Classification and identification of bacteria using mass spectrometry-based proteomics

Advancements in prokaryotic systematics and the role of Bergey's International Society for Microbial Systematicsin addressing challenges in the meta-data era

Prokaryotes are ubiquitous in the biosphere, important for human health and drive diverse biological and environmental processes. Systematics of prokaryotes, whose origins can be traced to the discovery of microorganisms in the 17th century, has transitioned from a phenotype-based classification to a more comprehensive polyphasic taxonomy and eventually to the current genome-based taxonomic approach. This transition aligns with a foundational shift from studies focused on phenotypic traits that have limited comparative value to those using genome sequences. In this context, Bergey's Manual of Systematics of Archaea and Bacteria (BMSAB) and Bergey's International Society for Microbial Systematics (BISMiS) play a pivotal role in guiding prokaryotic systematics. This review focuses on the historical development of prokaryotic systematics with a focus on the roles of BMSAB and BISMiS. We also explore significant contributions and achievements by microbiologists, highlight the latest progress in the field and anticipate challenges and opportunities within prokaryotic systematics. Additionally, we outline five focal points of BISMiS that are aimed at addressing these challenges. In conclusion, our collaborative effort seeks to enhance ongoing advancements in prokaryotic systematics, ensuring its continued relevance and innovative characters in the contemporary landscape of genomics and bioinformatics.

Shotgun proteomics for the identification of yeasts responsible for pink/red discoloration in commercial dairy products

Pink/red discoloration encompasses a series of relatively common spoilage defects of commercial dairy products. In this study, we used shotgun proteomics to identify the microorganism responsible for the production of intensely red-coloured slimes found on the surface of freshly opened commercial spreadable cheese and yogurt samples. Proteome-wide characterization of microbial proteins allowed to identify 1042 and 687 gene products from Rhodotorula spp. in spreadable cheese and yogurt samples, respectively, while no significant protein scores from other microorganisms were recorded. Subsequent microbiological analyses and sequencing of the 26S rRNA gene region supported the proteomic results demonstrating that the microorganism involved was Rhodotorula mucilaginosa, a carotenoid - producing basidiomycetous that can be potentially pathogenic to humans, especially for immunocompromised individuals. This is the first time that shotgun proteomics has been used to identify a microorganism responsible for spoilage in dairy products, proposing it as a relatively fast, sensitive, and reliable alternative or complement to conventional methods for microbial identification.

Evaluation of the Limit of Detection of Bacteria by Tandem Mass Spectrometry Proteotyping and Phylopeptidomics

Shotgun proteomics has proven to be an attractive alternative for identifying a pathogen and characterizing the antimicrobial resistance genes it produces. Because of its performance, proteotyping of microorganisms by tandem mass spectrometry is expected to become an essential tool in modern healthcare. Proteotyping microorganisms that have been isolated from the environment by culturomics is also a cornerstone for the development of new biotechnological applications. Phylopeptidomics is a new strategy that estimates the phylogenetic distances between the organisms present in the sample and calculates the ratio of their shared peptides, thus improving the quantification of their contributions to the biomass. Here, we established the limit of detection of tandem mass spectrometry proteotyping based on MS/MS data recorded for several bacteria. The limit of detection for Salmonella bongori with our experimental set-up is 4 × 10⁴ colony-forming units from a sample volume of 1 mL. This limit of detection is directly related to the amount of protein per cell and therefore depends on the shape and size of the microorganism. We have demonstrated that identification of bacteria by phylopeptidomics is independent of their growth stage and that the limit of detection of the method is not degraded in presence of additional bacteria in the same proportion.

The failure on the effectiveness of formalin on cadaver disinfection and alternative methods

Objective: It was aimed to identify the contaminant and determine the alternative disinfectant detection in the microbial growth observed in various parts of the cadaver stored in the formalin tank in the dissection laboratory of Marmara University Anatomy Department. We also performed a literature review of this unusual pathogen. Materials and Methods: Swab samples were inoculated on agar mediums. After incubation, matrix-assisted laser desorption ionizationtime of flight mass spectrometry (MALDI-TOF MS) analysis was used to identify the isolate from the detected uniform colonies. Sample solution from the cadaver tank, freshly prepared 5% formalin and 0.55% ortho-phthalaldehyde were used to determine the disinfectant sensitivity of the isolate. Results: According to 16s rDNA sequence analysis, it was concluded as Skermanella aerolata with 99% similarity. In the disinfectant susceptibility test, it was observed that S. aerolata and control bacteria could grow in 5% formalin taken from the cadaver tank. No growth was detected in other disinfectants. Conclusion: To prevent cadaver contamination in anatomy laboratories, the quality control of the embalming solutions and indoor air filtration of the dissection rooms should be checked at regular intervals. Members of Skermanella genus have been identified as environmental organisms in several studies, however, recent researches reported this bacterium as a human pathogen.

