New 3-Xa Vi Khuan Bang MS

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ESI; hence,we can consider nucleic acid as a measurable biomarker[23].

Over 50% of the cell dry weight consists of proteins [24]. Thislarge abundance is very attractive, because it allowsgood detectionsensitivity. Proteins represent the phenotype of the organism andin spite of their high diversity there areseveral thousand differentproteins in a cell they are the most often used and most success-ful biomarkers for bacteria identification,especiallyin combinationwith MALDI mass spectrometry.

Lipids constitute approximately 50% of the weight of cellularmembranes and 510% of the prokaryotic cell dry weight, butit means the highest number of molecules per cell [25]. Lipidbiomarkers were extensively investigated by pyrolysis-GC/MS andFAB in the early days of mass spectrometry bacteria identification.Py-GC/MS helped to introduce the MIDI system for the bacteriaidentification which is still provided by MIDI Inc. [26]. This systemis based on the analysis of the fatty acid methyl esters (FAMEs) bygas chromatography. The chromatographic profiles are then com-pared with the library. However, there is no MSin routine analysis,since flame ionization detector is used.

Lipids were of interest for soft ionization techniques as well;nevertheless, their analysis is not as widespread as protein pro-filing. The main complication is the lipids dependency on growthconditions. In spite of this, several studies using DESI have recentlybeen published, which indicates the possible renaissance of lipidprofiling.

Several approaches using lipopolysaccharides or Lipid Ahave been considered as alternative methods of identification.Lipopolysaccharides (LPS) and lipooligosaccharides (LOS) are com-ponentsoftheG bacteriaoutercellmembraneandareresponsiblefor the antigenic properties of bacterial cells. LPS consists of LipidA, which is considered to be the most conserved part (althoughvariations between or within genera may be observed), andoligosaccharidic core and O-antigen, which constitute converselythemostvariablepartandthusmaybeusedasaspecificbiomarker.Some experiments with LOS and LPS were performed using MALDIand ESI ionization; however, the results were not entirely convinc-

ing [27,28].The diversity of bacteria offers various metabolism pathways

that can be used for identification. This approach is more tar-geted than protein profiling. Techniques like GC/MS [29], SIFT(selected ion flying tube) [20] and DESI [19] are applied with vary-ing degrees of success. The requirement of measurability is crucialin this field, because the concentration of the analytes could bevery low and, unlike nucleic acid, there is no possibility to amplifythem.

3. GC/MS

3.1. Pyrolysis GCMS

It was GC/MS which was the early pioneer of bacteria identifi-cation by mass spectrometry. Many studies have been performedusing pyrolysis-MS and pyrolysis-GCMS (Py-GCMS), in whichwhole intact bacteria were analyzed [37]. Currently, there arenew techniques like SPME-GCMS analysis of bacterial cultureheadspace, but Py-GCMS still maintains its position. Since thefirst experiments in the 1970s, Py-MS has changed slightly. The70eV electron ionization (EI) was changed to low energy EI orreplaced by soft ionization (chemical ionization CI, metastableatom bombardment MAB), and thus, despite the dominance ofMALDI,Py-MS still finds applications even in the third millennium.

Classic electron ionization was used in the study by Miketovaet al. [7], where G+ and G bacteria were separated based on their

peak patterns. Six Gram positive species (Bacillus cereus, Bacillus

subtilis, Enterococcus faecalis, Staphylococcus epidermidis, Strepto-coccus pyogenes, Bacillus anthracis) and the same number of Gramnegative species (Enterobacter aerogenes, Proteus mirabilis, Pseu-domonas aeruginosa, Serratia marcescens, Brucella neotomae andFrancisella tularensis) were measured and the biological origins ofproduct ions were identified. Carbohydrate products were specificfor G+ bacteria, while lipid biomarkers dominated in the spectraof G bacteria. More specific data were presented by Dworzan-ski et al. [30]. They found 2-pyridinecarboxamide as the dominantcomponentinthespectraofG+ bacteria,whileG spectracontainedsignals for compounds derived from LPS.

Various other biomarkers have been found useful for pyrolysis.The flash Py-GCMS method for the detection of bacterio-hopanepolyols (BHPs) producing bacteria has been developed bySugden et al. [31]: fragment ions were found to originate fromC18:1 and C19:1 fatty acids and protein biomarkers (fragments oftryptophan) were identified in Brucella neotomae [32,33]; Wilkeset al. performed the phenotypic characterization ofSalmonellaenterica [34] and Vibrio isolates [35] using Py-MAB-MS; Goodacreet al. [36] found the pyridine ketonium ion specifically in pyrolysisspectra ofBacillus spores. It is assumed that pyridine ketonium isa thermal degradation product of dipicolinic acid (DPA), the sporespecific biomarker, as was proved by White et al. [37] two yearslater (see above).Beverly et al. [38] used in situ methylation of DPAfor detection ofBacillus anthracis spores.

3.2. SPME-GCMS

Solid phase micro-extraction (SPME) in combination withGC/MS isvery popular.It enables theextractionof analytes from liq-uid or gas matrices and thus has a wide field of application. Fromthe microbiological point of view, the analysis of volatile organiccompounds (VOCs) is the most important ability of SPME. It canbe used for the analysis of breath [29,39] or bacterial suspensionheadspace [39,40], for the detection of microbial growth in food[41], or in environmental research [42].

