Determining Alternative Protein Isoform Expression Using RNA Sequencing and Mass Spectrometry.
Ontology highlight
ABSTRACT:
SUBMITTER: Han Y
PROVIDER: S-EPMC7757315 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:We have combined ion mobility spectrometry-mass spectrometry with tandem mass spectrometry to characterise large, non-covalently bound macromolecular complexes in terms of mass, shape (cross-sectional area) and stability (dissociation) in a single experiment. The results indicate that the quaternary architecture of a complex influences its residual shape following removal of a single subunit by collision-induced dissociation tandem mass spectrometry. Complexes whose subunits are bound to several neighbouring subunits to create a ring-like three-dimensional (3D) architecture undergo significant collapse upon dissociation. In contrast, subunits which have only a single neighbouring subunit within a complex retain much of their original shape upon complex dissociation. Specifically, we have determined the architecture of two transient, on-pathway intermediates observed during in vitro viral capsid assembly. Knowledge of the mass, stoichiometry and cross-sectional area of each viral assembly intermediate allowed us to model a range of potential structures based on the known X-ray structure of the coat protein building blocks. Comparing the cross-sectional areas of these potential architectures before and after dissociation provided tangible evidence for the assignment of the topologies of the complexes, which have been found to encompass both the 3-fold and the 5-fold symmetry axes of the final icosahedral viral shell. Such insights provide unique information about virus assembly pathways that could allow the design of anti-viral therapeutics directed at the assembly step. This methodology can be readily applied to the structural characterisation of many other non-covalently bound macromolecular complexes and their assembly pathways.
| S-EPMC4789508 | biostudies-literature
Project description:Patient-derived scaffolds (PDSs) generated from primary breast cancer tumors can be used to model the tumor microenvironment in vitro. Patient-derived scaffolds are generated by repeated detergent washing, removing all cells. Here, we analyzed the protein composition of 15 decellularized PDSs using liquid chromatography-mass spectrometry/mass spectrometry. One hundred forty-three proteins were detected and their relative abundance was calculated using a reference sample generated from all PDSs. We performed heatmap analysis of all the detected proteins to display their expression patterns across different PDSs together with pathway enrichment analysis to reveal which processes that were connected to PDS protein composition. This protein dataset together with clinical information is useful to investigators studying the microenvironment of breast cancers. Further, after repopulating PDSs with either MCF7 or MDA-MB-231 cells, we quantified their gene expression profiles using RNA sequencing. These data were also compared to cells cultured in conventional 2D conditions, as well as to cells cultured as xenografts in immune-deficient mice. We investigated the overlap of genes regulated between these different culture conditions and performed pathway enrichment analysis of genes regulated by both PDS and xenograft cultures compared to 2D in both cell lines to describe common processes associated with both culture conditions. Apart from our described analyses of these systems, these data are useful when comparing different experimental model systems. Downstream data analyses and interpretations can be found in the research article "Patient-derived scaffolds uncover breast cancer promoting properties of the microenvironment" [1].
| S-EPMC7327418 | biostudies-literature
Project description:Autoantibodies are increasingly used as biomarkers in the detection of autoimmune disorders and cancer. Disease specific antibodies are generally detected by their binding to specific antigens. As an alternative approach, we propose to identify specific complementarity determining regions (CDR) of IgG that relate to an autoimmune disorder or cancer instead of the specific antigen(s). In this manuscript, we tested the technical feasibility to detect and identify CDRs of specific antibodies by mass spectrometry. We used a commercial pooled IgG preparation as well as purified serum IgG fractions that were spiked with different amounts of a fully human monoclonal antibody (adalimumab). These samples were enzymatically digested and analyzed by nanoLC Orbitrap mass spectrometry. In these samples, we were able to identify peptides derived from the CDRs of adalimumab. These peptides could be detected at an amount of 110 attomole, 5 orders of magnitude lower than the total IgG concentration in these samples. Using higher energy collision induced dissociation (HCD) fragmentation and subsequent de novo sequencing, we could successfully identify 50% of the detectable CDR peptides of adalimumab. In addition, we demonstrated that an affinity purification with anti-dinitrophenol (DNP) monoclonal antibody enhanced anti-DNP derived CDR detection in a serum IgG background. In conclusion, specific CDR peptides could be detected and sequenced at relatively low levels (attomole-femtomole range) which should allow the detection of clinically relevant CDR peptides in patient samples.