Selective Capture and Identification of Methicillin-Resistant Staphylococcus aureus by Combining Aptamer-Modified Magnetic Nanoparticles and Mass Spectrometry

A nucleic acid aptamer that specifically recognizes methicillin-resistant Staphylococcus aureus (MRSA) has been immobilized on magnetic nanoparticles to capture the target bacteria prior to mass spectrometry analysis. After the MRSA species were captured, they were further eluted from the nanoparticles and identified using matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). The combination of aptamer-based capture/enrichment and MS analysis of microorganisms took advantage of the selectivity of both techniques and should enhance the accuracy of MRSA identification. The capture and elution efficiencies for MRSA were optimized by examining factors such as incubation time, temperature, and elution solvents. The aptamer-modified magnetic nanoparticles showed a capture rate of more than 90% under the optimized condition, whereas the capture rates were less than 11% for non-target bacteria. The as-prepared nanoparticles exhibited only a 5% decrease in the capture rate and a 9% decrease in the elution rate after 10 successive cycles of utilization. Most importantly, the aptamer-modified nanoparticles revealed an excellent selectivity towards MRSA in bacterial mixtures. The capture of MRSA at a concentration of 10² CFU/mL remained at a good percentage of 82% even when the other two species were at 10⁴ times higher concentration (10⁶ CFU/mL). Further, the eluted MRSA bacteria were successfully identified using MALDI mass spectrometry.

TaxIt: An Iterative Computational Pipeline for Untargeted Strain-Level Identification Using MS/MS Spectra from Pathogenic Single-Organism Samples

Untargeted accurate strain-level classification of a priori unidentified organisms using tandem mass spectrometry is a challenging task. Reference databases often lack taxonomic depth, limiting peptide assignments to the species level. However, the extension with detailed strain information increases runtime and decreases statistical power. In addition, larger databases contain a higher number of similar proteomes. We present TaxIt, an iterative workflow to address the increasing search space required for MS/MS-based strain-level classification of samples with unknown taxonomic origin. TaxIt first applies reference sequence data for initial identification of species candidates, followed by automated acquisition of relevant strain sequences for low level classification. Furthermore, proteome similarities resulting in ambiguous taxonomic assignments are addressed with an abundance weighting strategy to increase the confidence in candidate taxa. For benchmarking the performance of our method, we apply our iterative workflow on several samples of bacterial and viral origin. In comparison to noniterative approaches using unique peptides or advanced abundance correction, TaxIt identifies microbial strains correctly in all examples presented (with one tie), thereby demonstrating the potential for untargeted and deeper taxonomic classification. TaxIt makes extensive use of public, unrestricted, and continuously growing sequence resources such as the NCBI databases and is available under open-source BSD license at https://gitlab.com/rki_bioinformatics/TaxIt.

Proteomic similarity of the Littorinid snails in the evolutionary context

BACKGROUND

The introduction of DNA-based molecular markers made a revolution in biological systematics. However, in cases of very recent divergence events, the neutral divergence may be too slow, and the analysis of adaptive part of the genome is more informative to reconstruct the recent evolutionary history of young species. The advantage of proteomics is its ability to reflect the biochemical machinery of life. It may help both to identify rapidly evolving genes and to interpret their functions.

METHODS

Here we applied a comparative gel-based proteomic analysis to several species from the gastropod family Littorinidae. Proteomes were clustered to assess differences related to species, geographic location, sex and body part, using data on presence/absence of proteins in samples and data on protein occurrence frequency in samples of different species. Cluster support was assessed using multiscale bootstrap resampling and the stability of clustering-using cluster-wise index of cluster stability. Taxon-specific protein markers were derived using IndVal method. Proteomic trees were compared to consensus phylogenetic tree (based on neutral genetic markers) using estimates of the Robinson-Foulds distance, the Fowlkes-Mallows index and cophenetic correlation.

RESULTS

Overall, the DNA-based phylogenetic tree and the proteomic similarity tree had consistent topologies. Further, we observed some interesting deviations of the proteomic littorinid tree from the neutral expectations. (1) There were signs of molecular parallelism in two Littoraria species that phylogenetically are quite distant, but live in similar habitats. (2) Proteome divergence was unexpectedly high between very closely related Littorina fabalis and L. obtusata, possibly reflecting their ecology-driven divergence. (3) Conservative house-keeping proteins were usually identified as markers for cryptic species groups ("saxatilis" and "obtusata" groups in the Littorina genus) and for genera (Littoraria and Echinolittorina species pairs), while metabolic enzymes and stress-related proteins (both potentially adaptively important) were often identified as markers supporting species branches. (4) In all five Littorina species British populations were separated from the European mainland populations, possibly reflecting their recent phylogeographic history. Altogether our study shows that proteomic data, when interpreted in the context of DNA-based phylogeny, can bring additional information on the evolutionary history of species.

