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      Seasonal succession of bacterial communities in cultured Caulerpa lentillifera detected by high-throughput sequencing

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          Abstract

          An increasing number of microorganisms are being identified as pathogens for diseases in macroalgae, but the species composition of bacteria related to Caulerpa lentillifera, fresh edible green macroalgae worldwide, remains largely unclear. The bacterial communities associated with C. lentillifera were investigated by high-throughput 16S rDNA sequencing, and the bacterial diversities in washed and control groups were compared in this study. A total of 4,388 operational taxonomic units were obtained from all the samples, and the predominant prokaryotic phyla were Proteobacteria, Bacteroidetes, Planctomycetes, Cyanobacteria, Actinobacteria, Verrucomicrobia, Chloroflexi, and Acidobacteria in C. lentillifera. The bacterial diversity changed with seasons and showed an increasing trend of diversity with the rising temperature in C. lentillifera. There were slight reductions in the abundance and diversity of bacteria after washing with tap water for 2 h, indicating that only parts of the bacterial groups could be washed out, and hidden dangers in C. lentillifera still exist. Although the reduction in the abundance of some bacteria revealed a positive significance of washing C. lentillifera with tap water on food safety, more effective cleaning methods still need to be explored.

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          Most cited references52

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          MUSCLE: multiple sequence alignment with high accuracy and high throughput.

          We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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            QIIME allows analysis of high-throughput community sequencing data.

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              FLASH: fast length adjustment of short reads to improve genome assemblies.

              Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome. We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds. The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash. t.magoc@gmail.com.
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                Author and article information

                Contributors
                Journal
                Open Life Sci
                Open Life Sci
                biol
                Open Life Sciences
                De Gruyter
                2391-5412
                28 January 2022
                2022
                : 17
                : 1
                : 10-21
                Affiliations
                Postdoctoral Innovation Practice Base, Shenzhen Polytechnic , Shenzhen 518055, China
                School of Applied Chemistry and Biological Technology, Shenzhen Polytechnic , Shenzhen 518055, China
                Author notes
                [1]

                Meixia Pang and Zhili Huang are co-first authors.

                Article
                biol-2022-0001
                10.1515/biol-2022-0001
                8800382
                35128065
                a33fee0a-6458-4148-94dd-b8d9e6cf1285
                © 2022 Meixia Pang et al., published by De Gruyter

                This work is licensed under the Creative Commons Attribution 4.0 International License.

                History
                : 27 March 2021
                : 18 October 2021
                : 19 October 2021
                Page count
                Pages: 12
                Categories
                Research Article

                16s rdna,bacterial diversity,caulerpa lentillifera,washing with tap water

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