scholarly journals A streamlined mass spectrometry–based proteomics workflow for large‐scale FFPE tissue analysis

2020 ◽  
Vol 251 (1) ◽  
pp. 100-112 ◽  
Author(s):  
Fabian Coscia ◽  
Sophia Doll ◽  
Jacob Mathias Bech ◽  
Lisa Schweizer ◽  
Andreas Mund ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Large Scale ◽  
Ffpe Tissue ◽  
Tissue Analysis

scholarly journals A streamlined mass spectrometry-based proteomics workflow for large scale FFPE tissue analysis

2019 ◽  
Author(s):  
Fabian Coscia ◽  
Sophia Doll ◽  
Jacob Mathias Bech ◽  
Andreas Mund ◽  
Ernst Lengyel ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Large Scale ◽  
Clinical Pathology ◽  
Ffpe Tissue ◽  
Great Promise ◽  
Glass Slides ◽  
Lower Protein ◽  
Ffpe Tissues ◽  
Ffpe Material ◽  
Efficient Extraction

ABSTRACTFormalin fixation and paraffin-embedding (FFPE) is the most common method to preserve human tissue for clinical diagnosis and FFPE archives represent an invaluable resource for biomedical research. Proteins in FFPE material are stable over decades but their efficient extraction and streamlined analysis by mass spectrometry (MS)-based proteomics has so far proven challenging. Here, we describe an MS-based proteomic workflow for quantitative profiling of large FFPE tissue cohorts directly from pathology glass slides. We demonstrate broad applicability of the workflow to clinical pathology specimens and variable sample amounts, including less than 10,000 cancer cells isolated by laser-capture microdissection. Using state-of-the-art data dependent acquisition (DDA) and data independent (DIA) MS workflows, we consistently quantify a large part of the proteome in 100 min single-run analyses. In an adenoma cohort comprising more than 100 samples, total work up took less than a day. We observed a moderate trend towards lower protein identifications in long-term stored samples (>15 years) but clustering into distinct proteomic subtypes was independent of archival time. Our results underline the great promise of FFPE tissues for patient phenotyping using unbiased proteomics and prove the feasibility of analyzing large tissue cohorts in a robust, timely and streamlined manner.

Algorithm of combining chromatography mass spectrometry-untargeted profiling and multivariate analysis for identification of marker-substances in samples of complex composition

2020 ◽  
Vol 86 (7) ◽  
pp. 12-19
Author(s):  
I. V. Plyushchenko ◽  
D. G. Shakhmatov ◽  
I. A. Rodin
Keyword(s):  
Mass Spectrometry ◽  
Multivariate Analysis ◽  
Large Scale ◽  
Complex Composition ◽  
Unified Protocol ◽  
Chromatography Mass Spectrometry ◽  
Marker Substances ◽  
Selection Testing ◽  
Untargeted Profiling

A viral development of statistical data processing, computing capabilities, chromatography-mass spectrometry, and omics technologies (technologies based on the achievements of genomics, transcriptomics, proteomics, metabolomics) in recent decades has not led to formation of a unified protocol for untargeted profiling. Systematic errors reduce the reproducibility and reliability of the obtained results, and at the same time hinder consolidation and analysis of data gained in large-scale multi-day experiments. We propose an algorithm for conducting omics profiling to identify potential markers in the samples of complex composition and present the case study of urine samples obtained from different clinical groups of patients. Profiling was carried out by the method of liquid chromatography mass spectrometry. The markers were selected using methods of multivariate analysis including machine learning and feature selection. Testing of the approach was performed using an independent dataset by clustering and projection on principal components.

scholarly journals Automated 16-Plex Plasma Proteomics with Real-Time Search and Ion Mobility Mass Spectrometry Enables Large-Scale Profiling in Naked Mole-Rats and Mice

2021 ◽  
Vol 20 (2) ◽  
pp. 1280-1295
Author(s):  
Aleksandr Gaun ◽  
Kaitlyn N. Lewis Hardell ◽  
Niclas Olsson ◽  
Jonathon J. O’Brien ◽  
Sudha Gollapudi ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Real Time ◽  
Ion Mobility ◽  
Large Scale ◽  
Ion Mobility Mass Spectrometry ◽  
Plasma Proteomics ◽  
Rats And Mice

Integrated mass spectrometry-based multi-omics for elucidating mechanisms of bacterial virulence

2021 ◽  
Author(s):  
Lok Man ◽  
William P. Klare ◽  
Ashleigh L. Dale ◽  
Joel A. Cain ◽  
Stuart J. Cordwell
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Large Scale ◽  
Lipid A ◽  
Phenotypic Characterization ◽  
Post Translational Modification ◽  
Form Of Life ◽  
Antimicrobial Interventions

