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Tetrodotoxin (TTX) is a potent neurotoxin that accumulates in Takifugu rubripes , commonly known as pufferfish, through the ingestion of TTX-bearing organisms as part of their food chain. Although researchers believe that pufferfish use TTX to relieve stress, data are not currently available on how TTX affects the gut microbiota of pufferfish. To address this gap, our study aimed to investigate whether administering TTX to fish could alter their gut microbiota and overall health under various salinity conditions, including 30.0 ppt, 8.5 ppt, and 1.7 ppt salinity, which represent full-strength, isosmotic, and low-salinity stress, respectively. We analyzed the effect of TTX ingestion on the community structure, core microbiome, and metabolic capabilities of the gut microbiome using high-throughput sequencing technologies. The predominant bacterial taxa within the gut microbiome were Firmicutes (21–85%), Campilobacterota (2.8–67%), Spirochaetota (0.5–14%), and Proteobacteria (0.7–9.8%), with Mycoplasma , uncultured Arcobacteraceae , Brevinema , Vibrio , Rubritalea, and uncultured Pirellulaceae as core genera. Our findings indicated that the impact of TTX on high-abundance genera at 30.0 ppt and 8.5 ppt salinity levels was negligible, indicating their stability and resilience to TTX ingestion. However, at 1.7 ppt, TTX-fed fish showed a significant increase in uncultured Arcobacteraceae. Furthermore, our analysis of TTX-fed fish revealed taxonomic alterations in low-abundance taxa, which altered the predicted functions of the gut microbiota at all salinity levels. These results suggest that TTX administration could cause subtle effects on the metabolic functions of gut microbial communities. Overall, our study provides insights into the complex relationship between a TTX-accumulating animal, T. rubripes , and its gut microbiota .

Arcobacter butzleri is a foodborne pathogen associated with gastrointestinal disorders in humans. Its antibiotic resistance is well documented, and in vitro studies have shown its ability to colonise and invade human cell lines. Murine models are essential for integrating host immune responses and gut microbiota dynamics in infection studies. This study aimed to evaluate the pathogenicity and infectivity of A. butzleri strains using a murine model, focusing on invasion mechanisms and impact on intestinal microbiota. Fifteen Mus musculus C57BL/6J mice were orally infected with 8.5 Log CFU/ml of two strains. Faecal samples were collected before infection and over 14 days, while organs were analysed post-mortem. Infection was assessed using culture-dependent and culture-independent methods to study microbiota alterations. Molecular analyses confirmed the presence of A. butzleri in faecal samples until day 4. Beta-diversity analyses revealed significant differences in colonic microbiota between mice infected with the two strains. The duodenal microbiota was dominated by Paramuribaculum , Duncaniella , Dubosiella , and Muribaculum , whereas Akkermansia , Duncaniella , and Paramuribaculum were most prevalent in colonic and faecal samples. A. butzleri persisted under gastrointestinal conditions, a key feature for foodborne pathogens. Alterations in host microbiota were strongly associated with infection, emphasizing the critical role of microbial dynamics in A. butzleri pathogenesis.

Members of the family Arcobacteraceae are distributed widely in aquatic environments, and some of its species have been associated with human and animal illness. However, information about the diversity and distribution of Arcobacteraceae in different water bodies is still limited. In order to better characterize the health risk posed by members in the family Arcobacteraceae, a systematic review and meta-analysis-based method was used to investigate the prevalence of Arcobacteraceae species in aquatic environments based on available data published worldwide. The database search was performed using related keywords and considering studies up to February 2021. The pooled prevalence in aquatic environments was 69.2%, ranging from 0.6 to 99.9%. These bacteria have a wide geographical distribution, being found in diverse aquatic environments with the highest prevalence found in raw sewage and wastewater treatment plants (WWTP), followed by seawater, surface water, ground water, processing water from food processing plants and water for human consumption. Assessing the effectiveness of treatments in WWTP in eliminating this contamination, it was found that the wastewater treatment may not be efficient in the removal of Arcobacteraceae. Among the analyzed Arcobacteraceae species, Al. butzleri was the most frequently found species. These results highlight the high prevalence and distribution of Arcobacteraceae in different aquatic environments, suggesting a risk to human health. Further, it exposes the importance of identifying and managing the sources of contamination and taking preventive actions to reduce the burden of members of the Arcobacteraceae family.

Marine microorganisms exert a profound influence on global carbon cycling and ecological relationships. Mixotrophy, characterized by the simultaneous utilization of both autotrophic and heterotrophic nutrition, has a significant impact on the global carbon cycling. This report characterizes a group of uncultivated bacteria Arcobacteraceae that thrived on the “hot time” of bulky particulate organic matter and exhibited mixotrophic strategy during the in situ organic mineralization. Compared with clades A and B, more unique metabolic pathways were retrieved in clade C, including the reverse tricarboxylic acid pathway for carbon fixation, thiosulfate disproportionation, methane oxidation, and fatty acid oxidation. Global metatranscriptomic data from the Tara Oceans expeditions confirmed the ubiquitous distribution and extensive transcriptional activity of Arcobacteraceae with the expression of genes putatively involved in carbon fixation, methane oxidation, multiple sulfur compound oxidation, and denitrification across all oceanic regions and depths.

Microorganisms encode proteins that function in the transformations of useful and harmful nitrogenous compounds in the global nitrogen cycle. The major transformations in the nitrogen cycle are nitrogen fixation, nitrification, denitrification, anaerobic ammonium oxidation, and ammonification. The focus of this report is the complex biogeochemical process of denitrification, which, in the complete form, consists of a series of four enzyme-catalyzed reduction reactions that transforms nitrate to nitrogen gas. Denitrification is a microbial strain-level ecological trait (characteristic), and denitrification potential (functional performance) can be inferred from trait rules that rely on the presence or absence of genes for denitrifying enzymes in microbial genomes. Despite the global significance of denitrification and associated large-scale genomic and scholarly data sources, there is lack of datasets and interactive computational tools for investigating microbial genomes according to denitrification trait rules. Therefore, our goal is to categorize archaeal and bacterial genomes by denitrification potential based on denitrification traits defined by rules of enzyme involvement in the denitrification reduction steps. We report the integration of datasets on genome, taxonomic lineage, ecosystem, and denitrifying enzymes to provide data investigations context for the denitrification potential of microbial strains. We constructed an ecosystem and taxonomic annotated denitrification potential dataset of 62,624 microbial genomes (866 archaea and 61,758 bacteria) that encode at least one of the twelve denitrifying enzymes in the four-step canonical denitrification pathway. Our four-digit binary-coding scheme categorized the microbial genomes to one of sixteen denitrification traits including complete denitrification traits assigned to 3280 genomes from 260 bacteria genera. The bacterial strains with complete denitrification potential pattern included Arcobacteraceae strains isolated or detected in diverse ecosystems including aquatic, human, plant, and Mollusca (shellfish). The dataset on microbial denitrification potential and associated interactive data investigations tools can serve as research resources for understanding the biochemical, molecular, and physiological aspects of microbial denitrification, among others. The microbial denitrification data resources produced in our research can also be useful for identifying microbial strains for synthetic denitrifying communities.