Species Differentiation of Seafood Spoilage and ... - ACS Publications

Species Differentiation of Seafood Spoilage and Pathogenic Gram-Negative Bacteria by MALDI-TOF Mass Fingerprinting Karola Bo ¨ hme,† Inmaculada C. Fernańdez-No,† Jorge Barros-Vela´zquez,† Jose´ M. Gallardo,‡ Pilar Calo-Mata,*,† and Benito Can ˜ as§ Department of Analytical Chemistry, Nutrition and Food Science, School of Veterinary Sciences, University of Santiago de Compostela, E-27002 Lugo, Spain, Department of Food Technology, Institute for Marine Research (IIM-CSIC), E-36208 Vigo, Spain, and Department of Analytical Chemistry, Faculty of Chemistry, University Complutense of Madrid, E-28040 Madrid, Spain Received January 19, 2010

Species differentiation is important for the early detection and identification of pathogenic and foodspoilage microorganisms that may be present in fish and seafood products. The main 26 species of seafood spoilage and pathogenic Gram-negative bacteria, including Aeromonas hydrophila, Acinetobacter baumanii, Pseudomonas spp., and Enterobacter spp. among others, were characterized by matrixassisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) of low molecular weight proteins extracted from intact bacterial cells by a fast procedure. From the acquired spectra, a library of specific mass spectral fingerprints was constructed. To analyze spectral fingerprints, peaks in the mass range of 2000-10 000 Da were considered and representative mass lists of 10-35 peak masses were compiled. At least one unique biomarker peak was observed for each species, and various genus-specific peaks were detected for genera Proteus, Providencia, Pseudomonas, Serratia, Shewanella, and Vibrio. Phyloproteomic relationships based on these data were compared to phylogenetic analysis based on the 16S rRNA gene, and a similar clustering was found. The method was also successfully applied for the identification of three bacterial strains isolated from seafood by comparing the spectral fingerprints with the created library of reference fingerprints. Thus, the proteomic approach demonstrated to be a competent tool for species identification. Keywords: seafood pathogens • seafood spoilage • MALDI-TOF MS • phyloproteomics • phylogenetics • bacterial differentiation • Gram negative bacteria

Introduction Seafood spoilage is caused by microorganisms, enzymes and chemical action, with bacteria being the major cause of spoilage of most aquatic food products.1 Spoilage microorganisms produce off-flavor and discoloration, resulting in large economic losses in the sectors of fisheries and aquaculture.2 In this sense, it is important to distinguish between spoilage microorganism and spoilage microflora, because not all species present in the microflora of spoiled product are a cause of the deterioration.3 Thus, spoilage microbiota includes both spoilage and nonspoilage bacteria, often making it difficult to determine the specific spoilage bacteria present. Most bacterial species that are related to food deterioration are able to form volatile metabolites like ammonia, organic acids, hypoxanthine, acetate, trimethylamine and volatile compounds of sulfur, resulting in off-flavors.4,5 Among these spoilage bacteria, there are * To whom correspondence should be addressed. Pilar Calo Mata, Dpt. Analytical Chemistry, Nutrition and Food Science, School of Veterinary Sciences, University of Santiago, Campus Universitario, E-27002 Lugo, Spain. Tel: +(34)647344274. Fax: +(34)982252195. E-mail: [email protected]. † University of Santiago de Compostela. ‡ Institute for Marine Research. § University Complutense of Madrid. 10.1021/pr100047q

 2010 American Chemical Society

species that are quite important in seafood spoilage such as Shewanella spp. and Pseudomonas spp.2 Spoilage bacteria can come from either the fish environment or from manipulation. Furthermore, some bacterial species of the family Enterobacteriaceae may play an important role in the seafood spoilage due to water pollution and contamination. The family of Enterobacteriaceae includes a variety of species that are involved in seafood spoilage, such as Proteus spp., Enterobacter spp., Providencia spp. and Serratia spp. Likewise, some species of Enterobacteriaceae, such as Morganella morganii, Enterobacter aerogenes, Hafnia alvei and Klebisella pneumoniae, are known as important histamine formers in fish products and can cause histamine poisoning.6,7 In addition, the presence of pathogenic microorganisms in products of marine origin should be considered for the potential negative consequences on food safety. In general, the indigenous microbiota of products of marine origin contains pathogenic Gram negative bacteria, such as A. hydrophila, A. baumanii, Stenotrophomonas maltophilia and Vibrio spp. Although the natural microbiota of seafood is dominated by Gram negative bacteria, pathogenic Gram positive microorganisms are often difficult to eliminate.8 Journal of Proteome Research 2010, 9, 3169–3183 3169 Published on Web 04/21/2010

research articles Traditionally, bacterial species identification has been performed by classic tools relying on bacterial culture coupled to morphological, physiological and biochemical characterization. The study of microbial spoilage has also been accomplished by the analysis of molecules such as trimethylamine (TMA), biogenous amines, hydrogen sulfide, etc. that are products of the microbial degradation of seafood.9 In the past decade, more sensitive methods of specific bacterial identification have been developed, such as genetic techniques including polymerase chain reaction (PCR), DNA hybridization, random amplification of polymorphic DNA (RAPD) analysis and restriction fragment length polymorphism (RFLP) analysis.10,11 At the same time, there have been important advances in bioinformatic tools. Recently, proteomic approaches, specifically mass spectrometry, have been introduced as a powerful tool for bacterial identification.12 More recently, important advances in the application of MALDI-TOF mass spectrometry have been developed, thus allowing it to become a rapid method for the characterization of bacteria at the genus, species and strain levels.13 Various studies have reported the differentiation of bacterial species by MALDI-TOF mass spectrometry by using the mass profile of molecular analytes with low mass weight (less than 20 000 Da) obtained from suspensions of whole bacterial cells14 in which characteristic high mass ions acquired by intact cell mass spectrometry (ICMS) were attributed to proteins.15,16 Other studies have described the optimization of sample preparation protocols to optimize both the spectral reproducibility17-22 and the evaluation of spectral data.23,24 Also, previous works have reported the detection and identification of genus- and species-specific marker analytes (biomarkers).25-27 It should be noted that most of the peaks observed by MALDI-TOF mass spectrometry of bacterial cell lysates are ribosomal proteins.28-30 In a novel bioinformaticbased approach for the identification of bacterial species, the experimentally determined masses of protein biomarkers are correlated with protein molecular weights available in public protein databases.31 In another approach, bacterial differentiation is carried out based on the elaboration of a mass spectral library of reference bacterial strains to subsequently compare and analyze an unknown spectrum.24,32,33 The main objective of this work is the development of methods that allow the early detection and identification of main pathogenic and food-spoilage microorganisms, which are present both in aquatic food products from extractive and in aquaculture facilities. The study involves the development of a mass spectra library obtained by MALDI-TOF MS, containing spectral fingerprints of pathogenic and spoilage Gram negative bacteria present in aquatic food products. This database is used to determine specific biomarkers at both the genus and species levels. In addition, a phyloproteomic analysis of the studied Gram negative bacteria was performed and compared with phylogenetic analysis based on 16S rRNA nucleotide sequences.

