Microbial Genomics最新文献

Homing, a biological phenomenon involving enzyme-mediated genetic exchange by homologous recombination, has been highlighted as a potential driver of phage genome evolution. In the current study, 18 lactococcal phages, belonging to the Skunavirus genus, were isolated from Dutch dairy facilities, and their genomes were sequenced. Together with 71 phages from previous studies involving Dutch dairy fermentation facilities, a total of 89 Skunavirus genomes were analysed, revealing a strong correlation between phage diversity and the applied starter culture. These analysed Skunavirus genomes were predicted to encode a total of 212 intact HNH endonucleases (HNHEs), which were classified into families based on structural homology and their insertion locations on the genome. Members of the I-HmuI-like HNHE family were observed to be present among most analysed genomes, though they varied in individual Skunavirus phages in both their number and genomic locations. Phylogenetic analysis revealed that these I-HmuI-like HNHEs cluster together according to their insertion locations and the corresponding starter cultures. Furthermore, the so-called genetic marker exclusion activity of particular expressed HNHEs against Skunavirus sk1 infection was observed, indicative of their role in phage genome evolution and associated adaptation processes.

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.

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.

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.

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.

Tuberculosis remains a global health problem. Making it easier and quicker to identify which antibiotics an infection is likely to be susceptible to will be a key part of the solution. Whilst whole-genome sequencing offers many advantages, the processing of the genetic reads to produce the relevant public health and clinical information is, surprisingly, often the responsibility of the end user, which inhibits uptake. Here, we characterize how well a freely available tool we have developed, gnomonicus, predicts the antibiotic resistance profile of a sample (given its variant call file) using our implementation of the second edition of the World Health Organization (WHO) catalogue of resistance-associated variants (WHOv2). To facilitate this, we have constructed a diverse test set of 2,663 publicly available Mycobacterium tuberculosis samples, which have both genetic and drug susceptibility testing (DST) data. We have chosen to apply the catalogue such that our tool will return a result of (i) Fail if there are insufficient reads at a genetic locus associated with resistance, (ii) Unknown if a genetic variant in a resistance gene not listed in the catalogue is encountered and (iii) Resistant if three or more short-reads support the presence of a resistance-associated variant. The last step increases the sensitivity for all 15 antibiotics but only reaches significance in a few in our test set. Comparing our results with those of TB-Profiler, an existing tool, highlights the different design choices and demonstrates that the performance of both tools on our diverse test set is comparable. By only considering high-confidence DST results, we show that gnomonicus, in combination with our translation of WHOv2, achieves sensitivities and specificities in excess of 95% for both isoniazid and rifampicin.

Leishmania (Sauroleishmania) tarentolae and Trypanosoma platydactyli are reptile-associated trypanosomatids transmitted by Sergentomyia minuta sand flies, posing challenges for accurate diagnosis due to the fact that they often occur in sympatry. This study aimed to isolate and characterize new strains of these parasites from reptiles and sand flies using morphological, molecular and genomic approaches. Fifty-five reptiles were captured in Apulia, Italy, and sand flies were collected and dissected under a surveillance framework. Blood samples and gut contents were cultured in Schneider's Drosophila (SC) and Tobie-Evans (TEv) media. Two positive cultures underwent whole-genome sequencing, and a new conventional PCR (cPCR) protocol targeting the β-tubulin gene was developed. T. platydactyli was isolated from 27% of Tarentola mauritanica geckos using SC medium and 12.5% with TE, while L. (S.) tarentolae was isolated from 4.15% of geckos exclusively with SC. Cytology confirmed T. platydactyli in 25% of gecko blood smears. cPCR revealed T. platydactyli in 18.75%, L. (S.) tarentolae in 12.5% and co-infections in 14.6%. No infections were found in Podarcis siculus or Hemidactylus turcicus. Out of 208 S. minuta sand flies tested, 19 (9.1%) were positive for T. platydactyli, 30 (14.4%) for L. (S.) tarentolae, and 15 (7.2%) were co-infected with both. The newly developed cPCR assay robustly differentiated these parasites in both reptile and sand fly samples. Monitoring of natural infections in geckos revealed persistent, low-level L. (S.) tarentolae infections, detectable only by molecular methods, in contrast to the intermittent parasitaemia of T. platydactyli, which was detectable by cytology and culture. Kimura 2-parameter (K2P) divergence profiles indicate no evidence of a recent mobilome in T. platydactyli, whereas L. (S.) tarentolae retains a small but detectable fraction of low-divergence transposable-element copies (≤5-10% K2P; <0.05% of the genome). These findings confirm the sympatric circulation of L. (S.) tarentolae and T. platydactyli in geckos and sand flies in southern Italy, highlighting T. mauritanica as the most common reptilian host. The successful isolation and genome assembly of these trypanosomatids, along with the newly developed molecular tool, lay a solid foundation for future epidemiological and comparative genomic investigations, emphasizing the role of reptilian hosts in maintaining trypanosomatid diversity.