Identification of bacteria in juice/lettuce using magnetic nanoparticles and selected reaction monitoring mass spectrometry

Ensuring food safety requires a rapid and reliable method for detecting food-borne pathogens. Mass spectrometry has been demonstrated as a powerful tool to classify pure bacterial species. However, matrix interference from food backgrounds may lead to false results because of the suppression of microbial signals. It is useful to develop a method for bacterial enrichment and marker identification in food samples. Magnetic zirconia nanoparticles were used to concentrate spiked microorganisms from apple juice/lettuce under specific conditions (pH 4.5). Bacterial identification was achieved using nanoLC-MS. Selected reaction monitoring of bacteria-related peptides was applied for the first time to identify bacteria including Staphylococcus aureus and Escherichia coli. This study presents an accurate means for bacterial identification in food matrixes using MS. The analysis time is less than 90 min and the minimum concentration of E. coli detected was 5 × 103 CFU/mL. The interaction between bacteria and the magnetic nanoparticles was electrostatic and nonspecific, in contrast to immunoassays which require specific antibodies. The targeted peptide analysis focuses on the bacterial markers, thus significantly simplifying the analysis and leading to an accurate identification of bacteria.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

Phenotypic typing and epidemiological survey of antifungal resistance of Candida species detected in clinical samples of Italian patients in a 17 months' period

INTRODUCTION

Yeast pathogens are emerging agents of nosocomial as well as community-acquired infections and their rapid and accurate identification is crucial for a better management of high-risk patients and for an adequate treatment.

METHODS

We performed a retrospective review of 156 yeast isolates collected during a 17 months' period of regular clinical practice at the Microbiology Department of San Camillo Hospital in Treviso, Italy and analyzed by the traditional culture-based method combined with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS).

RESULTS

Out of all the samples collected MALDI-TOF MS was able to characterize with a MT score ≥1.7 (accurate result at species level) 12 different yeast and yeast-like species from 140 samples: Candida albicans (63.7%), Candida glabrata (13.6%), Saccharomyces cerevisiae (6.5%), Candida parapsilosis (5.7%), Candida tropicalis (2.1%), Candida pararugosa (2.1%), Candida guilliermondii (2.1%), Candida kefyr (1.4%), Candida lusitaniae (0.7%), Candida palmioleophila (0.7%), Geotrichum silvicola (0.7%), Rhodotorula mucilaginosa (0.7%). Susceptibility testing toward seven common antifungal agents showed a characteristic MIC distribution of C. albicans isolates for echinocandins: particularly we noticed that 72% and 46% of C. albicans showed an MIC value close to clinical breakpoint as defined by EUCAST, respectively for anidulafungin and micafungin.

CONCLUSION

Accurate identification of microorganisms and the study of their antifungal susceptibility allow to understand the epidemiology of a particular area, permitting the choice of the most appropriate early antifungal treatment.

Typing and Characterization of Bacteria Using Bottom-up Tandem Mass Spectrometry Proteomics

Methods for rapid and reliable microbial identification are essential in modern healthcare. The ability to detect and correctly identify pathogenic species and their resistance phenotype is necessary for accurate diagnosis and efficient treatment of infectious diseases. Bottom-up tandem mass spectrometry (MS) proteomics enables rapid characterization of large parts of the expressed genes of microorganisms. However, the generated data are highly fragmented, making downstream analyses complex. Here we present TCUP, a new computational method for typing and characterizing bacteria using proteomics data from bottom-up tandem MS. TCUP compares the generated protein sequence data to reference databases and automatically finds peptides suitable for characterization of taxonomic composition and identification of expressed antimicrobial resistance genes. TCUP was evaluated using several clinically relevant bacterial species (Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus pneumoniae, Moraxella catarrhalis, and Haemophilus influenzae), using both simulated data generated by in silico peptide digestion and experimental proteomics data generated by liquid chromatography-tandem mass spectrometry (MS/MS). The results showed that TCUP performs correct peptide classifications at rates between 90.3 and 98.5% at the species level. The method was also able to estimate the relative abundances of individual species in mixed cultures. Furthermore, TCUP could identify expressed β-lactamases in an extended spectrum β-lactamase-producing (ESBL) E. coli strain, even when the strain was cultivated in the absence of antibiotics. Finally, TCUP is computationally efficient, easy to integrate in existing bioinformatics workflows, and freely available under an open source license for both Windows and Linux environments.