Materials and Methods Bacterial Strains and Culture Media. In this work, a collection of the main Gram negative pathogenic and spoilage bacteria was considered (Table 1). Reference strains were obtained from the Spanish Type Culture Collection (CECT) and reactivated in Brain-Heart-Infusion (BHI) (Becton and Dickinson, Le Pont de Claix, France). The strains Vibrio spp. and Shewanella algae were reactivated in Marine broth (Cultimed, Barcelona, Spain). The culture tubes were then incubated for 24 h at either 30 or 37 °C as required for each bacterial strain. 3170

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Bo ¨ hme et al. Table 1. Gram-Negative, Pathogenic, and Spoilage Bacterial Species Considered in This Study bacterial strain

code

GenBank

Acinetobacter baumanii ATCC 15308 Aeromonas hydrophila ATCC 7966 Enterobacter aerogenes ATCC 13048 Enterobacter cloacae ATCC 13047 Hafnia alvei ATCC 9760 Klebsiella oxytoca ATCC 13182 Raoultella planticola ATCC 33531 Klebsiella pneumoniae ATCC 10031 Morganella morganii ATCC 8076 Proteus mirabilis ATCC 14153 Proteus penneri ATCC 33519 Proteus vulgaris ATCC 9484 Pseudomonas fluorescens ATCC 13525 Pseudomonas fragi ATCC 4973 Pseudomonas syringae ATCC 19310 Providencia rettgeri ATCC 29944 Providencia stuartii ATCC 29914 Serratia liquefaciens ATCC 12926 Serratia marcescens ATCC 274 Stenotrophomonas maltophilia ATCC 13637 Shewanella algae ATCC 51192 Shewanella baltica CECT 323 Shewanella putrefaciens ATCC 8071 Vibrio alginolyticus ATCC 17749 Vibrio parahaemolyticus ATCC 17802 Vibrio vulnificus ATCC 27562

AiB11 AmH01 EbA01 EbC11 HaA02 KlOx11 KlP02 KlPn21 MoM02 PrM01 PrP11 PrV21 PsF12 PsFr51 PsS34 PvR61 PvS51 SrL71 SrM53 StM03 SwA02 SwB11 SwP21 ViA11 ViP02 ViV21

FJ971866 CP000462a FJ971882 FJ971883 FJ971884 FJ971867 FJ971885 FJ971886 FJ971868 FJ971887 FJ971869 FJ971888 FJ971870 FJ971871 FJ971872 FJ971874 FJ971875 FJ971876 FJ971877 FJ971878 FJ971879 FJ971880 FJ971881 X74690a GU460378 X74720a

a These sequences were identical to those in our study; thus, we included the reference accession number.

Table 2. Bacterial Strains Isolated from Fish and Seafood code

source

identified species by DNA and MALDI-TOF MS

2387T6 25MC6 BR03

Processed seafood Albacore tuna Sardine

Serratia marcescens Stenotrophomonas maltophilia Pseudomonas fragi

Afterward, bacterial cultures were grown on Plate-Count-Agar (PCA) (Oxoid, Hampshire, UK) with 5% NaCl (Panreac, Barcelona, Spain) at the appropriate temperature and single colonies were picked from the culture plates. Furthermore, three strains were selected from the laboratory intern collection of bacterial strains isolated from seafood in previous studies (see Table 2).34 The frozen stored strains were reactivated in BHI and later grown on PCA in the same manner as the reference strains as described before. Proteomic Analysis by MALDI-TOF MS. For proteomic analysis, bacterial strains were grown on PCA with 5% NaCl and incubated for 24 h at 30 or 37 °C as required. One loopful of each bacterial culture was harvested in a 100 µL solution of 50% acetonitrile (Merck, Darmstadt, Germany) and 1% aqueous trifluoracetic acid (TFA) (Acros Organics, NJ) and mixed by vortexing. After centrifugation, the supernatant was transferred into a new tube and stored frozen at -20 °C until analysis. A 1 µL aliquot of the sample solution was mixed with 10 µL of matrix solution containing saturated R-cyano-4-hydroxycinnamic acid (R-CHCA) (Sigma-Aldrich, Saint Louis, MO) in 50% acetonitrile and 2.5% aqueous TFA. From this final solution, including sample and matrix, a 1 µL aliquot was manually deposited onto a stainless steel plate and allowed to dry at room temperature. Mass spectra were obtained using a Voyager DE STR MALDI-TOF Mass Spectrometer (Applied Biosystems, Foster City, CA) operating in linear mode, extracting positive

Seafood Spoilage and Gram-Negative Bacteria Differentiation Ions with an accelerating voltage of 25 000 V and delay time of 350 ns. Grid voltage and guide wire were set to 95% and 0.05%, respectively. Every spectrum was the sum of accumulating at least 1000 laser shots, obtained in 10 different regions of the same sample spot, in the m/z range of 1500-15 000 Da. From each sample, two extractions were carried out and both extracts were measured in duplicate, leading to a total of four spectra for each bacterial strain. Spectra were calibrated using an external protein calibration mixture consisting of 2 pmol/µL insulin oxidized B chain and 2 pmol/µL of bovine insulin (Sigma-Aldrich). Mass spectra were analyzed with the DataExplorer software (Version 4.0.0.0), baseline corrected, and noise filtered, and data lists containing m/z values were extracted from mass spectral data, including signals with relative intensities higher than 2%. Afterward, all mass lists were analyzed and compared considering the mass interval 200010 000 Da, due to the good reproducibility of the spectral profile in that range. Then, all mass lists were further processed with the free available web-based application SPECLUST (http:// bioinfo.thep.lu.se/speclust.html).35 This web interface calculates the mass difference between two peaks taken from different peak lists and determines if the two peaks are identical after taking into account a certain measurement uncertainty (σ) and peak match score (s). The peak match score represents the probability that two peaks with measured masses m and m′ have a mass difference equal or larger than |m - m′|, given that the mass difference is only due to measurement errors.35 The application was used to examine the four spectra of each sample, extracting representative peaks that are present in all four spectra, taking into account that the peak match score should be larger than 0.7, corresponding to a measurement error of (5 Da. Arithmetic means and standard deviations were calculated for m/z values. All strain-specific mass lists were compared with each other with the application SPECLUST to determine characteristic peak masses and to obtain species-specific as well as genusspecific biomarkers. Elaborated peak lists of each strain were compared and the distances between peak mass pairs were calculated as described above. A mass was considered shared between two spectra if the peak match score was larger than 0.7, which corresponded to a width in peak match score of 10 Da. The spectra of the unknown strains isolated from seafood were compared to the created spectral library with the aim to classify and identify unknown species. Mass lists of all species (reference as well as unknown) were clustered with the clustering option available in the web interface SPECLUST. The agglomerative clustering method starts with creating one cluster for every peak list and calculates distances between the clusters. The two closest clusters, in this study the two clusters with the smallest average of pair wise distances (average linkage method), are then merged to a new cluster and the distances are recalculated. This process is continued until only one single cluster remains. For calculating distances between two peak lists, all individual similarity scores for every pair of two peak lists were added. The width in peak match score was set to 10 Da. Phylogenetic Analysis Based on the 16S rRNA Gene. For genomic analysis, the bacterial strains were grown on BHI (Becton and Dickinson) and incubated for 24 h at either 30 or 37 °C depending on the strain. The strain Pseudomonas syringae was incubated in Tryptone Soy Broth (TSB) (Oxoid). Total genomic DNA from bacterial strains were isolated from the

