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      Intra-host Trypanosoma cruzi strain dynamics shape disease progression: the missing link in Chagas disease pathogenesis

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          ABSTRACT

          Chronic Chagasic cardiomyopathy develops years after infection in 20–40% of patients, but disease progression is poorly understood. Here, we assessed Trypanosoma cruzi parasite dynamics and pathogenesis over a 2.5-year period in naturally infected rhesus macaques. Individuals with better control of parasitemia were infected with a greater diversity of parasite strains compared to those with increasing parasitemia over time. Also, the in vivo parasite multiplication rate decreased with increasing parasite diversity, suggesting competition among strains or a stronger immune response in multiple infections. Significant differences in electrocardiographic (ECG) profiles were observed in Chagasic macaques compared to uninfected controls, suggesting early conduction defects, and changes in ECG patterns over time were observed only in macaques with increasing parasitemia and lower parasite diversity. Disease progression was also associated with plasma fibronectin degradation, which may serve as a biomarker. These data provide a novel framework for the understanding of Chagas disease pathogenesis, with parasite diversity shaping disease progression.

          IMPORTANCE

          Chagas disease progression remains poorly understood, and patients at increased risk of developing severe cardiac disease cannot be distinguished from those who may remain asymptomatic. Monitoring of Trypanosoma cruzi strain dynamics and pathogenesis over 2–3 years in naturally infected macaques shows that increasing parasite diversity in hosts is detrimental to parasite multiplication and Chagasic cardiomyopathy disease progression. This provides a novel framework for the understanding of Chagas disease pathogenesis.

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          FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments

          Background We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability. Methodology/Principal Findings Where FastTree 1 used nearest-neighbor interchanges (NNIs) and the minimum-evolution criterion to improve the tree, FastTree 2 adds minimum-evolution subtree-pruning-regrafting (SPRs) and maximum-likelihood NNIs. FastTree 2 uses heuristics to restrict the search for better trees and estimates a rate of evolution for each site (the “CAT” approximation). Nevertheless, for both simulated and genuine alignments, FastTree 2 is slightly more accurate than a standard implementation of maximum-likelihood NNIs (PhyML 3 with default settings). Although FastTree 2 is not quite as accurate as methods that use maximum-likelihood SPRs, most of the splits that disagree are poorly supported, and for large alignments, FastTree 2 is 100–1,000 times faster. FastTree 2 inferred a topology and likelihood-based local support values for 237,882 distinct 16S ribosomal RNAs on a desktop computer in 22 hours and 5.8 gigabytes of memory. Conclusions/Significance FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments. FastTree 2 is freely available at http://www.microbesonline.org/fasttree.
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            Haplotype-based variant detection from short-read sequencing

            The direct detection of haplotypes from short-read DNA sequencing data requires changes to existing small-variant detection methods. Here, we develop a Bayesian statistical framework which is capable of modeling multiallelic loci in sets of individuals with non-uniform copy number. We then describe our implementation of this framework in a haplotype-based variant detector, FreeBayes. 9 pages, partial draft
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              Randomized Trial of Benznidazole for Chronic Chagas' Cardiomyopathy.

              The role of trypanocidal therapy in patients with established Chagas' cardiomyopathy is unproven.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Writing – original draftRole: Writing – review and editing
                Role: InvestigationRole: MethodologyRole: Writing – review and editing
                Role: InvestigationRole: MethodologyRole: Writing – review and editing
                Role: InvestigationRole: MethodologyRole: Writing – review and editing
                Role: InvestigationRole: MethodologyRole: Writing – review and editing
                Role: InvestigationRole: MethodologyRole: Writing – review and editing
                Role: InvestigationRole: ResourcesRole: Writing – review and editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Writing – review and editing
                Role: Editor
                Journal
                Microbiol Spectr
                Microbiol Spectr
                Spectrum
                Microbiology Spectrum
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2165-0497
                Sep-Oct 2023
                05 September 2023
                05 September 2023
                : 11
                : 5
                : e04236-22
                Affiliations
                [1 ] Department of Tropical Medicine, School of Public Health and Tropical Medicine, and Vector-Borne and Infectious Disease Research Center, Tulane University; , New Orleans, Louisiana, USA
                [2 ] Laboratorio de Parasitologia, Centro de Investigaciones Regionales “Dr. Hideyo Noguchi”, Universidad Autonoma de Yucatan, Merida; , Yucatan, Mexico
                [3 ] Division of Veterinary Medicine, Tulane National Primate Research Center, Tulane University; , Covington, Louisiana, USA
                [4 ] Division of Microbiology, Tulane National Primate Research Center, Tulane University; , Covington, Louisiana, USA
                Institut de Recherche pour le Développement; , Montpellier, France
                Author notes
                Address correspondence to Eric Dumonteil, edumonte@ 123456tulane.edu

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0001-9376-0209
                Article
                04236-22 spectrum.04236-22
                10.1128/spectrum.04236-22
                10581044
                37668388
                9fc38d59-2ee6-48cb-80ef-35e589bf15fb
                Copyright © 2023 Dumonteil et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 21 October 2022
                : 10 July 2023
                Page count
                supplementary-material: 1, authors: 8, Figures: 9, Tables: 1, References: 74, Pages: 21, Words: 10905
                Funding
                Funded by: HHS | National Institutes of Health (NIH);
                Award ID: P51 OD011104
                Award Recipient :
                Funded by: HHS | NIH | National Institute of Allergy and Infectious Diseases (NIAID);
                Award ID: R21AI175523
                Award Recipient :
                Categories
                Research Article
                host-microbial-interactions, Host-Microbial Interactions
                Custom metadata
                September/October 2023

                strain interactions,host-parasite relationship,intracellular parasites,competition,pathogenesis

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