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  • 2015-2019  (3)
  • 1
    Publication Date: 2019
    Description: 〈p〉All known phototrophic metabolisms on Earth rely on one of three categories of energy-converting pigments: chlorophyll-〈i〉a〈/i〉 (rarely -〈i〉d〈/i〉), bacteriochlorophyll-〈i〉a〈/i〉 (rarely -〈i〉b〈/i〉), and retinal, which is the chromophore in rhodopsins. While the significance of chlorophylls in solar energy capture has been studied for decades, the contribution of retinal-based phototrophy to this process remains largely unexplored. We report the first vertical distributions of the three energy-converting pigments measured along a contrasting nutrient gradient through the Mediterranean Sea and the Atlantic Ocean. The highest rhodopsin concentrations were observed above the deep chlorophyll-〈i〉a〈/i〉 maxima, and their geographical distribution tended to be inversely related to that of chlorophyll-〈i〉a〈/i〉. We further show that proton-pumping proteorhodopsins potentially absorb as much light energy as chlorophyll-〈i〉a〈/i〉–based phototrophy and that this energy is sufficient to sustain bacterial basal metabolism. This suggests that proteorhodopsins are a major energy-transducing mechanism to harvest solar energy in the surface ocean.〈/p〉
    Electronic ISSN: 2375-2548
    Topics: Natural Sciences in General
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  • 2
    Publication Date: 2016-09-02
    Description: With high-throughput sequencing (HTS), we are able to explore the hidden world of microscopic organisms to an unpre-cedented level. The fast development of molecular technology and statistical methods means that microbial ecologists must keep their toolkits updated. Here, we review and evaluate some of the more widely adopted and emerging techniques for analysis of diversity and community composition, and the inference of species interactions from co-occurrence data generated by HTS of marker genes. We emphasize the importance of observational biases and statistical properties of the data and methods. The aim of the review is to critically discuss the advantages and disadvantages of established and emerging statistical methods, and to contribute to the integration of HTS-based marker gene data into community ecology.
    Print ISSN: 0168-6445
    Electronic ISSN: 1574-6976
    Topics: Biology
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  • 3
    Publication Date: 2017-01-10
    Description: Viruses and their host genomes often share similar oligonucleotide frequency (ONF) patterns, which can be used to predict the host of a given virus by finding the host with the greatest ONF similarity. We comprehensively compared 11 ONF metrics using several k -mer lengths for predicting host taxonomy from among ~32 000 prokaryotic genomes for 1427 virus isolate genomes whose true hosts are known. The background-subtracting measure $d_2^*$ at k = 6 gave the highest host prediction accuracy (33%, genus level) with reasonable computational times. Requiring a maximum dissimilarity score for making predictions (thresholding) and taking the consensus of the 30 most similar hosts further improved accuracy. Using a previous dataset of 820 bacteriophage and 2699 bacterial genomes, $d_2^*$ host prediction accuracies with thresholding and consensus methods (genus-level: 64%) exceeded previous Euclidian distance ONF (32%) or homology-based (22-62%) methods. When applied to metagenomically-assembled marine SUP05 viruses and the human gut virus crAssphage, $d_2^*$ -based predictions overlapped (i.e. some same, some different) with the previously inferred hosts of these viruses. The extent of overlap improved when only using host genomes or metagenomic contigs from the same habitat or samples as the query viruses. The $d_2^*$ ONF method will greatly improve the characterization of novel, metagenomic viruses.
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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