Dual RNA Sequencing Meta-analysis in <italic toggle="yes">Plasmodium</italic> Infection Identifies Host-Parasite Interactions

ABSTRACT Dual RNA sequencing (RNA-Seq) is the simultaneous transcriptomic analysis of interacting symbionts, for example, in malaria. Potential cross-species interactions identified by correlated gene expression might highlight interlinked signaling, metabolic, or gene regulatory pathways in additio...

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Autores principales:	Parnika Mukherjee, Gaétan Burgio, Emanuel Heitlinger
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2021
Materias:	dual RNA-Seq malaria meta-analysis transcriptomics Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/060d5e7505f74c00a04567e2b006164b
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spelling	oai:doaj.org-article:060d5e7505f74c00a04567e2b006164b2021-12-02T19:22:27ZDual RNA Sequencing Meta-analysis in <italic toggle="yes">Plasmodium</italic> Infection Identifies Host-Parasite Interactions10.1128/mSystems.00182-212379-5077https://doaj.org/article/060d5e7505f74c00a04567e2b006164b2021-04-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00182-21https://doaj.org/toc/2379-5077ABSTRACT Dual RNA sequencing (RNA-Seq) is the simultaneous transcriptomic analysis of interacting symbionts, for example, in malaria. Potential cross-species interactions identified by correlated gene expression might highlight interlinked signaling, metabolic, or gene regulatory pathways in addition to physically interacting proteins. Often, malaria studies address one of the interacting organisms—host or parasite—rendering the other “contamination.” Here we perform a meta-analysis using such studies for cross-species expression analysis. We screened experiments for gene expression from host and Plasmodium. Out of 171 studies in Homo sapiens, Macaca mulatta, and Mus musculus, we identified 63 potential studies containing host and parasite data. While 16 studies (1,950 samples) explicitly performed dual RNA-Seq, 47 (1,398 samples) originally focused on one organism. We found 915 experimental replicates from 20 blood studies to be suitable for coexpression analysis and used orthologs for meta-analysis across different host-parasite systems. Centrality metrics from the derived gene expression networks correlated with gene essentiality in the parasites. We found indications of host immune response to elements of the Plasmodium protein degradation system, an antimalarial drug target. We identified well-studied immune responses in the host with our coexpression networks, as our approach recovers known broad processes interlinked between hosts and parasites in addition to individual host and parasite protein associations. The set of core interactions represents commonalities between human malaria and its model systems for prioritization in laboratory experiments. Our approach might also allow insights into the transferability of model systems for different pathways in malaria studies. IMPORTANCE Malaria still causes about 400,000 deaths a year and is one of the most studied infectious diseases. The disease is studied in mice and monkeys as lab models to derive potential therapeutic intervention in human malaria. Interactions between Plasmodium spp. and its hosts are either conserved across different host-parasite systems or idiosyncratic to those systems. Here we use correlation of gene expression from different RNA-Seq studies to infer common host-parasite interactions across human, mouse, and monkey studies. First, we find a set of very conserved interactors, worth further scrutiny in focused laboratory experiments. Second, this work might help assess to which extent experiments and knowledge on different pathways can be transferred from models to humans for potential therapy.Parnika MukherjeeGaétan BurgioEmanuel HeitlingerAmerican Society for Microbiologyarticledual RNA-Seqmalariameta-analysistranscriptomicsMicrobiologyQR1-502ENmSystems, Vol 6, Iss 2 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	dual RNA-Seq malaria meta-analysis transcriptomics Microbiology QR1-502
spellingShingle	dual RNA-Seq malaria meta-analysis transcriptomics Microbiology QR1-502 Parnika Mukherjee Gaétan Burgio Emanuel Heitlinger Dual RNA Sequencing Meta-analysis in <italic toggle="yes">Plasmodium</italic> Infection Identifies Host-Parasite Interactions
