Immunoinformatics (Amsterdam, Netherlands)最新文献_第2页

Challenges and future directions of AIRR-seq-based diagnostics 基于airr -seq的诊断的挑战和未来方向

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2025-09-01 Epub Date: 2025-07-17 DOI: 10.1016/j.immuno.2025.100056

Ulrik Stervbo , Paraskevas Filippidis , Felix Breden , Lindsay G. Cowell , Frederic Davi , Victor Greiff , Anton W. Langerak , Eline T. Luning Prak , Alexandra F. Sharland , Enkelejda Miho , Pieter Meysman

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a promising diagnostic method across various clinical conditions, yet its widespread implementation faces several challenges. This perspective examines the current landscape of AIRR-seq diagnostics and outlines key obstacles and opportunities for advancement. Critical challenges include the need for standardized quality controls, privacy protection under General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA) frameworks, and the development of clinically compatible bioinformatics pipelines. Machine learning approaches offer potential solutions for interpreting complex repertoire signatures, though these models must balance accuracy with interpretability for clinical adoption. Future applications may include early disease detection, prognosis, and monitoring of treatment and vaccine responses. However, successful clinical integration will require sustained collaboration among funding bodies, regulatory agencies, researchers, diagnosticians, and clinicians to establish clear guidelines and expand existing repositories with well-characterized patient samples. The collaborative efforts of the AIRR Diagnostics Working Group and the AIRR Community's initiatives are working towards unlocking the potential of AIRR-seq in precision medicine and enhancing diagnostic capabilities.

适应性免疫受体库测序（AIRR-seq）是一种很有前途的诊断方法，适用于各种临床条件，但其广泛实施面临着一些挑战。这一观点考察了AIRR-seq诊断的现状，并概述了发展的主要障碍和机会。关键的挑战包括需要标准化的质量控制，在通用数据保护条例（GDPR）和健康保险流通与责任法案（HIPAA）框架下的隐私保护，以及开发临床兼容的生物信息学管道。机器学习方法为解释复杂的曲目特征提供了潜在的解决方案，尽管这些模型必须平衡准确性和临床采用的可解释性。未来的应用可能包括早期疾病检测、预后、治疗和疫苗反应监测。然而，成功的临床整合将需要资助机构、监管机构、研究人员、诊断医生和临床医生之间的持续合作，以建立明确的指导方针，并扩大现有的具有良好特征的患者样本库。AIRR诊断工作组和AIRR社区的倡议正在共同努力，以释放AIRR-seq在精准医学和增强诊断能力方面的潜力。

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引用次数: 0

AnalyzAIRR: A user-friendly guided workflow for AIRR data analysis AnalyzAIRR：一个用户友好的指导工作流，用于AIRR数据分析

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2025-09-01 Epub Date: 2025-06-25 DOI: 10.1016/j.immuno.2025.100052

Vanessa Mhanna , Gabriel Pires , Grégoire Bohl-Viallefond , Karim El Soufi , Nicolas Tchitchek , David Klatzmann , Adrien Six , Hang P. Pham , Encarnita Mariotti-Ferrandiz

The analysis of bulk adaptive immune receptor repertoires (AIRR) enables the understanding of immune responses in both normal and pathological conditions. However, the complexity of AIRR calls for advanced, specialized methods to extract meaningful biological insights. These sophisticated approaches often present challenges for researchers with limited bioinformatics expertise, hindering access to comprehensive immune system analysis. To address this challenge, we developed AnalyzAIRR, an AIRR-compliant R package enabling advanced bulk AIRR sequencing data. The tool integrates state-of-the-art statistical and visualization methods applicable at various levels of granularity. It offers a platform for general data exploration, filtering and manipulation, and in-depth cross-comparisons of AIRR datasets, aimed at answering specific biological questions. We illustrate AnalyzAIRR functionalities using a published murine dataset of 18 T-cell receptor repertoires from three diferrent T cell subsets. We first detected and removed a major contaminant in a group of samples, before proceeding with the comparative analysis. Subsequent cross-sample analysis revealed differences in repertoire diversity that aligned with the respective cell phenotypes, and in repertoire convergence among the studied subsets. AnalyzAIRR’s set of analytical metrics is integrated into a Shiny web application and complemented with a tutorial to help users in their analytical strategy, making it user-friendly for biologists with little or no background in bioinformatics.