Tatumella saanichensis sp. nov., isolated from a cystic fibrosis patient

Polyphasic taxonomic analysis was performed on a clinical isolate (NML 06-3099T) from a cystic fibrosis patient, including whole-genome sequencing, proteomics, phenotypic testing, electron microscopy, chemotaxonomy and a clinical investigation. Comparative whole-genome sequence analysis and multilocus sequence analysis (MLSA) between Tatumella ptyseos ATCC 33301T and clinical isolate NML 06-3099T suggested that the clinical isolate was closely related to, but distinct from, the species T. ptyseos. By 16S rRNA gene sequencing, the clinical isolate shared 98.7 % sequence identity with T. ptyseos ATCC 33301T. A concatenate of six MLSA loci (totalling 4500 bp) revealed < 93.9 % identity between T. ptyseos ATCC 33301T, other members of the genus and the clinical isolate. A whole-genome sequence comparison between NML 06-3099T and ATCC 33301T determined that the average nucleotide identity was 76.24 %. The overall DNA G+C content of NML 06-3099T was 51.27 %, consistent with members of the genus Tatumella. By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS analysis, NML 06-3099T had a genus-level match, but not a species-level match, to T. ptyseos. By shotgun proteomics, T. ptyseos ATCC 33301T and NML 06-3099T were found to have unique proteomes. The two strains had similar morphologies and multiple fimbriae, as observed by transmission electron microscopy, but were distinguishable by phenotypic testing. Cellular fatty acids found were typical for members of the Enterobacteriaceae. NML 06-3099T was susceptible to commonly used antibiotics. Based on these data, NML 06-3099T represents a novel species in the genus Tatumella, for which the name Tatumella saanichensis sp. nov. is proposed (type strain NML 06-3099T = CCUG 55408T = DSM 19846T).

Emerging mass spectrometry techniques for the direct analysis of microbial colonies

One of the emerging areas in microbiology is detecting specialized metabolites produced by microbial colonies and communities with mass spectrometry. In this review/perspective, we illustrate the emerging mass spectrometry methodologies that enable the interrogation of specialized metabolites directly from microbial colonies. Mass spectrometry techniques such as imaging mass spectrometry and real-time mass spectrometry allow two and three-dimensional visualization of the distribution of metabolites, often with minimal sample pretreatment. The speed in which molecules are captured using these methods requires the development of new molecular visualization tools such as molecular networking. Together, these tools are beginning to provide unprecedented insight into the chemical world that microbes experience.

Detection of quorum sensing activity in the multidrug-resistant clinical isolate Pseudomonas aeruginosa strain GB11

A multidrug-resistant clinical bacteria strain GB11 was isolated from a wound swab on the leg of a patient. Identity of stain GB11 as Pseudomonas aeruginosa was validated by using matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS). Detection of the production of signaling molecules, N-acylhomoserine lactones (AHLs), was conducted using three different bacterial biosensors. A total of four different AHLs were found to be produced by strain GB11, namely N-butyryl homoserine lactone (C4-HSL), N-hexanoylhomoserine lactone (C6-HSL), N-octanoyl homoserine lactone (C8-HSL) and N-3-oxo-dodecanoylhomoserine lactone (3-oxo-C12-HSL) using high resolution liquid chromatography tandem mass spectrometry (LC-MS/MS). Of these detected AHLs, 3-oxo-C12-HSL was found to be the most abundant AHL produced by P. aeruginosa GB11.

Unusual multiple production of N-acylhomoserine lactones a by Burkholderia sp. strain C10B isolated from dentine caries

Bacteria realize the ability to communicate by production of quorum sensing (QS) molecules called autoinducers, which regulate the physiological activities in their ecological niches. The oral cavity could be a potential area for the presence of QS bacteria. In this study, we report the isolation of a QS bacterial isolate C10B from dentine caries. Preliminary screening using Chromobacterium violaceum CV026 biosensor showed that isolate C10B was able to produce N-acylhomoserine lactones (AHLs). This bacterium was further identified as a member of Burkholderia, an opportunistic pathogen. The isolated Burkholderia sp. was confirmed to produce N-hexanoyl-L-homoserine lactone (C6-HSL), N-octanoyl-L-homoserine lactone (C8-HSL), N-decanoyl-L-homoserine lactone (C10-HSL) and N-dodecanoyl-L-homoserine lactone (C12-HSL).

Reprint of "Assessment of marker proteins identified in whole cell extracts for bacterial speciation using liquid chromatography electrospray ionization tandem mass spectrometry"

Staphylococcal strains (CoNS) were speciated in this study. Digests of proteins released from whole cells were converted to tryptic peptides for analysis. Liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI MS/MS, Orbitrap) was employed for peptide analysis. Data analysis was performed employing the open-source software X!Tandem which uses sequenced genomes to generate a virtual peptide database for comparison to experimental data. The search database was modified to include the genomes of the 11 Staphylococcus species most commonly isolated from man. The number of total peptides matching each protein along with the number of peptides specifically matching to the homologue (or homologues) for strains of the same species were assessed. Any peptides not matching to the species examined were considered conflict peptides. The proteins typically identified with the largest percentage of sequence coverage, number of matched peptides and number of peptides corresponding to only the correct species were elongation factor Tu (EF Tu) and enolase (Enol). Additional proteins with consistently observed peptides as well as peptides matching only homologues from the same species were citrate synthase (CS) and 1-pyrroline-5-carboxylate dehydrogenase (1P5CD). Protein markers, previously identified from gel slices, (aconitate hydratase and oxoglutarate dehydrogenase) were found to provide low confidence scores when employing whole cell digests. The methodological approach described here provides a simple yet elegant way of identification of staphylococci. However, perhaps more importantly the technology should be applicable universally for identification of any bacterial species.

