Microbial Genomics最新文献

Non-tuberculous mycobacteria are emerging respiratory pathogens that can persist in treated water systems. In 2018, a cluster of Mycobacterium intracellulare lung infections was linked to a pool facility in Australia, prompting an epidemiological and genomic investigation. M. intracellulare was isolated from five sputum samples across four clinical cases and from fourteen pool water samples across a total of five collection time points. All cases were resolved following exclusion from the pool facility, with only one patient requiring short-term steroids; none of the patients required anti-mycobacterial treatment. To test if this was a point-source outbreak, whole-genome sequencing of mycobacteria recovered from patients and the pool was implemented. Initial analysis confirmed all patient and water isolates were M. intracellulare with sequence type 210. A complete, circular genome was constructed from one of the isolates linked to this cluster and was used as a reference genome for high-resolution core genome SNP analysis. This analysis showed tight clustering of M. intracellulare genomes from patient and pool water isolates that were distinct from other M. intracellulare. Thus, epidemiological and comparative genome analysis strongly implicated the pool as the origin of these infections.

Deep-sea polymetallic nodules, rich in cobalt, nickel and titanium, are valuable for electronics, aerospace and energy industries. However, the vertical distribution and ecological functions of prokaryotic communities in sediments beneath nodules from the Magellan seamounts, a unique microbial habitat characterized by ultra-slow sedimentation rates (0.4-4 mm ky^-1) and heterogeneous metal gradients, remain poorly characterized. In our research, 16S rRNA gene amplicon sequencing and metagenomic analyses of sediment cores (0-20 cm) from the western Pacific polymetallic nodule province revealed statistically significant decreases in prokaryotic diversity (Shannon index: 9.446 to 2.288; P<0.001). Proteobacteria, Crenarchaeota, Chloroflexi and Bacteroidota were the dominant taxa. The microbial co-occurrence network in the surface layer had a longer mean path length (2.11 vs 1 in the bottom layer) and a larger network diameter (11 vs 1), indicating a loose community structure and greater resistance to disturbance, while the bottom microbial network had a higher density (0.037 vs 0.01) and clustering coefficient (0.32 vs 1), suggesting tight microbial interactions. The concentrations of MnO (6.96-9.41 µg g^-1) and P₂O₅ (2.55-3.89 µg g^-1) gradually decreased with increasing depth. The concentrations of Co and Pb were relatively high in the surface sediments (0-8 cm) but decreased significantly below 8 cm. In contrast, the concentrations of Fe₂O₃ and As increased with depth. The environmental factors depth, MnO, Fe₂O₃ and heavy metals (Cr, Zn and Cu) were found to be the main drivers of the microbial community structure. We assembled 122 metagenome-assembled genomes from the metagenomic data. Gene abundance analysis revealed that sox genes (soxB/C/D/X/Y/Z) and assimilatory sulphate reduction genes (cysC and cysH) were highly abundant in the surface sediment, whereas the abundance of dissimilatory sulphate reduction genes (dsrA and dsrB) was enhanced in the bottom layer, reflecting a hierarchical adaptive strategy for sulphur metabolism. Our study expands current knowledge on the vertical variations of microbial diversity and microbially driven biogeochemical cycling in deep-sea settings underneath polymetallic nodules. Characterizing the microbial community underneath those nodules may provide insights into microbial resilience in extreme oligotrophic environments and valuable insights for future deep-sea mining activities.