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pellets of 1 mL of overnight cultures in BHI after spinning at 7500 rpm for 10 min. Bacterial cells were lysed and total DNA extracted and purified by means of the DNeasy tissue minikit (Qiagen, Valencia, CA) as described elsewhere.36 The concentration of purified DNA extracts was determined by fluorometry using the fluorometer QubitTM (Invitrogen, Paisley, U.K.). A fragment of the 16S rRNA gene was amplified by PCR using the universal primer pair p8FPL (forward: 5′-AGTTTGATCCTGGCTCAG-3′)andp806R(reverse:5′-GGACTACCAGGGTATCTAAT3′).37 PCR reaction mixtures contained 100 ng of template DNA, 25 µL of a master mix (BioMix, Bioline, London, U.K.), 25 pmol of each oligonucleotide primer and distilled water (Genaxis, Montigny le Bretonneaux, France) to achieve a final volume of 50 µL. Amplification conditions were as follows: a previous denaturing step (94 °C for 7 min) was coupled to 30 cycles of denaturation (94 °C for 60 s), annealing (55 °C for 60 s), extension (72 °C for 60 s), and finalized by an extension step (72 °C for 15 min). All PCR assays were carried out on a MyCycler Thermal Cycler (BioRad Laboratories, Hercules, CA). PCR products were visualized in 2.5% horizontal agarose (MS8, Pronadisa, Madrid, Spain) gels, containing 0.5 µg/mL of ethidium bromide. Prior to sequencing, the PCR products were purified by means of the ExoSAP-IT kit (GE Healthcare, Uppsala, Sweden). Direct sequencing was performed with the BigDye Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems). The same primers used for PCR were also employed for the sequencing of both strands of the PCR products, respectively. Sequencing reactions were analyzed in an automatic sequencing system (ABI 3730 XL DNA Analyzer, Applied Biosystems) with the POP-7 system and carefully reviewed by eye, using the Chromas software (Griffith University, Queensland, Australia). Alignment of the sequences was accomplished using the ClustalX software.38 The unknown bacterial strains isolated from seafood were identified by searching homologies of the DNA sequences with the published reference sequences by means of the BLAST tool (National Centre for Biotechnology Information). Phylogenetic and molecular evolutionary analyses were conducted with the MEGA software,39 using Neighbor-Joining method40 and Kimura 2-parameter with 1000 bootstrap replicates to construct distance based trees.

Results Analysis of Obtained Spectra and Generation of a Library of Mass Spectra. The preparation of protein extracts for proteomic analysis by means of MALDI-TOF mass spectrometry was carried out as described above with the goal to obtain soluble proteins with a low molecular weight of whole bacteria cells in a rapid and simple way. All spectra obtained were satisfactory and showed good resolution with a variety of peaks and specific spectral profiles for each strain studied. The method employs protein extraction and differs from common sample preparation protocols in which whole cells or cell suspensions are directly analyzed by MALDI-TOF. All spectral profiles of soluble protein extracts showed high reproducibility and good resolution with low noise and small mass errors. On the basis of these spectra, a library was compiled that included mass spectra obtained by MALDI-TOF MS of the studied strains in the 2000-10 000 Da range. This mass range was chosen due to the good reproducibility of the spectral profile. Peaks with masses above 10 000 Da could rarely be observed, showing poor reproducibility and being wide, thus producing high values of error in the assignation of masses. Journal of Proteome Research • Vol. 9, No. 6, 2010 3171

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Table 3. Species-Specific Peak Masses of Every Studied Strain and Genus-Specific Peak Massesa strain

species-specific peak masses

EbA01 EbC11 KlP02 KlOx11 KlPn21 HaA02 MoM02

3821; 7642 2477; 2557; 5112; 8295 3658; 7516 3841; 4133; 7682; 8268 7702; 8308 2810; 3887; 7771; 9640 3175; 3240; 3877; 6212; 8330; 8665; 9274 2995; 4468; 5989; 7824 6052 5507; 7812 6182; 6869; 8052 2885; 6453; 8282; 8974 6058; 9280 5219; 6112; 9204 2223; 4591; 6301; 9395 4810; 5629; 6189; 6570; 7091; 7291; 9425 5580; 7246 3354; 6597; 7274 2093; 5521 2399; 3755; 6357; 7507 2603; 3721; 4876; 5204; 6442 3438; 6076; 6618; 8812 6041; 7181; 8926 3328; 4834; 5122; 5971; 6418; 6650; 9099; 9665 2873; 5744; 7430 2267; 2778; 4852; 5264; 5881; 6854; 8439; 9573

PrM01 PrP11 PrV21 PvR61 PvS51 SrL71 SrM53 AmH01 SwA02 SwB11 SwP21 ViA11 ViP02 ViV21 PsF12 PsFr51 PsS34 AiB11 StM03

genus-specific peak masses

3980 ( 1; 7959 ( 2

2733 ( 1; 5463 ( 1; 6226 ( 1 3960 ( 1; 4347 ( 1; 7918 ( 1 8208 ( 2

4275 ( 1; 7189 ( 4

4126 ( 1; 8250 ( 3

a Peak masses are shown as [M + H]+ values; species-specific and genus-specific peak masses: (*) and (O) in Figures 1-4, respectively.

