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      Antiviral function and viral antagonism of the rapidly evolving dynein activating adaptor NINL

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          Abstract

          Viruses interact with the intracellular transport machinery to promote viral replication. Such host–virus interactions can drive host gene adaptation, leaving signatures of pathogen-driven evolution in host genomes. Here, we leverage these genetic signatures to identify the dynein activating adaptor, ninein-like (NINL), as a critical component in the antiviral innate immune response and as a target of viral antagonism. Unique among genes encoding components of active dynein complexes, NINL has evolved under recurrent positive (diversifying) selection, particularly in its carboxy-terminal cargo-binding region. Consistent with a role for NINL in host immunity, we demonstrate that NINL knockout cells exhibit an impaired response to interferon, resulting in increased permissiveness to viral replication. Moreover, we show that proteases encoded by diverse picornaviruses and coronaviruses cleave and disrupt NINL function in a host- and virus-specific manner. Our work reveals the importance of NINL in the antiviral response and the utility of using signatures of host–virus genetic conflicts to uncover new components of antiviral immunity and targets of viral antagonism.

          eLife digest

          Humans and viruses are locked in an evolutionary arms race. Viruses hijack cells, using their resources and proteins to build more viral particles; the cells fight back, calling in the immune system to fend off the attack. Both actors must constantly and quickly evolve to keep up with each other. This genetic conflict has been happening for millions of years, and the indelible marks it has left on genes can serve to uncover exactly how viruses interact with the organisms they invade.

          One hotspot in this host-virus conflict is the complex network of molecules that help to move cargo inside a cell. This system transports elements of the immune system, but viruses can also harness it to make more of themselves. Scientists still know very little about how viruses and the intracellular transport machinery interact, and how this impacts viral replication and the immune response.

          Stevens et al. therefore set out to identify new interactions between viruses and the transport system by using clues left in host genomes by evolution. They focused on dynein, a core component of this machinery which helps to haul molecular actors across a cell. To do so, dynein relies on adaptor molecules such as 'Ninein-like', or NINL for short.

          Closely examining the gene sequence for NINL across primates highlighted an evolutionary signature characteristic of host-virus genetic conflicts; this suggests that the protein may be used by viruses to reproduce, or by cells to fend off infection.

          And indeed, human cells lacking the NINL gene were less able to defend themselves, allowing viruses to grow much faster than normal. Further work showed that NINL was important for a major type of antiviral immune response. As a potential means to sabotage this defence mechanism, some viruses cleave NINL at specific sites and disrupt its role in intracellular transport.

          Better antiviral treatments are needed to help humanity resist old foes and new threats alike. The work by Stevens et al. demonstrates how the information contained in host genomes can be leveraged to understand what drives susceptibility to an infection, and to pinpoint molecular actors which could become therapeutic targets.

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          Most cited references73

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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              We introduce Salmon, a method for quantifying transcript abundance from RNA-seq reads that is accurate and fast. Salmon is the first transcriptome-wide quantifier to correct for fragment GC content bias, which we demonstrate substantially improves the accuracy of abundance estimates and the reliability of subsequent differential expression analysis. Salmon combines a new dual-phase parallel inference algorithm and feature-rich bias models with an ultra-fast read mapping procedure.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                12 October 2022
                2022
                : 11
                : e81606
                Affiliations
                [1 ] Department of Cellular and Molecular Medicine, University of California, San Diego ( https://ror.org/0168r3w48) La Jolla United States
                [2 ] Department of Molecular Biology, University of California, San Diego ( https://ror.org/0168r3w48) La Jolla United States
                [3 ] Howard Hughes Medical Institute ( https://ror.org/006w34k90) Chevy Chase United States
                [4 ] Nikon Imaging Center at UC San Diego, University of California, San Diego ( https://ror.org/0168r3w48) San Diego United States
                [5 ] Department of Cell and Developmental Biology, University of California, San Diego ( https://ror.org/0168r3w48) La Jolla United States
                University of Pennsylvania ( https://ror.org/00b30xv10) United States
                Yale University ( https://ror.org/03v76x132) United States
                University of Pennsylvania ( https://ror.org/00b30xv10) United States
                University of Pennsylvania ( https://ror.org/00b30xv10) United States
                University of Texas Medical Branch ( https://ror.org/016tfm930) United States
                Author notes
                [†]

                These authors contributed equally to this work.

                [‡]

                Department of Molecular Physiology and Biophysics, University of Vermont, Burlington, United States.

                Author information
                https://orcid.org/0000-0002-3732-9972
                https://orcid.org/0000-0003-0151-1091
                https://orcid.org/0000-0003-0268-8323
                https://orcid.org/0000-0002-2630-9837
                https://orcid.org/0000-0002-1553-465X
                https://orcid.org/0000-0002-4879-9603
                Article
                81606
                10.7554/eLife.81606
                9651953
                36222652
                be9a468b-0f9f-4b36-aff9-befaf29148d6
                © 2022, Stevens, Beierschmitt et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 04 July 2022
                : 11 October 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: GM133633
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: GM141825
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: GM007240
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000011, Howard Hughes Medical Institute;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: GRFP
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000011, Howard Hughes Medical Institute;
                Award ID: Gilliam Fellowship
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000875, Pew Charitable Trusts;
                Award ID: Biomedical Scholars Program
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000861, Burroughs Wellcome Fund;
                Award ID: Investigators in the Pathogenesis of Infectious Diseases
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Immunology and Inflammation
                Microbiology and Infectious Disease
                Custom metadata
                Evolution-guided functional analyses identify an activating adaptor of the dynein intracellular transportation machinery, NINL, as a novel component of the antiviral immune response and reveal a mechanism by which viruses antagonize NINL function in a species-specific manner.

                Life sciences
                host–virus evolution,innate antiviral immunity,microtubule-based transport,dynein,viral antagonist,viral protease,human,viruses

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