In humans, adenoviruses (AdVs) are frequently associated with respiratory illnesses, posing risks to children with developing immune systems and immunocompromised individuals. Outbreaks and epidemics are generally centred in close-contact settings, such as childcare facilities, and transmission occurs through faecal-oral and airborne pathways. AdVs have coevolved across the primate lineage, but very little is known about whether the early-life dynamics in non-human primates mirror those in humans. Here, we leverage longitudinal data collected on a population of geladas (Theropithecus gelada) in the Simien Mountains National Park, Ethiopia, to evaluate AdV dynamics across the gelada lifespan. We identified ten coding-complete AdV genomes representing seven unique simian adenovirus (SAdV) types, four of which are adequately different from the known ones to establish new species. We assessed behavioural and seasonal drivers of SAdV presence and richness across repeated faecal samples from known individuals. Contrary to our expectation that the highest risk would occur after the initiation of play behaviour in infancy (~6 months of age), when peer-to-peer transmission risk is expected to increase, SAdV likelihood was highest in infants under 6 months of age. Risk and richness declined over the lifespan, with very few adults infected, and higher minimum temperatures were weakly but significantly negatively associated with richness. Our results suggest that, unlike in humans, SAdV exposure occurs prior to the initiation of close-contact play behaviours and likely results from the close spatial proximity of conspecifics throughout the dependent period. Like AdVs in humans, SAdVs in geladas maintain low levels in adulthood, with early infections potentially conferring life-long immunity.

Streptococcus pneumoniae (Sp) is an opportunistic pathogen that colonizes the mucosal surfaces of the human upper respiratory tract. While transcriptomic studies of Sp have become more common, most have focused on laboratory-adapted strains such as D39 or TIGR4. These strains, though widely used in research, may not fully capture the biology of clinical isolates, particularly the hypervirulent serotype 1 (S1). S1 is clinically significant due to its association with invasive disease, epidemic outbreaks and a distinct global distribution, particularly in regions with a high pneumococcal disease burden. Unlike many other serotypes, S1 is frequently linked to hypervirulence and a propensity for rapid spread, making it a high-priority target for understanding the molecular mechanisms underpinning pneumococcal pathogenesis. In this study, we conducted a comprehensive in vitro transcriptomic analyses of Sp S1 strains, positioning this work as a valuable resource for the pneumococcal research community. Using a straightforward approach, we cultured three distinct S1 strains - ST306, ST217 and ST615, representing European, African and South American S1 lineages, respectively - in Brain Heart Infusion medium and compared transcriptomic profiles during exponential growth to those of the well-characterized laboratory-adapted D39 strain. Our analysis revealed significant differential expression of 292 genes in all three S1 isolates compared to D39. Among these, 151 genes had higher expression, including those involved in competence pathways and purine metabolism, while 141 genes exhibited lower expression, particularly those linked to lactose metabolism and iron/amino acid transport. These findings underscore the distinct molecular features of S1 strains, which likely contribute to the unique pathogenic properties of this serotype. The identification of the distinct transcriptional signatures of hypervirulent S1 strains paves the way for future efforts to design targeted therapeutics against pneumococcal S1 infections.

Introduction. Cholera, caused by Vibrio cholerae, remains a priority public health concern, particularly in developing countries. The first cholera outbreak in Zambia was documented in the 1970s, with recurring epidemics reported since then. In 2023, a cholera outbreak affected Zambia, particularly in districts bordering Malawi, Mozambique and the Democratic Republic of Congo, with significant cases reported in these neighbouring countries. This study aims to analyse cholera cases and isolates obtained during the 2023 epidemic, focusing on geographical distribution, genetic relatedness of isolates and their antibiotic resistance profiles.Methods. Stool samples were collected from patients presenting with cholera-like symptoms across three provinces of Zambia. A total of 98 samples were cultured on thiosulphate citrate bile salts sucrose agar, resulting in 32 sequenced V. cholerae isolates. Whole-genome sequencing was performed using Oxford Nanopore Technology, and phylogenetic inference was also achieved by the analysis of SNPs. Phenotypic antimicrobial resistance testing was conducted following Clinical and Laboratory Standards Institute guidelines. The genomic data were analysed for virulence factors and antimicrobial resistance profiles.Results. Of the 98 stool samples tested, 38 confirmed cholera cases were identified. A subset of 32 confirmed V. cholerae isolates, predominantly from the Eastern Province of Zambia (n=21), was selected for whole-genome sequencing. Genomic analysis revealed that all isolates belonged to the seventh pandemic El Tor lineage and the O1 serogroup, with two distinct clades identified corresponding to the 10th (T10) and 15th (T15) transmission events. Geographical analysis indicated a predominance of Ogawa serotypes in Eastern Province and Inaba in Northern Province. The virulence gene analysis confirmed the presence of key cholera toxin genes (ctxA and ctxB) and intestinal colonization factors. All isolates carried genes or mutations predicted to confer resistance to multiple antibiotics, including decreased susceptibility to ciprofloxacin, recommended for the treatment of cholera by the World Health Organization.Conclusion. The findings highlight the critical need for enhanced surveillance and targeted interventions to mitigate cholera outbreaks in Zambia. The emergence of resistant V. cholerae strains necessitates innovative strategies, including improved water sanitation, vaccination efforts and novel therapeutic approaches to combat this enduring public health threat.