description	ABSTRACT Dual RNA sequencing (RNA-Seq) is the simultaneous transcriptomic analysis of interacting symbionts, for example, in malaria. Potential cross-species interactions identified by correlated gene expression might highlight interlinked signaling, metabolic, or gene regulatory pathways in addition to physically interacting proteins. Often, malaria studies address one of the interacting organisms—host or parasite—rendering the other “contamination.” Here we perform a meta-analysis using such studies for cross-species expression analysis. We screened experiments for gene expression from host and Plasmodium. Out of 171 studies in Homo sapiens, Macaca mulatta, and Mus musculus, we identified 63 potential studies containing host and parasite data. While 16 studies (1,950 samples) explicitly performed dual RNA-Seq, 47 (1,398 samples) originally focused on one organism. We found 915 experimental replicates from 20 blood studies to be suitable for coexpression analysis and used orthologs for meta-analysis across different host-parasite systems. Centrality metrics from the derived gene expression networks correlated with gene essentiality in the parasites. We found indications of host immune response to elements of the Plasmodium protein degradation system, an antimalarial drug target. We identified well-studied immune responses in the host with our coexpression networks, as our approach recovers known broad processes interlinked between hosts and parasites in addition to individual host and parasite protein associations. The set of core interactions represents commonalities between human malaria and its model systems for prioritization in laboratory experiments. Our approach might also allow insights into the transferability of model systems for different pathways in malaria studies. IMPORTANCE Malaria still causes about 400,000 deaths a year and is one of the most studied infectious diseases. The disease is studied in mice and monkeys as lab models to derive potential therapeutic intervention in human malaria. Interactions between Plasmodium spp. and its hosts are either conserved across different host-parasite systems or idiosyncratic to those systems. Here we use correlation of gene expression from different RNA-Seq studies to infer common host-parasite interactions across human, mouse, and monkey studies. First, we find a set of very conserved interactors, worth further scrutiny in focused laboratory experiments. Second, this work might help assess to which extent experiments and knowledge on different pathways can be transferred from models to humans for potential therapy.
format	article
author	Parnika Mukherjee Gaétan Burgio Emanuel Heitlinger
author_facet	Parnika Mukherjee Gaétan Burgio Emanuel Heitlinger
author_sort	Parnika Mukherjee
title	Dual RNA Sequencing Meta-analysis in <italic toggle="yes">Plasmodium</italic> Infection Identifies Host-Parasite Interactions
title_short	Dual RNA Sequencing Meta-analysis in <italic toggle="yes">Plasmodium</italic> Infection Identifies Host-Parasite Interactions
title_full	Dual RNA Sequencing Meta-analysis in <italic toggle="yes">Plasmodium</italic> Infection Identifies Host-Parasite Interactions
title_fullStr	Dual RNA Sequencing Meta-analysis in <italic toggle="yes">Plasmodium</italic> Infection Identifies Host-Parasite Interactions
title_full_unstemmed	Dual RNA Sequencing Meta-analysis in <italic toggle="yes">Plasmodium</italic> Infection Identifies Host-Parasite Interactions
title_sort	dual rna sequencing meta-analysis in <italic toggle="yes">plasmodium</italic> infection identifies host-parasite interactions
publisher	American Society for Microbiology
publishDate	2021
url	https://doaj.org/article/060d5e7505f74c00a04567e2b006164b
work_keys_str_mv	AT parnikamukherjee dualrnasequencingmetaanalysisinitalictoggleyesplasmodiumitalicinfectionidentifieshostparasiteinteractions AT gaetanburgio dualrnasequencingmetaanalysisinitalictoggleyesplasmodiumitalicinfectionidentifieshostparasiteinteractions AT emanuelheitlinger dualrnasequencingmetaanalysisinitalictoggleyesplasmodiumitalicinfectionidentifieshostparasiteinteractions
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Dual RNA Sequencing Meta-analysis in <italic toggle="yes">Plasmodium</italic> Infection Identifies Host-Parasite Interactions

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