnick, A. Desai, E. Moradi and D. J. Ecker, Int. J.Mass Spectrom., 2005, 242, 23–41.

24 D. S. Wunschel, K. F. Fox, A. Fox, J. E. Bruce, D.C. Muddiman and R. D. Smith, Rapid Commun. MassSpectrom., 1996, 10, 29–35.

25 D. C. Muddiman, D. S. Wunschel, C. L. Liu, L. PasaTolic,K. F. Fox, A. Fox, G. A. Anderson and R. D. Smith, Anal.Chem., 1996, 68, 3705–3712.

26 D. C. Muddiman, G. A. Anderson, S. A. Hofstadler and R.D. Smith, Anal. Chem., 1997, 69, 1543–1549.

27 R. R. Drake, S. R. Boggs and S. K. Drake, J. Mass Spectrom.,2011, 46, 1223–1232.

28 K. Cottingham, Anal. Chem., 2004, 76, 261.29 C. D. Baldwin, G. B. Howe, R. Sampath, L. B. Blyn,

H. Matthews, V. Harpin, T. A. Hall, J. J. Drader, S.A. Hofstadler, M. W. Eshoo, K. Rudnick, K. Studarus,D. Moore, S. Abbott, J. M. Janda and C. A. Whitehouse,Diagn. Microbiol. Infect. Dis., 2009, 63, 403–408.

30 M. N. Van Ert, S. A. Hofstadler, Y. Jiang, J. D. Busch, D.M. Wagner, J. J. Drader, D. J. Ecker, J. C. Hannis, L.Y. Huynh, J. M. Schupp, T. S. Simonson and P. Keim,Biotechniques, 2004, 37, 642–648.

31 D. J. Ecker, R. Sampath, C. Massire, L. B. Blyn, T. A. Hall,M. W. Eshoo and S. A. Hofstadler, Nat. Rev. Microbiol.,2008, 6, 553–558.

32 T. Maier and M. Kostrzewa, Chim. Oggi, 2007, 25, 68–71.33 M. Welker, Proteomics, 2011, 11, 3143–3153.34 E. J. Kaleta, A. E. Clark, A. Cherkaoui, V. H. Wysocki, E.

L. Ingram, J. Schrenzel and D. M. Wolk, Clin. Chem., 2011,57, 1057–1067.

35 E. J. Kaleta, A. E. Clark, D. R. Johnson, D. C. Gamage, V.H. Wysocki, A. Cherkaoui, J. Schrenzel and D. M. Wolk, J.Clin. Microbiol., 2011, 49, 345–353.

36 M. W. Eshoo, C. D. Crowder, H. J. Li, H. E. Matthews, S.F. Meng, S. E. Sefers, R. Sampath, C. W. Stratton, L.B. Blyn, D. J. Ecker and Y. W. Tang, J. Clin. Microbiol.,2010, 48, 472–478.

37 D. J. Ecker, R. Sampath, H. Li, C. Massire, H. E. Matthews,D. Toleno, T. A. Hall, L. B. Blyn, M. W. Eshoo, R. Ranken,S. A. Hofstadler and Y. W. Tang, Expert Rev. Mol. Diagn.,2010, 10, 399–415.

38 T. A. Hall, R. Sampath, L. B. Blyn, R. Ranken, C. Ivy,R. Melton, H. Matthews, N. White, F. Li, V. Harpin, D.J. Ecker, L. K. McDougal, B. Limbago, T. Ross, D. M. Wolk,

V. Wysocki and K. C. Carroll, J. Clin. Microbiol., 2009, 47,1733–1741.

39 D. M. Wolk, L. B. Blyn, T. A. Hall, R. Sampath, R. Ranken,C. Ivy, R. Melton, H. Matthews, N. White, F. Li, V. Harpin,D. J. Ecker, B. Limbago, L. K. McDougal, V. H. Wysocki,M. Cai and K. C. Carroll, J. Clin. Microbiol., 2009, 47,3129–3137.

