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 ◽  
...  
2019 ◽  
Author(s):  
Fabian Coscia ◽  
Sophia Doll ◽  
Jacob Mathias Bech ◽  
Andreas Mund ◽  
Ernst Lengyel ◽  
...  

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.


2020 ◽  
Vol 86 (7) ◽  
pp. 12-19
Author(s):  
I. V. Plyushchenko ◽  
D. G. Shakhmatov ◽  
I. A. Rodin

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.


2021 ◽  
Vol 20 (2) ◽  
pp. 1280-1295
Author(s):  
Aleksandr Gaun ◽  
Kaitlyn N. Lewis Hardell ◽  
Niclas Olsson ◽  
Jonathon J. O’Brien ◽  
Sudha Gollapudi ◽  
...  

Author(s):  
Lok Man ◽  
William P. Klare ◽  
Ashleigh L. Dale ◽  
Joel A. Cain ◽  
Stuart J. Cordwell

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.


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

2020 ◽  
Author(s):  
Simon Ngao Mule ◽  
Andrè Guillherme da Costa Martins ◽  
Livia Rosa-Fernandes ◽  
Gilberto Santos de Oliveira ◽  
Carla Monadeli Rodrigues ◽  
...  

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.


2020 ◽  
Author(s):  
Diogo Borges Lima ◽  
Ying Zhu ◽  
Fan Liu

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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