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Carey MA, Medlock GL, Stolarczyk M, Petri WA, Guler JL, Papin JA. Comparative analyses of parasites with a comprehensive database of genome-scale metabolic models. PLoS Comput Biol 2022; 18:e1009870. [PMID: 35196325 PMCID: PMC8901074 DOI: 10.1371/journal.pcbi.1009870] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 03/07/2022] [Accepted: 01/27/2022] [Indexed: 01/01/2023] Open
Abstract
Protozoan parasites cause diverse diseases with large global impacts. Research on the pathogenesis and biology of these organisms is limited by economic and experimental constraints. Accordingly, studies of one parasite are frequently extrapolated to infer knowledge about another parasite, across and within genera. Model in vitro or in vivo systems are frequently used to enhance experimental manipulability, but these systems generally use species related to, yet distinct from, the clinically relevant causal pathogen. Characterization of functional differences among parasite species is confined to post hoc or single target studies, limiting the utility of this extrapolation approach. To address this challenge and to accelerate parasitology research broadly, we present a functional comparative analysis of 192 genomes, representing every high-quality, publicly-available protozoan parasite genome including Plasmodium, Toxoplasma, Cryptosporidium, Entamoeba, Trypanosoma, Leishmania, Giardia, and other species. We generated an automated metabolic network reconstruction pipeline optimized for eukaryotic organisms. These metabolic network reconstructions serve as biochemical knowledgebases for each parasite, enabling qualitative and quantitative comparisons of metabolic behavior across parasites. We identified putative differences in gene essentiality and pathway utilization to facilitate the comparison of experimental findings and discovered that phylogeny is not the sole predictor of metabolic similarity. This knowledgebase represents the largest collection of genome-scale metabolic models for both pathogens and eukaryotes; with this resource, we can predict species-specific functions, contextualize experimental results, and optimize selection of experimental systems for fastidious species.
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Affiliation(s)
- Maureen A. Carey
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- * E-mail: (MAC); (JP)
| | - Gregory L. Medlock
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Michał Stolarczyk
- Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - William A. Petri
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Jennifer L. Guler
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America
| | - Jason A. Papin
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- Department of Biochemistry & Molecular Genetics, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- * E-mail: (MAC); (JP)
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Dousti M, Manzano-Román R, Rashidi S, Barzegar G, Ahmadpour NB, Mohammadi A, Hatam G. A proteomic glimpse into the effect of antimalarial drugs on Plasmodium falciparum proteome towards highlighting possible therapeutic targets. Pathog Dis 2021; 79:ftaa071. [PMID: 33202000 DOI: 10.1093/femspd/ftaa071] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 11/13/2020] [Indexed: 02/07/2023] Open
Abstract
There is no effective vaccine against malaria; therefore, chemotherapy is to date the only choice to fight against this infectious disease. However, there is growing evidences of drug-resistance mechanisms in malaria treatments. Therefore, the identification of new drug targets is an urgent need for the clinical management of the disease. Proteomic approaches offer the chance of determining the effects of antimalarial drugs on the proteome of Plasmodium parasites. Accordingly, we reviewed the effects of antimalarial drugs on the Plasmodium falciparum proteome pointing out the relevance of several proteins as possible drug targets in malaria treatment. In addition, some of the P. falciparum stage-specific altered proteins and parasite-host interactions might play important roles in pathogenicity, survival, invasion and metabolic pathways and thus serve as potential sources of drug targets. In this review, we have identified several proteins, including thioredoxin reductase, helicases, peptidyl-prolyl cis-trans isomerase, endoplasmic reticulum-resident calcium-binding protein, choline/ethanolamine phosphotransferase, purine nucleoside phosphorylase, apical membrane antigen 1, glutamate dehydrogenase, hypoxanthine guanine phosphoribosyl transferase, heat shock protein 70x, knob-associated histidine-rich protein and erythrocyte membrane protein 1, as promising antimalarial drugs targets. Overall, proteomic approaches are able to partially facilitate finding possible drug targets. However, the integration of other 'omics' and specific pharmaceutical techniques with proteomics may increase the therapeutic properties of the critical proteins identified in the P. falciparum proteome.
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Affiliation(s)
- Majid Dousti
- Department of Parasitology and Mycology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Raúl Manzano-Román
- Proteomics Unit, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007, Salamanca, Spain
| | - Sajad Rashidi
- Department of Parasitology and Mycology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Gholamreza Barzegar
- Department of Parasitology and Mycology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Alireza Mohammadi
- Department of Disease Control, Komijan Treatment and Health Network, Arak University of Medical Science, Iran
| | - Gholamreza Hatam
- Basic Sciences in Infectious Diseases Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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Su XZ, Zhang C, Joy DA. Host-Malaria Parasite Interactions and Impacts on Mutual Evolution. Front Cell Infect Microbiol 2020; 10:587933. [PMID: 33194831 PMCID: PMC7652737 DOI: 10.3389/fcimb.2020.587933] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 09/22/2020] [Indexed: 12/22/2022] Open
Abstract
Malaria is the most deadly parasitic disease, affecting hundreds of millions of people worldwide. Malaria parasites have been associated with their hosts for millions of years. During the long history of host-parasite co-evolution, both parasites and hosts have applied pressure on each other through complex host-parasite molecular interactions. Whereas the hosts activate various immune mechanisms to remove parasites during an infection, the parasites attempt to evade host immunity by diversifying their genome and switching expression of targets of the host immune system. Human intervention to control the disease such as antimalarial drugs and vaccination can greatly alter parasite population dynamics and evolution, particularly the massive applications of antimalarial drugs in recent human history. Vaccination is likely the best method to prevent the disease; however, a partially protective vaccine may have unwanted consequences that require further investigation. Studies of host-parasite interactions and co-evolution will provide important information for designing safe and effective vaccines and for preventing drug resistance. In this essay, we will discuss some interesting molecules involved in host-parasite interactions, including important parasite antigens. We also discuss subjects relevant to drug and vaccine development and some approaches for studying host-parasite interactions.
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Affiliation(s)
- Xin-Zhuan Su
- Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Cui Zhang
- Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Deirdre A Joy
- Parasitology and International Programs Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
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