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. 2022 Oct 22;13(11):968.
doi: 10.3390/insects13110968.

Genome-Wide Screening for Pathogenic Proteins and microRNAs Associated with Parasite-Host Interactions in Trypanosoma brucei

Affiliations

Genome-Wide Screening for Pathogenic Proteins and microRNAs Associated with Parasite-Host Interactions in Trypanosoma brucei

Zhiyuan Yang et al. Insects. .

Abstract

Tsetse flies are a type of blood-sucking insect living in diverse locations in sub-Saharan Africa. These insects can transmit the unicellular parasite Trypanosoma brucei (T. brucei) which causes African trypanosomiasis in mammals. There remain huge unmet needs for prevention, early detection, and effective treatments for this disease. Currently, few studies have investigated the molecular mechanisms of parasite-host interactions underlying African trypanosomiasis, mainly due to a lack of understanding of the T. brucei genome. In this study, we dissected the genomic and transcriptomic profiles of T. brucei by annotating the genome and analyzing the gene expression. We found about 5% of T. brucei proteins in the human proteome, while more than 80% of T. brucei protein in other trypanosomes. Sequence alignment analysis showed that 142 protein homologs were shared among T. brucei and mammalian genomes. We identified several novel proteins with pathogenic potential supported by their molecular functions in T. brucei, including 24 RNA-binding proteins and six variant surface glycoproteins. In addition, 26 novel microRNAs were characterized, among which five miRNAs were not found in the mammalian genomes. Topology analysis of the miRNA-gene network revealed three genes (RPS27A, UBA52 and GAPDH) involved in the regulation of critical pathways related to the development of African trypanosomiasis. In conclusion, our work opens a new door to understanding the parasite-host interaction mechanisms by resolving the genome and transcriptome of T. brucei.

Keywords: Trypanosoma brucei; bioinformatics; microRNA; parasite–host interaction.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Workflow in this study. Our work was divided into two main parts: protein-coding gene analysis and miRNA analysis.
Figure 2
Figure 2
Homolog distribution of T. brucei proteins. (A) The homolog percentage of T. brucei when compared with other trypanosomes; (B) the homolog percentage of T. brucei when compared with other mammals.
Figure 3
Figure 3
Associated disease enrichment of TbrMam proteins by Metascape tools. This figure only shows the top 20 terms.
Figure 4
Figure 4
Genomic specificity of identified TbrMam genes when compared with the whole genome. (A) Comparison of coding sequencing length; (B) comparison of 3′-UTR length; (C) comparison of GC content; (D) comparison of exon numbers, the red bars indicate the TbrMam protein, while the gray bars indicate the background proteins. The asterisk symbol indicated the significance of statistical genomic specificity in the figures.
Figure 5
Figure 5
Multiple sequence alignment of Pi3K proteins among different species. The asterisk indicated the middle of two sites. The shadow indicated the similarity level in the site. Abbreviation for the species: bta, Bos taurus; hsa, Homo sapiens; mmu, Mus musculus; pal, Pteropus alecto; rno, Rattus norvegicus; tbr, Trypanosoma brucei; tco, Trypanosoma conorhini; tgr, Trypanosoma grayi; tth, Trypanosoma theileri.
Figure 6
Figure 6
The miRNA–gene interaction sub-network. The pink node represents a miRNA, while the light blue node represents a gene. The full view of this network is shown in the Supplementary Materials.

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