Assessment of marker proteins identified in whole cell extracts for bacterial speciation using liquid chromatography electrospray ionization tandem mass spectrometry

Staphylococcal strains (CoNS) were speciated in this study. Digests of proteins released from whole cells were converted to tryptic peptides for analysis. Liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI MS/MS, Orbitrap) was employed for peptide analysis. Data analysis was performed employing the open-source software X!Tandem which uses sequenced genomes to generate a virtual peptide database for comparison to experimental data. The search database was modified to include the genomes of the 11 Staphylococcus species most commonly isolated from man. The number of total peptides matching each protein along with the number of peptides specifically matching to the homologue (or homologues) for strains of the same species were assessed. Any peptides not matching to the species examined were considered conflict peptides. The proteins typically identified with the largest percentage of sequence coverage, number of matched peptides and number of peptides corresponding to only the correct species were elongation factor Tu (EF Tu) and enolase (Enol). Additional proteins with consistently observed peptides as well as peptides matching only homologues from the same species were citrate synthase (CS) and 1-pyrroline-5-carboxylate dehydrogenase (1P5CD). Protein markers, previously identified from gel slices, (aconitate hydratase and oxoglutarate dehydrogenase) were found to provide low confidence scores when employing whole cell digests. The methodological approach described here provides a simple yet elegant way of identification of staphylococci. However, perhaps more importantly the technology should be applicable universally for identification of any bacterial species.

A simple shotgun proteomics method for rapid bacterial identification

Bacterial pathogens were rapidly identified by shotgun proteomics using a novel, easy to implement database search strategy. Peptide sequence data from nano-LC-MS/MS was searched against a database represented by concatenated proteomes of completed genome sequences. Select bacterial species, including BSL-3 select agents, were used to demonstrate this method.

A gel-free proteomic-based method for the characterization of Bordetella pertussis clinical isolates

Bordetella pertussis (Bp) is the etiologic agent of pertussis or whooping cough, a highly contagious respiratory disease occurring primarily in infants and young children. Although vaccine preventable, pertussis cases have increased over the years leading researchers to re-evaluate vaccine control strategies. Since bacterial outer membrane proteins, comprising the surfaceome, often play roles in pathogenesis and antibody-mediated immunity, three recent Bp circulating isolates were examined using proteomics to identify any potential changes in surface protein expression. Fractions enriched for outer membrane proteins were digested with trypsin and the peptides analyzed by nano liquid chromatography-electrospray ionization-mass spectrometry (nLC-ESI-MS), followed by database analysis to elucidate the surfaceomes of our three Bp isolates. Furthermore, a less labor intensive non-gel based antibody affinity capture technology in conjunction with MS was employed to assess each Bp strains' immunogenic outer membrane proteins. This novel technique is generally applicable allowing for the identification of immunogenic surface expressed proteins on pertussis and other pathogenic bacteria.

Characterization of bacteria in ballast water using MALDI-TOF mass spectrometry

To evaluate a rapid and cost-effective method for monitoring bacteria in ballast water, several marine bacterial isolates were characterized by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Since International Maritime Organization (IMO) regulations are concerned with the unintended transportation of pathogenic bacteria through ballast water, emphasis was placed on detecting species of Vibrio, enterococci and coliforms. Seawater samples collected from the North Sea were incubated in steel ballast tanks and the presence of potentially harmful species of Pseudomonas was also investigated. At the genus-level, the identification of thirty six isolates using MALDI-TOF MS produced similar results to those obtained by 16S rRNA gene sequencing. No pathogenic species were detected either by 16S rRNA gene analysis or by MALDI-TOF MS except for the opportunistically pathogenic bacterium Pseudomonas aeruginosa. In addition, in house software that calculated the correlation coefficient values (CCV) of the mass spectral raw data and their variation was developed and used to allow the rapid and efficient identification of marine bacteria in ballast water for the first time.

Radiation-related changes in serum proteome profiles detected by mass spectrometry in blood of patients treated with radiotherapy due to larynx cancer

The study aimed to detect features of human serum proteome that were associated with exposure to ionizing radiation. The analyzed group consisted of 46 patients treated with radical radiotherapy for larynx cancer; patients were irradiated with total doses in a range from 51 to 72 Gy. Three consecutive blood samples were collected from each patient: before the start, 2 weeks after the start, and 4-6 weeks after the end of radiotherapy. The low-molecular-weight fraction of the serum proteome (2,000-13,000 Da) was analyzed by the MALDI-ToF mass spectrometry. Proteome profiles of serum samples collected before the start of radiotherapy and during the early stage of the treatment were similar. In marked contrast, mass profiles of serum samples collected several weeks after the end of the treatment revealed clear changes. We found that 41 out of 312 registered peptide ions changed their abundance significantly when serum samples collected after the final irradiation were compared with samples collected at the two earlier time points. We also found that abundances of certain serum peptides were associated with total doses of radiation received by patients. The results of this pilot study indicate that features of serum proteome analyzed by mass spectrometry have potential applicability as a retrospective marker of exposure to ionizing radiation.

