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      A genome sequence for Biomphalaria pfeifferi, the major vector snail for the human-infecting parasite Schistosoma mansoni

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          Abstract

          Background

          Biomphalaria pfeifferi is the world’s most widely distributed and commonly implicated vector snail species for the causative agent of human intestinal schistosomiasis, Schistosoma mansoni. In efforts to control S. mansoni transmission, chemotherapy alone has proven insufficient. New approaches to snail control offer a way forward, and possible genetic manipulations of snail vectors will require new tools. Towards this end, we here offer a diverse set of genomic resources for the important African schistosome vector, B. pfeifferi.

          Methodology/Principal findings

          Based largely on PacBio High-Fidelity long reads, we report a genome assembly size of 772 Mb for B. pfeifferi (Kenya), smaller in size than known genomes of other planorbid schistosome vectors. In a total of 505 scaffolds (N50 = 3.2Mb), 430 were assigned to 18 large linkage groups inferred to represent the 18 known chromosomes, based on whole genome comparisons with Biomphalaria glabrata. The annotated B. pfeifferi genome reveals a divergence time of 3.01 million years with B. glabrata, a South American species believed to be similar to the progenitors of B. pfeifferi which undertook a trans-Atlantic colonization < five million years ago.

          Conclusions/Significance

          The genome for this preferentially self-crossing species is less heterozygous than related species known to be preferential out-crossers; its smaller genome relative to congeners may similarly reflect its preference for selfing. Expansions of gene families with immune relevance are noted, including the FReD gene family which is far more similar in its composition to B. glabrata than to Bulinus truncatus, a vector for Schistosoma haematobium. Provision of this annotated genome will help better understand the dependencies of trematodes on snails, enable broader comparative insights regarding factors contributing to susceptibility/ resistance of snails to schistosome infections, and provide an invaluable resource with respect to identifying and manipulating snail genes as potential targets for more specific snail control programs.

          Author summary

          Biomphalaria pfeifferi is the world’s most widely distributed and commonly implicated vector snail for the causative agent of human intestinal schistosomiasis, Schistosoma mansoni. Understanding the basis of host-parasite compatibility relies on functional genomic resources, which will be helpful for developing genetic-based control of schistosomes and their vector snails. Here we report a high-quality, de novo–assembled whole genome for B. pfeifferi (PacBio High-Fidelity long reads), with in-depth gene model annotation for protein-coding and nonprotein-coding genes. Using these enriched molecular data, a divergence date of 3.01 Mya was calculated for B. pfeifferi and B. glabrata, consistent with the idea of Biomphalaria colonization of Africa from South America, and placing an upper boundary on the age of S. mansoni in Africa. The spread of S. mansoni was likely favored by its high degree of compatibility with B. pfeifferi-like snails. In addition, our evidence supports the idea that B. pfeifferi is a preferentially self-crossing species with a more homozygous and smaller genome than related species like B. glabrata known to be preferential out-crossers. Furthermore, several immune-related gene families have expanded differently between B. pfeifferi to B. glabrata. Resources provided here will deepen our general knowledge of molluscan biology, host-parasite co-evolution, vector biology, and genomics.

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          Most cited references149

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

            We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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              Highly accurate protein structure prediction with AlphaFold

              Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 7 . Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’ 8 —has been an important open research problem for more than 50 years 9 . Despite recent progress 10 – 14 , existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: MethodologyRole: ResourcesRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: MethodologyRole: ValidationRole: Writing – review & editing
                Role: ResourcesRole: ValidationRole: Writing – review & editing
                Role: Funding acquisitionRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: Funding acquisitionRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                PLoS Negl Trop Dis
                plos
                PLOS Neglected Tropical Diseases
                Public Library of Science (San Francisco, CA USA )
                1935-2727
                1935-2735
                24 March 2023
                March 2023
                : 17
                : 3
                : e0011208
                Affiliations
                [1 ] Department of Biology, Center for Evolutionary and Theoretical Immunology, Parasite Division Museum of Southwestern Biology, University of New Mexico, Albuquerque, New Mexico, United States of America
                [2 ] Center for Biotechnology Research and Development, Kenya Medical Research Institute, Nairobi, Kenya
                [3 ] College of Osteopathic Medicine of the Pacific–Northwest, Western University of Health Sciences, Lebanon, Oregon, United States of America
                NIAID: National Institute of Allergy and Infectious Diseases, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-8625-2732
                https://orcid.org/0000-0001-5073-3753
                Article
                PNTD-D-22-01163
                10.1371/journal.pntd.0011208
                10075465
                36961841
                148206b4-21a4-4df6-bf30-cdfb1c6eed0e
                © 2023 Bu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 7 September 2022
                : 27 February 2023
                Page count
                Figures: 9, Tables: 6, Pages: 41
                Funding
                Funded by: National Institutes of Health (NIH)
                Award ID: R37AI101438
                Award Recipient :
                This study was funded by the National Institute of Health ( https://www.nih.gov/) grant (R37AI101438 to ESL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Genomics
                Animal Genomics
                Invertebrate Genomics
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Helminths
                Schistosoma
                Schistosoma Mansoni
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Helminths
                Schistosoma
                Schistosoma Mansoni
                Biology and Life Sciences
                Genetics
                Genomics
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Molluscs
                Gastropods
                Snails
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Molluscs
                Gastropods
                Snails
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Helminths
                Schistosoma
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Helminths
                Schistosoma
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Molluscs
                Gastropods
                Snails
                Biomphalaria
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Molluscs
                Gastropods
                Snails
                Biomphalaria
                Biology and Life Sciences
                Biochemistry
                Proteins
                Protein Domains
                Biology and Life Sciences
                Immunology
                Immune System Proteins
                Immune Receptors
                Toll-like Receptors
                Medicine and Health Sciences
                Immunology
                Immune System Proteins
                Immune Receptors
                Toll-like Receptors
                Biology and Life Sciences
                Biochemistry
                Proteins
                Immune System Proteins
                Immune Receptors
                Toll-like Receptors
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Immune Receptors
                Toll-like Receptors
                Custom metadata
                vor-update-to-uncorrected-proof
                2023-04-05
                The raw genome sequencing data, as well as annotated genome sequences are available at NCBI under project accession: PRJNA855116. All other data generated or analyzed during this study are included in this published article and its supplementary information files.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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