A set of various VOCs was analyzed in the breath of patientsinfected by Helicobacter pylori [29]. Although the obtained dataindicated that isobutane, 2-butanone and ethyl acetate in breathmightserveassignsofinfection,statisticalanalysisshowedthattheresultswerenotsounambiguous.Betterresultshavebeenobtainedfor 2-aminoacetophenone (2-AA) as a potential breath biomarkerofPseudomonasaeruginosa inthelungsofpatientswithcysticfibro-sis [39]. In that study, the concentration of 2-AA was increased inthe culture headspace after 24h of growth as well as in the breathof patients with the P. aeruginosa infection, while non-infectedpatients had a significantly lower level of 2-AA. Twenty-eight newvolatile compounds ofP. aeruginosa were identified using SPMEcoupled with two-dimensional GCMS in recent work by Beanet al. [40]. Preti et al. [43] have observed several characteristic

compounds in the culture headspace for six bacteria commonlyassociated with sinusitis.Theanalysisoffattyacidmethylesters(FAMEs)profilesofbacte-

ria by SPME-GCMS has been conducted by Lu and Harrington[44]. The cells ofEnterococcus faecalis, P. aeruginosa, E. coli, S. enter-ica, Vibrio parahaemolyticus and Listeria innocua were mixed withtetramethylammonium hydroxide methanolic solution, generatedFAMEs were extracted by SPME, and the fatty acid compositionwas analyzed. Gram positive bacteria were well separated fromGram negative ones using PCA and the results were in good agree-ment with previous works by Basile [6] and Dworzanski et al. [30].Despite the fact that Lu and Harrington were even able to iden-tify bacteria, they achieved only a classification accuracy of 87%within these six species, which is still below the profiling accuracyfor proteins.
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4. MALDI MS

4.1. MALDI-based sequencing of DNA

One of the first to use MALDI MS for the detection of DNA wasG.B. Hurst in 1996 [23]. In his study, 108- and 168-base PCR prod-ucts from Legionella were detected in negative ion mode using3-hydroxypicolinic acid as a matrix. The same methodwasused forthe detection ofMethylosinus andMethylomicrobiumspecific genestwo years later [45].

DNA measurement by MALDI is significantly limited. Double-stranded nucleic acid is not usually detected due to the acidicnature of matrices. The protonation of bases disables Watson-Crick pairing; hence, double-strand nucleic acid denatures andtwosingle-stranded nucleic acids are detected [46]. Other problemsarise due to fragmentation [47] or salt formation of the phosphatebackbone.

For this reason, DNA is transcribed to the RNA form. The RNAmoleculeismorestableduringMALDIionization [48], whichisusedfor the MALDI-resequencing method (MALDI-RE)[49]. This methodis based on the PCR amplification of several housekeeping genes orvariable-tandem repeats (VNTRs). Amplicons are then transcribedin vitro and the resulting RNA is cleaved by specific RNAses. TheRNA fragments are desalted and the mass spectrum is measured inlinear mode in the mass range up to 10,000m/z. Final spectra arecompared to the in-silico sequence digest via a pattern matchingalgorithm to identify studied species. The concordance observedbetweentheMALDI-basedresequencingmethodandclassicSangerMLST sequencing exceeds 98% [49].

In 2002, von Wintzingerode et al. developed a rapid methodfor 16S ribosomal RNA mass spectrometry typing [50]. The ampli-con of 16S rDNA was used as a template for another PCR withbiotinylated primers and dUTP instead of dTTP. The PCR productswere then isolated by streptavidin-coated paramagnetic beads andabasic sites were generated using uracil-DNA-glycosylase. After

denaturation, the phosphate backbone was cleaved and the finalmix of rDNA fragments was obtained. These fragments consistedof C, G and A nucleotides and were cleaved in the place where theT (U) nucleotide is normally present. Different strains ofBordetella,Alcaligenes andAchromobacterwere used as a model of the closelyrelated microorganisms and their identification was successfullyperformed. Single base pair mutation can also be detected in thestudied gene sequence. Mutation can create a new specific site forcleavage, or, vice versa, the cleavage site may become lost becauseof the shift in the reading frame. Hence, changes in the molecularweight of the RNA fragments can be observed.

The MassARRAYsystem by Sequenom Inc. is currentlyavailable,although,not foruse in diagnostics.This systemwithiSEQ softwareenables microbes, viruses and other organisms to be identified viathe transcription of targeted DNA and base-specific RNA cleavage(Fig. 1). The main advantage of this method is that any genomicregion may be chosen for amplification.

In contrast to classic 16S rDNA sequencing, the cost is the mainbenefitofaMALDI-basedprocedure [51]. Thepossibilityofautoma-tion andstandardization, a 384-well formatallowing96 samples tobe identified at one stroke, the small amount of microbial culturerequired, and even the identification of mixed samples are otherbenefits of this method. On the other hand, two whole workingdays are required to achieve results.