40 J. A. Ecker, C. Massire, T. A. Hall, R. Ranken, T. T.D. Pennella, C. A. Ivy, L. B. Blyn, S. A. Hofstadler, T.P. Endy, P. T. Scott, L. Lindler, T. Hamilton, C. Gaddy,K. Snow, M. Pe, J. Fishbain, D. Craft, G. Deye, S. Riddell,E. Milstrey, B. Petruccelli, S. Brisse, V. Harpin, A. Schink,D. J. Ecker, R. Sampath and M. W. Eshoo, J. Clin.Microbiol., 2006, 44, 2921–2932.

41 J. C. Hannis, S. M. Manalili, T. A. Hall, R. Ranken,N. White, R. Sampath, L. B. Blyn, D. J. Ecker, R.E. Mandrell, C. K. Fagerquist, A. H. Bates, W. G. Millerand S. A. Hofstadler, J. Clin. Microbiol., 2008, 46,1220–1225.

42 C. A. Whitehouse, C. Baldwin, R. Sampath, L. B. Blyn,R. Melton, F. Li, T. A. Hall, V. Harpin, H. Matthews,M. Tediashvili, E. Jaiani, T. Kokashvili, N. Janelidze,C. Grim, R. R. Colwell and A. Huq, Appl. Environ.Microbiol., 2010, 76, 1996–2001.

43 D. J. Ecker, R. Sampath, L. B. Blyn, M. W. Eshoo, C. Ivy, J.A. Ecker, B. Libby, V. Samant, K. A. Sannes-Lowery, R.E. Melton, K. Russell, N. Freed, C. Barrozo, J. Wu,K. Rudnick, A. Desai, E. Moradi, D. J. Knize, D.W. Robbins, J. C. Hannis, P. M. Harrell, C. Massire, T.A. Hall, Y. Jiang, R. Ranken, J. J. Drader, N. White, J.A. McNeil, S. T. Crooke and S. A. Hofstadler, Proc. Natl.Acad. Sci. U. S. A., 2005, 102, 8012–8017.

44 R. J. Grant-Klein, C. D. Baldwin, M. J. Turell, C. A. Rossi,F. Li, R. Lovari, C. D. Crowder, H. E. Matthews, M.A. Rounds, M. W. Eshoo, L. B. Blyn, D. J. Ecker,R. Sampath and C. A. Whitehouse, Mol. Cell. Probes,2010, 24, 219–228.

45 R. Sampath, S. A. Hofstadler, L. B. Blyn, M. W. Eshoo, T.A. Hall, C. Massire, H. M. Levene, J. C. Hannis, P.M. Harrell, B. Neuman, M. J. Buchmeier, Y. Jiang,R. Ranken, J. J. Drader, V. Samant, R. H. Griffey, J.A. McNeil, S. T. Crooke and D. J. Ecker, Emerging Infect.Dis., 2005, 11, 373–379.

46 V. M. Deyde, R. Sampath, R. J. Garten, P. J. Blair, C.A. Myers, C. Massire, H. Matthews, P. Svoboda, M.S. Reed, J. Pohl, A. I. Klimov and L. V. Gubareva, PLoSOne, 2010, 5, e13293.

47 D. J. Ecker, C. Massire, L. B. Blyn, S. A. Hofstadler, J.C. Hannis, M. W. Eshoo, T. A. Hall and R. Sampath,Methods Mol. Biol., 2009, 551, 71–87.

48 R. Sampath, T. A. Hall, C. Massire, F. Li, L. B. Blyn, M.W. Eshoo, S. A. Hofstadler and D. J. Ecker, Ann. N. Y. Acad.Sci., 2007, 1102, 109–120.

