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The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma

BACKGROUND: Reference genome and transcriptome assemblies of helminths have reached a level of completion whereby secondary analyses that rely on accurate gene estimation or syntenic relationships can be now conducted with a high level of confidence. Recent public release of the v.3 assembly of the...

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Autores principales: James, Katherine, Olson, Peter D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204028/
https://www.ncbi.nlm.nih.gov/pubmed/32380953
http://dx.doi.org/10.1186/s12864-020-6710-1
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author James, Katherine
Olson, Peter D.
author_facet James, Katherine
Olson, Peter D.
author_sort James, Katherine
collection PubMed
description BACKGROUND: Reference genome and transcriptome assemblies of helminths have reached a level of completion whereby secondary analyses that rely on accurate gene estimation or syntenic relationships can be now conducted with a high level of confidence. Recent public release of the v.3 assembly of the mouse bile-duct tapeworm, Hymenolepis microstoma, provides chromosome-level characterisation of the genome and a stabilised set of protein coding gene models underpinned by bioinformatic and empirical data. However, interactome data have not been produced. Conserved protein-protein interactions in other organisms, termed interologs, can be used to transfer interactions between species, allowing systems-level analysis in non-model organisms. RESULTS: Here, we describe a probabilistic, integrated network of interologs for the H. microstoma proteome, based on conserved protein interactions found in eukaryote model species. Almost a third of the 10,139 gene models in the v.3 assembly could be assigned interaction data and assessment of the resulting network indicates that topologically-important proteins are related to essential cellular pathways, and that the network clusters into biologically meaningful components. Moreover, network parameters are similar to those of single-species interaction networks that we constructed in the same way for S. cerevisiae, C. elegans and H. sapiens, demonstrating that information-rich, system-level analyses can be conducted even on species separated by a large phylogenetic distance from the major model organisms from which most protein interaction evidence is based. Using the interolog network, we then focused on sub-networks of interactions assigned to discrete suites of genes of interest, including signalling components and transcription factors, germline multipotency genes, and genes differentially-expressed between larval and adult worms. Results show not only an expected bias toward highly-conserved proteins, such as components of intracellular signal transduction, but in some cases predicted interactions with transcription factors that aid in identifying their target genes. CONCLUSIONS: With key helminth genomes now complete, systems-level analyses can provide an important predictive framework to guide basic and applied research on helminths and will become increasingly informative as new protein-protein interaction data accumulate.
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spelling pubmed-72040282020-05-12 The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma James, Katherine Olson, Peter D. BMC Genomics Research Article BACKGROUND: Reference genome and transcriptome assemblies of helminths have reached a level of completion whereby secondary analyses that rely on accurate gene estimation or syntenic relationships can be now conducted with a high level of confidence. Recent public release of the v.3 assembly of the mouse bile-duct tapeworm, Hymenolepis microstoma, provides chromosome-level characterisation of the genome and a stabilised set of protein coding gene models underpinned by bioinformatic and empirical data. However, interactome data have not been produced. Conserved protein-protein interactions in other organisms, termed interologs, can be used to transfer interactions between species, allowing systems-level analysis in non-model organisms. RESULTS: Here, we describe a probabilistic, integrated network of interologs for the H. microstoma proteome, based on conserved protein interactions found in eukaryote model species. Almost a third of the 10,139 gene models in the v.3 assembly could be assigned interaction data and assessment of the resulting network indicates that topologically-important proteins are related to essential cellular pathways, and that the network clusters into biologically meaningful components. Moreover, network parameters are similar to those of single-species interaction networks that we constructed in the same way for S. cerevisiae, C. elegans and H. sapiens, demonstrating that information-rich, system-level analyses can be conducted even on species separated by a large phylogenetic distance from the major model organisms from which most protein interaction evidence is based. Using the interolog network, we then focused on sub-networks of interactions assigned to discrete suites of genes of interest, including signalling components and transcription factors, germline multipotency genes, and genes differentially-expressed between larval and adult worms. Results show not only an expected bias toward highly-conserved proteins, such as components of intracellular signal transduction, but in some cases predicted interactions with transcription factors that aid in identifying their target genes. CONCLUSIONS: With key helminth genomes now complete, systems-level analyses can provide an important predictive framework to guide basic and applied research on helminths and will become increasingly informative as new protein-protein interaction data accumulate. BioMed Central 2020-05-07 /pmc/articles/PMC7204028/ /pubmed/32380953 http://dx.doi.org/10.1186/s12864-020-6710-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
James, Katherine
Olson, Peter D.
The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma
title The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma
title_full The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma
title_fullStr The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma
title_full_unstemmed The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma
title_short The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma
title_sort tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of hymenolepis microstoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204028/
https://www.ncbi.nlm.nih.gov/pubmed/32380953
http://dx.doi.org/10.1186/s12864-020-6710-1
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