4.2. MALDI MS protein profiling

MALDI analysis of proteins is without doubt the most widelyused MS technique for bacteria identification. The differentiationof bacteria using protein profiling was introduced in 1994 by Cainet al. [52], who measured the mass spectra of bacterial cell lysates.The principle underlying this study has been confirmed by Hollandet al. [14] and Krishnamurthy et al. [15]. They have independentlyproven that protein profiles can be obtained not only from crudelysates but also from whole cells, the obtained spectra allowing

Fig. 1. The SEQUENOM MassARRAY iSEQ workflow.






reliable bacteria identification up to species level. Indeed, today,MALDI-TOF MS analysis of whole intact cells is a well-establishedmethod even in clinical microbiology laboratories [53]. Veterinaryscience [54], food and water quality monitoring [5557], and ecol-ogy [58,59] are some of the other fields in which this method hasbeen successfully applied.

The signals detected for intact cell measurement are mostly ofribosomal-protein origin [60]. The bacterial ribosome consists ofthreespecies ofRNA and52 species ofproteincomposing more than20% of total cell protein; that is, almost half of the mass of a grow-ing cell is composed of ribosomes [61]. Ryzhov and Fenselau [60]focused on 42 signals obtained in spectra from the Escherichia coliwhole cell. Twenty five of these signals were assigned as potentialribosomal proteins by comparison of the measured m/zwith theSwissprot/TrEMBL database.Moreover, ribosomalproteinsare verybasic (approx. pI= 10.5). It is well known that protonation of basicproteins is preferred during the MALDI ionization process [62].Other proteins found by comparison with the database were cold-shock proteins, DNA-binding proteins, and majorouter-membranelipoprotein precursor [62].

Spectra obtained from whole cells are reproducible underdefined growth conditions. Hence, creating a database and com-paring unknown samples with the database via a pattern matchingalgorithm is possible. The benefits of this approach include itsfast analysis times, low cost requirements, ease of use, and high-throughput. A further advantage is the possibility of automation.The cost of one sample analysis by MALDI MS is approximately1020 times cheaper than analysis by conventional automatedplatforms [63,64].

Currently, three identification databases are available: BrukerBioTyper, SARAMIS mainly provided by bioMrieux, and Andromasby Andromas SAS.

The most recent version of the Bruker Biotyper MSP databasecontains more than 4500 unique species. Analysis is usually per-formed on the benchtop Bruker MicroFlex (MALDI-TOF) massspectrometer and is based on the frequencies of species spe-cific peaks present in standard mass spectra compared to the

unknown sample. Calculation of the identification score requiresfour values: number of matches divided by number of peaksin unknown spectrum, number of matches divided by numberof peaks in reference spectrum, peak weight ranging from 0to 100 representing species specificity and the correlation fac-tor of the matching peaks intensity. Maximally seventy mostintensive peaks are taken into account in the standard identi-fication method. The obtained score is then converted into logscore, thus the highest score 1000 is represented by log score 3[64].

The SARAMIS database originally developed by AnagnosTecGmbHis availablein twoversions.The first version iscoupledwithaShimadzu Axima mass spectrometer and is provided by Shimadzuas a single product. The second re-developed and larger version

is also coupled with a Shimadzu Axima; however, it is providedby bioMrieux as the VITEK MS system. About 3000 microorgan-isms are included. Identification score is in linear scale. Each peakin the reference spectra is weighted from 0 to 40 points in accor-dance to species specificity andscore is calculated as the sumof thematching m/zvalues. Score is then expressed in percentile where99.9% represents the sum value of 999 or higher [65]. Andromaswas developed by Andromas SAS and contains approximately 700bacteria strains.

These systems are comparable with respect to the precisionof identification and all of them have been successfully con-fronted with classic biochemical tests and 16S RNA sequencing[63,64,6669]. Nevertheless, it should be noted that the size andprecision of the default database plays a significant role in reliable

identification.

Cherkaouiet al. [64] tested720 isolates of microorganisms orig-inating from human infections on the Bruker and Shimadzu MSsystems and compared the results to biochemical tests and 16SRNA sequencing. The Bruker MS system provided high-confidenceidentification for 680 out of the 720 isolates (94.4%), while the Shi-madzu system identified 639 isolates (88.8%). The high-confidenceidentification mean scores were1.7 for the Bruker MS and 70%for the Shimadzu MS system. Only 0.9% of the isolates were identi-fiedincorrectlyby theBruker MSsystemand 0.5% by theShimadzu.In a study by Martiny et al. [69], 986 out of 1003 routine isolateswere identified to species level using the three above-mentioneddatabases. These isolates originated from respiratory tract infec-tions, skin and soft tissue infections, urinary tract infections, bloodcultures, genital tractinfections, epidemiologicalsamples, and nor-mally sterile body fluids. The accuracy of the identification was92.7%, 93.2%, and 83.8% for the BioTyper, Vitek MS, and Shimadzusystems, respectively. Seventy-three isolates of anaerobes werealso tested in this work, resulting in an accuracy of identificationof 61.6% for the Biotyper and 75.3% for the Vitek MS. More resultsfrom comparative studies are shown in Table 1.

Worseresultsandobtainedspectraoflowqualitywerereportedfor Gram-positive bacteria [64,67,70,71]. The cell wall of Gram-positive bacteria is composed of thick peptidoglycan. It is assumedthat the disruption of the cell wall during the laser ablation andionization process is hindered by the multi-layer nature of peptid-oglycan. Therefore, MALDI is unable to ionize a sufficient numberof proteins. Different protocols have been evolved to help withcell wall disruption and protein extraction. Nevertheless, thereare no standardized guidelines for sample preparation. A protocoldesigned by Smole et al. [70] proposes enzymatic disruption; vanVeen et al. [53] used two-step extraction by 70% ethanol and 70%formic acid; Ferroni et al. [72] extracted proteins by detergent andtrifluoroacetic acid; La Scola and Raoult [73] presented two differ-ent protocols, in which both acetonitrile andtrifluoracetic acid wasused.

