PhyloQuant approach provides insights into Trypanosoma cruzi evolution using a systems-wide mass spectrometry-based quantitative protein profile

Abstract

The etiological agent of Chagas disease, Trypanosoma cruzi, is a complex of seven genetic subdivisions termed discrete typing units (DTUs), TcI-TcVI and Tcbat. The relevance of T. cruzi genetic diversity to the variable clinical course of the disease, virulence, pathogenicity, drug resistance, transmission cycles and ecological distribution requires understanding the parasite origin and population structure. In this study, we introduce the PhyloQuant approach to infer the evolutionary relationships between organisms based on differential mass spectrometry-based quantitative features. In particular, large scale quantitative bottom-up proteomics features (MS1, iBAQ and LFQ) were analyzed using maximum parsimony, showing a correlation between T. cruzi DTUs and closely related trypanosomes’ protein expression and sequence-based clustering. Character mapping enabled the identification of synapomorphies, herein the proteins and their respective expression profiles that differentiate T. cruzi DTUs and trypanosome species. The distance matrices based on phylogenetics and PhyloQuant clustering showed statistically significant correlation highlighting the complementarity between the two strategies. Moreover, PhyloQuant allows the identification of differentially regulated and strain/DTU/species-specific proteins, and has potential application in the identification of specific biomarkers and candidate therapeutic targets.

Leishmaniinae: evolutionary inferences based on protein expression profiles (PhyloQuant) congruent with phylogenetic relationships amongLeishmania, Endotrypanum, Porcisia, Zelonia, Crithidia,andLeptomonas

“…The PhyloQuant approach supports current phylogeny and taxonomy of Leishmaniinae and corroborate a new species of Zelonia and the polyphyly of Leptomonas . As we previously demonstrated for trypanosomes of the subgenus Schizotrypanum [1], mass spectrometry-based quantitative features and the use of different identification and quantification software reinforced the consistency of the PhyloQuant approach to provide new information that can aid resolve evolutionary relationships for taxonomical purposes. In addition, this technique allows for identifying protein expression profiles differing according to subgenus/species, thus unveiling proteins that can be used to understand the differences in many biological processes, host-parasite-vector interactions, and infectivity, pathogenicity, virulence, and disease manifestations.…”

“…The PhyloQuant method was used to infer the evolutionary relationships of the parasites under study as previously described [1]. Briefly, intensity-based absolute quantification (iBAQ) values were evaluated both as normalized and non-normalized quantitative features.…”

“…The PhyloQuant approach was developed to infer evolutionary relationships between organisms based on systems-wide differential protein expression obtained from mass spectrometry data [1]. This method was first applied to Trypanosoma cruzi and close-related bat trypanosomes of the subgenus Schizotrypanum , all species nesting into the major clade T. cruzi [2].…”

“…We demonstrated that PhyloQuant can arrange these trypanosomes according to species and intraspecific classification of T. cruzi DTUs (Discrete Typing Units TcI-TcVII), consistent with phylogeny based on multiple DNA sequences. Moreover, strains, DTUs, and species-specific proteins and protein expression profiles were highlighted by PhyloQuant, providing relevant data to any attempts in elucidating aspects on host-parasite interaction, adaptation to new hosts and vectors, and the evolution of pathogenicity within the clade T. cruzi [1].…”

Dissecando a patogênese da doença de Chagas através de abordagens glicômicas e glicoproteômicas.

“…Using large-scale mass spectrometry-based protein expression profiles, we have developed a novel technique termed "PhyloQuant" to infer evolutionary relationships between T. cruzi DTUs and closely related trypanosome species (26). Using MS1, iBAQ and LFQ quantitative features, we show close correlation between T. cruzi genetic subdivisions and levels of protein expression.…”