Chagas disease is a neglected tropical disease and a leading cause of heart failure in Latin America caused by a protozoan called Trypanosoma cruzi. This parasite presents a complex multi-stage life cycle. Anti-Chagas drugs currently available are limited to benznidazole and nifurtimox, both with severe side effects. Thus, there is a need for alternative and more efficient drugs. Genome-scale metabolic models (GEMs) can accurately predict metabolic capabilities and aid in drug discovery in metabolic genes. This work developed an extended GEM, hereafter referred to as iIS312, of the published and validated T. cruzi core metabolism model. From iIS312, we then built three stage-specific models through transcriptomics data integration, and showed that epimastigotes present the most active metabolism among the stages (see S1-S4 GEMs). Stage-specific models predicted significant metabolic differences among stages, including variations in flux distribution in core metabolism. Moreover, the gene essentiality predictions suggest potential drug targets, among which some have been previously proven lethal, including glutamate dehydrogenase, glucokinase and hexokinase. To validate the models, we measured the activity of enzymes in the core metabolism of the parasite at different stages, and showed the results were consistent with model predictions. Our results represent a potential step forward towards the improvement of Chagas disease treatment. To our knowledge, these stage-specific models are the first GEMs built for the stages Amastigote and Trypomastigote. This work is also the first to present an in silico GEM comparison among different stages in the T. cruzi life cycle.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7567352PMC
http://dx.doi.org/10.1371/journal.pntd.0008728DOI Listing

Publication Analysis

Top Keywords

core metabolism
12
stage-specific models
12
genome-scale metabolic
8
metabolic models
8
trypanosoma cruzi
8
chagas disease
8
life cycle
8
models gems
8
models
6
metabolic
5

Similar Publications

The systemic evolutionary theory of the origin of cancer (SETOC): an update.

Mol Med

January 2025

Association for Systems Science, Via S. Stefano, 42, I-75100, Matera, Italy.

The Systemic Evolutionary Theory of the Origin of Cancer (SETOC) is a recently proposed theory founded on two primary principles: the cooperative and endosymbiotic process of cell evolution as described by Lynn Margulis, and the integration of complex systems operating in eukaryotic cells, which is a core concept in systems biology. The SETOC proposes that malignant transformation occurs when cells undergo a continuous adaptation process in response to long-term injuries, leading to tissue remodeling, chronic inflammation, fibrosis, and ultimately cancer. This process involves a maladaptive response, wherein the 'endosymbiotic contract' between the nuclear-cytoplasmic system (derived from the primordial archaeal cell) and the mitochondrial system (derived from the primordial α-proteobacterium) gradually breaks down.

View Article and Find Full Text PDF

Many membrane proteins on the cell surface are constantly internalized from, and re-delivered to, the plasma membrane. This endocytic cycling, which relies on accurate SNARE-mediated fusion of vesicles containing cargo proteins, is highly important for the function of many proteins such as signaling receptors. While the SNARE proteins that mediate fusion during specific events, such as neurotransmitter and hormone release, in mammalian cells has been heavily studied, the SNARE proteins that mediate surface delivery of specific cargo such as the receptors for these released factors are still not known.

View Article and Find Full Text PDF

ESKAPE pathogens rapidly develop resistance against antibiotics in development in vitro.

Nat Microbiol

January 2025

Synthetic and Systems Biology Unit, Institute of Biochemistry, HUN-REN Biological Research Centre, National Laboratory of Biotechnology, Szeged, Hungary.

Despite ongoing antibiotic development, evolution of resistance may render candidate antibiotics ineffective. Here we studied in vitro emergence of resistance to 13 antibiotics introduced after 2017 or currently in development, compared with in-use antibiotics. Laboratory evolution showed that clinically relevant resistance arises within 60 days of antibiotic exposure in Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii and Pseudomonas aeruginosa, priority Gram-negative ESKAPE pathogens.

View Article and Find Full Text PDF

Dysregulated autoantibodies targeting AGTR1 are associated with the accumulation of COVID-19 symptoms.

NPJ Syst Biol Appl

January 2025

BIH Center for Regenerative Therapies (BCRT), Julius Wolff Institute (JWI), and Berlin Institute of Health (BIH); all Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH), 10117, Berlin, Germany.

Coronavirus disease 2019 (COVID-19) presents a wide spectrum of symptoms, the causes of which remain poorly understood. This study explored the associations between autoantibodies (AABs), particularly those targeting G protein-coupled receptors (GPCRs) and renin‒angiotensin system (RAS) molecules, and the clinical manifestations of COVID-19. Using a cross-sectional analysis of 244 individuals, we applied multivariate analysis of variance, principal component analysis, and multinomial regression to examine the relationships between AAB levels and key symptoms.

View Article and Find Full Text PDF

Robust collection and processing for label-free single voxel proteomics.

Nat Commun

January 2025

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures tissue heterogeneity, precluding proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single microscale tissue voxels and Surfactant-assisted One-Pot voxel processing method termed wcSOP for robust label-free single voxel proteomics.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!