Proteogenomic analysis of Mycobacterium tuberculosis by high resolution mass spectrometry

The genome sequencing of H37Rv strain of Mycobacterium tuberculosis was completed in 1998 followed by the whole genome sequencing of a clinical isolate, CDC1551 in 2002. Since then, the genomic sequences of a number of other strains have become available making it one of the better studied pathogenic bacterial species at the genomic level. However, annotation of its genome remains challenging because of high GC content and dissimilarity to other model prokaryotes. To this end, we carried out an in-depth proteogenomic analysis of the M. tuberculosis H37Rv strain using Fourier transform mass spectrometry with high resolution at both MS and tandem MS levels. In all, we identified 3176 proteins from Mycobacterium tuberculosis representing ~80% of its total predicted gene count. In addition to protein database search, we carried out a genome database search, which led to identification of ~250 novel peptides. Based on these novel genome search-specific peptides, we discovered 41 novel protein coding genes in the H37Rv genome. Using peptide evidence and alternative gene prediction tools, we also corrected 79 gene models. Finally, mass spectrometric data from N terminus-derived peptides confirmed 727 existing annotations for translational start sites while correcting those for 33 proteins. We report creation of a high confidence set of protein coding regions in Mycobacterium tuberculosis genome obtained by high resolution tandem mass-spectrometry at both precursor and fragment detection steps for the first time. This proteogenomic approach should be generally applicable to other organisms whose genomes have already been sequenced for obtaining a more accurate catalogue of protein-coding genes.     

Quantitative evaluation of cryptococcal pathogenesis and antifungal drugs using a silkworm infection model with Cryptococcus neoformans

Aims: To develop an in vivo system that could quantitatively evaluate the therapeutic effects of antifungal drugs using a silkworm infection model with Cryptococcus neoformans. Methods and Results: Silkworms reared at 37°C died after an injection of viable serotype A C. neoformans fungus into the haemolymph. The serotype A C. neoformans, which is known to have higher mammal pathogenicity than the serotype D, was also more virulent against the silkworm. Furthermore, the deletion mutants of genes gpa1, pka1 and cna1, which are genes known to be necessary for the pathogenesis in mammals, showed an increase in the number of fungal cells necessary to kill half of the silkworm population (LD₅₀ value). Antifungal drugs, amphotericin B, flucytosine, fluconazole and ketoconazole, showed therapeutic effects in silkworms infected with C. neoformans. However, amphotericin B was not therapeutically effective when injected into the silkworm intestine, comparable to the fact that amphotericin B is not absorbed by the intestine in mammals. Conclusions: The silkworm–C. neoformans infection model is useful for evaluating the therapeutic effects of antifungal drugs. Significance and Impact of the Study: The silkworm infection model has various advantages for screening antifungal drug candidates. We can also elucidate the cryptococcal pathogenesis and evaluate the in vivo pharmacokinetics and toxicity of each drug.     

An optimized protocol for metabolome analysis in yeast using direct infusion electrospray mass spectrometry

A method for the global analysis of yeast intracellular metabolites, based on electrospray mass spectrometry (ES-MS), has been developed. This has involved the optimization of methods for quenching metabolism in Saccharomyces cerevisiae and extracting the metabolites for analysis by positive-ion electrospray mass spectrometry. The influence of cultivation conditions, sampling, quenching and extraction conditions, concentration step, and storage have all been studied and adapted to allow direct infusion of samples into the mass spectrometer and the acquisition of metabolic profiles with simultaneous detection of more than 25 intracellular metabolites. The method, which can be applied to other micro-organisms and biological systems, may be used for comparative analysis and screening of metabolite profiles of yeast strains and mutants under controlled conditions in order to elucidate gene function via metabolomics. Examples of the application of this analytical strategy to specific yeast strains and single-ORF yeast deletion mutants generated through the EUROFAN programme are presented.     

Comparative analysis of the intergenic spacer regions and population structure of the species complex of the pathogenic yeast Cryptococcus neoformans

Cryptococcus neoformans is an opportunistic basidiomycete responsible for the high incidence of cryptococcosis in patients with AIDS and in other immune-compromised individuals. This study, which focused on the molecular structure and genetic variability of the two varieties in the C. neoformans and Cryptococcus gattii species complex, employed sequence analysis of the intergenic spacer regions, IGSI and IGSII. The IGS region is the most rapidly evolving region of the rDNA families. The IGSI displayed the most genetic variability represented by nucleotide base substitutions and the presence of long insertions/deletions (indels). In contrast, the IGSII region exhibited less heterogeneity and the indels were not as extensive as those displayed in the IGSI region. Both intergenic spacers contained short, interspersed repeat motifs, which can be related to length polymorphisms observed between sequences. Phylogenetic analysis undertaken in the IGSI, IGSII and IGSI +5S rRNA + IGSII regions revealed the presence of six major phylogenetic lineages, some of which segregated into subgroups. The major lineages are represented by genotypes 1 (C. neoformans var. grubii), genotype 2 (C. neoformans var. neoformans), and genotypes 3, 4, 5 and 6 represented by C. gattii. Genotype 6 is a newly described IGS genotypic group within the C. neoformans species complex. With the inclusion of IGS subgenotypic groups, our sequence analysis distinguished 12 different lineages. Sequencing of clones, which was performed to determine the presence of multiple alleles at the IGS locus in several hybrid strains, yielded a single IGS sequence type per isolate, thus suggesting that the selected group of cloned strains was mono-allelic at this locus. IGS sequence analyses proved to be a powerful technique for the delineation of the varieties of C. neoformans and C. gattii at genotypic and subgenotypic levels.     