For spectra analysis, arithmetic means for m/z values were calculated and the corresponding mass variability was less than (5 Da in the mass range above 7000 Da and less than (3 Da in the lower mass range. Specific mass lists, each including 10-35 peak masses, were generated for every bacterial strain and represented reproducible bacterial fingerprints. When comparing the masses, similarities between different species and genera, as well as unique masses, were found. To highlight both common and specific peaks in the spectra, symbols were added. Genus-specific peak masses (O) (Figures 1-4) were present in all spectra of each genus and did not appear in the spectra of other genera considered in this work. There was at least one defined species-specific peak mass (*) (Figures 1-4) with high intensity for every species considered used for species-level differentiation. Besides labeling of characteristic peak ions in the spectral profiles, species- and genus-specific peak masses are shown in Table 3. To get a characteristic and representative profile of each studied species, however, more peaks are important and the whole spectral pattern has to be considered. For instance, if an intense peak showed a mass in common with one or more peak masses of other species, then this peak could not be considered as a species-specific peak but rather as a characteristic peak. In this sense, various peak masses were found to be shared by all species of one genus, but the same mass appeared in the spectra of one or more species of different genera. Thus, these peaks (1) (Figures 1-4) could not be defined as genus-specific peaks although they represented characteristic peaks that could be used together with specific peaks to form a characteristic profile of every 3172


genus and species. In general, we conclude that the whole peak masses profile resulted to be important for the characterization of a bacterial species and/or a genus. All spectral fingerprints could be grouped easily. One group, which demonstrated profiles similar to each other, included all species belonging to the Enterobacteriaceae family (Figures 1-2). The number and intensities of peaks in a certain mass range were similar among the individual species but the analogue arrangement of peaks made it difficult to differentiate between the individual species by eye. A more detailed study of mass lists, however, showed certain differences in masses of related peaks. These relationships between the masses of characteristic peaks and the different species of Enterobacteriaceae are shown in Table 4. Both Serratia marcescens (SrM53) and Serratia liquefaciens (SrL71) were exceptions that showed spectral profiles different from those obtained for other species of Enterobacteriaceae (Figure 2) with a very intense peak mass of m/z 7918 ( 1. Besides this genus-specific peak, other two genus-specific peaks were observed for Serratia with masses m/z 3960 ( 1 and m/z 4347 ( 1, respectively. Concerning the family of Enterobacteriaceae, two small but reproducible peaks with the masses m/z 4182 ( 2 and m/z 8363 ( 5 (E) (Figures 1-2) were found. These peaks appeared in spectra of all species of the family Enterobacteriaceae except for M. morganii (MoM02) (Figure 2), which showed peaks with masses of m/z 4168 and m/z 8330, respectively. In general, spectra corresponding to the species Enterobacter aerogenes (EbA02), Enterobacter cloacae (EbC11), Klebsiella oxytoca (KlOx11), Klebsiella pneumoniae (KlPn21) and Raoultella planticola (KlP02) were very similar (Figure 1) and no differentiation between these genera could be found. Discrimination at species level, however, was possible due to a number of species-specific peaks (Table 3). Although genus-specific peaks for Enterobacter, Klebsiella, or Raoultella could not be defined, spectra of the mentioned genera had six mass ions in common (1) (Figure 1): those with m/z values of 2181 ( 1, 3577 ( 2, 3618 ( 3, 4360 ( 2 (the most intense in all the spectra), 7151 ( 3 and 7238 ( 2. The peaks at m/z 3618 ( 3 and 7238 ( 2 were found also in the spectra of the genus Providencia (PvS51, PvR61) (Figure 1) and that at m/z 3618 ( 3 was detected also in the spectra of H. alvei (HaA02), shown in Figure 2. For the genus Providencia, three genus-specific peaks at m/z 2733 ( 1, 5463 ( 1 and 6226 ( 1 were observed, as well as four species-specific peaks for Providencia stuartii and Providencia rettgeri (Table 3). Several peaks of Providencia spp. were shared by other species of Enterobacteriaceae, whereas those at m/z 2217 ( 1 and 4432 ( 2 were found in both spectra of the genus Providencia, as well as in all spectra of the genus Pseudomonas (1) (Figures 1 and 4). Spectra of H. alvei (HaA02) and M. morganii (MoM02) (Figure 2) had peaks in common with the masses of m/z 2187 ( 1 and 4372 ( 2, whereas the peak masses m/z 3635 ( 1 and 7267 ( 2 were characteristic for M. morganii and Proteus spp. The three spectra of the genus Proteus (PrM01, PrP11, PrV21) were very similar and had several peak masses in common (1) (Figure 2). Two genus-specific peaks were found for the genus Proteus at m/z 3980 ( 1 and 7959 ( 2 and various speciesspecific peak masses for both Proteus mirabilis and Proteus vulgaris. In the case of Proteus penneri, just one intense speciesspecific peak mass was observed (Table 3). The spectral profile of M. morganii was analogous to the typical peak arrangement of Enterobacteriaceae spectra, but

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Figure 1. MALDI-TOF MS spectral profiles of Enterobacter spp., R. planticola, Klebsiella spp. and Providencia spp. Species-specific peaks are indicated by (*), genus-specific peaks by (O) and further characteristic peaks by (1).

peak masses showed certain differences leading to seven species-specific peaks (Table 3).

Notwithstanding, there were various high intensity peak masses in the peak profile, illustrated in Table 4, that seemed Journal of Proteome Research • Vol. 9, No. 6, 2010 3173

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Figure 2. MALDI-TOF MS spectral profiles of H.alvei, M. morganii, Proteus spp. and Serratia spp. Species-specific peaks are indicated by (*), genus-specific peaks by (O) and further characteristic peaks by (1).

to be common for several species of Enterobacteriaceae, although the mass differed from species to species. In this 3174


sense, peaks with m/z 5377 ( 1, 5392 ( 2, 5405 ( 1, 5463 ( 1, 5491 ( 2 and 5507 were found in different spectra. Similarly,

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Seafood Spoilage and Gram-Negative Bacteria Differentiation a

Table 4. Characteristic Peak Masses of Enterobacteriaceae Family

bacterial strain PrM01

PrP11

PrV21

MoM02

HaA02

PvR61

PvS51

EbA01

EbC11

KlOx11

KlP02

KlPn21

SrL71

SrM53

2235 2746 ( 1 2824 ( 2 3554 ( 3 3635 ( 1 3980 ( 1 4182 ( 2 4468 5491 ( 1 6251 ( 2 7117 7267 ( 2 7959 ( 2 8363 ( 5 9472 ( 3 9582 ( 3