Application possibilities of MALDI are even greater. SerovarTyphi ofSalmonella enterica is distinguishable from other serovars

as reported by Kuhns et al. [74]. Serovars of Salmonella couldnot be distinguished using common intact cell experiments withthe Bruker BioTyper database; however, several serovar-specificbiomarkerionscanbeobservedinspectra,whichallowthediscrim-ination ofSalmonella Typhi from other serovars. The identificationof spores is also possible, although spectra are not so rich in sig-nals and, more often, MALDI is used to identify fungal rather thanbacterial spores. In contrast to bacterial cells, the accessibility ofspore biomarkers for MALDI is considerably lower due to sporerigidity. Analysis requires the extraction of biomarkers by an ace-tonitrile/water/trifluoracetic acid solution; sonication or coronaplasma discharge can also increase extraction efficiency [75]. Theextractedsporeproteinsbelong to familyof small acid-solublepro-teins [75,76]. The spores ofBacillus sp. are frequently examined

[75,7779]. Elhanany et al. [79] found four specific signals in spec-traofBacillusanthracissporeextract;Dickinson et al.[77] identifiedunique peaks in spores ofBacillus pumilus.

The standard intact cell method requires the culturing of bacte-ria to obtain a pure colony; however, the most recent protocolsenable direct analysis from infected liquid samples such as blood[90,96,97] ormilk [54]. In 2010,Stevenson et al.[97] introducedthefirst protocol forthe directanalysisof blood,in which bacteria wereseparated from red blood cells and plasma proteins by several cen-trifugation steps.The pelleted bacteria were lysed,and theproteinswere extracted by 70% ethanol and 70% formic acid and analyzedby BioTyper database. Of the 212 samples, 42 (19.8%) had a spec-tral score of






Table 1

Identification rates of thecommercially available mass spectrometry systems. Collection of data from recentworks.

Mass spectromery identifi cation system Identification rate [%]a at No. of samples Microorganisms Ref.

Species level Genus level

MALDI Biotyper 92.7 95.5 986 routine isolates [69]MALDI VITEK MS 93.2 93.6MALDI Saramis 83.8 86.9MALDI Biotyper 61.6 83.5 73 anaerobes [69]MALDI VITEK MS 75.3 78.0MALDI Saramis 9.6 9.6MALDI Biotyper 100 100 132 streptococci [80]MALDI Vitek MS 100 100MALDI Biotyper 67.2 67.2 290 anaerobes [67]MALDI Saramis 49.0 60.7MALDI Biotyper 72.5 97.0 200 non-fermenting G bacteria [66]MALDI VITEK MS 80.0 93.0MALDI Biotyper 83.4 94.9 296 routine isolates [81]MALDI Saramis 65.9 83.8MALDI Biotyper 51.0 61.0 79 anaerobes [82]MALDI Saramis 61.0 71.0MALDI Biotyper 62.8 93.2 148 lactobacilli [83]MALDI Biotyper 46.0 74.0 46 streptococci [84]MALDI Biotyper 82.0 93.0 440 G routine isolates [85]MALDI Biotyper 84.5 96.4 2781 routine isolates [86]MALDI Biotyper 79.0 152 anaerobes [87]MALDI Biotyper 94.3 96.9 273 blood culture isolates [88]

MALDI Sepsityper 93.8 93.8 32 blood culture isolates [89]MALDI Sepsityper 83.0 98.1 53 G+ cocci [89]MALDI Sepsityper 46.3 68.4 285 G+ blood culture isolates [90]MALDI Sepsityper 79.7 87.2 187 G blood culture isolates [90]MALDI Sepsityper 68.4 78.0 59 blood culture isolates [91]MALDI Andromas 91.4 93.8 162 blood culture isolates [92]MALDI Andromas 93.1 n.a. 2665 routine isolates [92]MALDI Andromas 90.7 99.7 659 G+ bacilli [68]MALDI Saramis 98.0 n.a. 1019 routine isolates [93]MALDI Vitek MS 86.7 94.9 767 routine isolates [94]MALDI-resequencing n.a. 97.7 147 Staphylococcus aureus [51]PCR-ESI-MS 95.2 96.5 273 blood culture isolates [88]PCR-ESI-MS 100 n.a. 317 Staphylococcus aureus [95]

n.a. notavailable.a The ratio of correctly indentified species (genera) to the total number of bacterial species (genera) tested.

procedure was commercialized by Bruker as the SepsiTyper Kit.According to the work of Stevenson et al. [97], an average successrate of 80% is stated in the official product information material,which agreed with recent evaluation studies [90,91,98]. The ten-times higher cost is the serious drawback of the Sepsityper kit incomparison with in-house methodpresented by Martiny et al.[91].