49 R. Sampath, K. L. Russell, C. Massire, M. W. Eshoo,V. Harpin, L. B. Blyn, R. Melton, C. Ivy, T. Pennella, F. Li,H. Levene, T. A. Hall, B. Libby, N. Fan, D. J. Walcott,R. Ranken, M. Pear, A. Schink, J. Gutierrez, J. Drader,D. Moore, D. Metzgar, L. Addington, R. Rothman, C.A. Gaydos, S. Yang, K. St George, M. E. Fuschino, A.B. Dean, D. E. Stallknecht, G. Goekjian, S. Yingst,M. Monteville, M. D. Saad, C. A. Whitehouse,

This journal is � The Royal Society of Chemistry 2013 RSC Adv., 2013, 3, 994–1008 | 1005

RSC Advances Review

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 13: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

C. Baldwin, K. H. Rudnick, S. A. Hofstadler, S. M. Lemonand D. J. Ecker, PLoS One, 2007, 2, e489.

50 L. B. Blyn, T. A. Hall, B. Libby, R. Ranken, R. Sampath,K. Rudnick, E. Moradi, A. Desai, D. Metzgar, K. L. Russell,N. E. Freed, M. Balansay, M. P. Broderick, M. A. Osuna, S.A. Hofstadler and D. J. Ecker, J. Clin. Microbiol., 2008, 46,644–651.

51 R. M. Alberici, R. C. Simas, G. B. Sanvido, W. Romao, P.M. Lalli, M. Benassi, I. B. Cunha and M. N. Eberlin, Anal.Bioanal. Chem., 2010, 398, 265–294.

52 D. R. Ifa, C. Wu, Z. Ouyang and R. G. Cooks, Analyst, 2010,135, 669–681.

53 Z. Takats, J. M. Wiseman, B. Gologan and R. G. Cooks,Science, 2004, 306, 471–473.

54 R. B. Cody, J. A. Laramee and H. D. Durst, Anal. Chem.,2005, 77, 2297–2302.

55 J. I. Zhang, A. B. Costa, W. A. Tao and R. G. Cooks, Analyst,2011, 136, 3091–3097.

56 Y. Song, N. Talaty, W. A. Tao, Z. Pan and R. G. Cooks,Chem. Commun., 2007, 61–63.

57 M. A. Meetani, Y. S. Shin, S. Zhang, R. Mayer and F. Basile,J. Mass Spectrom., 2007, 42, 1186–1193.

58 Z. Takats, J. M. Wiseman and R. G. Cooks, J. MassSpectrom., 2005, 40, 1261–1275.

59 Y. Song, N. Talaty, K. Datsenko, B. L. Wanner and R.G. Cooks, Analyst, 2009, 134, 838–841.

60 C. Y. Pierce, J. R. Barr, R. B. Cody, R. F. Massung, A.R. Woolfitt, H. Moura, H. A. Thompson and F.M. Fernandez, Chem. Commun., 2007, 807–809.

61 A. Fox, J. Clin. Microbiol., 2006, 44, 2677–2680.62 J. O. Lay Jr, Mass Spectrom. Rev., 2001, 20, 172–194.63 R. D. Holland, C. R. Duffy, F. Rafii, J. B. Sutherland, T.

M. Heinze, C. L. Holder, K. J. Voorhees and J. O. Lay Jr,Anal. Chem., 1999, 71, 3226–3230.

64 P. Cash, Proteomics, 2011, 11, 3190–3202.65 A. Alvarez-Buylla, E. Culebras and J. J. Picazo, Infect. Genet.

Evol., 2012, 12, 345–349.66 C. D. Calvano, C. G. Zambonin and F. Palmisano, Rapid

Commun. Mass Spectrom., 2011, 25, 1757–1764.67 P. Seng, J. M. Rolain, P. E. Fournier, B. La Scola,

M. Drancourt and D. Raoult, Future Microbiol., 2010, 5,1733–1754.

68 A. Bizzini and G. Greub, Clin. Microbiol. Infect., 2010, 16,1614–1619.

69 E. N. Ilina, A. D. Borovskaya, M. M. Malakhova, V.A. Vereshchagin, A. A. Kubanova, A. N. Kruglov, T.S. Svistunova, A. O. Gazarian, T. Maier, M. Kostrzewaand V. M. Govorun, J. Mol. Diagn., 2009, 11, 75–86.

70 C. Fenselau and P. A. Demirev, Mass Spectrom. Rev., 2001,20, 157–171.

71 M. A. Claydon, S. N. Davey, V. Edwards-Jones and D.B. Gordon, Nat. Biotechnol., 1996, 14, 1584–1586.

72 R. D. Holland, J. G. Wilkes, F. Rafii, J. B. Sutherland, C.C. Persons, K. J. Voorhees and J. O. Lay Jr, Rapid Commun.Mass Spectrom., 1996, 10, 1227–1232.