2241 ( 1 2746 ( 1 2824 ( 2 3554 ( 3 3635 ( 1 3980 ( 1 4182 ( 2 4481 ( 2 5491 ( 1 6261 7102 ( 2 7267 ( 2 7959 ( 2 8363 ( 5 9582 ( 3

2241 ( 1 2754 2824 ( 2 3554 ( 3 3635 ( 1 3980 ( 1 4182 ( 2 4481 ( 2 5507 6268 ( 1 7102 ( 2 7267 ( 2 7959 ( 2 8363 ( 5 9472 ( 3 9582 ( 3

2187 ( 1 2689 ( 1 3588 3635 ( 1 3877 4168 4372 ( 2 5377 ( 1 6212 7174 7267 ( 2 8330 9457 ( 2 -

2187 ( 1 2697 ( 2 2810 3543 3618 ( 3 3887 4182 ( 2 4372 ( 2 5392 ( 3 6251 ( 2 7084 7228 8363 ( 5 9550 9640

2217 ( 1 2733 ( 1 2853 ( 2 3554 ( 3 3618 ( 3 4182 ( 2 4432 ( 2 5463 ( 1 6226 ( 1 7102 ( 2 7238 ( 2 8363 ( 5 9515 -

2217 ( 1 2733 ( 1 2885 3554 ( 3 3618 ( 3 4182 ( 2 4432 ( 2 5463 ( 1 6226 ( 1 7102 ( 2 7238 ( 2 8363 ( 5 -

2181 ( 1 2697 ( 2 2853 ( 2 3577 ( 2 3618 ( 3 3821 4182 ( 2 4360 ( 2 5392 ( 3 6287 ( 1 7151 ( 3 7238 ( 2 8363 ( 5 9472 ( 3 -

2181 ( 1 2689 ( 1 3577 ( 2 3618 ( 3 4182 ( 2 4360 ( 2 5377 ( 1 6268 ( 1 7151 ( 3 7238 ( 2 8363 ( 5 9505 -

2181 ( 1 2703 ( 1 2836 ( 1 3577 ( 2 3618 ( 3 3841 4182 ( 2 4360 ( 2 5405 ( 1 6251 ( 2 7151 ( 3 7238 ( 2 8363 ( 5 9457 ( 2 -

2181 ( 1 2703 ( 1 2836 ( 1 3577 ( 2 3618 ( 3 3658 4182 ( 2 4360 ( 2 5405 ( 1 6251 ( 2 7151 ( 3 7238 ( 2 8363 ( 5 9457 ( 2 -

2181 ( 1 2689 ( 1 2853 ( 2 3577 ( 2 3618 ( 3 4182 ( 2 4360 ( 2 5377 ( 1 6287 ( 1 7151 ( 3 7238 ( 2 8363 ( 5 9472 ( 3 -

2697 ( 2 2824 ( 2 3960 ( 1 4182 ( 2 4347 ( 1 5392 ( 3 6238 7918 ( 1 8363 ( 5 9558 -

2689 2824 ( 2 3960 ( 1 4182 ( 2 4347 ( 1 5377 ( 1 6221 7918 ( 1 8363 ( 5 9530 -

a

Peak masses are presented as [M + H]+ values. Species-specific peaks are highlighted in bold and genus-specific peaks in bold italics.

Table 5. Characteristic Peaks of Shewanella spp., Vibrio spp., and A. hydrophilaa bacterial strain

a

AmH01

SwA02

SwB11

SwP21

ViA11

ViP02

ViV21

2131 ( 1 2525 ( 1 3049 4173 ( 3 4259 ( 2 4699 5048 ( 1 6096 7344 9395

2131 ( 1 2525 ( 1 3095 4105 ( 1 4259 ( 2 4713 5048 ( 1 6189 6570 7291 8208 ( 2 9425

2131 ( 1 2510 ( 1 3083 ( 1 4105 ( 1 4259 ( 2 4722 ( 2 5018 ( 1 6163 ( 1 6547 ( 1 7246 8208 ( 2 9439 ( 1

2131 ( 1 2510 ( 1 3083 ( 1 4105 ( 1 4259 ( 2 4722 ( 2 5018 ( 1 6163 ( 1 6547 ( 1 7274 8208 ( 2 9439 ( 1

2093 2590 ( 1 3596 ( 2 4173 ( 3 4275 ( 1 4722 ( 2 5177 ( 1 6163 ( 1 7189 ( 4 9445

2139 ( 1 2590 ( 1 3083 ( 1 3596 ( 2 4173 ( 3 4275 ( 1 4730 5177 ( 1 6163 ( 1 7189 ( 4 9459

2139 ( 1 2603 3083 ( 1 3596 ( 2 4173 ( 3 4275 ( 1 4751 5204 6163 ( 1 7189 ( 4 9503

Peak masses are presented as [M + H]+ values. Species-specific peaks are highlighted in bold and genus-specific peaks in bold italics.

two other intense peaks appeared in all spectra with masses between m/z 2685-2750 and m/z 6210-6290, respectively (see Table 4). These peaks appeared to be the same but did not relate to the genus level or to any correlation between the different species as mentioned above. Another group of spectral profiles included species that are typically found in marine environments including A. hydrophila (AmH01), Shewanella algae (SwA02), Shewanella baltica (SwB11), Shewanella putrefaciens (SwP21), Vibrio parahaemolyticus (ViP02), Vibrio alginolyticus (ViA11) and Vibrio vulnificus (ViV21). In this group, the spectral profiles (Figure 3) were different from each other at the genus level and peaks could not be related as was the case in the Enterobacteriaceae. A number of species-specific peak masses could be defined for each species (Table 3). At the genus level, there were only a few peaks in common. Thus, for the genus Vibrio, two genus-specific peaks (m/z 4275 ( 1, m/z 7189 ( 4) were observed. For the genus Shewanella, only one small genus-specific peak with the mass m/z 8208 ( 2 could be found. There were several peaks in common for some species of this group, however (Table 5). The peaks at m/z 4105 ( 1, 2131 ( 1 and 4259 ( 2 (1) (Figure 3) were common for Shewanella spp., whereas the last two ions were also present in the spectra of A. hydrophila. Peaks at m/z

