多队列分析确定了人类与恶性疟原虫之间保守的转录相互作用

Bárbara Fernandes Silva , Nágila Isleide Silva , Pedro Felipe Loyola Souza , Tiago Paiva Guimarães , Luiz Gustavo Gardinassi
{"title":"多队列分析确定了人类与恶性疟原虫之间保守的转录相互作用","authors":"Bárbara Fernandes Silva ,&nbsp;Nágila Isleide Silva ,&nbsp;Pedro Felipe Loyola Souza ,&nbsp;Tiago Paiva Guimarães ,&nbsp;Luiz Gustavo Gardinassi","doi":"10.1016/j.immuno.2024.100044","DOIUrl":null,"url":null,"abstract":"<div><p>Malaria is caused by <em>Plasmodium</em>, a parasite that replicates inside and ruptures erythrocytes, causing an intense inflammatory response. Advances in high-throughput sequencing technologies have enabled the simultaneous study of the gene expression in humans and <em>P. falciparum</em>. However, the high-dimensional correlational networks generated in previous studies challenge the interpretation of the underlying biology, whereas associations found in one cohort might not replicate in independent samples due confounding factors affecting gene expression. We combined multicohort analysis of correlations with a hierarchical grouping approach to improve the discovery and interpretation of transcriptional associations between humans and <em>P. falciparum</em>. We analyzed nine public dual-transcriptomes acquired from whole blood of individuals infected with <em>P. falciparum</em>. Blood Transcription Modules (BTM) were used to reduce the dimension of host transcriptomes and Spearman's correlation analysis was used to identify host-parasite associations. Following, we performed meta-analysis of correlations with Stouffer's method and Bonferroni correction that resulted in a major transcriptional meta-network between humans and <em>P. falciparum</em>. We identified, for example, positive correlations between <em>PAK1, NFKBIA, BIRC2, NLRC4, TLR4, RIPK2</em> expression and <em>PF3D7_1205800</em>, a putative <em>P. falciparum</em> high mobility group protein B3 (HMGB3). We also applied a leave-one-out strategy to prevent influence of confounding factors, resulting in highly conserved associations between host genes related to inflammation, immune cells, and glycerophospholipid metabolism with <em>PF3D7_1223400</em>, which encodes a putative phospholipid-transporting ATPase. Paired metabolomics and transcriptomics data revealed negative correlation between <em>PF3D7_1223400</em> expression and the relative abundance of 1-linoleoyl-GPG. Collectively, our study provides data-driven hypotheses about molecular mechanisms of host-parasite interaction.</p></div>","PeriodicalId":73343,"journal":{"name":"Immunoinformatics (Amsterdam, Netherlands)","volume":"16 ","pages":"Article 100044"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667119024000144/pdfft?md5=0bb5fec5def6b5a092876014fea42924&pid=1-s2.0-S2667119024000144-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Multicohort analysis identifies conserved transcriptional interactions between humans and Plasmodium falciparum\",\"authors\":\"Bárbara Fernandes Silva ,&nbsp;Nágila Isleide Silva ,&nbsp;Pedro Felipe Loyola Souza ,&nbsp;Tiago Paiva Guimarães ,&nbsp;Luiz Gustavo Gardinassi\",\"doi\":\"10.1016/j.immuno.2024.100044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Malaria is caused by <em>Plasmodium</em>, a parasite that replicates inside and ruptures erythrocytes, causing an intense inflammatory response. Advances in high-throughput sequencing technologies have enabled the simultaneous study of the gene expression in humans and <em>P. falciparum</em>. However, the high-dimensional correlational networks generated in previous studies challenge the interpretation of the underlying biology, whereas associations found in one cohort might not replicate in independent samples due confounding factors affecting gene expression. We combined multicohort analysis of correlations with a hierarchical grouping approach to improve the discovery and interpretation of transcriptional associations between humans and <em>P. falciparum</em>. We analyzed nine public dual-transcriptomes acquired from whole blood of individuals infected with <em>P. falciparum</em>. Blood Transcription Modules (BTM) were used to reduce the dimension of host transcriptomes and Spearman's correlation analysis was used to identify host-parasite associations. Following, we performed meta-analysis of correlations with Stouffer's method and Bonferroni correction that resulted in a major transcriptional meta-network between humans and <em>P. falciparum</em>. We identified, for example, positive correlations between <em>PAK1, NFKBIA, BIRC2, NLRC4, TLR4, RIPK2</em> expression and <em>PF3D7_1205800</em>, a putative <em>P. falciparum</em> high mobility group protein B3 (HMGB3). We also applied a leave-one-out strategy to prevent influence of confounding factors, resulting in highly conserved associations between host genes related to inflammation, immune cells, and glycerophospholipid metabolism with <em>PF3D7_1223400</em>, which encodes a putative phospholipid-transporting ATPase. Paired metabolomics and transcriptomics data revealed negative correlation between <em>PF3D7_1223400</em> expression and the relative abundance of 1-linoleoyl-GPG. Collectively, our study provides data-driven hypotheses about molecular mechanisms of host-parasite interaction.</p></div>\",\"PeriodicalId\":73343,\"journal\":{\"name\":\"Immunoinformatics (Amsterdam, Netherlands)\",\"volume\":\"16 \",\"pages\":\"Article 100044\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2667119024000144/pdfft?md5=0bb5fec5def6b5a092876014fea42924&pid=1-s2.0-S2667119024000144-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Immunoinformatics (Amsterdam, Netherlands)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667119024000144\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Immunoinformatics (Amsterdam, Netherlands)","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667119024000144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