Besides blood, the Sepsityper kit was also used for the testingof milk samples [54].Juliana Barreiro et al. inoculated pasteurizedand homogenized samples of whole milk with 103108 colony-forming units (CFU) ofEscherichia coli, Enterococcus faecalis andStaphylococcus aureus per ml. Samples were processed by Sepsi-typer with a protocol adjusted to the milk matrix and analyzed bythe Bruker BioTyper database. The detection limit forE. faecalisandS. aureuswas106 CFUperml; thedetectionofE. coli required a level

of 107

CFU per ml.

4.3. MALDIMS identification based on lipid and

lipopolysaccharide analysis

The analysis of lipids is the major domain of methods suchas GC/MS or pyrolysis-mass spectrometry. However, the time-consuming sample pre-treatment (hydrolysis, derivatization) andcomplicated data interpretation involved in pyrolysis-GC/MSdecrease the speed of these methods; hence, soft ionization tech-niques have become alternative tools for lipid characterization.Different phospholipids can be ionized by MALDI. While phos-phatidylcholines, sphingomyelins, and some sterols are detectablein positive ion mode, signals for phosphatidylinositols, phos-

phatidylserines and sulfates are visible in negative ion mode, and

those for phosphatidylethanolamines are visible in both. Unfortu-nately, the ionization is hindered by strong suppression effects,especially in positive ion mode, and is highly dependent on thepolar head of the molecule.

The first experiments with bacterial lipid analysis were per-formedby Helleret al. [99] in 1987,who measured laser desorptionmass spectra of polar lipids in the presence of KCl. They obtainedlipid mass fingerprints ofE. coli and Bacillus subtilis. In 1998, Hoand Fenselau [100] used an infra-red laser with a wavelength of1.06m and a bacterial suspension mixed with a liquid matrixconsisting of a cobalt or graphite particles/glycerol mixture. Peaksobserved in the spectra of the intact cells corresponded to phos-phoethanolamines (PE), phosphatidylglycerols (PG) and respectivepotassiated adduct ions. Two Gram-negative (Erwinia herbicola

and Escherichia coli) and two Gram-positive bacteria (Bacillusthuringiensis and Bacillus sphaericus) were analyzed and distin-guished on the basis of lipid spectra. Ishida et al. [101] introducedUV MALDI using spotted individual bacterial colonies on a MALDIplate as a sample. Prior to matrix deposition, 3l of NaI solutionwas added to each spot to increase the signals from lipids. Simi-larly to the work of Ho and Fenselau, phosphoethanolamines andphosphoglycerols were detected. Ishida was able to differentiateKlebsiella, Shigella, Escherichia and Salmonella species on the basisof themasses andrelative intensities of 15 specific peaks.However,intensity is not the ideal parameter, due to problems with MALDIrepeatability.Shu et al. [102] introducedMALDI lipidfingerprintinginto bioaerosol-MALDI mass spectrometry (BAMS). They analyzedlipid profiles from Bacillus, Escherichia and Salmonella whole cell

extracts and were also able to differentiate the measured species.






Lipids such as diglycosyldiacylglycerol (DGDG), PE, and PG wereobserved in the mass spectra. More information about bioaerosol-MALDI analysis is presented later.

While the above-mentioned studies were conducted in posi-tive ion mode, Calvano et al. [103] introduced a lipid fingerprintingmethod in negative ion mode for the identification of lactobacilli.Using 1,8-bis(dimethylamino)naphthalene (DMAN), different lipidspecies weredetected, mainly phosphatidylglycerols andcardiolip-ins. Diglycosyldiacyglycerols and triglycosyldiacylglycerols werealsoobservedwithinthemassrangeofm/z2002000. The presenceof specific signals enabled Lactobacillus plantarumand Lactobacillussanfranciscensis to be differentiated.

Several studies have been devoted to LPS and LOS analysisin both MALDI and ESI MS [27,28,104]. Gibson et al. studied O-deacylated LOS ofSalmonella typhimurium, Haemophilus influenzaeand Haemophylus ducreyi by MALDI post-source decay (PSD) massspectrometry in positive and negative mode and demonstrated theusefulness of PSD in LOS structure investigation. In-source decayalso takes place and the resulting fragments increase the com-plexity and unpredictability of the spectra; thus, no identificationmethod based on LPS or LOS mass spectrometry analysis has yetbeen developed.

5. ESI MS

5.1. PCR/ESI-MS

Electrospray ionization is considered as one of the softest ion-ization techniques. The ESI process provides much lower samplefragmentation;thus,accuratespectracanbeobtainedwiththehighresolution of complementary strands up to a length of 500 bp. ESI,however, requires a very clean sample; this means that purificationof the PCR by precipitation, microdialysis, or ion exchange resin isneeded [105].

The history of nucleic acid measurements on an ESI massspectrometerissimilartothatofMALDI.Thefirststudieswerepub-

lished by Muddiman et al. [106] and Wunschel et al. [107] in 1996.In both cases, PCR products ofBacillus cereus and Bacillus subtilisrRNA fragments were detected in negative ion mode.

