Experimental evolution reveals post-transcriptional regulation as a novel driver ofLeishmaniafitness gain

Abstract

The protozoan parasite Leishmania donovani causes fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver in Leishmania fitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting to in vitro culture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network driving parasite fitness, with genome instability causing highly reproducible, gene dosage-dependent changes in protein linked to post-transcriptional regulation. These in turn were associated with a gene dosage-independent reduction in flagellar transcripts and a coordinated increase in abundance of coding and non-coding RNAs known to regulate ribosomal biogenesis and protein translation. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence that Leishmania fitness gain may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model for Leishmania fitness gain, where differential regulation of mRNA stability and the generation of fitness-adapted ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach to Leishmania epidemiology and identifies the Leishmania non-coding small RNome as a potential novel source for biomarker discovery.

Transcriptional Shift and Metabolic Adaptations during Leishmania Quiescence Using Stationary Phase and Drug Pressure as Models

“…In the process of catabolism of amino acids via the Ehrlich pathway, the gene encoding a putative alpha keto acid decarboxylase was upregulated. This pathway is a source of alpha keto acids such as pyruvate during conditions of nutritional starvation [44]. The biological process, "modulation of process of other organism", represented by genes encoding a major metalloendopeptidase called Leishmanolysin/GP63, was also upregulated.…”

A phased genome assembly for allele-specific analysis in Trypanosoma brucei

“…It would be interesting to analyse quantitative proteomic data in the aneuploid clones to see if there is a compensatory mechanism at this stage or if the parasite can deal with chromosome-wide 50% increase in protein level. In Leishmania parasites, several studies have also shown an overall correlation of ploidy and transcription [53,54,55], albeit with gene dosage-independent fluctuations for some chromosomes and indications of regulatory mechanisms compensating at the protein expression level [55]. On a practical matter, the observation that there is a direct correlation of mRNA transcript level and ploidy, indicates that comparative RNA-seq data could be used to directly determine deviations from euploidy in T. brucei field isolates.…”

Transcriptional shift and metabolic adaptations during Leishmania quiescence using stationary-phase and drug pressure as models

“…Although the transcriptome size was diminished in all quiescent states measured compared to proliferative cells, the transcriptome composition revealed particular mRNAs whose proportion increased or decreased relative to others during quiescence. Since the transcriptome has a moderate correlation with levels of protein expression [40,41], comparative transcriptome composition can provide insights into the biological processes associated with quiescence. We specifically sought changes found in quiescent cells irrespective of the life cycle stage or stimulus, and using GO/GSEA analysis identified three main functional categories as being upregulated: autophagy, proteolysis associated with leishmanolysin (GP63), and amastin/amastin-like proteins.…”