Subtyping of hepatitis C virus with high resolution mass spectrometry
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PROVIDER: S-EPMC11322781 | biostudies-literature | 2017 Jan
REPOSITORIES: biostudies-literature
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Project description:Hepatitis B virus (HBV) is a major human pathogen. In addition to its importance in human health, there is growing interest in adapting HBV and other viruses for drug delivery and other nanotechnological applications. In both contexts, precise biophysical characterization of these large macromolecular particles is fundamental. HBV capsids are unusual in that they exhibit two distinct icosahedral geometries, nominally composed of 90 and 120 dimers with masses of approximately 3 and approximately 4 MDa, respectively. Here, a mass spectrometric approach was used to determine the masses of both capsids to within 0.1%. It follows that both lattices are complete, consisting of exactly 180 and 240 subunits. Nanoindentation experiments by atomic-force microscopy indicate that both capsids have similar stabilities. The data yielded a Young's modulus of approximately 0.4 GPa. This experimental approach, anchored on very precise and accurate mass measurements, appears to hold considerable potential for elucidating the assembly of viruses and other macromolecular particles.
| S-EPMC2453694 | biostudies-literature
Project description:Native mass spectrometry (MS) involves the analysis and characterization of macromolecules, predominantly intact proteins and protein complexes, whereby as much as possible the native structural features of the analytes are retained. As such, native MS enables the study of secondary, tertiary, and even quaternary structure of proteins and other biomolecules. Native MS represents a relatively recent addition to the analytical toolbox of mass spectrometry and has over the past decade experienced immense growth, especially in enhancing sensitivity and resolving power but also in ease of use. With the advent of dedicated mass analyzers, sample preparation and separation approaches, targeted fragmentation techniques, and software solutions, the number of practitioners and novel applications has risen in both academia and industry. This review focuses on recent developments, particularly in high-resolution native MS, describing applications in the structural analysis of protein assemblies, proteoform profiling of─among others─biopharmaceuticals and plasma proteins, and quantitative and qualitative analysis of protein-ligand interactions, with the latter covering lipid, drug, and carbohydrate molecules, to name a few.
| S-EPMC9052423 | biostudies-literature
Project description:Hepatitis C virus (HCV) is classified into seven major genotypes and 67 subtypes. Recent studies have shown that in HCV genotype 1-infected patients, response rates to regimens containing direct-acting antivirals (DAAs) are subtype dependent. Currently available genotyping methods have limited subtyping accuracy. We have evaluated the performance of a deep-sequencing-based HCV subtyping assay, developed for the 454/GS-Junior platform, in comparison with those of two commercial assays (Versant HCV genotype 2.0 and Abbott Real-time HCV Genotype II) and using direct NS5B sequencing as a gold standard (direct sequencing), in 114 clinical specimens previously tested by first-generation hybridization assay (82 genotype 1 and 32 with uninterpretable results). Phylogenetic analysis of deep-sequencing reads matched subtype 1 calling by population Sanger sequencing (69% 1b, 31% 1a) in 81 specimens and identified a mixed-subtype infection (1b/3a/1a) in one sample. Similarly, among the 32 previously indeterminate specimens, identical genotype and subtype results were obtained by direct and deep sequencing in all but four samples with dual infection. In contrast, both Versant HCV Genotype 2.0 and Abbott Real-time HCV Genotype II failed subtype 1 calling in 13 (16%) samples each and were unable to identify the HCV genotype and/or subtype in more than half of the non-genotype 1 samples. We concluded that deep sequencing is more efficient for HCV subtyping than currently available methods and allows qualitative identification of mixed infections and may be more helpful with respect to informing treatment strategies with new DAA-containing regimens across all HCV subtypes.
