Discrimination ofFrancisella tularensissubspecies using surface enhanced laser desorption ionization mass spectrometry and multivariate data analysis

Determination of Pathogens by Electrophoretic and Spectrometric Techniques

In modern medical diagnostics, where analytical chemistry plays a key role, fast and accurate identification of pathogens is becoming increasingly important. Infectious diseases pose a growing threat to public health due to population growth, international air travel, bacterial resistance to antibiotics, and other factors. For instance, the detection of SARS-CoV-2 in patient samples is a key tool to monitor the spread of the disease. While there are several techniques for identifying pathogens by their genetic code, most of these methods are too expensive or slow to effectively analyze clinical and environmental samples that may contain hundreds or even thousands of different microbes. Standard approaches (e.g., culture media and biochemical assays) are known to be very time- and labor-intensive. The purpose of this review paper is to highlight the problems associated with the analysis and identification of pathogens that cause many serious infections. Special attention was paid to the description of mechanisms and the explanation of the phenomena and processes occurring on the surface of pathogens as biocolloids (charge distribution). This review also highlights the importance of electromigration techniques and demonstrates their potential for pathogen pre-separation and fractionation and demonstrates the use of spectrometric methods, such as MALDI-TOF MS, for their detection and identification.

Optimized MALDI TOF Mass Spectrometry Identification of Francisella tularensis Subsp. holarctica

Francisella tularensis is a tier 1 agent causing the zoonosis tularemia. This highly infectious Gram-negative bacterium is occasionally isolated from human samples (especially blood samples) in routine clinical microbiology laboratories. A rapid and accurate method for identifying this pathogen is needed in order to optimize the infected patient’s healthcare management and prevent contamination of the laboratory personnel. MALDI TOF mass spectrometry has become the gold standard for the rapid identification of most human pathogens. However, F. tularensis identification using such technology and commercially available databases is currently considered unreliable. Real-time PCR-based methods for rapid detection and accurate identification of F. tularensis are not available in many laboratories. As a national reference center for tularemia, we developed a MALDI TOF database allowing accurate identification of the species F. tularensis and its differentiation from the closely related neighbor species F. tularensis subsp. novicida and F. philomiragia. The sensitivity and specificity of this database were validated by testing 71 F. tularensis strains and 165 strains from 63 species not belonging to the Francisella genus. We obtained accurate identification at the species level and differentiation of all the tested bacterial strains. In particular, F. tularensis could be accurately differentiated from other small Gram-negative bacilli occasionally isolated from human samples, including species of the HACEK group and Brucella melitensis.

Biotechnological innovations in farm and pet animal disease diagnosis

The application of innovative diagnostic technologies for the detection of animal pathogens at an early stage is essential in restricting the economic loss incurred due to emerging infectious animal diseases. The desirable characteristics of such diagnostic methods are easy to use, cost-effective, highly sensitive, and specific, coupled with the high-throughput detection capabilities. The enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) are still the most common assays used for the detection of animal pathogens across the globe. However, utilizing the principles of ELISA and PCR, several serological and molecular technologies have been developed to achieve higher sensitivity, rapid, and point-of-care (POC) detection such as lateral flow assays, biosensors, loop-mediated isothermal amplification, recombinase polymerase amplification, and molecular platforms for field-level detection of animal pathogens. Furthermore, animal disease diagnostics need to be updated regularly to capture new, emerging and divergent infectious pathogens, and biotechnological innovations are helpful in fulfilling the rising demand for such diagnostics for the welfare of the society. Therefore, this chapter primarily describes and discusses in detail the serological, molecular, novel high-throughput, and POC assays to detect pathogens affecting farm and companion animals.

Rapid Identification and Characterization of Francisella by Molecular Biology and Other Techniques

Francisella tularensis is the causative pathogen of tularemia and a Tier 1 bioterror agent on the CDC list. Considering the fact that some subpopulation of the F. tularensis strains is more virulent, more significantly associated with mortality, and therefore poses more threat to humans, rapid identification and characterization of this subpopulation strains is of invaluable importance. This review summarizes the up-to-date developments of assays for mainly detecting and characterizing F. tularensis and a touch of caveats of some of the assays.

