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      Jumbo Phages: A Comparative Genomic Overview of Core Functions and Adaptions for Biological Conflicts

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          Abstract

          Jumbo phages have attracted much attention by virtue of their extraordinary genome size and unusual aspects of biology. By performing a comparative genomics analysis of 224 jumbo phages, we suggest an objective inclusion criterion based on genome size distributions and present a synthetic overview of their manifold adaptations across major biological systems. By means of clustering and principal component analysis of the phyletic patterns of conserved genes, all known jumbo phages can be classified into three higher-order groups, which include both myoviral and siphoviral morphologies indicating multiple independent origins from smaller predecessors. Our study uncovers several under-appreciated or unreported aspects of the DNA replication, recombination, transcription and virion maturation systems. Leveraging sensitive sequence analysis methods, we identify novel protein-modifying enzymes that might help hijack the host-machinery. Focusing on host–virus conflicts, we detect strategies used to counter different wings of the bacterial immune system, such as cyclic nucleotide- and NAD +-dependent effector-activation, and prevention of superinfection during pseudolysogeny. We reconstruct the RNA-repair systems of jumbo phages that counter the consequences of RNA-targeting host effectors. These findings also suggest that several jumbo phage proteins provide a snapshot of the systems found in ancient replicons preceding the last universal ancestor of cellular life.

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          Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

          S Altschul (1997)
          The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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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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              MUSCLE: a multiple sequence alignment method with reduced time and space complexity

              Background In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUSCLE to achieve the highest scores reported to date on four alignment accuracy benchmarks. Here we present a more complete discussion of the algorithm, describing several previously unpublished techniques that improve biological accuracy and / or computational complexity. We introduce a new option, MUSCLE-fast, designed for high-throughput applications. We also describe a new protocol for evaluating objective functions that align two profiles. Results We compare the speed and accuracy of MUSCLE with CLUSTALW, Progressive POA and the MAFFT script FFTNS1, the fastest previously published program known to the author. Accuracy is measured using four benchmarks: BAliBASE, PREFAB, SABmark and SMART. We test three variants that offer highest accuracy (MUSCLE with default settings), highest speed (MUSCLE-fast), and a carefully chosen compromise between the two (MUSCLE-prog). We find MUSCLE-fast to be the fastest algorithm on all test sets, achieving average alignment accuracy similar to CLUSTALW in times that are typically two to three orders of magnitude less. MUSCLE-fast is able to align 1,000 sequences of average length 282 in 21 seconds on a current desktop computer. Conclusions MUSCLE offers a range of options that provide improved speed and / or alignment accuracy compared with currently available programs. MUSCLE is freely available at .
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Viruses
                Viruses
                viruses
                Viruses
                MDPI
                1999-4915
                05 January 2021
                January 2021
                : 13
                : 1
                : 63
                Affiliations
                [1 ]National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA; lakshmin@ 123456mail.nih.gov (L.M.I.); ananthar@ 123456mail.nih.gov (V.A.); burrough@ 123456mail.nih.gov (A.M.B.)
                [2 ]Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Berhampur, Odisha 760010, India; akrishnan@ 123456iiserbpr.ac.in
                Author notes
                [* ]Correspondence: aravind@ 123456mail.nih.gov
                Author information
                https://orcid.org/0000-0002-4844-2022
                https://orcid.org/0000-0001-8395-0009
                https://orcid.org/0000-0002-2229-8771
                https://orcid.org/0000-0003-0771-253X
                Article
                viruses-13-00063
                10.3390/v13010063
                7824862
                33466489
                9e4ae067-ef78-4d23-8479-1136d9c7898d
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 24 November 2020
                : 31 December 2020
                Categories
                Article

                Microbiology & Virology
                dna viruses,anti-phage systems,nicotinamide dinucleotide,dna polymerases,dna polymerase iii,rna polymerase,transcription,nucleotides,virus evolution

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