TiO2 nanoparticle assisted mass spectrometry as biosensor of Staphylococcus aureus, key pathogen in nosocomial infections from air, skin surface and human nasal passage

For the first time, we have demonstrated the use of mass spectrometry as a biosensor for detecting a clinically important bacterium: Staphylococcus aureus in air, nasal passage and skin samples using culture-free, rapid, direct analysis via TiO(2) nanoparticles (NPs) assisted MALDI-MS. When this bacterium is predominating, the nasal passage of an individual is observed to lead to wound infections especially when the individual has a surgery or some wounds. This study indicates that even at very low concentrations of an individual bacterium can be directly detected from a mixture of bacteria using the MALDI-MS analysis without the requirement of any culturing steps or any other sample pretreatment techniques. The current approach is extremely simple, rapid, straightforward and sensitive which could be widely applied for the detection of this deadly pathogen in clinical as well as environmental samples.

Sample preparation methods for MALDI-MS profiling of bacteria

Direct matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) bacterial cell or lysate analysis appears to meet all the criteria required for a rapid and reliable analytical microorganism identification and taxonomical classification tool. Few-minute analytical procedure providing information extending up to sub-species level underlines the potential of the MALDI-MS profiling in comparison with other methods employed in the field. However, the quality of MALDI-MS profiles and consequently the performance of the method are influenced by numerous factors, which involve particular steps of the sample preparation procedure. This review is aimed at advances in development and optimization of the MALDI-MS profiling methodology. Approaches improving the quality of the MALDI-MS profiles and universal feasibility of the method are discussed.

Mass spectrometry-based analysis of therapy-related changes in serum proteome patterns of patients with early-stage breast cancer

Background

The proteomics approach termed proteome pattern analysis has been shown previously to have potential in the detection and classification of breast cancer. Here we aimed to identify changes in serum proteome patterns related to therapy of breast cancer patients.

Methods

Blood samples were collected before the start of therapy, after the surgical resection of tumors and one year after the end of therapy in a group of 70 patients diagnosed at early stages of the disease. Patients were treated with surgery either independently (26) or in combination with neoadjuvant chemotherapy (5) or adjuvant radio/chemotherapy (39). The low-molecular-weight fraction of serum proteome was examined using MALDI-ToF mass spectrometry, and then changes in intensities of peptide ions registered in a mass range between 2,000 and 14,000 Da were identified and correlated with clinical data.

Results

We found that surgical resection of tumors did not have an immediate effect on the mass profiles of the serum proteome. On the other hand, significant long-term effects were observed in serum proteome patterns one year after the end of basic treatment (we found that about 20 peptides exhibited significant changes in their abundances). Moreover, the significant differences were found primarily in the subgroup of patients treated with adjuvant therapy, but not in the subgroup subjected only to surgery. This suggests that the observed changes reflect overall responses of the patients to the toxic effects of adjuvant radio/chemotherapy. In line with this hypothesis we detected two serum peptides (registered m/z values 2,184 and 5,403 Da) whose changes correlated significantly with the type of treatment employed (their abundances decreased after adjuvant therapy, but increased in patients treated only with surgery). On the other hand, no significant correlation was found between changes in the abundance of any spectral component or clinical features of patients, including staging and grading of tumors.

Conclusions

The study establishes a high potential of MALDI-ToF-based analyses for the detection of dynamic changes in the serum proteome related to therapy of breast cancer patients, which revealed the potential applicability of serum proteome patterns analyses in monitoring the toxicity of therapy.

Methods for typing std pathogens (N. Gonorrhoeae, C. Trachomatis, T. Pallidum)

Phenotypic methods were initially used for bacterial typing yet they have a number of drawbacks limiting their use. Methods of molecular and genetic typing have become wide-spread today. Among these methods, bacterial typing based on multilocus sequence typing (Multilocus Sequence Typing - MLST) has been developing at the fastest rate. However, schemes of molecular and genetic typing of STD pathogens as compared to other bacteria are insufficiently developed, which considerably complicates the planning of measures aimed at the reduction of their spread.

Mass spectrometry-based serum proteome pattern analysis in molecular diagnostics of early stage breast cancer

Background

Mass spectrometric analysis of the blood proteome is an emerging method of clinical proteomics. The approach exploiting multi-protein/peptide sets (fingerprints) detected by mass spectrometry that reflect overall features of a specimen's proteome, termed proteome pattern analysis, have been already shown in several studies to have applicability in cancer diagnostics. We aimed to identify serum proteome patterns specific for early stage breast cancer patients using MALDI-ToF mass spectrometry.

Methods

Blood samples were collected before the start of therapy in a group of 92 patients diagnosed at stages I and II of the disease, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and the low-molecular-weight proteome fraction was examined using MALDI-ToF mass spectrometry after removal of albumin and other high-molecular-weight serum proteins. Protein ions registered in a mass range between 2,000 and 10,000 Da were analyzed using a new bioinformatic tool created in our group, which included modeling spectra as a sum of Gaussian bell-shaped curves.