3596 ( 2 and 4173 ( 3 (1) (Figure 3) appeared in all spectra of Vibrio spp. samples and that at m/z 4173 ( 3 was also common for A. hydrophila. The last group considered in this work included the genus Pseudomonas and the species A. baumanii and S. maltophila. Spectral profiles of these species were different from the other spectra discussed above (Figure 4). Spectra of the species Pseudomonas fluorescens (PsF12), Pseudomonas fragi (PsFr51) and Pseudomonas syringae (PsS34) showed spectral profiles with many peaks and were very similar to each other (Figure 4). Two genus-specific peaks at m/z 4126 ( 1 and 8250 ( 3, as well as a number of peak masses in common, were observed (Table 6). Those at m/z 2217 ( 1, 3588 ( 4, 3617 ( 1, 4432 ( 2 and 7230 ( 4 (1) (Figure 4) were detected in all spectra of the genus Pseudomonas, but were also shared with other species of different genera and could not be assigned as genusspecific peaks. Differentiation on species-level, however, was possible due to several species-specific peaks for each species of Pseudomonas spp. (Table 3). The most atypical spectral profile was observed for A. baumanii (AiB11) (Figure 4): two species-specific peaks were observed, one very intense at m/z 5744 and the other at m/z 2873, being signals for all other ions almost suppressed. Journal of Proteome Research • Vol. 9, No. 6, 2010 3175

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Figure 3. MALDI-TOF MS spectral profiles of Shewanella spp., A. hydrophila and Vibrio spp. Species-specific peaks are indicated by (*), genus-specific peaks by (O) and further characteristic peaks by (1).

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Figure 4. MALDI-TOF MS spectral profiles of Pseudomonas spp., A. baumanii and S. maltophilia. Species-specific peaks are indicated by (*), genus-specific peaks by (O) and further characteristic peaks by (1).

Table 6. Characteristic Peaks of Species Pseudomonas spp.a bacterial strain PsF12

PsFr51

PsS34

2217 ( 1 2533 ( 1 3588 ( 4 3618 ( 3 4126 ( 1 4432 ( 2 5063 ( 1 7167 ( 2 7230 ( 3 7594 ( 4 8250 ( 3

2217 ( 1 2533 ( 1 3588 ( 4 3618 ( 3 4126 ( 1 4432 ( 2 5063 ( 1 7181 7230 ( 3 7594 ( 4 8250 ( 3

2217 ( 1 2562 3588 ( 4 3618 ( 3 4126 ( 1 4432 ( 2 5122 7167 ( 2 7230 ( 3 7573 8250 ( 3

a Peak masses are presented as [M + H]+ values. Species-specific peaks are highlighted in bold and genus-specific peaks in bold italics.

Similarly, the spectrum of S. maltophila (StM03) (Figure 4) was uncommon, showing a profile with a typical number of peaks, most of which represented species-specific peak masses (Table 3). Classification of Unknown Strains Isolated from Seafood by MALDI-TOF MS Fingerprinting. Spectral profiles obtained for the strains isolated from seafood were compared to the created spectral library. All three spectra could be easily classified on genus level by comparison of spectral fingerprints. The comparison of the peak mass lists and the search for characteristic peak masses resulted in a clear attribution of all three spectra to one bacterial species respectively, present in the reference library. Thus, the spectral profiles of the strains 2387T6, 25MC6 and BR03 were clearly correlated to the spectra Journal of Proteome Research • Vol. 9, No. 6, 2010 3177

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Figure 5. MALDI-TOF MS spectral profiles of strains isolated from seafood and the corresponding reference strains. Species-specific peaks are indicated by (*), genus-specific peaks by (O) and further characteristic peaks by (1).

of Serratia marcescens (SrM53), Stenotrophomonas maltophilia (StM03) and Pseudomonas fragi (PsFr51), respectively (Figure 5). Previous determined genus-specific peak masses for Serratia and Pseudomonas were also found in the spectra of the strains 2387T6 and BR03, respectively (O in Figure 5), and allowed the rapid determination of the genus. Comparing the whole 3178


spectral profiles, discrimination of the bacterial species inside the genus was also possible, although some of the determined species-specific peak masses were not detected in the spectra of the strains isolated from seafood. Thus, for the strain BR03 two P. fragi-specific peaks with the mass m/z 6041 and 7181 were observed, whereas the peak mass of m/z 8926 could not


Figure 6. Phyloproteomic tree of studied species. The scale below the dendrogram indicates the relative distance used in the clustering (see Materials and Methods).

be found (* in Figure 5). In the same way, for the strain 2387T6, just the peak mass of m/z 6112 was species-specific for S. marcescens (* in Figure 5). Furthermore, all species-specific peak masses assigned for S. maltophilia were also present in the spectra of the strain 25MC6 (* in Figure 5). Phyloproteomic Analysis. Clustering of the elaborated mass lists by means of the web-interface SPECLUST (Figure 6) reflected precisely the results discussed above. In this fashion, spectra comparison searching for similarities and differences of spectral profiles were derived more easily from the dendrogram. Since clustering is based on mass spectral relations of proteins, it is possible to talk about phyloproteomic relationships.15 The cluster demonstrated a clear separation of the species S. maltophilia and A. baumanii, forming an outgroup. The other species were divided into three groups, according to the differentiation of the spectral profiles as mentioned before. One group included the genera Shewanella and Vibrio, separated in two clusters respectively, and the species A. hydrophila that was closer to the genus Vibrio than to Shewanella spp. Another branch included the genus Pseudomonas, well separated from the cluster of all species of the Enterobacteriaceae family. This last cluster grouped together genera Serratia, Proteus and Providencia. Species Klebsiella spp., Enterobacter spp. and R. planticola were grouped together as expected because of the similarity of their spectral profiles. In contrast, the species S. liquefaciens, S. marcescens and M. morganii that showed some differences in their spectral profiles

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in comparison to the other Enterobacteriaceae, were located more distant in the cluster. Furthermore, the clustering of the peak mass lists allowed a clear and rapid classification of the unknown bacterial species isolated from seafood. The three strains were grouped on the tree with the corresponding reference species respectively. Genomic Analysis. All phyloproteomic relationships were compared with commonly used phylogenetic tools by analysis of the 16S rRNA gene, also considered in this study. Thus, an approximately 800 bp fragment of the 16S rRNA gene was amplified using universal primers and all sequences of the reference strains were deposited in GenBank (accession numbers are compiled in Table 1). Furthermore, a phylogenetic tree of the aligned sequences was constructed, showing phylogenetic relationships with good correlation to the cluster obtained by phyloproteomic studies (Figure 7). In the phylogenetic tree the species A. baumanii and S. maltophila were separated from all the other Gram negative strains, whereas all species belonging to the Enterobacteriaceae family were clustered together. As expected, the species belonging to the genus Pseudomonas were grouped together, as were the genus Vibrio and Shewanella spp. that appeared together with A. hydrophila in a separated branch. Within the Enterobacteriaceae cluster, species belonging to genera Proteus and Providencia were well grouped at the genus level and formed, together with M. morganii, a branch separated from the other Enterobacteriaceae species. In the latter group, no differentiation at the genus level was found. This group could also be observed in the phyloproteomic study, where the species Klebsiella spp., Enterobacter spp. and R. planticola were very close to each other and could not be distinguished at the genus level, whereas the genus Serratia could be differentiated easily from other genera. The unknown bacterial strains isolated from seafood were identified by searching sequence homologies against the database GenBank (National Center for Biotechnology Information). The strain 2387T6 was identified as Serratia marcescens and the strain 25MC6 as Stenotrophomonas maltophilia. When searching the sequence of the strain BR03 against the database, high homology was found to strains of Pseudomonas spp., but no clear identification of the species could be made, because of the high similarity found with several species of the genus Pseudomonas. However, in the phylogenetic analysis of the unknown strains and the reference strains studied in this work, the strain BR03 was grouped together with Pseudomonas fragi.