73 T. Krishnamurthy and P. L. Ross, Rapid Commun. MassSpectrom., 1996, 10, 1992–1996.

74 R. J. Arnold, J. A. Karty, A. D. Ellington and J. P. Reilly,Anal. Chem., 1999, 71, 1990–1996.

75 R. J. Arnold and J. P. Reilly, Rapid Commun. MassSpectrom., 1998, 12, 630–636.

76 Z. Wang, L. Russon, L. Li, D. C. Roser and S. R. Long,Rapid Commun. Mass Spectrom., 1998, 12, 456–464.

77 K. J. Welham, M. A. Domin, D. E. Scannell, E. Cohen andD. S. Ashton, Rapid Commun. Mass Spectrom., 1998, 12,176–180.

78 Y. Dai, L. Li, D. C. Roser and S. R. Long, Rapid Commun.Mass Spectrom., 1999, 13, 73–78.

79 V. Ryzhov and C. Fenselau, Anal. Chem., 2001, 73,746–750.

80 D. B. Wall, D. M. Lubman and S. J. Flynn, Anal. Chem.,1999, 71, 3894–3900.

81 D. Dubois, D. Leyssene, J. P. Chacornac, M. Kostrzewa, P.O. Schmit, R. Talon, R. Bonnet and J. Delmas, J. Clin.Microbiol., 2010, 48, 941–945.

82 B. Amiri-Eliasi and C. Fenselau, Anal. Chem., 2001, 73,5228–5231.

83 H. Y. Chen and Y. C. Chen, Rapid Commun. MassSpectrom., 2005, 19, 3564–3568.

84 M. Sulc, K. Peslova, M. Zabka, M. Hajduch andV. Havlicek, Int. J. Mass Spectrom., 2009, 280, 162–168.

85 C. J. Seneviratne, Y. Wang, L. Jin, Y. Abiko and L.P. Samaranayake, Proteomics, 2010, 10, 1444–1454.

86 O. Coulibaly, C. Marinach-Patrice, C. Cassagne,R. Piarroux, D. Mazier and S. Ranque, Med. Mycol.,2011, 49, 621–626.

87 A. D. Buskirk, J. M. Hettick, I. Chipinda, B. F. Law, P.D. Siegel, J. E. Slaven, B. J. Green and D. H. Beezhold,Anal. Biochem., 2011, 411, 122–128.

88 A. Kubesova, J. Salplachta, M. Horka, F. Ruzicka andK. Slais, Analyst, 2012, 137, 1937–1943.

89 Y. L. Pan, N. H. Chow, T. C. Chang and H. C. Chang,Diagn. Microbiol. Infect. Dis., 2011, 70, 344–354.

90 E. De Carolis, B. Posteraro, C. Lass-Florl, A. Vella, A.R. Florio, R. Torelli, C. Girmenia, C. Colozza, A.M. Tortorano, M. Sanguinetti and G. Fadda, Clin.Microbiol. Infect., 2012, 18, 475–484.

91 L. N. Shi, F. Q. Li, M. Huang, J. F. Lu, X. X. Kong, S.Q. Wang and H. F. Shao, BMC Microbiol., 2012, 12, 11.

92 H. Wirth, M. von Bergen, J. Murugaiyan, U. Rosler,T. Stokowy and H. Binder, J. Microbiol. Methods, 2012, 88,83–97.

93 Y. J. Kim, A. Freas and C. Fenselau, Anal. Chem., 2001, 73,1544–1548.

94 Z. P. Yao, P. A. Demirev and C. Fenselau, Anal. Chem.,2002, 74, 2529–2534.

95 S. Zhou, Q. Wan, Y. Huang, X. Huang, J. Cao, L. Ye, T.K. Lim, Q. Lin and Q. Qin, Proteomics, 2011, 11,2236–2248.

96 C. F. Franco, M. C. Mellado, P. M. Alves and A. V. Coelho,Talanta, 2010, 80, 1561–1568.

97 M. L. Diaz, A. Solari and C. I. Gonzalez, J. Proteomics, 2011,74, 1673–1682.

98 P. A. Demirev, Y. P. Ho, V. Ryzhov and C. Fenselau, Anal.Chem., 1999, 71, 2732–2738.

99 K. Sogawa, M. Watanabe, K. Sato, S. Segawa, C. Ishii,A. Miyabe, S. Murata, T. Saito and F. Nomura, Anal.Bioanal. Chem., 2011, 400, 1905–1911.

