Metabolites as predictive biomarkers for Trypanosoma cruzi exposure in triatomine bugs

Interaction of Trypanosoma cruzi, Triatomines and the Microbiota of the Vectors-A Review

This review summarizes the interactions between Trypanosoma cruzi, the etiologic agent of Chagas disease, its vectors, triatomines, and the diverse intestinal microbiota of triatomines, which includes mutualistic symbionts, and highlights open questions. T. cruzi strains show great biological heterogeneity in their development and their interactions. Triatomines differ from other important vectors of diseases in their ontogeny and the enzymes used to digest blood. Many different bacteria colonize the intestinal tract of triatomines, but only Actinomycetales have been identified as mutualistic symbionts. Effects of the vector on T. cruzi are indicated by differences in the ability of T. cruzi to establish in the triatomines and in colonization peculiarities, i.e., proliferation mainly in the posterior midgut and rectum and preferential transformation into infectious metacyclic trypomastigotes in the rectum. In addition, certain forms of T. cruzi develop after feeding and during starvation of triatomines. Negative effects of T. cruzi on the triatomine vectors appear to be particularly evident when the triatomines are stressed and depend on the T. cruzi strain. Effects on the intestinal immunity of the triatomines are induced by ingested blood-stage trypomastigotes of T. cruzi and affect the populations of many non-symbiotic intestinal bacteria, but not all and not the mutualistic symbionts. After the knockdown of antimicrobial peptides, the number of non-symbiotic bacteria increases and the number of T. cruzi decreases. Presumably, in long-term infections, intestinal immunity is suppressed, which supports the growth of specific bacteria, depending on the strain of T. cruzi. These interactions may provide an approach to disrupt T. cruzi transmission.

Small molecule mediators of host-T. cruzi-environment interactions in Chagas disease

Small molecules (less than 1,500 Da) include major biological signals that mediate host-pathogen-microbiome communication. They also include key intermediates of metabolism and critical cellular building blocks. Pathogens present with unique nutritional needs that restrict pathogen colonization or promote tissue damage. In parallel, parts of host metabolism are responsive to immune signaling and regulated by immune cascades. These interactions can trigger both adaptive and maladaptive metabolic changes in the host, with microbiome-derived signals also contributing to disease progression. In turn, targeting pathogen metabolic needs or maladaptive host metabolic changes is an important strategy to develop new treatments for infectious diseases. Trypanosoma cruzi is a single-celled eukaryotic pathogen and the causative agent of Chagas disease, a neglected tropical disease associated with cardiac and intestinal dysfunction. Here, we discuss the role of small molecules during T. cruzi infection in its vector and in the mammalian host. We integrate these findings to build a theoretical interpretation of how maladaptive metabolic changes drive Chagas disease and extrapolate on how these findings can guide drug development.

Fast mass spectrometry search and clustering of untargeted metabolomics data

The throughput of mass spectrometers and the amount of publicly available metabolomics data are growing rapidly, but analysis tools such as molecular networking and Mass Spectrometry Search Tool do not scale to searching and clustering billions of mass spectral data in metabolomics repositories. To address this limitation, we designed MASST+ and Networking+, which can process datasets that are up to three orders of magnitude larger than those processed by state-of-the-art tools.

Artificial Intelligence Models for Zoonotic Pathogens: A Survey

Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the factors that contribute to their spread. The aim of this literature survey is to synthesize and analyze machine learning, and deep learning approaches applied to study zoonotic diseases to understand predictive models to help researchers identify the risk factors, and develop mitigation strategies. Based on our survey findings, machine learning and deep learning are commonly used for the prediction of both foodborne and zoonotic pathogens as well as the factors associated with the presence of the pathogens.

The state of the art of extracellular vesicle research in protozoan infection

Protozoan diseases seriously affect the health of human beings, livestock and poultry and lead to high economic and medical costs. Extracellular vesicles (EVs) are membranous structures formed through biological processes that play important roles in immune regulation. Studies have shown that parasites transmit information to hosts through EVs to modulate host immune responses. The major roles played by EVs released from parasites involve facilitating parasitization of the host. In this review, we discuss relevant recently obtained data on EVs secreted by different kinds of protozoa, including their molecular mechanisms, and discuss the roles played by EVs in the occurrence and development of parasitic diseases.

Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

BACKGROUND

The causative agent of Chagas disease, Trypanosoma cruzi, and its nonpathogenic relative, Trypanosoma rangeli, are transmitted by haematophagous triatomines and undergo a crucial ontogenetic phase in the insect's intestine. In the process, the parasites interfere with the host immune system as well as the microbiome present in the digestive tract potentially establishing an environment advantageous for development. However, the coherent interactions between host, pathogen and microbiota have not yet been elucidated in detail. We applied a metagenome shotgun sequencing approach to study the alterations in the microbiota of Rhodnius prolixus, a major vector of Chagas disease, after exposure to T. cruzi and T. rangeli focusing also on the functional capacities present in the intestinal microbiome of the insect.

RESULTS

The intestinal microbiota of R. prolixus was dominated by the bacterial orders Enterobacterales, Corynebacteriales, Lactobacillales, Clostridiales and Chlamydiales, whereas the latter conceivably originated from the blood used for pathogen exposure. The anterior and posterior midgut samples of the exposed insects showed a reduced overall number of organisms compared to the control group. However, we also found enriched bacterial groups after exposure to T. cruzi as well as T rangeli. While the relative abundance of Enterobacterales and Corynebacteriales decreased considerably, the Lactobacillales, mainly composed of the genus Enterococcus, developed as the most abundant taxonomic group. This applies in particular to vectors challenged with T. rangeli and at early timepoints after exposure to vectors challenged with T. cruzi. Furthermore, we were able to reconstruct four metagenome-assembled genomes from the intestinal samples and elucidate their unique metabolic functionalities within the triatomine microbiome, including the genome of a recently described insect symbiont, Candidatus Symbiopectobacterium, and the secondary metabolites producing bacteria Kocuria spp.

CONCLUSIONS

Our results facilitate a deeper understanding of the processes that take place in the intestinal tract of triatomine vectors during colonisation by trypanosomal parasites and highlight the influential aspects of pathogen-microbiota interactions. In particular, the mostly unexplored metabolic capacities of the insect vector's microbiome are clearer, underlining its role in the transmission of Chagas disease. Video Abstract.

Molecular networking in infectious disease models

Small molecule metabolites are the product of many enzymatic reactions. Metabolomics thus opens a window into enzyme activity and function, integrating effects at the post-translational, proteome, transcriptome and genome level. In addition, small molecules can themselves regulate enzyme activity, expression and function both via substrate availability mechanisms and through allosteric regulation. Metabolites are therefore at the nexus of infectious diseases, regulating nutrient availability to the pathogen, immune responses, tropism, and host disease tolerance and resilience. Analysis of metabolomics data is however complex, particularly in terms of metabolite annotation. An emerging valuable approach to extend metabolite annotations beyond existing compound libraries and to identify infection-induced chemical changes is molecular networking. In this chapter, we discuss the applications of molecular networking in the context of infectious diseases specifically, with a focus on considerations relevant to these biological systems.