In-depth quantitative proteomics uncovers specie-specific metabolic programs in Leishmania (Viannia) species.
2020
Leishmania species are responsible for a broad spectrum of diseases, denominated Leishmaniasis, affecting over 12 million people worldwide. During the last decade, there have
been impressive efforts for sequencing the genome of most of the pathogenic Leishmania
spp. as well as hundreds of strains, but large-scale proteomics analyses did not follow these
achievements and the Leishmania proteome remained mostly uncharacterized. Here, we
report a comprehensive comparative study of the proteomes of strains representing L. braziliensis, L. panamensis and L. guyanensis species. Proteins extracted by SDS-mediated
lysis were processed following the multi-enzyme digestion-filter aided sample preparation
(FASP) procedure and analysed by high accuracy mass spectrometry. “Total Protein
Approach” and “Proteomic Ruler” were applied for absolute quantification of proteins. Principal component analysis demonstrated very high reproducibility among biological replicates
and a very clear differentiation of the three species. Our dataset comprises near 7000 proteins, representing the most complete Leishmania proteome yet known, and provides a
comprehensive quantitative picture of the proteomes of the three species in terms of protein
concentration and copy numbers. Analysis of the abundance of proteins from the major
energy metabolic processes allow us to highlight remarkably differences among the species
and suggest that these parasites depend on distinct energy substrates to obtain ATP.
Whereas L. braziliensis relies the more on glycolysis, L. panamensis and L. guyanensis
seem to depend mainly on mitochondrial respiration. These results were confirmed by biochemical assays showing opposite profiles for glucose uptake and O2 consumption in these
species. In addition, we provide quantitative data about different membrane proteins, transporters, and lipids, all of which contribute for significant species-specific differences and provide rich substrate for explore new molecules for diagnosing purposes. Data are available via ProteomeXchange with identifier PXD017696.
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