100 D. Steensels, J. Verhaegen and K. Lagrou, Acta Clin. Belg.,2011, 66, 267–273.

1006 | RSC Adv., 2013, 3, 994–1008 This journal is � The Royal Society of Chemistry 2013

Review RSC Advances

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 14: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

101 E. Carbonnelle, J. L. Beretti, S. Cottyn, G. Quesne,P. Berche, X. Nassif and A. Ferroni, J. Clin. Microbiol.,2007, 45, 2156–2161.

102 E. Carbonnelle, C. Mesquita, E. Bille, N. Day, B. Dauphin,J. L. Beretti, A. Ferroni, L. Gutmann and X. Nassif, Clin.Biochem., 2011, 44, 104–109.

103 U. Eigner, M. Holfelder, K. Oberdorfer, U. Betz-Wild,D. Bertsch and A. M. Fahr, Clin. Lab., 2009, 55, 289–296.

104 E. Bessede, M. Angla-Gre, Y. Delagarde, S. Sep Hieng,A. Menard and F. Megraud, Clin. Microbiol. Infect., 2011,17, 533–538.

105 A. Croxatto, G. Prod’hom and G. Greub, FEMS Microbiol.Rev., 2012, 36, 380–407.

106 A. El Khechine, C. Couderc, C. Flaudrops, D. Raoult andM. Drancourt, PLoS One, 2011, 6, e24720.

107 A. Wieser, L. Schneider, J. Jung and S. Schubert, Appl.Microbiol. Biotechnol., 2012, 93, 965–974.

108 T. Krishnamurthy, P. L. Ross and U. Rajamani, RapidCommun. Mass Spectrom., 1996, 10, 883–888.

109 M. A. Winkler, J. Uher and S. Cepa, Anal. Chem., 1999, 71,3416–3419.

110 R. E. Mandrell, L. A. Harden, A. Bates, W. G. Miller, W.F. Haddon and C. K. Fagerquist, Appl. Environ. Microbiol.,2005, 71, 6292–6307.

111 C. K. Fagerquist, W. G. Miller, L. A. Harden, A. H. Bates,W. H. Vensel, G. Wang and R. E. Mandrell, Anal. Chem.,2005, 77, 4897–4907.

112 C. L. Nilsson, Rapid Commun. Mass Spectrom., 1999, 13,1067–1071.

113 M. Alispahic, K. Hummel, D. Jandreski-Cvetkovic,K. Nobauer, E. Razzazi-Fazeli, M. Hess and C. Hess, J.Med. Microbiol., 2010, 59, 295–301.

114 E. C. Lynn, M. C. Chung, W. C. Tsai and C. C. Han, RapidCommun. Mass Spectrom., 1999, 13, 2022–2027.

115 M. Erhard, H. von Dohren and P. Jungblut, Nat.Biotechnol., 1997, 15, 906–909.

116 M. Erhard, H. von Dohren and P. R. Jungblut, RapidCommun. Mass Spectrom., 1999, 13, 337–343.

117 G. Sandh, L. Ran, L. Xu, G. Sundqvist, V. Bulone andB. Bergman, Proteomics, 2011, 11, 406–419.

118 J. K. Nzoughet, J. T. Hamilton, C. H. Botting, A. Douglas,L. Devine, J. Nelson and C. T. Elliott, Mol. Cell. Proteomics,2009, 8, 1811–1822.