Results

We have identified features of serum proteome patterns that were significantly different between blood samples of healthy individuals and early stage breast cancer patients. The classifier built of three spectral components that differentiated controls and cancer patients had 83% sensitivity and 85% specificity. Spectral components (i.e., protein ions) that were the most frequent in such classifiers had approximate m/z values of 2303, 2866 and 3579 Da (a biomarker built from these three components showed 88% sensitivity and 78% specificity). Of note, we did not find a significant correlation between features of serum proteome patterns and established prognostic or predictive factors like tumor size, nodal involvement, histopathological grade, estrogen and progesterone receptor expression. In addition, we observed a significantly (p = 0.0003) increased level of osteopontin in blood of the group of cancer patients studied (however, the plasma level of osteopontin classified cancer samples with 88% sensitivity but only 28% specificity).

Conclusion

MALDI-ToF spectrometry of serum has an obvious potential to differentiate samples between early breast cancer patients and healthy controls. Importantly, a classifier built on MS-based serum proteome patterns outperforms available protein biomarkers analyzed in blood by immunoassays.

Environmental proteomics: applications of proteome profiling in environmental microbiology and biotechnology

In this review, we present the use of proteomics to advance knowledge in the field of environmental biotechnology, including studies of bacterial physiology, metabolism and ecology. Bacteria are widely applied in environmental biotechnology for their ability to catalyze dehalogenation, methanogenesis, denitrification and sulfate reduction, among others. Their tolerance to radiation and toxic compounds is also of importance. Proteomics has an important role in helping uncover the pathways behind these cellular processes. Environmental samples are often highly complex, which makes proteome studies in this field especially challenging. Some of these challenges are the lack of genome sequences for the vast majority of environmental bacteria, difficulties in isolating bacteria and proteins from certain environments, and the presence of complex microbial communities. Despite these challenges, proteomics offers a unique dynamic view into cellular function. We present examples of environmental proteomics of model organisms, and then discuss metaproteomics (microbial community proteomics), which has the potential to provide insights into the function of a community without isolating organisms. Finally, the environmental proteomics literature is summarized as it pertains to the specific application areas of wastewater treatment, metabolic engineering, microbial ecology and environmental stress responses.

Mass spectrometry in biodefense

Potential agents for biological attacks include both microorganisms and toxins. In mass spectrometry (MS), rapid identification of potential bioagents is achieved by detecting the masses of unique biomarkers, correlated to each agent. Currently, proteins are the most reliable biomarkers for detection and characterization of both microorganisms and toxins, and MS-based proteomics is particularly well suited for biodefense applications. Confident identification of an organism can be achieved by top-down proteomics following identification of individual protein biomarkers from their tandem mass spectra. In bottom-up proteomics, rapid digestion of intact protein biomarkers is again followed by MS/MS to provide unambiguous bioagent identification and characterization. Bioinformatics obviates the need for culturing and rigorous control of experimental variables to create and use MS fingerprint libraries for various classes of bioweapons. For specific applications, MS methods, instruments and algorithms have also been developed for identification based on biomarkers other than proteins and peptides.

Tandem mass spectrometry for the detection of plant pathogenic fungi and the effects of database composition on protein inferences

LC-MS/MS has demonstrated potential for detecting plant pathogens. Unlike PCR or ELISA, LC-MS/MS does not require pathogen-specific reagents for the detection of pathogen-specific proteins and peptides. However, the MS/MS approach we and others have explored does require a protein sequence reference database and database-search software to interpret tandem mass spectra. To evaluate the limitations of database composition on pathogen identification, we analyzed proteins from cultured Ustilago maydis, Phytophthora sojae, Fusarium graminearum, and Rhizoctonia solani by LC-MS/MS. When the search database did not contain sequences for a target pathogen, or contained sequences to related pathogens, target pathogen spectra were reliably matched to protein sequences from nontarget organisms, giving an illusion that proteins from nontarget organisms were identified. Our analysis demonstrates that when database-search software is used as part of the identification process, a paradox exists whereby additional sequences needed to detect a wide variety of possible organisms may lead to more cross-species protein matches and misidentification of pathogens.

Mass spectrometry for rapid characterization of microorganisms

Advances in instrumentation, proteomics, and bioinformatics have contributed to the successful applications of mass spectrometry (MS) for detection, identification, and classification of microorganisms. These MS applications are based on the detection of organism-specific biomarker molecules, which allow differentiation between organisms to be made. Intact proteins, their proteolytic peptides, and nonribosomal peptides have been successfully utilized as biomarkers. Sequence-specific fragments for biomarkers are generated by tandem MS of intact proteins or proteolytic peptides, obtained after, for instance, microwave-assisted acid hydrolysis. In combination with proteome database searching, individual biomarker proteins are unambiguously identified from their tandem mass spectra, and from there the source microorganism is also identified. Such top-down or bottom-up proteomics approaches permit rapid, sensitive, and confident characterization of individual microorganisms in mixtures and are reviewed here. Examples of MS-based functional assays for detection of targeted microorganisms, e.g., Bacillus anthracis, in environmental or clinically relevant backgrounds are also reviewed.