| S-EPMC4290919 | biostudies-literature
Project description:Matrix-assisted ionization (MAI) is demonstrated to be a robust and sensitive analytical method capable of analyzing proteins such as cholera toxin B-subunit and pertussis toxin mutant from conditions containing relatively high amounts of inorganic salts, buffers, and preservatives without the need for prior sample clean-up or concentration. By circumventing some of the sample preparation steps, MAI simplifies and accelerates the analytical workflow for biological samples in complex media. The benefits of multiply charged ions characteristic of electrospray ionization (ESI) and the robustness of matrix-assisted laser desorption/ionization (MALDI) can be obtained from a single method, making it well suited for analysis of proteins and other biomolecules at ultra-high resolution as demonstrated on an Orbitrap Fusion where protein subunits were resolved for which MALDI-time-of-flight failed. MAI results are compared with those obtained with ESI, MALDI, and laserspray ionization methods and fundamental commonalities discussed.
| S-EPMC4930895 | biostudies-literature
Project description:BackgroundHigh resolution mass spectrometry has been employed to rapidly and accurately type and subtype influenza viruses. The detection of signature peptides with unique theoretical masses enables the unequivocal assignment of the type and subtype of a given strain. This analysis has, to date, required the manual inspection of mass spectra of whole virus and antigen digests.ResultsA computer algorithm, FluTyper, has been designed and implemented to achieve the automated analysis of MALDI mass spectra recorded for proteolytic digests of the whole influenza virus and antigens. FluTyper incorporates the use of established signature peptides and newly developed naïve Bayes classifiers for four common influenza antigens, hemagglutinin, neuraminidase, nucleoprotein, and matrix protein 1, to type and subtype the influenza virus based on their detection within proteolytic peptide mass maps. Theoretical and experimental testing of the classifiers demonstrates their applicability at protein coverage rates normally achievable in mass mapping experiments. The application of FluTyper to whole virus and antigen digests of a range of different strains of the influenza virus is demonstrated.ConclusionsFluTyper algorithm facilitates the rapid and automated typing and subtyping of the influenza virus from mass spectral data. The newly developed naïve Bayes classifiers increase the confidence of influenza virus subtyping, especially where signature peptides are not detected. FluTyper is expected to popularize the use of mass spectrometry to characterize influenza viruses.
| S-EPMC3098065 | biostudies-literature
Project description:MicroRNAs (miRNAs) are small single-stranded non-coding RNAs that post-transcriptionally regulate gene expression, and play key roles in the regulation of a variety of cellular processes and in disease. New tools to analyze miRNAs will add understanding of the physiological origins and biological functions of this class of molecules. In this study, we investigate the utility of high resolution mass spectrometry for the analysis of miRNAs through proof-of-concept experiments. We demonstrate the ability of mass spectrometry to resolve and separate miRNAs and corresponding 3' variants in mixtures. The mass accuracy of the monoisotopic deprotonated peaks from various miRNAs is in the low ppm range. We compare fragmentation of miRNA by collision-induced dissociation (CID) and by higher-energy collisional dissociation (HCD) which yields similar sequence coverage from both methods but additional fragmentation by HCD versus CID. We measure the linear dynamic range, limit of detection, and limit of quantitation of miRNA loaded onto a C18 column. Lastly, we explore the use of data-dependent acquisition of MS/MS spectra of miRNA during online LC-MS and demonstrate that multiple charge states can be fragmented, yielding nearly full sequence coverage of miRNA on a chromatographic time scale. We conclude that high resolution mass spectrometry allows the separation and measurement of miRNAs in mixtures and a standard LC-MS setup can be adapted for online analysis of these molecules.
| S-EPMC4153431 | biostudies-literature
Project description: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.