对大量适应性免疫受体（AIRR）的分析使我们能够理解正常和病理条件下的免疫反应。然而，AIRR的复杂性需要先进的、专门的方法来提取有意义的生物学见解。这些复杂的方法往往给生物信息学专业知识有限的研究人员带来挑战，阻碍了获得全面的免疫系统分析。为了应对这一挑战，我们开发了AnalyzAIRR，这是一个符合AIRR标准的R包，可以实现先进的批量AIRR测序数据。该工具集成了适用于不同粒度级别的最先进的统计和可视化方法。它为一般数据探索、过滤和操作提供了一个平台，并对AIRR数据集进行了深入的交叉比较，旨在回答特定的生物学问题。我们使用已发表的来自三个不同T细胞亚群的18个T细胞受体的小鼠数据集来说明AnalyzAIRR的功能。在进行对比分析之前，我们首先在一组样品中检测并去除了一种主要污染物。随后的跨样本分析揭示了与各自细胞表型一致的库多样性差异，以及研究亚群之间的库收敛性差异。AnalyzAIRR的分析指标集集成到Shiny的web应用程序中，并辅以教程来帮助用户进行分析策略，使其对生物信息学背景很少或没有背景的生物学家来说都是用户友好的。

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引用次数: 0

Challenges for the immunoglobulin and T cell receptor gene nomenclatures in the modern genomics era 免疫球蛋白和T细胞受体基因命名在现代基因组学时代的挑战

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2025-09-01 Epub Date: 2025-06-27 DOI: 10.1016/j.immuno.2025.100053

Andrew M. Collins , Corey T. Watson , Henk-Jan van den Ham , Luc Teyton , Elisa Rosati , Yana Safonova

For over thirty years, an approach to the nomenclatures of human immunoglobulin (IG) and T cell receptor (TR) genes has operated successfully and has been widely supported by the research community. The principles behind the human nomenclatures were then applied to the development of nomenclatures for IG and TR genes in non-human species. More recently, however, genomic sequencing has highlighted the limitations of this historic approach to nomenclature. The sequencing of IG and TR gene loci from multiple individuals and from a number of species has unveiled an extraordinary level of structural variation within the loci of all species that have so far been studied in this way. The designated gene naming authority - the International Union of Immunological Societies (IUIS) IG and TR Nomenclature Sub-Committee - has determined that a more careful approach is required before the genes of any species are officially named. In this opinion piece, we outline the challenges of the IG and TR nomenclatures, hoping to stimulate dialogue within the research community. Such dialogue would help guide the formulation of official policies to determine the appropriate level of knowledge of a locus that should be required before official gene names can be assigned. Strategies are also presented that should allow the unambiguous reporting and discussion of IG and TR gene sequences if their official naming is delayed.

三十多年来，一种命名人类免疫球蛋白（IG）和T细胞受体（TR）基因的方法已经成功运作，并得到了研究界的广泛支持。人类命名法背后的原则随后被应用于非人类物种IG和TR基因命名法的发展。然而，最近，基因组测序突出了这种历史命名方法的局限性。对多个个体和多个物种的IG和TR基因座的测序揭示了迄今为止以这种方式研究的所有物种的基因座内的异常水平的结构变异。指定的基因命名机构——国际免疫学会联合会（IUIS） IG和TR命名小组委员会——已经确定，在正式命名任何物种的基因之前，需要采取更谨慎的方法。在这篇观点文章中，我们概述了IG和TR命名所面临的挑战，希望能激发研究界的对话。这种对话将有助于指导官方政策的制定，以确定在指定官方基因名称之前对基因座的适当知识水平。如果IG和TR基因序列的正式命名延迟，还提出了应允许明确报告和讨论的策略。

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引用次数: 0

Building immunoglobulin and T cell receptor gene databases for the future 未来建立免疫球蛋白和T细胞受体基因数据库

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2025-09-01 Epub Date: 2025-08-27 DOI: 10.1016/j.immuno.2025.100059

Corey T. Watson , Andrew M. Collins , Mats Ohlin , James M. Heather , Ayelet Peres , William D. Lees , Gur Yaari

Genetic databases for immunoglobulin (IG) and T cell receptor (TR) genes have evolved from small catalogs to critical resources underpinning immunogenetic research. Accurate annotation enables the analysis of repertoire diversity, somatic hypermutation, clonal relationships, and lineage development. Recent advances in high-throughput repertoire sequencing and long-read genomics now allow for unprecedented discovery of germline variation across populations and species, but they also expose limitations of existing resources. Here, we discuss the historical evolution of IG/TR databases, highlight the challenges and opportunities presented by changing data landscapes, and outline strategies for building future databases that integrate genomic and expression data, support population diversity, and align with evolving nomenclature frameworks. Enhanced germline resources will be essential for accurate annotation, reproducible research, and the next generation of immunological discovery and clinical translation.