Despite being considered the simplest form of life, bacteria remain enigmatic, particularly in light of pathogenesis and evolving antimicrobial resistance. After three decades of genomics, we remain some way from understanding these organisms, and a substantial proportion of genes remain functionally unknown. Methodological advances, principally mass spectrometry (MS), are paving the way for parallel analysis of the proteome, metabolome and lipidome. Each provides a global, complementary assay, in addition to genomics, and the ability to better comprehend how pathogens respond to changes in their internal (e.g. mutation) and external environments consistent with infection-like conditions. Such responses include accessing necessary nutrients for survival in a hostile environment where co-colonizing bacteria and normal flora are acclimated to the prevailing conditions. Multi-omics can be harnessed across temporal and spatial (sub-cellular) dimensions to understand adaptation at the molecular level. Gene deletion libraries, in conjunction with large-scale approaches and evolving bioinformatics integration, will greatly facilitate next-generation vaccines and antimicrobial interventions by highlighting novel targets and pathogen-specific pathways. MS is also central in phenotypic characterization of surface biomolecules such as lipid A, as well as aiding in the determination of protein interactions and complexes. There is increasing evidence that bacteria are capable of widespread post-translational modification, including phosphorylation, glycosylation and acetylation; with each contributing to virulence. This review focuses on the bacterial genotype to phenotype transition and surveys the recent literature showing how the genome can be validated at the proteome, metabolome and lipidome levels to provide an integrated view of organism response to host conditions.

scholarly journals Challenges in Large-Scale Computational Mass Spectrometry and Multiomics

2016 ◽  
Vol 15 (3) ◽  
pp. 681-682
Author(s):  
Oliver Kohlbacher ◽  
Olga Vitek ◽  
Susan T. Weintraub
Keyword(s):  
Mass Spectrometry ◽  
Large Scale

scholarly journals New insights into Trypanosoma cruzi evolution and genotyping based on system-wide protein expression profiles (PhyloQuant)

2020 ◽  
Author(s):  
Simon Ngao Mule ◽  
Andrè Guillherme da Costa Martins ◽  
Livia Rosa-Fernandes ◽  
Gilberto Santos de Oliveira ◽  
Carla Monadeli Rodrigues ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Trypanosoma Cruzi ◽  
Protein Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Shotgun Proteomics ◽  
Close Correlation ◽  
Evolutionary Relationships ◽  
Trypanosome Species ◽  
Protein Expression Profiles

AbstractThe etiological agent of Chagas disease, Trypanosoma cruzi, is subdivided into seven genetic subdivisions termed discrete typing units (DTUs), TcI-TcVI and Tcbat. The relevance of T. cruzi genetic diversity to the variable clinical course of the disease, virulence, pathogenicity, drug resistance, transmission cycles and ecological distribution justifies the concerted efforts towards understanding the population structure of T. cruzi strains. In this study, we introduce a novel approach termed ‘phyloquant’ to infer the evolutionary relationships and assignment of T. cruzi strains to their DTUs based on differential protein expression profiles evidenced by bottom up large scale mass spectrometry-based quantitative proteomic features. Mass spectrometry features analyzed using parsimony (MS1, iBAQ and LFQ) showed a close correlation between protein expression and T. cruzi DTUs and closely related trypanosome species. Although alternative topologies with minor differences between the three MS features analyzed were demonstrated, we show congruence to well accepted evolutionary relationships of T. cruzi DTUs; in all analyses TcI and Tcbat were sister groups, and the parental nature of genotype TcII and the hybrid genotypes TcV/TcVI were corroborated. Character mapping of genetic distance matrices based on phylogenetics and phyloquant clustering showed statistically significant correlations. We propose the first quantitative shotgun proteomics approach as a complement strategy to the genetic-based assignment of T. cruzi strains to DTUs and evolutionary inferences. Moreover, this approach allows for the identification of differentially regulated and strain/DTU/species-specific proteins, with potential application in the identification of strain/DTU specific biomarkers and candidate therapeutic targets. In addition, the correlation between multi-gene protein expression and divergence of trypanosome species was evaluated, adding another level to understand the genetic subdivisions among T. cruzi DTUs.

scholarly journals XlinkCyNET: a Cytoscape application for visualization of protein interaction networks based on cross-linking mass-spectrometry identifications

2020 ◽  
Author(s):  
Diogo Borges Lima ◽  
Ying Zhu ◽  
Fan Liu
Keyword(s):  
Mass Spectrometry ◽  
Protein Interaction ◽  
Large Scale ◽  
Interaction Network ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Cross Linking ◽  
Protein Interaction Data ◽  
Interaction Data ◽  
Link Type

ABSTRACTSoftware tools that allow visualization and analysis of protein interaction networks are essential for studies in systems biology. One of the most popular network visualization tools in biology is Cytoscape, which offers a large selection of plugins for interpretation of protein interaction data. Chemical cross-linking coupled to mass spectrometry (XL-MS) is an increasingly important source for such interaction data, but there are currently no Cytoscape tools to analyze XL-MS results. In light of the suitability of Cytoscape platform but also to expand its toolbox, here we introduce XlinkCyNET, an open-source Cytoscape Java plugin for exploring large-scale XL-MS-based protein interaction networks. XlinkCyNET offers rapid and easy visualization of intra and intermolecular cross-links and the locations of protein domains in a rectangular bar style, allowing subdomain-level interrogation of the interaction network. XlinkCyNET is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/xlinkcynet and at https://www.theliulab.com/software/xlinkcynet.

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