Bioterrorism and the Role of the Clinical Microbiology Laboratory

Regular review of the management of bioterrorism is essential for maintaining readiness for these sporadically occurring events. This review provides an overview of the history of biological disasters and bioterrorism. I also discuss the recent recategorization of tier 1 agents by the U.S. Department of Health and Human Services, the Laboratory Response Network (LRN), and specific training and readiness processes and programs, such as the College of American Pathologists (CAP) Laboratory Preparedness Exercise (LPX). LPX examined the management of cultivable bacterial vaccine and attenuated strains of tier 1 agents or close mimics. In the LPX program, participating laboratories showed improvement in the level of diagnosis required and referral of isolates to an appropriate reference laboratory. Agents which proved difficult to manage in sentinel laboratories included the more fastidious Gram-negative organisms, especially Francisella tularensis and Burkholderia spp. The recent Ebola hemorrhagic fever epidemic provided a check on LRN safety processes. Specific guidelines and recommendations for laboratory safety and risk assessment in the clinical microbiology are explored so that sentinel laboratories can better prepare for the next biological disaster.

MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis

Currently microorganisms are best identified using 16S rRNA and 18S rRNA gene sequencing. However, in recent years matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has emerged as a potential tool for microbial identification and diagnosis. During the MALDI-TOF MS process, microbes are identified using either intact cells or cell extracts. The process is rapid, sensitive, and economical in terms of both labor and costs involved. The technology has been readily imbibed by microbiologists who have reported usage of MALDI-TOF MS for a number of purposes like, microbial identification and strain typing, epidemiological studies, detection of biological warfare agents, detection of water- and food-borne pathogens, detection of antibiotic resistance and detection of blood and urinary tract pathogens etc. The limitation of the technology is that identification of new isolates is possible only if the spectral database contains peptide mass fingerprints of the type strains of specific genera/species/subspecies/strains. This review provides an overview of the status and recent applications of mass spectrometry for microbial identification. It also explores the usefulness of this exciting new technology for diagnosis of diseases caused by bacteria, viruses, and fungi.

Rapid high-throughput characterisation, classification and selection of recombinant mammalian cell line phenotypes using intact cell MALDI-ToF mass spectrometry fingerprinting and PLS-DA modelling

Despite many advances in the generation of high producing recombinant mammalian cell lines over the last few decades, cell line selection and development is often slowed by the inability to predict a cell line's phenotypic characteristics (e.g. growth or recombinant protein productivity) at larger scale (large volume bioreactors) using data from early cell line construction at small culture scale. Here we describe the development of an intact cell MALDI-ToF mass spectrometry fingerprinting method for mammalian cells early in the cell line construction process whereby the resulting mass spectrometry data are used to predict the phenotype of mammalian cell lines at larger culture scale using a Partial Least Squares Discriminant Analysis (PLS-DA) model. Using MALDI-ToF mass spectrometry, a library of mass spectrometry fingerprints was generated for individual cell lines at the 96 deep well plate stage of cell line development. The growth and productivity of these cell lines were evaluated in a 10L bioreactor model of Lonza's large-scale (up to 20,000L) fed-batch cell culture processes. Using the mass spectrometry information at the 96 deep well plate stage and phenotype information at the 10L bioreactor scale a PLS-DA model was developed to predict the productivity of unknown cell lines at the 10L scale based upon their MALDI-ToF fingerprint at the 96 deep well plate scale. This approach provides the basis for the very early prediction of cell lines' performance in cGMP manufacturing-scale bioreactors and the foundation for methods and models for predicting other mammalian cell phenotypes from rapid, intact-cell mass spectrometry based measurements.

Phenotypic and genotypic properties of Microbacterium yannicii, a recently described multidrug resistant bacterium isolated from a lung transplanted patient with cystic fibrosis in France

BACKGROUND

Cystic fibrosis (CF) lung microbiota consists of diverse species which are pathogens or opportunists or have unknown pathogenicity. Here we report the full characterization of a recently described multidrug resistant bacterium, Microbacterium yannicii, isolated from a CF patient who previously underwent lung transplantation.