Understanding the interactions between gut microbiota, bile acid (BA) metabolism and systemic health is critical for supporting gestational physiological stability in sows, especially during the physiologically demanding late gestation period. Although physiological advantages vary by breed in late-gestation sows, the microbiota-related mechanisms underlying these differences remain poorly understood. This study compared serum antioxidant enzyme activity, oxidative damage markers, inflammatory cytokine levels, gut microbiota composition (analysed via 16S rRNA sequencing), and BA profiles (assessed through targeted metabolomics) between purebred large white (LW) and large white×landrace (LW×LR) crossbred sows during late gestation. Results showed that LW×LR crossbred sows exhibited significantly higher serum superoxide dismutase (SOD) activity and IL-10 levels, alongside reduced IL-6 levels (P<0.05), indicating enhanced antioxidant and anti-inflammatory capacity. Gut microbiota analysis revealed greater alpha diversity (Shannon indices) and a lower Simpson index, along with distinct beta diversity (P<0.05) in crossbred sows, with notable enrichment of functional taxa such as Treponema and Prevotella. Additionally, faecal concentrations of modified BAs, specifically 3-oxolithocholic acid and 7-ketolithocholic acid, were significantly elevated, correlating with increased abundance of gut microbiota encoding BA: Na⁺ symporter (BASS family) proteins, as well as the increased 7-α-hydroxysteroid dehydrogenase activity (P<0.05). In contrast, LW sows exhibited enrichment of Terrisporobacter and Clostridium sensu stricto 1, alongside accumulation of primary (e.g. chenodeoxycholic acid) and unconjugated BAs (e.g. deoxycholic acid) (P<0.05). Correlation analysis demonstrated that the accumulation of Terrisporobacter and primary BAs was positively correlated with exacerbation of inflammation. In conclusion, under intensive production conditions, significant differences in the gut microbiota-BA axis between LW and LW×LR crossbred sows may underlie variations in oxidative stress and inflammatory status during late pregnancy. These findings provide valuable insights into microbiome-BA-host associations underlying the physiological advantages (enhanced antioxidant and anti-inflammatory capacity) of crossbred sows.

Ongoing viral evolution is a key driver of global pandemics, such as COVID-19, contributing to the repeated emergence and spread of new variants of concern. Identifying emerging viral variants is crucial for controlling the spread of infection; however, patient testing is not always feasible, and clinical samples are not routinely sequenced. As a result, new approaches, such as environmental-based surveillance, are needed for monitoring genetic diversity. Floor swabs provide greater spatial resolution than other environmental sampling approaches, but pose challenges for genomic analyses due to microbial RNA/DNA yields. We investigate the potential of obtaining whole-genome diversity data from floor swab samples to detect circulating lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Floor swabs (n=23) were collected and sequenced from public locations in Ottawa, Canada, during December 2022, and were compared with contemporaneous human samples. Low biomass recovery remained a challenge, as approximately half of the swabs did not yield sufficient genetic material for analysis. The most commonly identified lineages from the floor swabs were XBB, while B (12.5%) and BA (12.5%) lineages appeared less frequently. In contrast, swab results from humans most often identified BQ (49.3%), BA (23.8%) and BF (17.8%), with XBB detected at a lower prevalence (2.7%). XBB became the dominant lineage in the region in the month following floor swab collection, suggesting that floor swabs may offer early signals of emerging outbreaks in comparison with hospital-based clinical sampling. This may suggest a role for floor swabs in outbreak prediction; however, larger studies are needed to validate this approach.