119 T. Mott, M. Soler, S. Grigsby, R. Medley and G.C. Whitlock, J. Clin. Microbiol., 2010, 48, 4186–4192.

120 A. Minan, A. Bosch, P. Lasch, M. Stammler, D. O. Serra,J. Degrossi, B. Gatti, C. Vay, M. D’Aquino, O. Yantorno andD. Naumann, Analyst, 2009, 134, 1138–1148.

121 E. Vanlaere, K. Sergeant, P. Dawyndt, W. Kallow,M. Erhard, H. Sutton, D. Dare, B. Devreese, B. Samynand P. Vandamme, J. Microbiol. Methods, 2008, 75,279–286.

122 N. Degand, E. Carbonnelle, B. Dauphin, J. L. Beretti, M. LeBourgeois, I. Sermet-Gaudelus, C. Segonds, P. Berche,X. Nassif and A. Ferroni, J. Clin. Microbiol., 2008, 46,3361–3367.

123 P. G. Saleeb, S. K. Drake, P. R. Murray and A. M. Zelazny, J.Clin. Microbiol., 2011, 49, 1790–1794.

124 C. Bouakaze, C. Keyser, A. Gonzalez, W. Sougakoff,N. Veziris, H. Dabernat, B. Jaulhac and B. Ludes, J. Clin.Microbiol., 2011, 49, 3292–3299.

125 A. M. Haag, S. N. Taylor, K. H. Johnston and R. B. Cole, J.Mass Spectrom., 1998, 33, 750–756.

126 J. R. Barreiro, C. R. Ferreira, G. B. Sanvido, M. Kostrzewa,T. Maier, B. Wegemann, V. Bottcher, M. N. Eberlin and M.V. dos Santos, J. Dairy Sci., 2010, 93(12), 5661–5667.

127 S. Ayalew, A. W. Confer, S. D. Hartson and B. Shrestha,Proteomics, 2010, 10, 2151–2164.

128 S. Persson, C. P. Sonksen, N. U. Frigaard, R. P. Cox,P. Roepstorff and M. Miller, Eur. J. Biochem., 2000, 267,450–456.

129 I. Schoenian, M. Spiteller, M. Ghaste, R. Wirth, H. Herzand D. Spiteller, Proc. Natl. Acad. Sci. U. S. A., 2011, 108,1955–1960.

130 R. Stephan, D. Ziegler, V. Pfluger, G. Vogel and A. Lehner,J. Clin. Microbiol., 2010, 48, 2846–2851.

131 K. D. Hofle, R. Christen and I. Brettar, Aquat. Microb.Ecol., 2008, 53, 19.

132 Y. Hotta, H. Sato, A. Hosoda and H. Tamura, FEMSMicrobiol. Lett., 2012, 330, 23–29.

133 R. Dieckmann, I. Graeber, I. Kaesler, U. Szewzyk andH. von Dohren, Appl. Microbiol. Biotechnol., 2005, 67,539–548.

134 J. Koubek, O. Uhlik, K. Jecna, P. Junkova, J. Vrkoslavova,J. Lipov, V. Kurzawova, T. Macek and M. Mackova, Int.Biodeterior. Biodegrad., 2012, 69, 82–86.

135 P. A. Demirev and C. Fenselau, J. Mass Spectrom., 2008, 43,1441–1457.

136 E. Seibold, T. Maier, M. Kostrzewa, E. Zeman andW. Splettstoesser, J. Clin. Microbiol., 2010, 48, 1061–1069.

137 C. Marinach-Patrice, A. Lethuillier, A. Marly, J. Y. Brossas,J. Gene, F. Symoens, A. Datry, J. Guarro, D. Mazier andC. Hennequin, Clin. Microbiol. Infect., 2009, 15, 634–642.

138 T. Y. Li, B. H. Liu and Y. C. Chen, Rapid Commun. MassSpectrom., 2000, 14, 2393–2400.

139 A. Pinto, C. Halliday, M. Zahra, S. van Hal, T. Olma,K. Maszewska, J. R. Iredell, W. Meyer and S. C. Chen, PLoSOne, 2011, 6, e25712.