RESULTS

Our strain PS01 (CSUR-P191) is an aerobic, rod shaped, non-motile, yellow pigmented, gram positive, oxidase negative and catalase positive bacterial isolate. Full length 16S rRNA gene sequence showed 98.8% similarity with Microbacterium yannicii G72T type strain, which was previously isolated from Arabidopsis thaliana. The genome size is 3.95Mb, with an average G+C content of 69.5%. In silico DNA-DNA hybridization analysis between our Microbacterium yannicii PS01isolate in comparison with Microbacterium testaceum StLB037 and Microbacterium laevaniformans OR221 genomes revealed very weak relationship with only 28% and 25% genome coverage, respectively. Our strain, as compared to the type strain, was resistant to erythromycin because of the presence of a new erm 43 gene encoding a 23S rRNA N-6-methyltransferase in its genome which was not detected in the reference strain. Interestingly, our patient received azithromycin 250 mg daily for bronchiolitis obliterans syndrome for more than one year before the isolation of this bacterium.

CONCLUSIONS

Although significance of isolating this bacterium remains uncertain in terms of clinical evolution, this bacterium could be considered as an opportunistic human pathogen as previously reported for other species in this genus, especially in immunocompromised patients.

MALDI TOF MS profiling of bacteria at the strain level: a review

Since the advent of the use of matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry (TOF MS) as a tool for microbial characterization, efforts to increase the taxonomic resolution of the approach have been made. The rapidity and efficacy of the approach have suggested applications in counter-bioterrorism, prevention of food contamination, and monitoring the spread of antibiotic-resistant bacteria. Strain-level resolution has been reported with diverse bacteria, using library-based and bioinformatics-enabled approaches. Three types of characterization at the strain level have been reported: strain categorization, strain differentiation, and strain identification. Efforts to enhance the library-based approach have involved sample pre-treatment and data reduction strategies. Bioinformatics approaches have leveraged the ever-increasing amount of publicly available genomic and proteomic data to attain strain-level characterization. Bioinformatics-enabled strategies have facilitated strain characterization via intact biomarker identification, bottom-up, and top-down approaches. Rigorous quantitative and advanced statistical analyses have fostered success at the strain level with both approaches. Library-based approaches can be limited by effects of sample preparation and culture conditions on reproducibility, whereas bioinformatics-enabled approaches are typically limited to bacteria, for which genetic and/or proteomic data are available. Biological molecules other than proteins produced in strain-specific manners, including lipids and lipopeptides, might represent other avenues by which strain-level resolution might be attained. Immunological and lectin-based chemistries have shown promise to enhance sensitivity and specificity. Whereas the limits of the taxonomic resolution of MALDI TOF MS profiling of bacteria appears bacterium-specific, recent data suggest that these limits might not yet have been reached.

Application of matrix-assisted laser desorption ionization-time of flight mass spectrometry for discrimination of Escherichia strains possessing highly conserved ribosomal RNA gene sequences

We evaluated the capability of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) to discriminate twelve Escherichia strains: E. blattae, E. fergusonii, E. hermanii and nine E. coli, whose ribosomal RNA (rRNA) gene sequence homologies are in the range of 96-100%. Similarities obtained by MALDI-TOF MS were found to be 78-92% among the E. coli strains, and 74% between E. coli and E. fergusonii. E. blattae and E. hermanii showed only 32% similarity when compared to the other species. Thus, MALDI-TOF MS provides capability of distinguishing bacterial species or even strains possessing highly conserved rRNA gene sequences.

SELDI-TOF MS analysis of alkylphenol exposed Atlantic cod with phenotypic variation in gonadosomatic index

Proteomics is a new and promising approach to evaluate potential effects of pollution. In order to investigate if there is a direct link between the protein expression profiles obtained by the SELDI-TOF MS technology and effects observed at the organism level in fish, plasma samples from unexposed and 20 ppb alkylphenol exposed female Atlantic cod (Gadus morhua) with high phenotypic variation in gonadosomatic index (GSI) were analyzed by SELDI-TOF MS. Principle component analysis (PCA) showed that the major proteomic variation present in the dataset (i.e. 23.6%) could be significantly correlated to the individual variation in GSI, which indicates that SELDI-TOF MS data can reflect effects observed at higher levels of organization in fish. Further exploration of the other principal components revealed an additional proteomic pattern specific for the alkylphenol exposed females. Hence, this study supports the usefulness of SELDI-TOF MS as a proteomic tool in ecotoxicological research.

