Trypanosomatids of the genera Angomonas and Strigomonas live in a mutualistic association characterized by extensive metabolic cooperation with obligate endosymbiotic Betaproteobacteria. However, the role played by the symbiont has been more guessed by indirect means than evidenced. Symbiont-harboring trypanosomatids, in contrast to their counterparts lacking symbionts, exhibit lower nutritional requirements and are autotrophic for essential amino acids. To evidence the symbiont’s contributions to this autotrophy, entire genomes of symbionts and trypanosomatids with and without symbionts were sequenced here.

Trypanosoma cruzi, the etiologic agent of Chagas disease, cycles through different life stages characterized by defined molecular traits associated with the proliferative or differentiation state. In particular, T. cruzi epimastigotes are the replicative forms that colonize the intestine of the Triatomine insect vector before entering the stationary phase that is crucial for differentiation into metacyclic trypomastigotes, which are the infective forms of mammalian hosts. The transition from proliferative exponential phase to quiescent stationary phase represents an important step that recapitulates the early molecular events of metacyclogenesis, opening new possibilities for understanding this process. In this study, we report a quantitative shotgun proteomic analysis of the T. cruzi epimastigote in the exponential and stationary growth phases. More than 3000 proteins were detected and quantified, highlighting the regulation of proteins involved in different subcellular compartments. Ribosomal proteins were upregulated in the exponential phase, supporting the higher replication rate of this growth phase. Autophagy-related proteins were upregulated in the stationary growth phase, indicating the onset of the metacyclogenesis process. Moreover, this study reports the regulation of N-terminally acetylated proteins during growth phase transitioning, adding a new layer of regulation to this process. Taken together, this study reports a proteome-wide rewiring during T. cruzi transit from the replicative exponential phase to the stationary growth phase, which is the preparatory phase for differentiation.

DNA is an intelligent data storage medium due to its stability and high density. It has been used by nature for over 3.5 billion years. Compared with traditional methods, DNA offers better compression and physical density. DNA can retain information for thousands of years. However, challenges exist in scalability, standardization, metadata gathering, biocybersecurity, and specialized tools. Addressing these challenges is crucial for widespread implementation. Collaboration among experts, as well as keeping the future in mind, is needed to unlock the full potential of DNA data storage, which promises low energy costs, high-density storage, and long-term stability.

Proline racemase (PRAC) enzymes of Trypanosoma cruzi (TcPRAC), the agent of Chagas disease, and Trypanosoma vivax (TvPRAC), the agent of livestock trypanosomosis, have been implicated in the B-cells polyclonal activation contributing to immunosuppression and the evasion of host defences. The similarity to prokaryotic PRAC and the absence in Trypanosoma brucei and Trypanosoma congolense have raised many questions about the origin, evolution, and functions of trypanosome PRAC (TryPRAC) enzymes. We identified TryPRAC homologs as single copy genes per haploid genome in 12 of 15 Trypanosoma species, including T. cruzi and T. cruzi marinkellei, T. dionisii, T. erneyi, T. rangeli, T. conorhini and T. lewisi, all parasites of mammals. Polymorphisms in TcPRAC genes matched T. cruzi genotypes: TcI-TcIV and Tcbat have unique genes, while the hybrids TcV and TcVI contain TcPRACA and TcPRACB from parental TcII and TcIII, respectively. PRAC homologs were identified in trypanosomes from anurans, snakes, crocodiles, lizards, and birds. Most trypanosomes have intact PRAC genes. T. rangeli possesses only pseudogenes, maybe in the process of being lost. T. brucei, T. congolense and their allied species, except the more distantly related T. vivax, have completely lost PRAC genes. The genealogy of TryPRAC homologs supports an evolutionary history congruent with the Trypanosoma phylogeny. This finding, together with the synteny of PRAC loci, the relationships with prokaryotic PRAC inferred by taxon-rich phylogenetic analysis, and the absence in trypanosomatids of any other genera or in bodonids or euglenids suggest that a common ancestor of Trypanosoma gained PRAC gene by a single and ancient horizontal gene transfer (HGT) from a Firmicutes bacterium more closely related to Gemella and other species of Bacilli than to Clostridium as previously suggested. Our broad phylogenetic study allowed investigation of TryPRAC evolution over long and short timescales. TryPRAC genes diverged to become species-specific and genotype-specific for T. cruzi and T. rangeli, with resulting genealogies congruent with those obtained using vertically inherited genes. The inventory of TryPRAC genes described here is the first step toward the understanding of the roles of PRAC enzymes in trypanosomes differing in life cycles, virulence, and infection and immune evasion strategies.

Retrotransposon Hot Spot (RHS) is the most abundant gene family in Trypanosoma cruzi, with unknown function in this parasite. The aim of this work was to shed light on the organization and expression of RHS in T. cruzi. The diversity of the RHS protein family in T. cruzi was demonstrated by phylogenetic and recombination analyses. Transcribed sequences carrying the RHS domain were classified into ten distinct groups of monophyletic origin. We identified numerous recombination events among the RHS and traced the origins of the donors and target sequences. The transcribed RHS genes have a mosaic structure that may contain fragments of different RHS inserted in the target sequence. About 30% of RHS sequences are located in the subtelomere, a region very susceptible to recombination. The evolution of the RHS family has been marked by many events, including gene duplication by unequal mitotic crossing-over, homologous, as well as ectopic recombination, and gene conversion. The expression of RHS was analyzed by immunofluorescence and immunoblotting using anti-RHS antibodies. RHS proteins are evenly distributed in the nuclear region of T. cruzi replicative forms (amastigote and epimastigote), suggesting that they could be involved in the control of the chromatin structure and gene expression, as has been proposed for T. brucei.

BACKGROUND: Predicting individual vaccine responses is a substantial public health challenge. We developed Immunaut, an open-source, data-driven framework for systems vaccinologists to analyze and predict immunological outcomes across diverse vaccination settings, beyond traditional assessments. METHODS: Using a comprehensive live attenuated influenza vaccine (LAIV) dataset from 244 Gambian children, Immunaut integrated prevaccination and postvaccination humoral, mucosal, cellular, and transcriptomic data. Through advanced modeling, our framework provided a holistic, systems-level view of LAIV-induced immunity. RESULTS: The analysis identified 3 distinct immunophenotypic profiles driven by baseline immunity: (a) CD8 ⁺ T cell responders with strong preexisting immunity boosting memory T cell responses; (b) mucosal responders with prior influenza A virus immunity developing robust mucosal IgA and subsequent influenza B virus seroconversion; and (c) systemic, broad influenza A virus responders starting from immune naivety who mounted broad systemic antibody responses. Pathway analysis revealed how preexisting immune landscapes and baseline features, such as mucosal preparedness and cellular support, quantitatively dictate vaccine outcomes. CONCLUSION: Our findings emphasize the power of integrative, predictive frameworks for advancing precision vaccinology. The Immunaut framework is a valuable resource for deciphering vaccine response heterogeneity and can be applied to optimize immunization strategies across diverse populations and vaccine platforms. FUNDING: Wellcome Trust (110058/Z/15/Z); Bill & Melinda Gates Foundation (INV-004222); HIC-Vac Consortium; NIAID (R21 AI151917); NIAID CEIRR Network (75N93021C00045).