Recent protocolsare mostlybasedon MLST analysis.PCR ampli-cons of the chosen genes are analyzed by ESI mass spectrometry,and the base composition is determined using the exact mass ofthe monoisotopic peak [95,108]. The commercial fully-automatedPLEX-ID system developed by Abbott Molecular provides resultswithin 46h. This system combines broad-range PCR with mul-tiple primers, ESI-MS, and computerized triangulation to identifythe organism in the sample. More than one organism can bedetermined in complex samples such as sputum. Various humanpathogens were successfully identified, including Haemophilusinfluenzae [109], Neisseria meningitides [109], Streptococcus pyo-

genes [109], methicillin-resistant Staphylococcus aureus (MRSA)[95,110], Vibrio [111], Klebsiella [112], Esherichia [113], Salmonella[113], Shigella [113],Acinetobacter[112,114], Ehrlichia [115] etc.

In the comparative study by Kaleta et al. [88], the PCR-ESI-MS method was compared with the MALDI-TOF BioTyper. Bothmethods achieved a similar accuracy of microorganism identifica-tion from positive blood broths. PCR-ESI-MS achieved an accuracyof identification of 96.7% (n=273) at the genus level and 95.6%at the species level, while Bruker MALDI-ToF with BioTyper 2.0achieved respective scores of 97.1% and 94.9%. The genetic basis ofPCR makes the combination of PCR/ESI-MS advantageous, becauseit additionally allows access to information about resistance toantibiotics. This method even enables uncultivable microorgan-isms in the sample to be detected and identified. On the other

hand, the consumables cost per sample is a strong argument in

favor of MALDI-TOF.PCR/ESI-MSrequires DNA extraction, primers,enzymes and purification, resulting in an overall cost of between$50 and $100 per sample, while consumables for MALDI includeonly media for bacteria growth, the matrix, and the calibrationstandard, with an overall cost of $3 to $7 per sample. The utiliza-tion of SepsiTyper makes MALDI even faster; however, this rapidlyincreases the cost.

PCR/ESI-MS enables semi-quantitative analysis using the addi-tion of nucleic acid of known concentration to each PCR. Thesequence similarity of theaddednucleic acid andthe target sampleis required.The semi-quantitative analysis is based on the compar-ison of the analyte peak heights and standard ones. The additionof known nucleic acid also serves as the internal positive control[108].

Despite PLEX-ID acquiring CE certificates(EuropeanConformitymarking), obtained at the beginning of 2012,the distribution of thesystem has ceased.

5.2. ESI MS identification based on the analysis of proteins

The identification of bacteria by ESI via protein analysis is notas successful as by MALDI. Basic ESI workflow includes samplepreparation. The measurement of intact cells usually leads to nee-dle clogging, and the direct injection of crude extracts providesextremely complex spectra. A typical cell lysate consists of a largenumber of biomolecules and cellular debris, which significantlyreduce sensitivity and make reasonable analysis impossible. Theanalysis of intact cells by Goodacre et al. [11] and that of crudecell lysates described by Vaidyanathan et al.[116] offered complexspectra,inwhichlipidsignalsdominatedandrevealedthenecessityfor sample purification. Liquid chromatography[117119] or dial-ysis [10,24] are commonly used for proper cell lysate processing.

Electrospray ionization offers effective tandem mass spectrom-etry, which is the basis of the modern approach, first proposedby Demirev et al. [120]. As described by Dworzanski et al. [117],information about peptide amino acid sequences can be used forrelevant bacteria identification. This method is based on whole

bacteria proteome digestion coupled with liquid chromatographyand tandem mass spectrometry (LC-MS/MS). Obtained data arematched afterwards with the proteome database derived fromthe genomes of microorganisms. Microorganisms with a knowngenome can be identified straightforwardly while multivariate sta-tistical methods can be usedto characterize bacteriawithunknowngenome [121,122]. The classification is based on the similarity ofthe peptide-sequence of the unknown sample and known bacte-ria in established taxons. The similarity is determined by principalcomponent analysis or cluster analysis.

Selective proteotypic-peptide analysis (SPA) is a method whichenables identification of bacteria in mixed cultures. The trypticdigest of a sample protein extract is analyzed by LC-MS/MS [123]or CE-MS/MS [124] and specific peptide markers are monitored

at expected elution time windows. The peptide retention timeis calculated on the basis of their sequence. Afterwards, all tan-dem spectra are matched against a protein database to identifyproteins andtheir origin. Information about accurate mass andelu-tion time increases the confidence of peptide identification andmoreover enables the components of the bacterial mixture to bedistinguished and identified.

5.3. ESI MS identification based on lipid and LPS analysis

A large number of isobaric lipid ions required tandem MSfor further characterization. Better fragmentation efficiency favorselectrospray ionization over MALDI. In 1995, Smith et al. [5]observed different phospholipid fragmentation spectra of G+ and

G

bacteria during measurements of their lipid extracts. Several






other studies between 1996 and 2000 [125128] described thecharacterization of various bacteria; however, lipid analysis hasrecently been used for the detection of microbial presence, as itis suppressed by protein profile measurements. Zink et al. usedintact polar phospholipids as microbial life markers in marinesediments [129]; Rossel et al. [130] demonstrated that the quan-titative analysis of phospholipids discriminated between archealand bacterial biomass.