Discussion In the past decade, molecular techniques have revolutionized the development of sensitive, rapid and automated methods for the detection and identification of a variety of microbial species associated with foodborne disease and food spoilage. Few efforts have been made, however, to develop rapid and sensitive methods for the early detection of these kinds of bacterial species in fish and seafood products. MALDI-TOF MS has been shown to be a suitable tool for the characterization of microorganisms and for the analysis of whole bacterial cells. This method is also an accurate and rapid method for bacterial identification in the area of clinical diseases. In this study, spectra were taken from an extract of soluble proteins, which were obtained in an easy and rapid manner directly from cell cultures. This kind of sample preparation was described by Wang et al. (1998) and differs from the commonly applied Journal of Proteome Research • Vol. 9, No. 6, 2010 3179

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Figure 7. Phylogenetic analysis of the nucleotide sequences of the 16S rRNA gene of main seafood-borne and spoilage bacteria by means of the neighbor-joining method. Numbers above and below branches indicate bootstrap values from neighbor-joining analysis.

analysis of whole cell suspensions in studies of MALDI-TOF MS analysis of bacteria.41-44 An important advantage of this method is that time-consuming washing steps are not required and the extracts can be obtained in just one dissolution/ centrifugation step. Cells are lysed by use of an organic solvent (acetonitrile) and a high concentration of a strong acid (TFA). An even more rapid sample preparation, described by some authors, was based on the direct application of bacterial biomass taken from culture plates to the MALDI-TOF MS sample plate. Later the bacterial cells are mixed with the matrix solution directly on the plate.24,45 However, analyses of whole cell suspensions have several disadvantages over the analysis of cell extracts. Thus, spectral profiles obtained from cell extracts used in our study showed less noise but more reproducible mass ions in comparison to spectra obtained from cell suspensions (data not shown). Several authors have studied the reproducibility of mass spectra in relation to bacterial culture conditions and sample preparation with the aim of optimizing and standardizing the protocol. As a result, it was found that spectral profiles were less sensitive to the culture conditions but showed high variability depending on the sample preparation protocol.18,46,47 The disadvantage of using different sample preparation protocols is that mass spectra and mass lists obtained could not be compared to each other. In this study, analysis was carried out in quadruplicate for every strain to demonstrate biological and technical reproduc3180


ibility. Final peak mass lists included between 10 and 35 average peak masses and the mass variability was less than (5 Da, which was in agreement with previous works by other authors.15,44,48 Furthermore, for some bacterial species, a few peak masses reported in this study had already been described by other authors through the use of different protocols. Mazzeo et al. (2006) obtained spectral profiles very similar to the spectra obtained in our study for the species M. morganii, P. vulgaris and P. mirabilis, and included many common peaks. Thus, in the spectra of P. mirabilis and P. vulgaris described by these authors, the peak mass m/z 4182 ( 2 was also present, in agreement with our results. The spectral profile of P. fluorescens, however, differed from our results and just six identical peaks were found.44 In a different work, 17 Aeromonas species were analyzed and a genus-specific peak mass m/z 6301 for all Aeromonas species was observed.48 In our study, the ion with the mass m/z 6301 was defined as a species-specific peak mass for A. hydrophila. Furthermore, Donohue et al. (2006) analyzed the same A. hydrophila strain and when comparing with the peak list obtained in our study, seven identical peak masses could be found. A further study described spectral profiles of some species of the Enterobacteriaceae family, finding for the species P. rettgeri and K. pneumoniae several peak masses in common with our study.49 In general, characteristic mass patterns obtained by MALDITOF MS of intact bacterial cells are attributed to proteins.13,14 Conway et al. (2001) demonstrated that most of the mass

Seafood Spoilage and Gram-Negative Bacteria Differentiation patterns detected by MALDI-TOF MS of bacteria were proteins by comparing the spectral profiles obtained after treatment of the bacterial cells with lysozyme and proteinase K and the spectral profiles obtained from untreated cell suspensions. Spectra analysis aimed at bacterial species identification could be carried out by either identifying ion biomarker masses that could be correlated with theoretically determined protein masses in databases or by comparing the spectral profile of all bacteria (fingerprinting).16 In the first approach, the identification of biomarker proteins plays an important role for the analysis of spectral data. Demirev et al. (2004) determined the masses of biomarkers for Escherichia coli and Bacillus subtilis by MALDI-TOF MS and searched against a protein database to identify the organisms by matching the masses against sequence-derived masses. Various authors identified protein biomarkers by MALDI-TOF MS for a number of bacterial species of clinical interest,25,27,50 whereas no similar work has been performed for the determination of biomarker proteins for bacterial species that are associated with seafood-borne diseases or seafood spoilage. A critical challenge of protein database searches is the high mass accuracy that is necessary to determine masses of biomarker proteins and that some proteins have very similar masses.51 Furthermore, identification is limited to well-characterized microorganisms with known protein sequences available in proteome databases. The second approach relies on differentiation of bacterial species based on the comparison of their spectral profiles. For this purpose, it is not necessary to identify the proteins but just to extract characteristic peaks that are representative of the corresponding species or genus and that are part of a specific profile (named fingerprint). In fact, bacterial species and genera can be distinguished by a few characteristic peaks. Several authors showed the possibility of bacterial species classification by means of specific spectral fingerprints and biomarker patterns were defined for E. coli, Bacillus spp., Campylobacter spp., Staphylococcus spp. and Streptococcus spp.20,22,27,42,47,52-54 In the present work, the fingerprint approach was carried out by studying various species of the Enterobacteriaceae family by finding two family specific peak masses and a high spectral similarity. Furthermore, when comparing the spectra at the genus level, only some genera could be differentiated. The genera Providencia, Proteus and Serratia could easily be distinguished from the other genera due to a number of characteristic peak masses. Similarly, species of the genus Pseudomonas showed similar spectral profiles, but they were different from the other studied genera. In the case of the above-named genera, species belonging to the same genus showed similar profiles, and a number of common peak masses were observed, thus allowing for easy classification at the genus level. In contrast, the genera Shewanella and Vibrio did not show such similarities at the genus level and only a few common peak masses could be found. Nevertheless, spectral profiles of the two genera, as well as the spectrum of A. hydrophila that are all part of the indigenous microflora of aquatic ambiences, could be clearly distinguished from the other studied species and various peak masses were found in common for this group. In our study, a number of species-specific peak masses were found for all species considered. Furthermore, genus-specific peaks were found for the genera Proteus, Providencia, Pseudomonas, Serratia, Shewanella and Vibrio. It should be noted, however, that these peaks were assigned as biomarker pattern masses in the context of the studied species. When a new