疟疾是由疟原虫引起的,这种寄生虫在红细胞内复制并破裂,引起强烈的炎症反应。高通量测序技术的进步使得人类和恶性疟原虫基因表达的同步研究成为可能。然而,以往研究中生成的高维相关网络对解释潜在的生物学问题提出了挑战,而在一个队列中发现的关联可能无法在独立样本中复制,因为影响基因表达的因素会造成混淆。我们将多队列相关性分析与分层分组方法相结合,以改进人类与恶性疟原虫之间转录关联的发现和解释。我们分析了从恶性疟原虫感染者全血中获取的九个公开双转录组。血液转录模块(BTM)被用来降低宿主转录组的维度,斯皮尔曼相关分析被用来识别宿主与寄生虫之间的关联。随后,我们用斯托弗方法和邦费罗尼校正法对相关性进行了元分析,结果发现了人类与恶性疟原虫之间的主要转录元网络。例如,我们发现 PAK1、NFKBIA、BIRC2、NLRC4、TLR4、RIPK2 的表达与 PF3D7_1205800(恶性疟原虫高迁移率基团蛋白 B3 (HMGB3))之间存在正相关。我们还采用了剔除策略以防止混杂因素的影响,结果发现与炎症、免疫细胞和甘油磷脂代谢相关的宿主基因与 PF3D7_1223400 之间存在高度保守的关联,PF3D7_1223400 编码一种推测的磷脂转运 ATP 酶。成对的代谢组学和转录组学数据显示,PF3D7_1223400 的表达与 1-linoleoyl-GPG 的相对丰度呈负相关。总之,我们的研究为宿主与寄生虫相互作用的分子机制提供了数据驱动的假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multicohort analysis identifies conserved transcriptional interactions between humans and Plasmodium falciparum

Multicohort analysis identifies conserved transcriptional interactions between humans and Plasmodium falciparum

Malaria is caused by Plasmodium, a parasite that replicates inside and ruptures erythrocytes, causing an intense inflammatory response. Advances in high-throughput sequencing technologies have enabled the simultaneous study of the gene expression in humans and P. falciparum. However, the high-dimensional correlational networks generated in previous studies challenge the interpretation of the underlying biology, whereas associations found in one cohort might not replicate in independent samples due confounding factors affecting gene expression. We combined multicohort analysis of correlations with a hierarchical grouping approach to improve the discovery and interpretation of transcriptional associations between humans and P. falciparum. We analyzed nine public dual-transcriptomes acquired from whole blood of individuals infected with P. falciparum. Blood Transcription Modules (BTM) were used to reduce the dimension of host transcriptomes and Spearman's correlation analysis was used to identify host-parasite associations. Following, we performed meta-analysis of correlations with Stouffer's method and Bonferroni correction that resulted in a major transcriptional meta-network between humans and P. falciparum. We identified, for example, positive correlations between PAK1, NFKBIA, BIRC2, NLRC4, TLR4, RIPK2 expression and PF3D7_1205800, a putative P. falciparum high mobility group protein B3 (HMGB3). We also applied a leave-one-out strategy to prevent influence of confounding factors, resulting in highly conserved associations between host genes related to inflammation, immune cells, and glycerophospholipid metabolism with PF3D7_1223400, which encodes a putative phospholipid-transporting ATPase. Paired metabolomics and transcriptomics data revealed negative correlation between PF3D7_1223400 expression and the relative abundance of 1-linoleoyl-GPG. Collectively, our study provides data-driven hypotheses about molecular mechanisms of host-parasite interaction.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Immunoinformatics (Amsterdam, Netherlands)
Immunoinformatics (Amsterdam, Netherlands) Immunology, Computer Science Applications
自引率
0.00%
发文量
0
审稿时长
60 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信