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      Bacterial Metabolic Potential and Micro-Eukaryotes Enriched in Stony Coral Tissue Loss Disease Lesions

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      Frontiers in Marine Science
      Frontiers Media SA

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          Abstract

          The epizootic disease outbreak known as stony coral tissue loss disease (SCTLD) is arguably the most devastating coral disease in recorded history. SCTLD emerged off the coast of South Florida in 2014 and has since moved into the Caribbean, resulting in coral mortality rates that have changed reef structure and function. Currently, the cause of SCTLD is unknown, but there is evidence from 16S rRNA gene sequencing and bacterial culture studies that the microbial community plays a role in the progression of SCTLD lesions. In this study, we applied shotgun metagenomics to characterize the potential function of bacteria, as well as the composition of the micro-eukaryotic community, associated with SCTLD lesions. We re-examined samples that were previously analyzed using 16S rRNA gene high-throughput sequencing from four coral species: Stephanocoenia intersepta, Diploria labyrinthiformis, Dichocoenia stokesii, and Meandrina meandrites. For each species, tissue from apparently healthy (AH) corals, and unaffected tissue (DU) and lesion tissue (DL) on diseased corals, were collected from sites within the epidemic zone of SCTLD in the Florida Keys. Within the micro-eukaryotic community, the taxa most prominently enriched in DL compared to AH and DU tissue were members of Ciliophora. We also found that DL samples were relatively more abundant in less energy-efficient pathways like the pentose phosphate pathways. While less energy-efficient processes were identified, there were also relatively higher abundances of nucleotide biosynthesis and peptidoglycan maturation pathways in diseased corals compared to AH, which suggests there was more bacteria growth in diseased colonies. In addition, we generated 16 metagenome-assembled genomes (MAGs) belonging to the orders Pseudomonadales, Beggiatoales, Rhodobacterales, Rhizobiales, Rs-D84, Flavobacteriales, and Campylobacterales, and all MAGs were enriched in DL samples compared to AH samples. Across all MAGs there were antibiotic resistance genes that may have implications for the treatment of SCTLD with antibiotics. We also identified genes and pathways linked to virulence, such as nucleotide biosynthesis, succinate dehydrogenase, ureases, nickel/iron transporters, Type-1 secretion system, and metalloproteases. Some of these enzymes/pathways have been previously targeted in the treatment of other bacterial diseases and they may be of interest to mitigate SCTLD lesion progression.

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          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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            Basic local alignment search tool.

            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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              CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

              Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.
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                Author and article information

                Journal
                Frontiers in Marine Science
                Front. Mar. Sci.
                Frontiers Media SA
                2296-7745
                January 6 2022
                January 6 2022
                : 8
                Article
                10.3389/fmars.2021.776859
                48643220-df5e-43f1-a956-abc31bd496ae
                © 2022

                Free to read

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

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