140 J. Kemptner, M. Marchetti-Deschmann, R. Mach, I.S. Druzhinina, C. P. Kubicek and G. Allmaier, RapidCommun. Mass Spectrom., 2009, 23, 877–884.

141 M. A. Pfaller and D. J. Diekema, Crit. Rev. Microbiol., 2010,36, 1–53.

142 B. J. Park, K. A. Wannemuehler, B. J. Marston,N. Govender, P. G. Pappas and T. M. Chiller, AIDS,2009, 23, 525–530.

143 B. Posteraro, A. Vella, M. Cogliati, E. De Carolis, A.R. Florio, P. Posteraro, M. Sanguinetti and A.M. Tortorano, J. Clin. Microbiol., 2012, 50, 2472–2476.

144 L. R. McTaggart, E. Lei, S. E. Richardson, L. Hoang,A. Fothergill and S. X. Zhang, J. Clin. Microbiol., 2011, 49,3050–3053.

145 J. P. Quinn, Clin. Infect. Dis., 1998, 27, S117–124.146 A. R. Hauser, M. Jain, M. Bar-Meir and S. A. McColley,

Clin. Microbiol. Rev., 2011, 24, 29–70.147 D. L. Kiska, A. Kerr, M. C. Jones, J. A. Caracciolo,

B. Eskridge, M. Jordan, S. Miller, D. Hughes, N. Kingand P. H. Gilligan, J. Clin. Microbiol., 1996, 34, 886–891.

148 J. D. McMenamin, T. M. Zaccone, T. Coenye,P. Vandamme and J. J. LiPuma, Chest, 2000, 117,1661–1665.

This journal is � The Royal Society of Chemistry 2013 RSC Adv., 2013, 3, 994–1008 | 1007

RSC Advances Review

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online

Page 15: RSC Advances - USPposvnp.org/artigos-cientificos/2013/Braga_PAC.pdf · amounts of material. For PCR analysis, nucleic acids must be extracted, and several protocols using specific

149 A. Mellmann, J. Cloud, T. Maier, U. Keckevoet,I. Ramminger, P. Iwen, J. Dunn, G. Hall, D. Wilson,P. Lasala, M. Kostrzewa and D. Harmsen, J. Clin.Microbiol., 2008, 46, 1946–1954.

150 A. Mellmann, F. Bimet, C. Bizet, A. D. Borovskaya, R.R. Drake, U. Eigner, A. M. Fahr, Y. He, E. N. Ilina,M. Kostrzewa, T. Maier, L. Mancinelli, W. Moussaoui,G. Prevost, L. Putignani, C. L. Seachord, Y. W. Tang andD. Harmsen, J. Clin. Microbiol., 2009, 47, 3732–3734.

151 J. J. Lipuma, Clin. Microbiol. Rev., 2010, 23, 299–323.152 A. Fernandez-Olmos, M. Garcia-Castillo, M. I. Morosini,

A. Lamas, L. Maiz and R. Canton, J. Cystic Fibrosis, 2012,11, 59–62.

153 S. Schubert, K. Weinert, C. Wagner, B. Gunzl, A. Wieser,T. Maier and M. Kostrzewa, J. Mol. Diagn., 2011, 13,701–706.

154 J. Kok, L. C. Thomas, T. Olma, S. C. Chen and J. R. Iredell,PLoS One, 2011, 6, e23285.

155 G. Prod’hom, A. Bizzini, C. Durussel, J. Bille and G. Greub,J. Clin. Microbiol., 2010, 48, 1481–1483.

156 J. R. Barreiro, P. A. Braga, C. R. Ferreira, M. Kostrzewa,T. Maier, B. Wegemann, V. Boettcher, M. N. Eberlin andM. V. Dos Santos, Proteomics, 2012, 12, 2739–2745.

