Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues

Wang, Shengbo; García-Seisdedos, David; Prakash, Ananth; Kundu, Deepti Jaiswal; Collins, Andrew; George, Nancy; Fexová, Silvie; Moreno, Pablo; Papatheodorou, Irene; Jones, Andrew R.; Vizcaíno, Juan Antonio

doi:10.1371/journal.pcbi.1010174

Cited by 14 publications

(30 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This enables that (i) the computing requirements for the reanalyses are realistic, given the large volume of files included in the potentially very large-combined datasets; (ii) interesting additional datasets could be added at a different time point without having to reanalyze all datasets together again; (iii) future updates in the results are more feasible to perform; and (iv) (semi)-automation of the reanalyses is achievable, making these efforts more sustainable again. As mentioned above, we followed this same overall approach in the recent study that we performed in mouse and rat tissues in baseline conditions . Additionally, we compared our results with previous analogous studies performed in baseline tissues using MS and also the antibody-based data available in the HPA.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Integrated View of Baseline Protein Expression in Human Tissues

et al. 2022

Self Cite

View full text Add to dashboard Cite

The availability of proteomics datasets in the public domain, and in the PRIDE database, in particular, has increased dramatically in recent years. This unprecedented large-scale availability of data provides an opportunity for combined analyses of datasets to get organism-wide protein abundance data in a consistent manner. We have reanalyzed 24 public proteomics datasets from healthy human individuals to assess baseline protein abundance in 31 organs. We defined tissue as a distinct functional or structural region within an organ. Overall, the aggregated dataset contains 67 healthy tissues, corresponding to 3,119 mass spectrometry runs covering 498 samples from 489 individuals. We compared protein abundances between different organs and studied the distribution of proteins across these organs. We also compared the results with data generated in analogous studies. Additionally, we performed gene ontology and pathway-enrichment analyses to identify organ-specific enriched biological processes and pathways. As a key point, we have integrated the protein abundance results into the resource Expression Atlas, where they can be accessed and visualized either individually or together with gene expression data coming from transcriptomics datasets. We believe this is a good mechanism to make proteomics data more accessible for life scientists.

show abstract

Section: Discussionmentioning

confidence: 99%

“…First of all, we reported the reanalysis and integration into the Expression Atlas of 11 public quantitative datasets coming from cell lines and human tumor samples . Additionally, we have recently reported the reanalysis and integration of 23 datasets coming from mouse and rat tissues in baseline conditions …”

Section: Introductionmentioning

confidence: 99%

Integrated View of Baseline Protein Expression in Human Tissues

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…This enables that: (i) computing requirements for the reanalyses are realistic given the large volume of files included in the potentially very large- combined datasets; (ii) interesting additional datasets could be added at a different time point without having to reanalyse all datasets together again; (iii) future updates in the results are more feasible to perform; and (iv) (semi)-automation of the reanalyses is achievable, making again these efforts more sustainable. We followed this same overall approach in the recent study we performed in mouse and rat tissues in baseline conditions [23]. Additionally, we compared our results with previous analogous studies performed in baseline tissue using MS and also the antibody-based data available in the HPA.…”

Section: Discussionmentioning

confidence: 99%

“…Unlike what was done in one previous study performed by us [22], and analogously to what we did with a more recent study performed using data generated from baseline rat and mouse tissues [23], here we analysed each dataset separately using the same software and the same search protein sequence database. The disadvantage of this approach is that the FDR statistical thresholds are applied at a dataset level and not to all datasets together as a whole, with the potential accumulation of false positives across datasets.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

An integrated view of baseline protein expression in human tissues

Prakash

García-Seisdedos

Wang

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

The availability of proteomics datasets in the public domain, and in the PRIDE database in particular, has increased dramatically in recent years. This unprecedented large-scale availability of data provides an opportunity for combined analyses of datasets to get organism-wide protein expression data in a consistent manner. We have reanalysed 25 public proteomics datasets from healthy human individuals, to assess baseline protein abundance in 32 organs. We defined tissue as a distinct functional or structural region within an organ. Overall, the aggregated dataset contains 68 healthy tissues, corresponding to 3,167 mass spectrometry runs covering 501 samples, coming from 492 individuals. We compared protein expression between the different organs, studied the distribution of proteins across organs, and identified proteins, as well as their isoforms, that are uniquely expressed in certain organs. We also performed gene ontology and pathway enrichment analyses to identify organ-specific enriched biological processes and pathways. As a key point, we have integrated the protein expression results into the resource Expression Atlas, where it can be accessed and visualised either individually or together with gene expression data coming from transcriptomics datasets.

show abstract

Mass Spectrometry-Based Atlas of Extracellular Matrix Proteins across 25 Mouse Organs

2023

View full text Add to dashboard Cite

The extracellular matrix (ECM) is a critical non-cellular component of multicellular organisms containing a variety of proteins, glycoproteins, and proteoglycans which have been implicated in a wide variety of essential biological processes, including development, wound healing, and aging. Due to low solubility, many ECM proteins have been underrepresented in previous proteomic datasets. Using an optimized three-step decellularization and ECM extraction method involving chaotrope extraction and digestion via hydroxylamine hydrochloride, we have generated coverage of the matrisome across 25 organs. We observe that the top 100 most abundant proteins from the ECM fractions of all tissues are generally present in all tissues, indicating that tissue matrices are principally composed of a shared set of ECM proteins. However, these proteins vary up to 4000-fold between tissues, resulting in highly unique matrix profiles even with the same primary set of proteins. A data reduction approach was used to reveal related networks of expressed ECM proteins across varying tissues, including basement membrane and collagen subtypes.

show abstract

Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues

Cited by 14 publications

References 57 publications

Integrated View of Baseline Protein Expression in Human Tissues

Integrated View of Baseline Protein Expression in Human Tissues

An integrated view of baseline protein expression in human tissues

Mass Spectrometry-Based Atlas of Extracellular Matrix Proteins across 25 Mouse Organs

Contact Info

Product

Resources

About