免疫球蛋白（IG）和T细胞受体（TR）基因的遗传数据库已经从小型目录发展成为支持免疫遗传学研究的关键资源。准确的注释能够分析曲目多样性，体细胞超突变，克隆关系和谱系发展。高通量全库测序和长读基因组学的最新进展现在允许在种群和物种之间前所未有地发现生殖系变异，但它们也暴露了现有资源的局限性。本文讨论了IG/TR数据库的历史演变，强调了不断变化的数据格局所带来的挑战和机遇，并概述了构建整合基因组和表达数据、支持种群多样性并与不断发展的命名框架保持一致的未来数据库的策略。增强生殖系资源对于准确注释、可重复性研究以及下一代免疫学发现和临床翻译至关重要。

引用次数: 0

Is the vaccination-induced B cell receptor repertoire predictable? 疫苗诱导的B细胞受体库可预测吗？

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2025-09-01 Epub Date: 2025-08-25 DOI: 10.1016/j.immuno.2025.100057

Eve Richardson , Lisa Willemsen , Pramod Shinde , Morten Nielsen , Bjoern Peters

Vaccines trigger an immune response that results in a population of memory cells that can quickly respond to subsequent antigen re-encounters. Most vaccines are designed to induce memory B cells with vaccine-specific B cell receptors (BCRs). Post-vaccination, clonal expansion of B cells results in measurably expanded vaccine-specific BCR clonotypes. We set out to determine to what extent it is predictable which specific BCR clonotypes are vaccine-induced in an individual. We sequenced the BCR heavy chain repertoire in a cohort of 19 individuals prior- and 7 days post Tdap booster vaccination. We tested two modalities to predict which clonotypes were expanded post-vaccination: first, we utilized a small database of monoclonal antibodies with known specificity to Tdap vaccine antigens and tested various sequence look-up methods, identifying clonal look-up as the best method. We then utilized a leave-one-out approach in which expanded clonotypes in one individual were predicted using data from other members of the cohort. The second approach significantly outperformed the first, indicating that BCR clonotype expansion can be learned across subjects. These results support the utility of systematically collecting BCR specificity data through efforts like the Immune Epitope database and highlight the limitations on general prediction approaches resulting from relatively small dataset sizes for BCRs with known specificities. Additionally, our study provides 1) a comparison of several BCR specificity prediction methods, 2) a dataset that can be used for benchmarking of subsequent methods, and 3) a methodological framework for comparing BCR repertoires pre- and post-vaccination.

疫苗会引发免疫反应，导致记忆细胞群迅速对随后再次遇到的抗原做出反应。大多数疫苗被设计成用疫苗特异性B细胞受体（BCRs）诱导记忆B细胞。接种后，B细胞克隆扩增导致可测量扩增的疫苗特异性BCR克隆型。我们着手确定在多大程度上可以预测疫苗在个体中诱导的特定BCR克隆型。我们对接种Tdap加强疫苗前和接种后7天的19名个体的BCR重链库进行了测序。我们测试了两种方法来预测疫苗接种后扩增的克隆型：首先，我们利用了一个已知Tdap疫苗抗原特异性的小型单克隆抗体数据库，并测试了各种序列查找方法，确定克隆查找方法是最佳方法。然后，我们使用了一种“留一”方法，其中使用来自队列其他成员的数据预测一个个体的扩展克隆型。第二种方法明显优于第一种方法，表明BCR克隆型扩增可以跨受试者学习。这些结果支持通过免疫表位数据库等工作系统地收集BCR特异性数据的效用，并突出了由于已知特异性的BCR相对较小的数据集大小而导致的一般预测方法的局限性。此外，我们的研究提供了1)几种BCR特异性预测方法的比较，2)可用于对后续方法进行基准测试的数据集，以及3)比较接种前和接种后BCR库的方法框架。

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引用次数: 0

Corrigendum to “T-cell receptor binding prediction: A machine learning revolution” [ImmunoInformatics, Volume 15, September 2024, 100040] “t细胞受体结合预测：机器学习革命”的更正[免疫信息学，第15卷，2024年9月，100040]

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2025-06-01 Epub Date: 2025-03-17 DOI: 10.1016/j.immuno.2025.100049

Prof. María Rodríguez Martínez

引用次数: 0

Molecular mimicry impact of the COVID-19 pandemic: Sequence homology between SARS-CoV-2 and autoimmune diseases epitopes COVID-19大流行的分子模拟影响：SARS-CoV-2与自身免疫性疾病表位的序列同源性

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2025-06-01 Epub Date: 2025-03-13 DOI: 10.1016/j.immuno.2025.100050