157 C. Viguier, S. Arora, N. Gilmartin, K. Welbeck andR. O’Kennedy, Trends Biotechnol., 2009, 27, 486–493.

158 K. Poole, J Mol. Microbiol. Biotechnol., 2001, 3, 255–264.159 P. A. Lambert, Adv. Drug Delivery Rev., 2005, 57,

1471–1485.160 G. D. Wright, Adv. Drug Delivery Rev., 2005, 57, 1451–1470.161 M. Muroi, K. Shima, M. Igarashi, Y. Nakagawa and

K. Tanamoto, Biol. Pharm. Bull., 2012, 35, 1841–1845.162 A. L. Koch, Crit. Rev. Microbiol., 2000, 26, 205–220.163 G. Bou, Methods Mol. Biol., 2007, 391, 29–49.164 K. Sparbier, S. Schubert, U. Weller, C. Boogen and

M. Kostrzewa, J. Clin. Microbiol., 2012, 50, 927–937.165 C. Marinach, A. Alanio, M. Palous, S. Kwasek, A. Fekkar, J.

Y. Brossas, S. Brun, G. Snounou, C. Hennequin,D. Sanglard, A. Datry, J. L. Golmard and D. Mazier,Proteomics, 2009, 9, 4627–4631.

166 M. Trevino, D. Navarro, G. Barbeito, C. Garcia-Riestra,C. Crespo and B. J. Regueiro, Microb. Drug Resist., 2011,17, 433–442.

167 V. Edwards-Jones, M. A. Claydon, D. J. Evason, J. Walker,A. J. Fox and D. B. Gordon, J. Med. Microbiol., 2000, 49,295–300.

168 L. G. Harris, K. El-Bouri, S. Johnston, E. Rees,L. Frommelt, N. Siemssen, M. Christner, A. P. Davies,H. Rohde and D. Mack, Int. J. Artif. Organs, 2010, 33,568–574.

169 A. Beceiro, E. Llobet, J. Aranda, J. A. Bengoechea,M. Doumith, M. Hornsey, H. Dhanji, H. Chart, G. Bou,D. M. Livermore and N. Woodford, Antimicrob. AgentsChemother., 2011, 55, 3370–3379.

170 E. Nagy, S. Becker, J. Soki, E. Urban and M. Kostrzewa, J.Med. Microbiol., 2011, 60, 1584–1590.

171 I. Wybo, A. De Bel, O. Soetens, F. Echahidi,K. Vandoorslaer, M. Van Cauwenbergh and D. Pierard,J. Clin. Microbiol., 2011, 49, 1961–1964.

172 H. Grundmann, D. M. Livermore, C. G. Giske, R. Canton,G. M. Rossol ini , J . Campos, A. Vatopoulos,M. Gniadkowski, A. Toth, Y. Pfeifer, V. Jarlier andY. Carmeli, Euro Surveill, 2010, 15.

173 I. Burckhardt and S. Zimmermann, J. Clin. Microbiol.,2011, 49, 3321–3324.

174 J. R. Barreiro, C. R. Ferreira, G. B. Sanvido, M. Kostrzewa,T. Maier, B. Wegemann, V. Bottcher, M. N. Eberlin and M.V. dos Santos, J. Dairy Sci., 2010, 93, 5661–5667.

175 W. Moussaoui, B. Jaulhac, A. M. Hoffmann, B. Ludes,M. Kostrzewa, P. Riegel and G. Prevost, Clin. Microbiol.Infect., 2010, 16, 1631–1638.

176 M. Christner, H. Rohde, M. Wolters, I. Sobottka,K. Wegscheider and M. Aepfelbacher, J. Clin. Microbiol.,2010, 48, 1584–1591.

177 M. Hecker, D. Becher, S. Fuchs and S. Engelmann, Int. J.Med. Microbiol., 2010, 300, 76–87.

178 D. Becher, K. Buttner, M. Moche, B. Hessling andM. Hecker, Proteomics, 2011, 11, 2971–2980.

179 A. Otto, J. Bernhardt, M. Hecker and D. Becher, Curr.Opin. Microbiol., 2012, 15, 364–372.

1008 | RSC Adv., 2013, 3, 994–1008 This journal is � The Royal Society of Chemistry 2013

Review RSC Advances

Publ

ishe

d on

24

Oct

ober

201

2. D

ownl

oade

d by

UN

IVE

RSI

DA

D S

AO

PA

UL

O o

n 30

/04/

2014

19:

16:5

3.

View Article Online