White et al. [37] developed HPLC/ESI tandem mass spectrome-try for the analysis of neutral and polar lipids, lipopolysaccharidesof Gram-negative bacteria, and 2,6-dipicolinic acid, a specific sporebiomarker. The limit of detection was 100 fg of 2,6-dipicolinic acidperl(i.e.,2.3103 sporesofB.subtilis).Thelinearityofthecalibra-tion curve was over three degrees of magnitude. Thedetection limitof the phosphatidylglycerol assay was as much as 90amoll1

using multiple reaction monitoring (MRM).Besides experiments with MALDI [27], Gibson et al. [28] have

also used electrospray ionization. In their study, the structural het-erogeneity of LOS from Haemophilus and Neisseria and LPS fromSalmonella were investigated. ESI mass spectrometry in combi-nation with capillary electrophoresis was used for the detailedinvestigation ofMoraxella and Haemophilus lipooligosaccharides[131,132]. Attention was also to the characterization of Lipid Aobtained from various bacteria, including Shigella flexneri [133],Haemophilus influenzae [134], Escherichia coli [135,136], Pseu-domonas aeruginosa [137] and Agrobacterium tumefaciens [135]. Itis worth mentioning that no commercial method for the identifica-tion of bacteria based on the MSanalysis of lipid A, LPS or LOS massspectra has yet been introduced.

6. Ambient techniques

6.1. DESI and DART MS

Desorption electrospray ionization (DESI) has been used tostudy bacterial biomarkers several times since its invention in

2004 [18]. The mechanism of DESI is ideally designed for theanalysis of intact bacteria. In 2007, Song et al. [19] measuredthe spectra of intact cells of Escherichia coli (3 strains) andSalmonella typhimurium (2 strains) in the mass range up to m/zof 1600, where lipids were chiefly identified. Species and evenindividual strains were successfully differentiated using princi-pal component analysis (PCA) of the obtained results. A fewmonths later, an extended study of seven different bacteria(Escherichia coli, Salmonella typhimurium, Bordetella bronchisep-tica, Staphylococcus aureus, Enterococcus sp., Bacillus thuringiensis,Bacillus subtilis) was performed by Meetani et al. [138]. Sig-nals detected in the low mass range (m/z 50500) enabled thefine classification of all measured bacteria by PCA. The charac-terization of Bacillus subtilis from a still growing biofilm was

demonstrated in 2009. The characterization was based on thesignals for surfactin, the antibiotic lipopeptide excreted into thegrowth medium. While previous works used biofilms or cells sus-pended in water, Zhang et al. [139] resuspended cells in 70%ethanol. Spectra obtained from 3l of this suspension contain-ing approximately 3000cfu provided signals for various lipids andlipopeptides, including PG, PE and lysophospholipids, in the massrange up to m/z of 1000. Using PCA, the authors reliably iden-tified Bacillus subtilis, Escherichia coli, Staphylococcus aureus andSalmonella. Even four different strains ofSalmonellawere well sep-arated.

A direct analysis in real time (DART) method for the rapididentification of microorganisms has been tested in a proof-of-principle study by Pierce et al. [140]. This work was focused on the

fatty acid methyl ester (FAME) composition of bacteria routinely

used for the identification of clinically important pathogens. Thearrangement of the DART mass spectrometer enables in situ ester-ification of bacterial fatty acids in the space between the ionsource exit and the inlet of the mass analyzer. FAMEs were gen-erated from the whole cell bacteria suspensions of 5 differentspecies. Signals for fatty acids from C8:1 to C24:0 were regis-tered and several species-specific fatty acids were observed, e.g.,C19:1 for E. coli, C11:1 for S. pyogenes and C15:1 for Coxiellabrunetii; however, the authors assumed that sophisticated statis-tical tools would be needed for relevant identifications. Although,the results of this study were promising, no further results haveappeared.

6.2. SIFT MS

Selected ion flow tube mass spectrometry (SIFT MS) is a tech-nique for the measurement of concentrations of trace gases andVOCs under ambient conditions. In contrast to GCMS, theSIFT tech-nique enables real-time analysis of samples such as air, breathor headspace of bacterial cultures. In 1996, Smith and Spanel[20] introduced a novel method for diagnosingHelicobacter pyloriinfection, based on the measurement of the ammonia level in

breath after an oral dose of urea. They observed a significantincrease in ammonia 2040 min after administration to a personinfected with Helicobacter against the uninfected control. Stud-ies of breath by Enderby et al. [141] and Shestivska et al. [142]suggest the levels of hydrogen cyanide (HCN) and methyl thio-cyanate as possible diagnostic markers ofPseudomonas aeruginosainfection of the lungs, which is major cause of mortality inpatients with cystic fibrosis. Other applications have also beenintroduced, e.g., lactose intolerance diagnosis; thus. it appears thatthe analysis of breath is a non-invasive diagnostic method witha bright future. Nevertheless, it is limited by the unpredictabilityof the human body, because basic levels of analytes in exhaledair are individual and may be influenced or overlaid by otherfactors.