Pablo Maldonado-Catala , Ram Gouripeddi , Naomi Schlesinger , Julio C. Facelli

Molecular mimicry is one mechanism by which an infectious agent may trigger an autoimmune disease in a human subject and occurs when foreign- and self-peptides contain similar epitopes that activate an autoimmune response in a susceptible individual. Here, we employ a scalable in-silico approach, to identify 861 pairs of known SARS-CoV-2 and autoimmune disease epitopes, out of more than one billion possible pairs. These SARS-CoV-2 epitopes show 1) sequence homology to human autoimmune disorder epitopes, 2) empirical binding data that predict that they bind the same major histocompatibility complex (MHC) molecule and 3) exhibit high empirical immunogenicity. Analysis of these epitope pairs reveals an association between autoimmune disorders, such as type 1 diabetes, autoimmune uveitis, ankylosing spondylitis, and SARS-CoV-2 infection. These associations are consistent with those reported in the literature from the analysis of clinical records.

分子模仿是一种机制，通过这种机制，感染因子可以在人体受试者中引发自身免疫疾病，当外源肽和自身肽含有相似的表位时，就会发生这种机制，从而激活易感个体的自身免疫反应。在这里，我们采用可扩展的计算机方法，从超过10亿对可能的表位中鉴定出861对已知的SARS-CoV-2和自身免疫性疾病表位。这些SARS-CoV-2表位显示1)序列与人类自身免疫性疾病表位同源，2)经验结合数据预测它们结合相同的主要组织相容性复合体（MHC）分子，3)具有高的经验免疫原性。对这些表位对的分析揭示了自身免疫性疾病，如1型糖尿病、自身免疫性葡萄膜炎、强直性脊柱炎和SARS-CoV-2感染之间的关联。这些关联与临床记录分析文献中报道的一致。

引用次数: 0

Deciphering the role of molecular mimicry in the etiopathogenesis of Autoimmune Hemolytic Anemia using an immunoinformatics approach. 利用免疫信息学方法解读自身免疫性溶血性贫血发病机制中的分子模拟作用。

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2025-03-01 Epub Date: 2025-02-06 DOI: 10.1016/j.immuno.2025.100047

Pratyusha Patidar , Arihant Jain , Tulika Prakash

Autoimmune hemolytic anemia (AIHA) is a chronic autoimmune disease characterized by the self-destruction of red blood cells (RBCs). For investigating the role molecular mimicry in the onset of AIHA manifestations, we identified the microbial epitopes as precipitating factors in the disease etiopathology using an integrated immunoinformatics pipeline which includes sequence homology search between microbial and RBC proteins, followed by B-cell and T-cell epitope prediction. These epitopes were further subjected to a homology search with the human gut microbial proteins. Eight out of the ten analysed infectious agents, including Hepatitis C Virus (HCV), Cytomegalovirus (CMV), Epstein-Barr Virus (EBV), Herpes Simplex Virus (HSV), Human Papillomavirus (HPV), Human Immunodeficiency Virus (HIV), Mycoplasma pneumoniae (MP), and Treponema pallidum (TP), possessed B-cell and T-cell epitopes. Interestingly, EBV, HSV, MP, and TP displayed conformational B-cell epitopes, which overlapped with their linear B-cell epitopes. HLA DRB1_0305 was found to exhibit binding with several bacterial epitopes indicating its predisposing potential to AIHA. Further, we report cross-reactive microbial epitopes against RBC proteins that have been experimentally proven to be associated with AIHA indicating a high possibility of those epitopes causing AIHA. Additionally, many B-cell and T-cell epitopes exhibited exact homologies with various human gut microbial proteins. The functional annotation highlighted the involvement of specialized RBC functions, such as cytoskeleton organization, ammonium homeostasis, signalling transduction, in the underlying disease mechanism. These findings suggest that infection-causing pathogens and gut microbes might have a plausible association with AIHA in the context of molecular mimicry.

