The establishment of variant surface glycoprotein monoallelic expression revealed by single-cell RNA-seq of Trypanosoma brucei in the tsetse fly salivary glands.
Sebastian HutchinsonSophie FoulonAline CrouzolsRoberta MenafraBrice RotureauAndrew D GriffithsPhilippe BastinPublished in: PLoS pathogens (2021)
The long and complex Trypanosoma brucei development in the tsetse fly vector culminates when parasites gain mammalian infectivity in the salivary glands. A key step in this process is the establishment of monoallelic variant surface glycoprotein (VSG) expression and the formation of the VSG coat. The establishment of VSG monoallelic expression is complex and poorly understood, due to the multiple parasite stages present in the salivary glands. Therefore, we sought to further our understanding of this phenomenon by performing single-cell RNA-sequencing (scRNA-seq) on these trypanosome populations. We were able to capture the developmental program of trypanosomes in the salivary glands, identifying populations of epimastigote, gamete, pre-metacyclic and metacyclic cells. Our results show that parasite metabolism is dramatically remodeled during development in the salivary glands, with a shift in transcript abundance from tricarboxylic acid metabolism to glycolytic metabolism. Analysis of VSG gene expression in pre-metacyclic and metacyclic cells revealed a dynamic VSG gene activation program. Strikingly, we found that pre-metacyclic cells contain transcripts from multiple VSG genes, which resolves to singular VSG gene expression in mature metacyclic cells. Single molecule RNA fluorescence in situ hybridisation (smRNA-FISH) of VSG gene expression following in vitro metacyclogenesis confirmed this finding. Our data demonstrate that multiple VSG genes are transcribed before a single gene is chosen. We propose a transcriptional race model governs the initiation of monoallelic expression.
Keyphrases
- single cell
- rna seq
- gene expression
- induced apoptosis
- poor prognosis
- single molecule
- cell cycle arrest
- genome wide
- dna methylation
- high throughput
- oxidative stress
- quality improvement
- long non coding rna
- machine learning
- transcription factor
- cell death
- genome wide identification
- cell proliferation
- electronic health record
- toxoplasma gondii
- pi k akt
- artificial intelligence
- antibiotic resistance genes
- atomic force microscopy
- quantum dots
- anaerobic digestion