bioRxiv Science⌕ Search

bioRxiv · 10.1101/472001

Insights into the microbiota of Asian seabass (Lates calcarifer) with tenacibaculosis symptoms and description of sp. nov. Tenacibaculum singaporense

Abstract

Outbreaks of diseases in farmed fish remain a recurring problem despite the development of vaccines and improved hygiene standards on aquaculture farms. One commonly observed bacterial disease in tropical aquaculture of the South-East Asian region is tenacibaculosis, which is attributed to members of the Bacteroidetes genus Tenacibaculum, most notably T. maritimum. The impact of tenacibaculosis on fish microbiota remains poorly understood. In this study, we analysed the microbiota of different tissue types of commercially reared Asian seabass (Lates calcarifer) that showed symptoms of tenacibaculosis and compared the microbial communities to those of healthy and experimentally infected fish that were exposed to diseased farm fish. The microbiota of diseased farm fish was dominated by Proteobacteria (relative abundance{+/-}standard deviation, 74.5%{+/-}22.8%) and Bacteroidetes (18.07%{+/-}21.7%), the latter mainly comprised by a high abundance of Tenacibaculum species (17.6%{+/-}20.7%). In healthy seabass Proteobacteria had also highest relative abundance (48.04%{+/-}0.02%), but Firmicutes (34.2%{+/-}0.02%) and Fusobacteria (12.0%{+/-}0.03%) were the next two major constituents. Experimentally infected fish developed lesions characteristic for tenacibaculosis, but the microbiota was primarily dominated by Proteobacteria (90.4%{+/-}0.2%) and Firmicutes (6.2%{+/-}0.1%). The relative abundance of Tenacibaculum species in experimentally infected fish was significantly lower than in the commercially reared diseased fish and revealed a higher prevalence of different Tenacibaculum species. One strain was isolated and is described here as sp. nov. Tenacibaculum singaporense TLL-A1T (=DSM 106434T, KCTC 62393T). The genome of T. singaporense was sequenced and compared to those of T. maritimum DSM 17995T and the newly sequenced T. mesophilum DSM 13764T.\n\nImportanceFish production from aquaculture facility has become a major source of protein for human consumption and is expected to further grow to meet the growing demands. Devastating fish diseases, such as tenacibaculosis, can eradicate entire stocks of aquaculture fish in a short time and pose a serious threat to individual fish farmers and overall fish production. Understanding the disease processes and the individual microbial players involved has the potential to develop methods to prevent or mitigate infections on aquaculture farms. This study provides important insights into the microbial ecology of tenacibaculosis from an aquaculture facility in Singapore and highlights the complexity of this fish disease at two different disease stages. Furthermore, the isolation of a novel Tenacibaculum species and comparative genome analysis of three different Tenacibaculum species enhance our view of this economically and environmentally important bacterial genus.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Miyake, S., Soh, M., Azman, M. N., Ngoh, S. Y., Orban, L., Seedorf, H.. 2018-11-19. Insights into the microbiota of Asian seabass (Lates calcarifer) with tenacibaculosis symptoms and description of sp. nov. Tenacibaculum singaporense. https://doi.org/10.1101/472001

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Cell-scale confinement reorders bacterial speed rankings

Which bacterium swims fastest depends on where the race is run. Speeds are usually measured in open liquid, yet many bacteria live in pores, mucus and host passages no wider than a cell. Using a microfluidic device with eight channel widths (0.80-3.00 m) in one field of view, we tracked unlabeled cells of eight species spanning five motility systems. Chamber height, a polymer additive and channel width each reordered the ranking. Vibrio alginolyticus, the fastest in open liquid, slowed to ~4 m/s in 1.25-m channels, whereas Campylobacter jejuni and Bacillus subtilis kept 33-46 m/s. Open liquid speed did not predict robustness to confinement. In two unrelated lineages, host symbionts that pass through narrow passages during colonization, Caballeronia insecticola and Vibrio fischeri, outran their non-symbiotic relatives in the channels, and crossed them with flagella wrapped around the cell body at nearly the speed of unwrapped cells. Where space is tight, the ability to keep moving, not top speed, sets the ranking.

microbiology↗

The biochemical composition of coronavirus Nucleocapsid proteins drives the bicistronic properties of their sub-genomic mRNAs

The nucleocapsid (N) gene of coronaviruses (CoVs) encodes a structural RNA-binding protein required for viral assembly. In SARS- and MERS-CoV viruses, reading frame 2 of N contains an overlapping open reading frame (ORF) encoding an innate immune antagonist accessory protein. However, the extent of this dual coding capacity across the CoV family, and the genetic features driving overlapping ORF formation, remain unexamined. Here, we developed an in-silico tool (ORFan) to screen structural gene sub-genomic mRNA sequences from 152 species of coronavirus for the presence of overlapping accessory gene candidates. We found that frame 2 of the N gene in Alpha-, Beta- and Delta-CoVs frequently contains a potential accessory ORF (AcORF), conserved at the subgenus level, unlike the spike, envelope and membrane genes. We also show that CoV nucleotide biases in conjunction with codon biases integral to N protein function drive the relatively high abundances of start codons in frame two and stop codons in frame three, explaining the tendency towards frame 2 AcORFs. We further suggest that viral nucleotide biases and the codon composition required for RNA-binding function facilitate overlapping ORF formation in other virus families

microbiology↗

Evaluating non-oxidative glycolysis using 13C metabolic flux analysis

Non-oxidative glycolysis (NOG) converts glucose to acetyl-CoA without emitting CO2 during Escherichia coli bioproduction. Although 13C-metabolic flux analysis (13C-MFA) has the potential to evaluate NOG flux distribution in vivo, the precision of these estimates depends on the labeling patterns of glucose tracers. Because E. coli has multiple native glycolysis pathways, selecting the optimal glucose tracer is important for precise estimates. This study used simulations to evaluate the performance of 18 commercially available glucose tracers in precisely predicting NOG flux. We artificially generated flux distributions of central metabolic pathways, including three types of NOG pathways, and obtained 13C labeling patterns of amino acids metabolized from each glucose tracer. Using these data, we then calculated 95% confidence intervals (CIs) for NOG pathway fluxes. Comparing the sum of CI widths from three NOG fluxes showed that estimation with [1,3-13C]-glucose yielded the narrowest CIs. Several tracers, including [2,3-13C]glucose, were capable of determining fluxes with high precision, but [1-13C]glucose was not one of them, despite often being used for estimating glycolytic fluxes. We then experimentally evaluated [2,3-13C]- and [1-13C]glucose as tracers in E. coli strains with and without the expression of phosphoketolase, which is required for NOG pathways to function. The results suggested that [1-13C]glucose could not detect NOG fluxes, whereas [2,3-13C]glucose estimated the fluxes of all three NOG pathways with narrow CIs.

microbiology↗