McLuskey, K. | Search bioRxiv

bioRxiv2022

TORC1 is an essential regulator of nutrient-dependent differentiation in Leishmania

Leishmania parasites undergo differentiation between various proliferating and non-dividing forms to adapt to changing host environments. The mechanisms that link environmental cues with the parasites developmental changes remain elusive. Here, we report that Leishmania TORC1 is a key environmental sensor for parasite differentiation in the sand fly-stage promastigotes and for replication of mammalian-stage amastigotes. We show that Leishmania RPTOR1, interacts with TOR1 and LST8. We investigate TORC1 function by conditional deletion of RPTOR1, where under nutrient rich conditions RPTOR1 depletion results in decreased protein synthesis and growth, G1 cell cycle arrest and premature differentiation from proliferative promastigotes to non-dividing mammalian-infective metacyclic forms. These parasites cannot develop into proliferative amastigotes in the mammalian host, or respond to nutrients to differentiate to proliferative retroleptomonads, which are required for their blood-meal induced amplification in sand flies and enhanced mammalian infectivity. RPTOR1-dependent TORC1 functionality represents a critical mechanism for driving parasite growth and proliferation.

cell biology↗

bioRxiv2020

Decomposing metabolite set activity levels with PALS

MotivationRelated metabolites can be grouped into metabolite sets in many ways. Examples of these include the grouping of metabolites through their participation in a series of chemical reactions (forming metabolic pathways); or based on fragmentation spectral similarities and shared chemical substructures. Understanding how such metabolite sets change across samples can be incredibly useful in the interpretation and understanding of complex metabolomics data. However many of the available tools suitable for the enrichment analysis of metabolite sets are based on simple methods that badly handle the missing features inherent in untargeted metabolomics measurements and can be difficult to integrate into existing applications. ResultsWe present PALS (Pathway Activity Level Scoring), a Python library, command-line tool and Web application that performs the ranking of significantly-changing metabolite sets over different experimental conditions. As example applications, PALS is used to analyse metabolites grouped as pathways and by common MS-MS fragmentation structures. A comparison of PALS with two other commonly used methods (ORA and GSEA) is also given, and reveals that PALS is more robust to missing peaks and noisy data than the alternatives. We report results from using PALS to analyse pathways from a study of Human African Trypanosomiasis. Finally, we also report how PALS used tandem MS fragmentation structures to reveal enriched metabolite sets between clades in Rhamnaceae plant data, and on American Gut Project data. AvailabilityPALS is freely available from our project Web site at https://pals.glasgowcompbio.org/. It can be imported as a Python library, run as a stand-alone tool or used as a web application.

bioinformatics↗