Identification of disease-related genes in Plasmodium berghei by network module analysis

• Published in: BMC microbiology Vol. 23; no. 1; pp. 1 - 264
• Main Authors: Lin, Junhao, Zeng, Shan, Chen, Qiong, Liu, Guanghui, Pan, Suyue, Liu, Xuewu
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 21.09.2023; BioMed Central; BMC
• Subjects: Algorithms; Analysis; Annotations; Antigenic determinants; Biological activity; Cluster analysis; Clusters; Control; Developmental stages; Disease; Epitopes; Experimental cerebral malaria (ECM); Extracellular matrix; Genes; Genetic engineering; Genomes; Genomics; High-throughput screening (Biochemical assaying); Identification and classification; Lymphocytes T; Major histocompatibility complex; Malaria; Methods; Modules; Network module; Nucleotide sequence; Ontology; Parasites; Pathogenesis; Phenotype; Plasmodium berghei; Plasmodium falciparum; Prevention; Proteins; Risk factors; T cells; Vector-borne diseases; China
• ISSN: 1471-2180; 1471-2180
• DOI: 10.1186/s12866-023-03019-0

Plasmodium berghei has been used as a preferred model for studying human malaria, but only a limited number of disease-associated genes of P. berghei have been reported to date. Identification of new disease-related genes as many as possible will provide a landscape for better understanding the pathogenesis of P. berghei. Network module analysis method was developed and applied to identify disease-related genes in P. berghei genome. Sequence feature identification, gene ontology annotation, and T-cell epitope analysis were performed on these genes to illustrate their functions in the pathogenesis of P. berghei. 33,314 genes were classified into 4,693 clusters. 4,127 genes shared by six malaria parasites were identified and are involved in many aspects of biological processes. Most of the known essential genes belong to shared genes. A total of 63 clusters consisting of 405 P. berghei genes were enriched in rodent malaria parasites. These genes participate in various stages of parasites such as liver stage development and immune evasion. Combination of these genes might be responsible for P. berghei infecting mice. Comparing with P. chabaudi, none of the clusters were specific to P. berghei. P. berghei lacks some proteins belonging to P. chabaudi and possesses some specific T-cell epitopes binding by class-I MHC, which might together contribute to the occurrence of experimental cerebral malaria (ECM). We successfully identified disease-associated P. berghei genes by network module analysis. These results will deepen understanding of the pathogenesis of P. berghei and provide candidate parasite genes for further ECM investigation.