Literature DB >> 33482903

Gene co-expression network analysis of Trypanosoma brucei in tsetse fly vector.

Kennedy W Mwangi1,2, Rosaline W Macharia3, Joel L Bargul4,5.   

Abstract

BACKGROUND: Trypanosoma brucei species are motile protozoan parasites that are cyclically transmitted by tsetse fly (genus Glossina) causing human sleeping sickness and nagana in livestock in sub-Saharan Africa. African trypanosomes display digenetic life cycle stages in the tsetse fly vector and in their mammalian host. Experimental work on insect-stage trypanosomes is challenging because of the difficulty in setting up successful in vitro cultures. Therefore, there is limited knowledge on the trypanosome biology during its development in the tsetse fly. Consequently, this limits the development of new strategies for blocking parasite transmission in the tsetse fly.
METHODS: In this study, RNA-Seq data of insect-stage trypanosomes were used to construct a T. brucei gene co-expression network using the weighted gene co-expression analysis (WGCNA) method. The study identified significant enriched modules for genes that play key roles during the parasite's development in tsetse fly. Furthermore, potential 3' untranslated region (UTR) regulatory elements for genes that clustered in the same module were identified using the Finding Informative Regulatory Elements (FIRE) tool.
RESULTS: A fraction of gene modules (12 out of 27 modules) in the constructed network were found to be enriched in functional roles associated with the cell division, protein biosynthesis, mitochondrion, and cell surface. Additionally, 12 hub genes encoding proteins such as RNA-binding protein 6 (RBP6), arginine kinase 1 (AK1), brucei alanine-rich protein (BARP), among others, were identified for the 12 significantly enriched gene modules. In addition, the potential regulatory elements located in the 3' untranslated regions of genes within the same module were predicted.
CONCLUSIONS: The constructed gene co-expression network provides a useful resource for network-based data mining to identify candidate genes for functional studies. This will enhance understanding of the molecular mechanisms that underlie important biological processes during parasite's development in tsetse fly. Ultimately, these findings will be key in the identification of potential molecular targets for disease control.

Entities:  

Keywords:  Gene co-expression network; Trypanosoma brucei; Tsetse fly; Weighted gene co-expression network analysis

Mesh:

Substances:

Year:  2021        PMID: 33482903      PMCID: PMC7821691          DOI: 10.1186/s13071-021-04597-6

Source DB:  PubMed          Journal:  Parasit Vectors        ISSN: 1756-3305            Impact factor:   3.876


  57 in total

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Review 8.  More than meets the eye: understanding Trypanosoma brucei morphology in the tsetse.

Authors:  Cher-Pheng Ooi; Philippe Bastin
Journal:  Front Cell Infect Microbiol       Date:  2013-11-13       Impact factor: 5.293

9.  Gene co-expression analysis for functional classification and gene-disease predictions.

Authors:  Sipko van Dam; Urmo Võsa; Adriaan van der Graaf; Lude Franke; João Pedro de Magalhães
Journal:  Brief Bioinform       Date:  2018-07-20       Impact factor: 11.622

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Authors:  Reuben Sharma; Eva Gluenz; Lori Peacock; Wendy Gibson; Keith Gull; Mark Carrington
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  1 in total

1.  In silico-driven analysis of the Glossina morsitans morsitans antennae transcriptome in response to repellent or attractant compounds.

Authors:  Consolata Gakii; Billiah Kemunto Bwana; Grace Gathoni Mugambi; Esther Mukoya; Paul O Mireji; Richard Rimiru
Journal:  PeerJ       Date:  2021-07-01       Impact factor: 2.984

  1 in total

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