Objectives. Vibrio cholerae remains a significant public health threat in Africa, with antimicrobial resistance (AMR) complicating treatment. This study leverages whole-genome sequencing (WGS) of V. cholerae isolates from Côte d'Ivoire, Ghana, Zambia and South Africa to assess genomic diversity, AMR profiles and virulence, demonstrating the utility of WGS for enhanced surveillance within the PulseNet Africa network.Methods. We analysed Vibrio isolates from clinical and environmental sources (2010-2024) using Oxford Nanopore sequencing and hybracter assembly. Phylogenetic analysis, MLST, virulence and AMR gene detection were performed using Terra, Pathogenwatch and Cloud Infrastructure for Microbial Bioinformatics platforms, with comparisons against 118 global reference genomes for broader genomic context.Results. Of 79 high-quality assemblies, 67 were confirmed as V. cholerae, with serogroup O1 accounting for the majority (43 out of 67, 67%). ST69 accounted for 60% (40 out of 67) of isolates, with 8 sequence types identified overall. Thirty-seven isolates formed distinct sub-clades within AFR12 and AFR15 O1 lineages, suggesting local clonal expansions. AMR gene analysis revealed genes associated with resistance to trimethoprim in 96% of isolates and genes associated with resistance to quinolones in 83%, while genes associated with resistance to azithromycin, rifampicin and tetracycline remained low (≤7%). A significant proportion of the serogroup O1 isolates (41 out of 43, 95%) harboured resistance genes in at least 3 antibiotic classes.Conclusions. This study highlights significant genetic diversity and AMR prevalence in African V. cholerae isolates, with expanding AFR12 and AFR15 clades in the region. The widespread presence of genes associated with resistance to trimethoprim and quinolones raises concerns for treatment efficacy, although azithromycin and tetracycline remain viable options. WGS enables precise identification of species and genotyping, reinforcing PulseNet Africa's pivotal role in advancing genomic surveillance and enabling timely public health responses to cholera outbreaks.

Shiga toxin-producing Escherichia coli (STEC) O157:H7 is a globally dispersed zoonotic pathogen capable of causing severe disease outcomes, including bloody diarrhoea and haemolytic uraemic syndrome. While variations in Shiga toxin subtype are well-recognized drivers of disease severity, many unexplained differences remain among strains carrying the same toxin profile.We applied explainable machine learning (ML) approaches - Random Forest and Extreme Gradient Boosting - to whole-genome sequencing data from 1,030 STEC O157:H7 isolates to predict patient clinical outcomes, using data collected over 2 years of routine surveillance in England. A phylogeny-informed cross-validation strategy was implemented to account for population structure and avoid data leakage, ensuring robust model generalizability. Extreme Gradient Boosting outperformed Random Forest in predicting minority classes and correctly predicted high-risk isolates in traditionally low-risk lineages, illustrating its utility for capturing complex genomic signatures beyond known virulence genes. Feature importance analyses highlighted phage-encoded elements, including potentially novel intergenic regulators, alongside established virulence factors. Moreover, key genomic regions linked to small RNAs and stress-response pathways were enriched in isolates causing severe disease. These findings underscore the capacity of explainable ML to refine risk assessments, offering a valuable tool for early detection of high-risk STEC O157:H7 and guiding targeted public health interventions.