Transcriptomes of Trypanosoma brucei rhodesiense from sleeping sickness patients, rodents and culture: Effects of strain, growth conditions and RNA preparation methods

PLoS Neglected Tropical Diseases
Julius MulindwaChristine Clayton

Abstract

All of our current knowledge of African trypanosome metabolism is based on results from trypanosomes grown in culture or in rodents. Drugs against sleeping sickness must however treat trypanosomes in humans. We here compare the transcriptomes of Trypanosoma brucei rhodesiense from the blood and cerebrospinal fluid of human patients with those of trypanosomes from culture and rodents. The data were aligned and analysed using new user-friendly applications designed for Kinetoplastid RNA-Seq data. The transcriptomes of trypanosomes from human blood and cerebrospinal fluid did not predict major metabolic differences that might affect drug susceptibility. Usefully, there were relatively few differences between the transcriptomes of trypanosomes from patients and those of similar trypanosomes grown in rats. Transcriptomes of monomorphic laboratory-adapted parasites grown in in vitro culture closely resembled those of the human parasites, but some differences were seen. In poly(A)-selected mRNA transcriptomes, mRNAs encoding some protein kinases and RNA-binding proteins were under-represented relative to mRNA that had not been poly(A) selected; further investigation revealed that the selection tends to result in loss of longer mRNAs.

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Citations

Feb 1, 2020·BMC Medical Genomics·Julius MulindwaChristine Clayton
Feb 4, 2021·International Journal for Parasitology. Parasites and Wildlife·María Buendía-AbadLuis Miguel De Pablos
Dec 15, 2020·Trends in Parasitology·Juan F QuintanaMark C Field
Sep 14, 2021·PLoS Neglected Tropical Diseases·Julius MulindwaChristine Clayton

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Datasets Mentioned

BETA
E-MTAB-5293
E-MTAB-5294
E-MTAB-6125

Methods Mentioned

BETA
RNASeq
PCR
environmental stresses
RNA-Seq

Software Mentioned

DEseqU1
pheatmap
DESeq2
ClusterViewer
bowtie
Kaleidograph
Samtools
FastQC
Cutadapt
R package DESeq2

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