Advances in mass spectrometry for the identification of pathogens

Mass spectrometry (MS) has become an important technique to identify microbial biomarkers. The rapid and accurate MS identification of microorganisms without any extensive pretreatment of samples is now possible. This review summarizes MS methods that are currently utilized in microbial analyses. Affinity methods are effective to clean, enrich, and investigate microorganisms from complex matrices. Functionalized magnetic nanoparticles might concentrate traces of target microorganisms from sample solutions. Therefore, nanoparticle-based techniques have a favorable detection limit. MS coupled with various chromatographic techniques, such as liquid chromatography and capillary electrophoresis, reduces the complexity of microbial biomarkers and yields reliable results. The direct analysis of whole pathogenic microbial cells with matrix-assisted laser desorption/ionization MS without sample separation reveals specific biomarkers for taxonomy, and has the advantages of simplicity, rapidity, and high-throughput measurements. The MS detection of polymerase chain reaction (PCR)-amplified microbial nucleic acids provides an alternative to biomarker analysis. This review will conclude with some current applications of MS in the identification of pathogens.

Comparative SELDI-TOF-MS profiling of low-molecular-mass proteins from Lignosus rhinocerus (Cooke) Ryvarden grown under stirred and static conditions of liquid fermentation

Mushrooms are considered as important source of biologically active compounds which include low-molecular-mass protein/peptides (LMMP). In this study, we attempted to profile the LMMP from Lignosus rhinocerus, a wild medicinal mushroom, grown by static cultures (SC) and in stirred tank reactor (STR). Crude water extract (CWE) and protein fractions were profiled using H50 ProteinChip® arrays and SELDI-TOF-MS. Three protein peaks of 5.8, 6.9 and 9.1 kDa were found to be common to spectra of L. rhinocerus CWE from both culture conditions. Partial protein purification has resulted in detection of more peaks in the spectra of protein fractions. For protein fractions of L. rhinocerus cultured in STR, most peaks were observed in the range of 3-8 kDa whereas some peaks with molecular mass up to 14.3 kDa were noted in spectra of protein fractions from SC. Our results have demonstrated the optimization of profiling method using SELDI-TOF-MS for fungal LMMP.

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.

Identification of pathogens by mass spectrometry

BACKGROUND

Mass spectrometry (MS) is a suitable technology for microorganism identification and characterization.

CONTENT

This review summarizes the MS-based methods currently used for the analyses of pathogens. Direct analysis of whole pathogenic microbial cells using MS without sample fractionation reveals specific biomarkers for taxonomy and provides rapid and high-throughput capabilities. MS coupled with various chromatography- and affinity-based techniques simplifies the complexity of the signals of the microbial biomarkers and provides more accurate results. Affinity-based methods, including those employing nanotechnology, can be used to concentrate traces of target microorganisms from sample solutions and, thereby, improve detection limits. Approaches combining amplification of nucleic acid targets from pathogens with MS-based detection are alternatives to biomarker analyses. Many data analysis methods, including multivariate analysis and bioinformatics approaches, have been developed for microbial identification. The review concludes with some current clinical applications of MS in the identification and typing of infectious microorganisms, as well as some perspectives.

SUMMARY

Advances in instrumentation (separation and mass analysis), ionization techniques, and biological methodologies will all enhance the capabilities of MS for the analysis of pathogens.

Identification of Francisella tularensis by whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry: fast, reliable, robust, and cost-effective differentiation on species and subspecies levels

Francisella tularensis, the causative agent of tularemia, is a potential agent of bioterrorism. The phenotypic discrimination of closely related, but differently virulent, Francisella tularensis subspecies with phenotyping methods is difficult and time-consuming, often producing ambiguous results. As a fast and simple alternative, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) was applied to 50 different strains of the genus Francisella to assess its ability to identify and discriminate between strains according to their designated species and subspecies. Reference spectra from five representative strains of Francisella philomiragia, Francisella tularensis subsp. tularensis, Francisella tularensis subsp. holarctica, Francisella tularensis subsp. mediasiatica, and Francisella tularensis subsp. novicida were established and evaluated for their capability to correctly identify Francisella species and subspecies by matching a collection of spectra from 45 blind-coded Francisella strains against a database containing the five reference spectra and 3,287 spectra from other microorganisms. As a reference method for identification of strains from the genus Francisella, 23S rRNA gene sequencing was used. All strains were correctly identified, with both methods showing perfect agreement at the species level as well as at the subspecies level. The identification of Francisella strains by MALDI-TOF MS and subsequent database matching was reproducible using biological replicates, different culture media, different cultivation times, different serial in vitro passages of the same strain, different preparation protocols, and different mass spectrometers.