Identification of bacteria using matrix-assisted laser desorption ionization time-of-flight mass spectrometry

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS or simply MALDI)1 has become ubiquitous in the identification and analysis of biomacromolecules. As a technique that allows for the molecular weight determination of otherwise nonvolatile molecules, MALDI has had a profound impact in the molecular biosciences, especially in the field of proteomics. MALDI analysis of whole organisms allows for the generation of a phenotypic profile or "molecular fingerprint;" once established, these fingerprints can be used for identification purposes.

Desorption electrospray ionization mass spectrometry of intact bacteria

Desorption electrospray ionization (DESI) mass spectrometry (MS) was used to differentiate seven bacteria species on the basis of their measured DESI-mass spectral profile. Both gram-positive and gram-negative bacteria were tested and included Escherichia coli, Staphyloccocus aureus, Enterococcus sp., Bordetella bronchiseptica, Bacillus thuringiensis, Bacillus subtilis and Salmonella typhimurium. Distinct DESI-mass spectra, in the mass range of 50-500 u, were obtained from whole bacteria in either positive or negative ion modes in less than 2 mins analysis time. Positive ion DESI-mass spectral fingerprints were compared using principal components analysis (PCA) to investigate reproducibility for the intraday and the day-to-day measurements and the method selectivity to differentiate the bacteria studied. Detailed study of variances in the assay revealed that a large contribution to the DESI-mass spectral fingerprint variation was the growth media preparation procedure. Specifically, experiments conducted with the growth media prepared using the same batch yielded highly reproducible DESI-mass spectra, both in intraday and in day-to-day analyses (i.e. one batch of growth media used over a 3-day period versus a new batch every day over the same 3-day period). Conclusions are drawn from our findings in terms of strategies for rapid biodetection with DESI-MS.

Bacterial outer membrane protein analysis by electrophoresis and microchip technology

Outer membrane proteins are indispensable components of bacterial cells and participate in several relevant functions of the microorganisms. Changes in the outer membrane protein composition might alter antibiotic sensitivity and pathogenicity. Furthermore, the effects of various factors on outer membrane protein expression, such as antibiotic treatment, mutation, changes in the environment, lipopolysaccharide modification and biofilm formation, have been analyzed. Traditionally, the outer membrane protein profile determination was performed by sodium dodecyl sulfate polyacrylamide gel electrophoresis. Converting this technique to capillary electrophoresis format resulted in faster separation, lower sample consumption and automation. Coupling capillary electrophoresis with mass spectrometry enabled the fast identification of bacterial proteins, while immediate quantitative analysis permitted the determination of up- and downregulation of certain outer membrane proteins. Adapting capillary electrophoresis to microchip format ensured a further ten- to 100-fold decrease in separation time. Application of different separation techniques combined with various sensitive detector systems has ensured further opportunities in the field of high-throughput bacterial protein analysis. This review provides an overview using selected examples of outer membrane proteins and the development and application of the electrophoretic and microchip technologies for the analysis of these proteins.

Guidelines for the validation and application of typing methods for use in bacterial epidemiology

For bacterial typing to be useful, the development, validation and appropriate application of typing methods must follow unified criteria. Over a decade ago, ESGEM, the ESCMID (Europen Society for Clinical Microbiology and Infectious Diseases) Study Group on Epidemiological Markers, produced guidelines for optimal use and quality assessment of the then most frequently used typing procedures. We present here an update of these guidelines, taking into account the spectacular increase in the number and quality of typing methods made available over the past decade. Newer and older, phenotypic and genotypic methods for typing of all clinically relevant bacterial species are described according to their principles, advantages and disadvantages. Criteria for their evaluation and application and the interpretation of their results are proposed. Finally, the issues of reporting, standardisation, quality assessment and international networks are discussed. It must be emphasised that typing results can never stand alone and need to be interpreted in the context of all available epidemiological, clinical and demographical data relating to the infectious disease under investigation. A strategic effort on the part of all workers in the field is thus mandatory to combat emerging infectious diseases, as is financial support from national and international granting bodies and health authorities.

Mass spectrometry-based proteomics for the detection of plant pathogens

Plant diseases caused by fungi, oomycetes, viruses, and bacteria are devastating both to the economy and to the food supply of a nation. Therefore, the development of new, rapid methods to identify these pathogens is a highly important area of research that is of international concern. MS-based proteomics has become a powerful and increasingly popular approach to not only identify these pathogens, but also to better understand their biology. However, there is a distinction between identifying a pathogen protein and identifying a pathogen based upon the detection of one of its proteins and this must be considered before the general application of MS for plant pathogen detection is made. There has been a recent push in the proteomics community to make data from large-scale proteomics experiments publicly available in the form of a centralized repository. Such a resource could enable the use of MS as a universal plant pathogen detection technology.