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      Microscopic and Genetic Characterization of Bacterial Symbionts With Bioluminescent Potential in Pyrosoma atlanticum

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      Frontiers in Marine Science
      Frontiers Media SA

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          Abstract

          The pelagic tunicate pyrosome, Pyrosoma atlanticum, is known for its brilliant bioluminescence, but the mechanism causing this bioluminescence has not been fully characterized. This study identifies the bacterial bioluminescent symbionts of P. atlanticumcollected in the northern Gulf of Mexico using several methods such as light and electron microscopy, as well as molecular genetics. The bacteria are localized within the pyrosome light organs. Greater than 50% of the bacterial taxa present in the tunicate samples were the bioluminescent symbiotic bacteria Vibrionaceae as determined by utilizing current molecular genetics methodologies. A total of 396K MiSeq16S rRNA reads provided total pyrosome microbiome profiles to determine bacterial symbiont taxonomy. After comparing with the Silva rRNA database, a Photobacteriumsp. r33-like bacterium (which we refer to as “ PhotobacteriumPa-1”) matched at 99% sequence identity as the most abundant bacteria within Pyrosoma atlanticumsamples. Specifically designed 16S rRNA V4 probes for fluorescence in situhybridization (FISH) verified the PhotobacteriumPa-1 location as internally concentrated along the periphery of each dual pyrosome luminous organ. While searching for bacterial luxgenes in two tunicate samples, we also serendipitously generated a draft tunicate mitochondrial genome that can be used for Pyrosoma atlanticumidentification. Scanning (SEM) and transmission (TEM) electron microscopy confirmed the presence of intracellular rod-like bacteria in the light organs. This intracellular localization of bacteria may represent bacteriocyte formation reminiscent of other invertebrates.

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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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            QIIME allows analysis of high-throughput community sequencing data.

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              Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

              The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
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                Author and article information

                Journal
                Frontiers in Marine Science
                Front. Mar. Sci.
                Frontiers Media SA
                2296-7745
                February 3 2021
                February 3 2021
                : 8
                Article
                10.3389/fmars.2021.606818
                fe47e6ba-0026-4db7-8601-dc0c7d29d1ff
                © 2021

                Free to read

                https://creativecommons.org/licenses/by/4.0/

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