Rapid identification of Staphylococcus aureus by surface enhanced laser desorption and ionization time of flight mass spectrometry

Staphylococcus aureus (S. aureus), a vital nosocomial pathogen, is responsible for several diseases. With the increasing isolation rate in clinical specimens, rapid identification of this bacterial species is required. But present identification via conventional methods is time-consuming and lacks accuracy. The purpose of the current study was to evaluate the use of surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF MS) for rapid identification of S. aureus. A total of 120 clinical isolates of S. aureus and 153 non-S. aureus species were identified by conventional methods, and the species nature of all staphylococci was further confirmed by 16S rDNA sequencing. All strains observed were analyzed by SELDI-TOF MS. An identification model for S. aureus was developed and validated by an artificial neural network. The model based on 6 protein peaks exhibited a sensitivity of 98.4% and specificity of 98.6%. This strategy has the potential for rapid identification of S. aureus.

Rapid identification of Staphylococci isolated in clinical microbiology laboratories by matrix-assisted laser desorption ionization-time of flight mass spectrometry

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) of intact bacteria yields a reproducible spectrum depending upon growth conditions, strain, or species. Using whole viable bacteria we describe here the application of MALDI-TOF-MS to the identification of coagulase-negative staphylococci (CoNS). Our aim was, once a bacterium has been recognized as Micrococcaceae, to identify peaks in the spectrum that can be used to identify the species or subspecies. MALDI-TOF-MS was performed using bacteria obtained from one isolated colony. One reference strain for each of the 23 clinically relevant species or subspecies of Micrococcaceae was selected. For each reference strain, the MALDI-TOF-MS profile of 10 colonies obtained from 10 different passages was analyzed. For each strain, only peaks that were conserved in the spectra of all 10 isolated colonies and with a relative intensity above 0.1 were retained, thus leading to a set of 3 to 14 selected peaks per strain. The MALDI-TOF-MS profile of 196 tested strains was then compared with that of the set of selected peaks of each of the 23 reference strains. In all cases the best hit was with the set of peaks of the reference strain belonging to the same species as that of the tested strain, thus demonstrating that the 23 sets of selected peaks can be used as a database for the rapid species identification of CoNS. Similar results were obtained using four different growth conditions. Extending this strategy to other groups of relevant pathogenic bacteria will allow rapid bacterial identification.

Bioinformatics approaches in clinical proteomics

Protein expression profiling is increasingly being used to discover, validate and characterize biomarkers that can potentially be used for diagnostic purposes and to aid in pharmaceutical development. Correct analysis of data obtained from these experiments requires an understanding of the underlying analytic procedures used to obtain the data, statistical principles underlying high-dimensional data and clinical statistical tools used to determine the utility of the interpreted data. This review summarizes each of these steps, with the goal of providing the nonstatistician proteomics researcher with a working understanding of the various approaches that may be used by statisticians. Emphasis is placed on the process of mining high-dimensional data to identify a specific set of biomarkers that may be used in a diagnostic or other assay setting.

Strain and phase identification of the U.S. category B agent Coxiella burnetii by matrix assisted laser desorption/ionization time-of-flight mass spectrometry and multivariate pattern recognition

Accurate bacterial identification is important in diagnosing disease and in microbial forensics. Coxiella burnetii, a highly infective microorganism causative of the human disease Q fever, is now considered a U.S. category B potential bioterrorism agent. We report here an approach for the confirmatory identification of C. burnetii at the strain level which involves the combined use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and supervised pattern recognition via Partial Least Squares-Discriminant Analysis (PLS-DA). C. burnetii isolates investigated in this study included the following prototype strains from different geographical and/or historical origins and with different antigenic properties: Nine Mile I, Australian QD, M44, KAV, PAV, Henzerling, and Ohio. After culture and purification following standard protocols, linear MALDI-TOF mass spectra of pure bacterial cultures were acquired in positive ion mode. Mass spectral data were normalized, baseline-corrected, denoised, binarized and modeled by PLS-DA under crossvalidation conditions. Robustness with respect to uncontrolled variations in the sample preparation and MALDI analysis protocol was assessed by repeating the experiment on five different days spanning a period of 6 months. The method was validated by the prediction of unknown C. burnetii samples in an independent test set with 100% sensitivity and specificity for five out of six strain classes.

