Dataset Information

Identification of blood MHC-binding peptides in mice after Brucella infection

ABSTRACT: We infected mice with Brucella, took mouse blood 6 days after infection, MHC binding antigenic peptides were collected by immunoprecipitation method and verified by mass spectrometry

ORGANISM(S): Mus Musculus

SUBMITTER: Yufei Wang

PROVIDER: PXD032855 | iProX | Sun Mar 27 00:00:00 GMT 2022

REPOSITORIES: iProX

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Identification of potential antigenic peptides of Brucella through proteome and peptidome.

Pei Meijuan M Dong Ao A Ma Xueping X Li Shulei S Guo Yan Y Li Menglan M Wang Zhenghui Z Wang Hengliang H Zhu Li L Pan Chao C Wang Yufei Y

Veterinary medicine and science 20221230 1

<h4>Background</h4>Brucellosis, caused by Brucella spp., is a major zoonotic public health threat. Although several Brucella vaccines have been demonstrated for use in animals, Brucella spp. can cause human infection and to date, there are no human-use vaccines licensed by any agency. Recently, methods in vaccine informatics have made major breakthroughs in peptide-based epitopes, opening up a new avenue of vaccine development.<h4>Objectives</h4>The purpose of this article was to identify potent ...[more]

PMID: 36583994

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Project description:Goal: High-throughput sequencing-by-synthesis (Illumina) RNA sequencing technology was carried out with an aim to gain deeper understanding of immune host protective mechanisms. Here, RNA-seq was applied to understand the differential gene expression profile of mice spleen following immunization with Brucella abortus S19∆per mutant (perosamine synthetase gene mutant of Brucella abortus S19) in comparison to mock immunized mice spleen (PBS inoculated). Methods: RNA-seq data of 15th day post immunized mice spleen (with Brucella abortus S19∆per) and PBS control mice were generated by deep sequencing ( in duplicate) using IlluminaNextSeq 500 . The sequence reads that passed quality filters were analyzed for transcript abundance using RSEM package (RNA-Seq by Expectation Maximization) (Li and Dewey, 2011). Breifly, the RSEM package generated a reference sequence based on given mouse transcript annotations (Mus_musculus.GrCm38.83.chr.gtf.gz). The Bowtie allignmet tool available within the package was used to calculate expected counts (number of mapped reads) using quality trimmed reads and reference sequence. Finally, the expected counts estimated by RSEM were fed into different DE package tools, such as DESeq2 (Love et al., 2014), edgeR (Robinson et al., 2010) and EBSeq (Leng et al., 2013) in order to identify differentially expressed genes across spleen samples (B. abortus S19∆per versus (vs) PBS control. Functional annotation of differently expressed genes were carried out using g:Profiler (Reimandet al., 2016; http://biit.cs.ut.ee/gprofiler/). Results: A mean of 37.58 million processed reads (range: 30.51 million to 51.79 million reads per individual RNA-seq library) were generated during the experiment. The expected counts generated by the RSEM package followed by differential analysis calculation using different DE packages identified a total of 1917 differentially expressed genes (DEGs), of which 968 and 949 genes were up- and down-regulated respectively. Functional annotation revealed 545 significantly enriched genes to be associated with immune system processes within the total 1917 differentially expressed genes. Further analysis revealed 21 genes showing significant expression were also in MHC-I and MHC-II antigen processing and presentation pathway during S19∆per immunization. Conclusions:The RNA-seq data revealed the coordinated up-regulation of MHC-I and MHC-II processing pathways providing insights into the molecular mechanism of immune protection conferred by B. abortus S19∆per in mice at day 15 post immunization and might aid in the development of new attenuated vaccine strains with improved efficacy.

Dataset Information

Identification of blood MHC-binding peptides in mice after Brucella infection

Publications

Identification of potential antigenic peptides of Brucella through proteome and peptidome.

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