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species is included, some specific masses may change the designation of specific peaks. In this sense, we have found that spectral profiles of strains isolated from seafood varied in some peaks from the spectra of reference strains and not all previously determined species-specific peak masses could be observed. Thus, for species identification the whole fingerprint is more accurate than just the classification based on a few species- or genus-specific biomarker ions. Furthermore, the assignment of well-defined species or genus-specific biomarkers could be improved by increasing the number of strains studied. Many efforts have been made in creating databases of spectra of bacterial strains. These databases continue to grow steadily by the regular addition of new spectral profiles. Thus, the Spectral Archive and Microbial Identification System (Saramis; www.anagnostec.de) includes a database of spectral profiles of more than 200 bacterial species, as well as yeasts and fungi, and allows for the rapid identification of these microorganisms by means of matching an unknown spectral profile against the database.55 Another database is the Microbelynx bacterial identification system,33,51 which is also fully automated and searches against an ample database of more than 500 bacterial species from validated bacterial strains obtained from the National Collection of Type Cultures (NCTC). The critical challenge of these techniques is the limited availability of such reference databases and the fact the same protocol has to be followed strictly for direct comparison and searching against the database. Furthermore, the abovementioned databases, as well as most of the studies in the area of bacterial identification by MALDI-TOF MS, are targeted at clinical diagnostics of bacterial strains associated with human infectious diseases. Our work was also aimed at compiling a library of spectral fingerprints of the main pathogenic and spoilage bacterial species potentially present in seafood, in a similar way to that previously described by Mazzeo et al. (2006). These authors constructed a library containing spectra of 24 food-borne bacterial species, including Escherichia, Yersinia, Proteus, Morganella, Salmonella, Staphylococcus, Micrococcus, Lactococcus, Pseudomonas, Leuconostoc and Listeria. Although the spectral profiles are freely available on the Web (http://bioinformatica. isa.cnr.it/Descr_Bact_Dbase.htm), the library only includes a few bacterial species important in seafood-borne diseases and/ or seafood spoilage. The difficulty of developing an “in house” database lays in the need for particular algorithms to analyze and compare obtained spectra or to carry out searches against the constructed reference library. Jarman et al. (2000) developed an automated peak detection algorithm to extract representative mass ions from a fingerprint and to compare spectra to fingerprints in a reference library. In our study, the freely available web-based application SPECLUST was used to extract representative peak masses and to obtain final mass lists for each species. Later on, required mass lists can be compared and common peak masses defined. The web program was very fast, easy to handle, and could be extended by new spectral mass lists in a simple manner. Although it was not possible to search an unknown spectrum directly against the library, comparison of peak mass lists could be carried out and common peaks determined with the aim of analyzing a spectral profile of an unknown strain. Thus, three strains isolated from different seafood were characterized and the corresponding species identified. The critical challenge of this technique, Journal of Proteome Research • Vol. 9, No. 6, 2010 3181

research articles however, is the limited coverage of the created library. Therefore, species identification can only be carried out for strains covered within the library, otherwise results can only provide an indication of the unknown strain.51 Furthermore, all peak mass lists were clustered and the obtained dendrogram showed phyloproteomic relationships that reflected accurate species classification at both genus and family level. Likewise, clustering was in good correlation to the results obtained by phylogenetic analysis, as previously observed by other authors.56-58 It should also be stressed that bacterial species identification by genomic methods, such as the phylogenetic analysis of the 16S rRNA gene, is not always successful due to the identical sequences of some species. In our study, the strain BR03 could not be attributed to a certain Pseudomonas species by analysis of the 16S rRNA sequence. In contrast, analysis of the spectral profile obtained by MALDITOF MS allowed the classification to Pseudomonas fragi due to the presence of characteristic peak masses and the absence of peak masses specific for the other two Pseudomonas species. In this regard, Holland et al. (1996) showed that it was possible to differentiate E. coli and Shigella flexneri by unique biomarkers, whereas it is difficult to distinguish these species by genomic methods. Accordingly, clustering proved to be a method to analyze spectral data and distinguish bacterial species in a fast and simple way.

Conclusions A library of mass spectral fingerprints of the main pathogenic and spoilage bacterial species present in fish and seafood products was created. Characteristic peak masses were defined and could be used as reference data to allow the identification of unknown pathogenic and spoilage bacteria present in such food products. In our study, we demonstrated the ability of this technique to discriminate unknown bacterial strains, by analyzing three strains isolated from seafood. Comparison of peak masses showed certain relationships among several species as well as specificities. Finally, at least one speciesspecific peak for each species, as well as a number of genusspecific peaks, were designated. A new approach was the clustering of the selected mass lists using the web interface SPECLUST. This method demonstrated phyloproteomic relationships that correlated well to the results obtained by phylogenomic analysis. Thus, the clustering of species enabled the fast identification of unknown strains by phyloproteomic analysis by comparison with the created library constructed from reference fingerprints. In conclusion, the proteomic approach demonstrated to be a competent tool for species differentiation due to the highly specific fingerprints and this method could be applied for the identification of unknown bacterial species isolated from seafood. Abbreviations: ATCC, American Type Culture Collection; CECT, Spanish Type Culture Collection; MALDI-TOF MS, matrix-assisted laser desorption ionization-time of flight mass spectrometry.

Acknowledgment. We thank Dr. Francisco Barros (Unidad de Medicina Molecular, Fundacioń Pu ´ blica Galega de Medicina Xeno´mica, Santiago de Compostela) for his excellent technical assistance with 16S rRNA sequencing. This work was funded by the PGIDIT Research Program (Project PGIDIT06PXIB261164PR) of the Xunta de Galicia (Galician Council for Industry Commerce and Innovation). 3182


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Journal of Proteome Research • Vol. 9, No. 6, 2010 3183

Species Differentiation of Seafood Spoilage and ... - ACS Publications

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