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Ho, S. F. S.

Publications and source records attributed to Ho, S. F. S..

3 recordsLinked to original sources

The Kocurious case of Noodlococcus: genomic insights into Kocuria rhizophila from characterisation of a laboratory contaminant

The laboratory contaminant Noodlococcus was named for its coccoid cells and unusual colony morphology, which resembled a pile of noodles. Along with laboratory characterisation and electron microscopy, we generated a complete Noodlococcus genome sequence using Illumina and Oxford Nanopore data. The genome consisted of a single, circular, 2732108 bp chromosome that shared 97.5% Average Nucleotide Identity (ANI) with the Kocuria rhizophila type strain TA68. We identified genomic features involved in replication (oriC), carotenoid synthesis (crt), and genome defence (CRISPR-Cas), and discovered four novel mobile elements (ISKrh4-7). Despite its environmental ubiquity and relevance to food production, bioremediation, and human medicine, there have been few genomic studies of the Kocuria genus. We conducted a comparative, phylogenetic, and pangenomic examination of all 257 publicly available Kocuria genomes, with a particular focus on the 56 that were identified as K. rhizophila. We found that there are two phylogenetically distinct clades of K. rhizophila, with within-clade ANI values of 96.7-100.0% and between-clade values of 89.5-90.4%. The second clade, which we refer to as K. pseudorhizophila, exhibited ANI values of <95% relative to TA68 and constitutes a separate species. Delineation of the two clades would be consistent with the rest of the genus, where all other species satisfy the 95% ANI threshold criteria. Differences in the K. rhizophila and K. pseudorhizophila pangenomes likely reflect phenotypic as well as evolutionary divergence. This distinction is relevant to clinical and industrial settings, as strains and genomes from both clades are currently used interchangeably, which may lead to reproducibility issues and phenotype-genotype discordance. Investigating an innocuous laboratory contaminant has therefore provided useful insights into the understudied species K. rhizophila, prompting an unexpected reassessment of its taxonomy. Impact statementBacterial genome sequence databases are dominated by a relatively small number of medically relevant genera, while most of the global bacterial populations diversity is largely uncharacterised. Kocuria is a widespread bacterial genus with industrial and medical relevance. Despite its ubiquity, only 22 complete and 235 draft Kocuria genomes were publicly available at the outset of this study. Our phylogenetic and pangenomic examination of all available Kocuria genomes was the first for this genus, providing insights into its diversity and taxonomy. Most notably, we found that Kocuria rhizophila is comprised of two clades that are sufficiently divergent to constitute different species, but are frequently used interchangeably in experimental and genomic research. The complete, high-quality Noodlococcus genome generated and characterised here can serve as a reference for true K. rhizophila, particularly while there is only a draft genome sequence available for type strain TA68. Data summarySequencing reads and the assembled Noodlococcus genome are available from NBCI BioProject accession PRJNA835814 and BioSample accession SAMN28111796. The complete sequence of the Noodlococcus chromosome can be found in the GenBank nucleotide database under accession number CP097204.1. Entries for the novel insertion sequences ISKrh4 to ISKrh7 can be found in the ISFinder database (https://isfinder.biotoul.fr).

genomics↗

Comprehensive benchmarking of tools to identify phages in metagenomic shotgun sequencing data

BackgroundThe prediction of bacteriophage sequences in metagenomic datasets has become a topic of considerable interest, leading to the development of many novel bioinformatic tools. A comparative analysis of ten state-of-the-art phage identification tools was performed to inform their usage in microbiome research. MethodsArtificial contigs generated from complete RefSeq genomes representing phages, plasmids, and chromosomes, and a previously sequenced mock community containing four phage species, were used to evaluate the precision, recall and F1-scores of the tools. We also generated a dataset of randomly shuffled sequences to quantify false positive calls. In addition, a set of previously simulated viromes was used to assess diversity bias in each tools output. ResultsVirSorter2 achieved the highest F1 score (0.92) in the RefSeq artificial contigs dataset, with several other tools also performing well. Kraken2 had the highest F1 score (0.86) in the mock community benchmark by a large margin (0.3 higher than DeepVirFinder in second place), mainly due to its high precision (0.96). Generally, k-mer based tools performed better than reference similarity tools and gene-based methods. Several tools, most notably PPR Meta, called a high number of false positives in the randomly shuffled sequences. When analysing the diversity of the genomes that each tool predicted from a virome set, most tools produced a viral genome set that had similar alpha and beta diversity patterns to the original population, with Seeker being a notable exception. ConclusionsThis study provides key metrics used to assess performance of phage detection tools, offers a framework for further comparison of additional viral discovery tools, and discusses optimal strategies for using these tools. We highlight that the choice of tool for identification of phages in metagenomic datasets, as well as their parameters, can bias the results and provide pointers for different use case scenarios. We have also made our benchmarking dataset available for download in order to facilitate future comparisons of phage identification tools.

microbiology↗

Microbiota analysis of rural and urban surface waters and sediments in Bangladesh identifies human waste as driver of antibiotic resistance

In many low- and middle-income countries antibiotic resistant bacteria spread in the environment due to inadequate treatment of wastewater and the poorly regulated use of antibiotics in agri- and aquaculture. Here we characterised the abundance and diversity of antibiotic-resistant bacteria and antibiotic resistance genes in surface waters and sediments in Bangladesh through quantitative culture of Extended-Spectrum Beta-Lactamase (ESBL)-producing coliforms and shotgun metagenomics. Samples were collected from highly urbanised settings (n = 7), from rural ponds with a history of aquaculture-related antibiotic use (n = 11) and from rural ponds with no history of antibiotic use (n = 6). ESBL-producing coliforms were found to be more prevalent in urban samples than in rural samples. Shotgun sequencing showed that sediment samples were dominated by the phylum Proteobacteria (on average 73.8% of assigned reads), while in the water samples Cyanobacteria (on average 60.9% of assigned reads) were the predominant phylum. Antibiotic resistance genes were detected in all samples, but their abundance varied 1,525-fold between sites, with the highest levels of antibiotic resistance genes being present in urban surface water samples. We identified an IncQ1 sulphonamide resistance plasmid ancestral to the widely studied RSF1010 in one of the urban water samples. The abundance of antibiotic resistance genes was significantly correlated (R2 = 0.73; P = 8.9 x 10-15) with the abundance of bacteria originating from the human gut, which suggests that the release of untreated sewage is a driver for the spread of environmental antibiotic resistance genes in Bangladesh, particularly in highly urbanised settings. ImportanceLow- and middle-income countries (LMICs) have higher burdens of multidrug-resistant infections than high-income countries and there is thus an urgent need to elucidate the drivers of the spread of antibiotic-resistant bacteria in LMICs. Here we study the diversity and abundance of antibiotic resistance genes in surface water and sediments from rural and urban settings in Bangladesh. We found that urban surface waters are particularly rich in antibiotic resistance genes, with a higher number of them associated with plasmids indicating that they are more likely to spread horizontally. The abundance of antibiotic resistance genes was strongly correlated with the abundance of bacteria that originate from the human gut, suggesting that uncontrolled release of human waste is a major driver for the spread of antibiotic resistance in the urban environment. Improvements in sanitation in LMICs may thus be a key intervention to reduce the dissemination of antibiotic resistant bacteria.

microbiology↗