| S-EPMC3275902 | biostudies-other
Project description:In this report, we explored the benefits of cyclic ion mobility (cIM) mass spectrometry in the analysis of isomeric post-transcriptional modifications of RNA. Standard methyl-cytidine samples were initially utilized to test the ability to correctly distinguish different structures sharing the same elemental composition and thus molecular mass. Analyzed individually, the analytes displayed characteristic arrival times (tD ) determined by the different positions of the modifying methyl groups onto the common cytidine scaffold. Analyzed in mixture, the widths of the respective signals resulted in significant overlap that initially prevented their resolution on the tD scale. The separation of the four isomers was achieved by increasing the number of passes through the cIM device, which enabled to fully differentiate the characteristic ion mobility behaviors associated with very subtle structural variations. The placement of the cIM device between the mass-selective quadrupole and the time-of-flight analyzer allowed us to perform gas-phase activation of each of these ion populations, which had been first isolated according to a common mass-to-charge ratio and then separated on the basis of different ion mobility behaviors. The observed fragmentation patterns confirmed the structures of the various isomers thus substantiating the benefits of complementing unique tD information with specific fragmentation data to reach more stringent analyte identification. These capabilities were further tested by analyzing natural mono-nucleotide mixtures obtained by exonuclease digestion of total RNA extracts. In particular, the combination of cIM separation and post-mobility dissociation allowed us to establish the composition of methyl-cytidine and methyl-adenine components present in the entire transcriptome of HeLa cells. For this reason, we expect that this technique will benefit not only epitranscriptomic studies requiring the determination of identity and expression levels of RNA modifications, but also metabolomics investigations involving the analysis of natural extracts that may possibly contain subsets of isomeric/isobaric species.
| S-EPMC8363168 | biostudies-literature
Project description:High resolution mass spectrometry (HRMS) was successfully applied to elucidate the structure of a polyfluorinated polyether (PFPE)-based formulation. The mass spectrum generated from direct injection into the MS was examined by identifying the different repeating units manually and with the aid of an instrument data processor. Highly accurate mass spectral data enabled the calculation of higher-order mass defects. The different plots of MW and the nth-order mass defects (up to n = 3) could aid in assessing the structure of the different repeating units and estimating their absolute and relative number per molecule. The three major repeating units were -C2H4O-, -C2F4O-, and -CF2O-. Tandem MS was used to identify the end groups that appeared to be phosphates, as well as the possible distribution of the repeating units. Reversed-phase HPLC separated of the polymer molecules on the basis of number of nonpolar repeating units. The elucidated structure resembles the structure in the published manufacturer technical data. This analytical approach to the characterization of a PFPE-based formulation can serve as a guide in analyzing not just other PFPE-based formulations but also other fluorinated and non-fluorinated polymers. The information from MS is essential in studying the physico-chemical properties of PFPEs and can help in assessing the risks they pose to the environment and to human health. Graphical Abstract ᅟ.
| S-EPMC4723628 | biostudies-literature
Project description:BackgroundRetinoblastoma is an ocular neoplastic cancer caused primarily due to the mutation/deletion of RB1 gene. Due to the rarity of the disease very limited information is available on molecular changes in primary retinoblastoma. High throughput analysis of retinoblastoma transcriptome is available however the proteomic landscape of retinoblastoma remains unexplored. In the present study we used high resolution mass spectrometry-based quantitative proteomics to identify proteins associated with pathogenesis of retinoblastoma.MethodsWe used five pooled normal retina and five pooled retinoblastoma tissues to prepare tissue lysates. Equivalent amount of proteins from each group was trypsin digested and labeled with iTRAQ tags. The samples were analyzed on Orbitrap Velos mass spectrometer. We further validated few of the differentially expressed proteins by immunohistochemistry on primary tumors.ResultsWe identified and quantified a total of 3587 proteins in retinoblastoma when compared with normal adult retina. In total, we identified 899 proteins that were differentially expressed in retinoblastoma with a fold change of ≥2 of which 402 proteins were upregulated and 497 were down regulated. Insulin growth factor 2 mRNA binding protein 1 (IGF2BP1), chromogranin A, fetuin A (ASHG), Rac GTPase-activating protein 1 and midkine that were found to be overexpressed in retinoblastoma were further confirmed by immunohistochemistry by staining 15 independent retinoblastoma tissue sections. We further verified the effect of IGF2BP1 on cell proliferation and migration capability of a retinoblastoma cell line using knockdown studies.ConclusionsIn the present study mass spectrometry-based quantitative proteomic approach was applied to identify proteins differentially expressed in retinoblastoma tumor. This study identified the mitochondrial dysfunction and lipid metabolism pathways as the major pathways to be deregulated in retinoblastoma. Further knockdown studies of IGF2BP1 in retinoblastoma cell lines revealed it as a prospective therapeutic target for retinoblastoma.
| S-EPMC5080735 | biostudies-literature