Genomics and proteomics of bone cancer

Although the control of bone metastasis has been the focus of intensive investigation, relatively little is known about the molecular mechanisms that regulate or predict the process, even though widespread skeletal dissemination is an important step in the progression of many tumors. As a result, understanding the complex interactions contributing to the metastatic behavior of tumor cells is essential for the development of effective therapies. Using a state-of-the-art combination of gene expression profiling and functional annotation of human tumor cells, and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry of patient serum, we have shown that changes in tumor biochemistry correlate with disease progression and help to define the aggressive tumor phenotype. Based on these approaches, it is apparent that the metastatic phenotype of tumor cells is extremely complex. The identification of the phenotype of tumor cells has benefited greatly from the application of gene expression profiling (microarray analysis). This technology has been used by many investigators to identify changes in gene expression and cytokine and growth factor elaboration (such as interleukin 8). The tumor phenotype(s) presumably also include changes in the cell surface carbohydrate profile (via altered glycosyltransferase expression) and heparan sulfate expression (via increased heparanase activity), to name but a few. These specific alterations in gene expression, identified by functional annotation of accumulated microarray data, have been validated using a variety of approaches. Collectively, the data described here suggest that each of these activities is associated with distinct aspects of the aggressive tumor cell phenotype. Collectively, the data suggest that multiple factors constitute the complex phenotype of metastatic tumor cells. In particular, the differences observed in gene expression profiles and serum protein biomarkers play a critical role in defining the mechanisms responsible for bone-specific colonization and growth of tumors in bone. Future studies will identify the mechanisms that participate in the formation of secondary tumor growths of cancers in bone.

Clinicopathologic aspects of animal and zoonotic diseases of bioterrorism

We live in an era of emerging infectious diseases and the threat of bioterrorism. Most of the infectious agents of modern concern, from plague to avian influenza H5N1, are zoonotic diseases: infectious agents that reside in quiet animal reservoir cycles that are transmitted occasionally to humans. The public health, health care, and veterinary communities have an enormous challenge in the early recognition, reporting, treatment, and prevention of zoonotic diseases. An intimate understanding of the natural ecology, geographic distribution, clinical signs, lesions, and diagnosis of these diseases is essential for the early recognition and control of these diseases.

Immunoproteomic characterization of Brucella abortus 1119-3 preparations used for the serodiagnosis of Brucella infections

The diagnosis of brucellosis is mainly based on the detection of anti-LPS antibodies. Due to substantial similarity of the O-polysaccharide of Brucella LPS to that of various other Gram-negative bacteria, serological tests of samples containing high amounts of LPS lack specificity. Hence, the development of assays based on more specific protein antigens is an essential subject in brucellosis research. The aim of this study was proteomic characterization of various antigen preparations of the diagnostic reference strain Brucella abortus 1119-3 and the identification of immunogenic proteins suitable for serological assays. Seventeen out of 383 protein spots of B. abortus 1119-3 were identified to be immunogenic by 2-D immunoblotting. These immunogenic spots were assigned to 6 proteins by MALDI-MS and nLC-ESI-MS/MS: Cu-Zn SOD, BCSP31, L7/L12, GroEL, GroES, and DnaK. All immunogenic proteins were present in three different antigen preparations investigated, i.e. native antigen, standard agglutination and commercially available agglutination antigen. 2-D immunoblotting of bacteria cross-reacting with Brucellae in agglutination tests proved that cross-reactivity of proteins is negligible. Surface enhanced laser desorption/ionization mass spectrometry (SELDI-MS) spectra also differentiated B. abortus clearly from cross-reacting bacteria. The combination of SELDI-MS analysis with the specificity of antibody binding will improve the identification of Brucella specific immunogenic proteins.