Characterization of quillaja bark extracts and evaluation of their purity using liquid chromatography–high resolution mass spectrometry

In the course of development of semi-preparative liquid chromatographic methods for the isolation of individual quillaja saponins from Quillaja saponaria (L.), some commercially available quillaja bark extracts revealed a distinctive and characteristic pattern of additional peaks in the chromatogram that could not be attributed to saponins commonly present in quillaja. To identify these peaks, analytical procedures based on HPLC coupled with high resolution MS detection were optimized which allowed the identification of the additional saponins Mi saponin A, Mi saponin B, Mi saponin C, madhucoside A and madhucoside B. These compounds are known to be the main saponins of the Indian plant Madhuca longifolia (L.). Tandem MS experiments were performed for the unambiguous assignment of the sapogenin. Madhuca saponins yielded a characteristic fragment of protobassic acid, whereas quillaja saponins showed a fragment of quillaic acid as expected. In addition, samples from madhuca seed kernels were analysed to verify the origin of the characteristic chromatographic peak pattern observed frequently in commercially available quillaja bark extracts.     

Comprehensive characterisation of the heterogeneity of adalimumab via charge variant analysis hyphenated on-line to native high resolution Orbitrap mass spectrometry

Charge variant analysis is a widely used tool to monitor changes in product quality during the manufacturing process of monoclonal antibodies (mAbs). Although it is a powerful technique for revealing mAb heterogeneity, an unexpected outcome, for example the appearance of previously undetected isoforms, requires further, time-consuming analysis. The process of identifying these unknowns can also result in unwanted changes to the molecule that are not attributable to the manufacturing process. To overcome this, we recently reported a method combining highly selective cation exchange chromatography-based charge variant analysis with on-line mass spectrometric (MS) detection. We further explored and adapted the chromatographic buffer system to expand the application range. Moreover, we observed no salt adducts on the native protein, also supported by the optimal choice of MS parameters, resulting in increased data quality and mass accuracy. Here, we demonstrate the utility of this improved method by performing an in-depth analysis of adalimumab before and after forced degradation. By combining molecular mass and retention time information, we were able to identify multiple modifications on adalimumab, including lysine truncation, glycation, deamidation, succinimide formation, isomerisation, N-terminal aspartic acid loss or C-terminal proline amidation and fragmentation along with the N-glycan distribution of each of these identified proteoforms. Host cell protein (HCP) analysis was performed using liquid chromatography-mass spectrometry that verified the presence of the protease Cathepsin L. Based on the presence of trace HCPs with catalytic activity, it can be questioned if fragmentation is solely driven by spontaneous hydrolysis or possibly also by enzymatic degradation.     

Measurement of pyrethroid,organophosphorus, and carbamate insecticides in human plasma using isotope dilution gas chromatography–high resolution mass spectrometry

We have developed a gas chromatography–high resolution mass spectrometry method for measuring pyrethroid, organophosphorus, carbamate and fipronil pesticides and the synergist piperonyl butoxide in human plasma. Plasma samples were extracted using solid phase extraction and were then concentrated for injection and analysis using isotope dilution gas chromatography–high resolution mass spectrometry. The limits of detection ranged from 10 to 158 pg/mL with relative recoveries at concentrations near the LODs (e.g., 25 or 250 pg/mL) ranging from 87% to 156% (9 of the 16 compounds were within ±15% of 100%). The extraction recoveries ranged from 20% to 98% and the overall method relative standard deviations were typically less than 20% with some exceptions. Analytical characteristics were determined at 25, 250, and 1000 pg/mL.     

Separation and identification of mouse brain tissue microproteins using top‐down method with high resolution nanocapillary liquid chromatography mass spectrometry

Microproteins and endogenous peptides in the brain contain important substances that have critical roles in diverse biological processes, contributing to signal transduction and intercellular signaling. However, variability in their physical or chemical characteristics, such as molecule size, hydrophobicity, and charge states, complicate the simultaneous analysis of these compounds, although this would be highly beneficial for the field of neuroscience research. Here, we present a top‐down analytical method for simultaneous analysis of microproteins and endogenous peptides using high‐resolution nanocapillary LC‐MS/MS. This method is detergent‐free and digestion‐free, which allows for extracting and preserving intact microproteins and peptides for direct LC‐MS analysis. Both higher energy collision dissociation and electron‐transfer dissociation fragmentations were used in the LC‐MS analysis to increase the identification rate, and bioinformatics tools ProteinGoggle and PEAKS Studio software were utilized for database search. In total, we identified 471 microproteins containing 736 proteoforms, including brain‐derived neurotrophic factor and a number of fibroblast growth factors. In addition, we identified 599 peptides containing 151 known or potential neuropeptides such as somatostatin‐28 and neuropeptide Y. Our approach bridges the gap for the characterization of brain microproteins and peptides, which permits quantification of a diversity of signaling molecules for biomarker discovery or therapy diagnosis in the future.