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      Genetic determinants of host tropism in Klebsiella phages

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          Summary

          Bacteriophages play key roles in bacterial ecology and evolution and are potential antimicrobials. However, the determinants of phage-host specificity remain elusive. Here, we isolate 46 phages to challenge 138 representative clinical isolates of Klebsiella pneumoniae, a widespread opportunistic pathogen. Spot tests show a narrow host range for most phages, with <2% of 6,319 phage-host combinations tested yielding detectable interactions. Bacterial capsule diversity is the main factor restricting phage host range. Consequently, phage-encoded depolymerases are key determinants of host tropism, and depolymerase sequence types are associated with the ability to infect specific capsular types across phage families. However, all phages with a broader host range found do not encode canonical depolymerases, suggesting alternative modes of entry. These findings expand our knowledge of the complex interactions between bacteria and their viruses and point out the feasibility of predicting the first steps of phage infection using bacterial and phage genome sequences.

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          Highlights

          • Klebsiella capsular diversity restricts the host range of most Klebsiella phages

          • Phage-encoded depolymerase domains can predict capsular tropism

          • Capsular tropism predictability is limited by post-adsorptive resistance mechanisms

          • Phages lacking capsule dependency and depolymerases exhibit broader host ranges

          Abstract

          Beamud et al. analyze the host tropism of bacteriophages infecting Klebsiella pneumoniae, a nosocomial pathogen of global concern. They identify phage sequence domains that predict capsular tropism, the main determinant of infectivity. This work demonstrates how phenotypic and genomic data can be combined to better understand virus-host interactions.

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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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              SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

              The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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                Author and article information

                Contributors
                Journal
                Cell Rep
                Cell Rep
                Cell Reports
                Cell Press
                2211-1247
                06 February 2023
                28 February 2023
                06 February 2023
                : 42
                : 2
                : 112048
                Affiliations
                [1 ]Joint Research Unit Infection and Public Health, FISABIO-Universitat de València, 46020 València, Spain
                [2 ]Institute for Integrative Systems Biology (I 2SysBio), Universitat de València-CSIC, 46980 Paterna, Spain
                Author notes
                []Corresponding author fernando.gonzalez@ 123456uv.es
                [∗∗ ]Corresponding author pilar.domingo@ 123456uv.es
                [∗∗∗ ]Corresponding author rafael.sanjuan@ 123456uv.es
                [3]

                Lead contact

                Article
                S2211-1247(23)00059-1 112048
                10.1016/j.celrep.2023.112048
                9989827
                36753420
                27ca3ec9-1853-4e28-8db0-255a46e4d89c
                © 2023 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 2 June 2022
                : 25 November 2022
                : 13 January 2023
                Categories
                Article

                Cell biology
                bacteriophage,klebsiella,host range,bacterial capsule,depolymerase,microbial evolution,horizontal gene transfer,genomics

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