自身免疫性溶血性贫血（AIHA）是一种以红细胞（rbc）自我破坏为特征的慢性自身免疫性疾病。为了研究分子模仿在AIHA发病中的作用，我们使用综合免疫信息学管道确定微生物表位是疾病病因病理学的沉淀因素，其中包括微生物和RBC蛋白之间的序列同源性搜索，然后是b细胞和t细胞表位预测。这些表位进一步与人类肠道微生物蛋白进行同源性搜索。在分析的10种感染因子中，有8种具有b细胞和t细胞表位，包括丙型肝炎病毒（HCV）、巨细胞病毒（CMV）、eb病毒（EBV）、单纯疱疹病毒（HSV）、人乳头瘤病毒（HPV）、人类免疫缺陷病毒（HIV）、肺炎支原体（MP）和梅毒体（TP）。有趣的是，EBV、HSV、MP和TP显示构象b细胞表位，与它们的线性b细胞表位重叠。发现HLA DRB1_0305与几种细菌表位结合，表明其易患AIHA。此外，我们报道了抗红细胞蛋白的交叉反应性微生物表位，这些表位已被实验证明与AIHA相关，这表明这些表位极有可能引起AIHA。此外，许多b细胞和t细胞表位与各种人类肠道微生物蛋白具有精确的同源性。功能注释强调了特殊的红细胞功能，如细胞骨架组织、铵态平衡、信号转导，在潜在的疾病机制中的参与。这些发现表明，在分子拟态的背景下，引起感染的病原体和肠道微生物可能与AIHA有似是而非的关联。

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引用次数: 0

Comparative analysis of SLA-1 and SLA-2 genetic diversity in exotic, hybrid, and local pig breeds of Cameroon in relation to adaptive immunity against African swine virus 喀麦隆外来、杂交和地方猪种SLA-1和SLA-2遗传多样性与非洲猪病毒适应性免疫的比较分析

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2025-03-01 Epub Date: 2025-02-06 DOI: 10.1016/j.immuno.2025.100048

Ebanja Joseph Ebwanga , Jess Bouhuijzen Wenger , Robert Adamu Shey , Nadine Buys , Rob Lavigne , Stephen Mbigha Ghogomu , Jan Paeshuyse

African swine fever is a severe hemorrhagic swine disease that greatly affects smallholder pig farm productivity in low-income countries as well as some developed countries. Research has shown that the indigenous pigs and wild suids in Africa are either tolerant or resistant to the disease. Also, resistance to disease and favourable production traits are attributed to polymorphism within the major histocompatibility complex (MHC), which is crucial for the vertebrate's adaptive immune response. The polymorphism within the swine leukocyte antigen (SLA) is attributable to host-pathogen co-evolution which results in improved resistance to disease as well as adaptation to diverse environments. While this makes the SLA essential for comparative diversity studies, comparative SLA studies are absent in this context. We undertook SLA-1 and SLA-2 exon-2 comparative genetic diversity study within the locally adapted (local) breed, hybrid (a cross between local and exotic), and the exotic breed of pigs in Cameroon using the polymerase chain reaction sequence-based typing method on 41 animals. Our data analyses provide evidence of positive balancing selection as well as conserved private alleles within the local breeds, the highest expected heterozygosity within the tolerant population while the exotic population had the highest number of haplotypes for both SLA-1 and SLA-2 . The results from this study contribute to our expanding knowledge of SLA genetic diversity while providing the first SLA data for the indigenous and exotic breeds of pigs in Cameroon.

非洲猪瘟是一种严重的出血性猪病，严重影响低收入国家和一些发达国家小农养猪场的生产力。研究表明，非洲的本地猪和野生猪对这种疾病要么具有耐受性，要么具有耐药性。此外，对疾病的抵抗力和有利的生产性状归因于主要组织相容性复合体（MHC）内的多态性，这对脊椎动物的适应性免疫反应至关重要。猪白细胞抗原（SLA）的多态性可归因于宿主-病原体的共同进化，从而提高了对疾病的抵抗力以及对不同环境的适应。虽然这使得二语习得对比较多样性研究至关重要，但在这一背景下，二语习得的比较研究是缺失的。我们采用基于聚合酶链反应序列的分型方法，对喀麦隆当地适应（本地）品种、杂交（本地与外来杂交）和外来猪品种的SLA-1和SLA-2外显子-2进行了遗传多样性比较研究。我们的数据分析提供了本地品种中正平衡选择和保守的私有等位基因的证据，在耐受群体中具有最高的期望杂合性，而在外来群体中具有最高的SLA-1和SLA-2单倍型数量。本研究的结果有助于我们扩大SLA遗传多样性的知识，同时为喀麦隆的本地和外来猪种提供了第一个SLA数据。

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引用次数: 0

Multicohort analysis identifies conserved transcriptional interactions between humans and Plasmodium falciparum 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

Immunoinformatics (Amsterdam, Netherlands)

Pub Date : 2024-12-01 Epub Date: 2024-09-16 DOI: 10.1016/j.immuno.2024.100044

Bárbara Fernandes Silva , Nágila Isleide Silva , Pedro Felipe Loyola Souza , Tiago Paiva Guimarães , Luiz Gustavo Gardinassi

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.

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。

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引用次数: 0