| S-EPMC3018266 | biostudies-literature
Project description:Over the past decades, protein O-GlcNAcylation has been found to play a fundamental role in cell cycle control, metabolism, transcriptional regulation, and cellular signaling. Nevertheless, quantitative approaches to determine in vivo GlcNAc dynamics at a large-scale are still not readily available. Here, we have developed an approach to isotopically label O-GlcNAc modifications on proteins by producing (13)C-labeled UDP-GlcNAc from (13)C6-glucose via the hexosamine biosynthetic pathway. This metabolic labeling was combined with quantitative mass spectrometry-based proteomics to determine protein O-GlcNAcylation turnover rates. First, an efficient enrichment method for O-GlcNAc peptides was developed with the use of phenylboronic acid solid-phase extraction and anhydrous DMSO. The near stoichiometry reaction between the diol of GlcNAc and boronic acid dramatically improved the enrichment efficiency. Additionally, our kinetic model for turnover rates integrates both metabolomic and proteomic data, which increase the accuracy of the turnover rate estimation. Other advantages of this metabolic labeling method include in vivo application, direct labeling of the O-GlcNAc sites and higher confidence for site identification. Concentrating only on nuclear localized GlcNAc modified proteins, we are able to identify 105 O-GlcNAc peptides on 42 proteins and determine turnover rates of 20 O-GlcNAc peptides from 14 proteins extracted from HeLa nuclei. In general, we found O-GlcNAcylation turnover rates are slower than those published for phosphorylation or acetylation. Nevertheless, the rates widely varied depending on both the protein and the residue modified. We believe this methodology can be broadly applied to reveal turnovers/dynamics of protein O-GlcNAcylation from different biological states and will provide more information on the significance of O-GlcNAcylation, enabling us to study the temporal dynamics of this critical modification for the first time.
| S-EPMC4937517 | biostudies-literature
Project description:The thermal instability of the anticoagulant heparin is associated, in part, with the solvolytic loss of N-sulfo groups. This study describes a new method to assess the increased content of unsubstituted amino groups present in thermally stressed and autoclave-sterilized heparin formulations. N-Acetylation of heparin samples with acetic anhydride-d6 is followed by exhaustive heparinase treatment and disaccharide analysis by hydrophilic interaction chromatography mass spectrometry (HILIC-MS). The introduction of a stable isotopic label provides a sensitive probe for the detection and localization of the lost N-sulfo groups, potentially providing valuable insights into the degradation mechanism and the reasons for anticoagulant potency loss.
| S-EPMC4119833 | biostudies-literature
Project description:BackgroundMounting evidence demonstrates a causal role for S100 proteins in tumourigenesis and several S100 isoforms have shown utility as biomarkers of several types of cancer. The S100 family is comprised of 21 small isoforms, many of them implicated in important cellular functions such as proliferation, motility and survival. Furthermore, in vivo experiments have proven the role of S100 proteins in tumour growth and disease progression, while other studies have shown their prognostic value and involvement in resistance to chemotherapy drugs. Taken together, all these aspects highlight S100 proteins as potential therapeutic targets and as a promising panel of cancer biomarkers. In this work, we have developed a mass spectrometry (MS)-based method for the multiplexed and specific analysis of the entire S100 protein family in tumour tissues and have applied it to investigate the expression of S100 isoforms in the context of thyroid cancer, the main endocrine malignancy.MethodsSelected Reaction Monitoring (SRM)-MS and stable isotope labelling/label-free analysis were employed to investigate the expression of the 21 S100 protein isoforms in thyroid tissue samples. Specimens included 9 normal thyroid tissues and 27 tumour tissues consisting of 9 follicular adenomas (FA), 8 follicular carcinomas (FTC) and 10 papillary carcinomas (PTC).ResultsThe multiplexed and targeted mass spectrometry method led to the detection of eleven S100 protein isoforms across all tissues. Label- and label-free analyses showed the same significant differences and results were confirmed by western blot. S100A6, S100A11 and its putative interaction partner annexin A1 showed the highest overexpression in PTC compared to normal thyroid. S100A13 was also elevated in PTC. Reduced S100A4 expression was observed in FA compared to all other tissues. FA and FTC showed reduction of S100A10 and annexin A2 expression.ConclusionsTargeted mass spectrometry allows the multiplexed and specific analysis of S100 protein isoforms in tumour tissue specimens. It revealed S100A13 as a novel candidate PTC biomarker. Results show that S100A6, S100A11 and Annexin A1 could help discriminate follicular and papillary tumours. The diagnostic and functional significance of S100A4 and S100A10 reduction in follicular tumours requires further investigation.