The analysis of bacterial culture headspace is another goodopportunity for the application of SIFT. It has been proven thatvolatile metabolites can be analyzed in the headspace of liquidbacterial cultures [143,144]. Allardyce et al. took advantage of thisknowledge in identifying bacteremia from blood culture medium.They measured a set of 14 VOC levels for five bacterial strains cul-tured in blood culture bottles and they selected a list of nine VOCsfor the detection and identification of species. SIFT analysis wasable to detect bacterial growth in 24h cultures, and, in selectedion mode (SIM), even in 6h cultures. It is worth noting that theconventional blood culture method takes at least 2 days to detectbacteria. InthefollowingexperimentbyScotteretal. [145], SIFT-MSanalysis was compared with an automated blood culture system.Blood samples from healthy patients were inoculated with 5 or

100 cfu of bacteremia-causing organisms. Positive results by SIFTwere observed for 88.3% of samples after 8h of growth in bloodculture bottles, and 96.6% after 24h, while the automated systemdidnot give positive notification of growth in less than 12h, usuallyin 1424 h. Moreover, SIFT enabled bacteria species to be identi-fied. A similar approach was applied for studying microbial growthin urine [146]. Sterile urine from healthy males was infected withone of the seven bacteria strains or withCandida albicansand incu-batedfor6hat37 C. The concentrations of twenty-one VOCs weremeasured and the resulting levels confirmed some findings in pre-vious studies [147149], for example the significant production ofammonia by S. aureus [147]. Although it was not possible to fullydifferentiate between eight used species, the potential of the SIFTtechnique for rapid microbe identification in urine samples was

demonstrated.






Fig. 2. Bioaerosol mass spectrometer as presented by Fergenson et al. [150].

7. Bioaerosol mass spectrometry

Recently, several groups have attempted to identify bacteria bymass spectrometryat thelevelof singlecells. Bioaerosol mass spec-trometry (BAMS) is the result, in which particles can be drawndirectly into the mass spectrometer to be ionized, or they can becovered by a matrix and dried prior to sampling.

The first successful discrimination of species was performed byFergensonetal. [150], whowasabletodistinguishsporesofBacillusatrophaeus and Bacillus thuringiensis in various background mix-tures. The novel bioaerosol-LDI/TOF mass spectrometer was used.Dried spores were introduced into the apparatus directly from theenvironment through a nozzle and two scattering light detectors

were used for the determination of spore size and velocity. A laserpulse at 266 nm was fired to ionize analytes from the particles andboth positive and negative spectra were simultaneously collectedby two opposite direction TOF analyzers (Fig. 2).

BAMS analysis ofBacillus spores was also performed by Czer-wieniecz et al. [151], Srivastava et al. [152] and Steele et al. [153].They confirmed Fergensons results and the functionality of thedevice. Tobias et al. [154] demonstrated BAMS capacity to followmorphological and biochemical changes during the sporulationprocess ofB. atrophaeus cells. Growing signals for DPA adductswere detected in negative mass spectra, which corresponds withthe endospore formation. Other work by Tobias et al. [155] wastargeted on Mycobacterium tuberculosis airborne particles. Specificbiomarkers were found in spectra forM. tuberculosis ,M. smegmatis,

B. atrophaeus and B. cereus allowing particle identification.BAMS without a matrix allows quick real-time measurements;however, it is not possible to ionize larger molecules and biopoly-mers using this method. The above-mentioned works did notexceed m/z of 400. Hence, particles coated by a matrix may bemeasured instead. To maintain the possibility of real-time anal-ysis, Stowers et al. [21] developed a unique method for matrixdeposition in 2004. The aerosol from particles was mixed withmatrix vapors in the flow cell, then the mixture was cooled andthe matrix condensed onto the aerosol. Afterwards, matrix coatedparticles were pulled into the ion source and fired by laser pulse.A single peak at 1224Da was detected in mass spectra ofB. subtilisspores coated by the matrix and it was identified as peptidoglycan.Various matrices have also been tested. In Stowerss work, sinap-

inic acid, picolinic acid and 3-nitrobenzyl alcohol were used. In the

following study by van Wuijckhuijse et al. [156], a mass range upto 20kDa was scanned using ferulic acid as a matrix. Additionalpeaks for Bacillus spores were found, two of them assigned assmall acid soluble proteins (SASP). Besides Bacillus spores, cells ofErwinia herbicola [157] and E. coli [158] were analyzed; however,there have been no recent developments in intact cell or sporebioaerosol mass spectrometry of any significance.

8. Insights into the future

The ability of mass spectrometry to identify bacteria is anotherproof of its versatility; hence, microbiology has become anotherfield in which mass spectrometryis used.Mass spectrometryis ableto target a wide range of biomarkers through a variety of ioniza-tion techniques.Currently,proteomicprofiling is commercially themost successful method. It can be assumed that MS has the poten-tial to completely displace classic biochemical methods in clinicalwork in the near future. This process has already begun; however,not only clinical microbiology is involved. The quality control offood, air and water, environmental studies, defense against bioter-rorism are all fields where mass spectrometry has already beenapplied and will be applied on a larger scale in the future.

Despite the demise of the iSeq method, the improved analysisof DNA and RNA could provide a definite method of identification,which would also include information about antibiotic resistance.Current progress in single cell mass spectrometry enables onlysingle cells to be analyzed, which can be considered a very good

starting point for the measurement of bacteria directly from bloodwithout cultivation. Alternatively, cell enrichment could help withsample preparation. The branch of metabolomics, which began todevelop just a fewyears ago, shows great promise. Finally, SIFT andGC/MS techniques have yielded their first results and have demon-strated great potential in helping with the direct identification oflung or stomach infections.

Acknowledgements

This work was supported by Czech Science Foundation(P503/10/0664) and by specific university research (MSMT No21/2012).MatthewNichollsis greatly acknowledged forproofread-ing of the manuscript.


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