| S-EPMC4391164 | biostudies-literature
Project description:Chemical modifications of the nucleosides that comprise transfer RNAs are diverse. However, the structure, location and extent of modifications have been systematically charted in very few organisms. Here, we describe an approach in which rapid prediction of modified sites through reverse transcription-derived signatures in high-throughput transfer RNA-sequencing (tRNA-seq) data is coupled with identification of tRNA modifications through RNA mass spectrometry. Comparative tRNA-seq enabled prediction of several Vibrio cholerae modifications that are absent from Escherichia coli and also revealed the effects of various environmental conditions on V. cholerae tRNA modification. Through RNA mass spectrometric analyses, we showed that two of the V. cholerae-specific reverse transcription signatures reflected the presence of a new modification (acetylated acp3U (acacp3U)), while the other results from C-to-Ψ RNA editing, a process not described before. These findings demonstrate the utility of this approach for rapid surveillance of tRNA modification profiles and environmental control of tRNA modification.
| S-EPMC8172280 | biostudies-literature
Project description:Post-transcriptional modifications (PTMs) of RNA represent an understudied mechanism involved in the regulation of translation in the central nervous system (CNS). Recent evidence has linked specific neuronal RNA modifications to learning and memory paradigms. Unfortunately, conventional methods for the detection of these epitranscriptomic features are only capable of characterizing highly abundant RNA modifications in bulk tissues, precluding the assessment of unique PTM profiles that may exist for individual neurons within the activated behavioral circuits. In this protocol, an approach is described-single-neuron RNA modification analysis by mass spectrometry (SNRMA-MS)-to simultaneously detect and quantify numerous modified ribonucleosides in single neurons. The approach is validated using individual neurons of the marine mollusk, Aplysia californica, beginning with surgical isolation and enzymatic treatment of major CNS ganglia to expose neuron cell bodies, followed by manual single-neuron isolation using sharp needles and a micropipette. Next, mechanical and thermal treatment of the sample in a small volume of buffer is done to liberate RNA from an individual cell for subsequent RNA digestion. Modified nucleosides are then identified and quantified using an optimized liquid chromatography-mass spectrometry method. SNRMA-MS is employed to establish RNA modification patterns for single, identified neurons from A. californica that have known morphologies and functions. Examples of qualitative and quantitative SNRMA-MS are presented that highlight the heterogeneous distribution of RNA modifications across individual neurons in neuronal networks.
| S-EPMC9116202 | biostudies-literature
Project description:There are an increasing variety of applications in which peptides are both synthesized and used attached to solid surfaces. This has created a need for high throughput sequence analysis directly on surfaces. However, common sequencing approaches that can be adapted to surface bound peptides lack the throughput often needed in library-based applications. Here we describe a simple approach for sequence analysis directly on solid surfaces that is both high speed and high throughput, utilizing equipment available in most protein analysis facilities. In this approach, surface bound peptides, selectively labeled at their N-termini with a positive charge-bearing group, are subjected to controlled degradation in ammonia gas, resulting in a set of fragments differing by a single amino acid that remain spatially confined on the surface they were bound to. These fragments can then be analyzed by MALDI mass spectrometry, and the peptide sequences read directly from the resulting spectra.
| S-EPMC5736625 | biostudies-literature
Project description:RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have focus on characterization of isoform-level expression patterns at the single-cell level. In this study, we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of isoform pairs from the same gene in single-cell isoform-level expression data.We define six principal patterns of isoform expression relationships and describe a method for differential-pattern analysis. We demonstrate ISOP through analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in three independent datasets. We assigned the pattern types to each of 16 562 isoform-pairs from 4929 genes. Among those, 26% of the discovered patterns were significant (P<0.05), while remaining patterns are possibly effects of transcriptional bursting, drop-out and stochastic biological heterogeneity. Furthermore, 32% of genes discovered through differential-pattern analysis were not detected by differential-expression analysis. Finally, the effects of drop-out events and expression levels of isoforms on ISOP's performances were investigated through simulated datasets. To conclude, ISOP provides a novel approach for characterization of isoform-level preference, commitment and heterogeneity in single-cell RNA-sequencing data.The ISOP method has been implemented as a R package and is available at https://github.com/nghiavtr/ISOP under a GPL-3 license.Supplementary data are available at Bioinformatics online.
| S-EPMC6041805 | biostudies-other