Trends in shigellosis notifications in England, January 2016 to March 2023.

We reviewed all diagnoses of Shigella species notified to the UK Health Security Agency from January 2016 to March 2023. An overall increase in notifications of shigellosis was seen between 2016 (n = 415/quarter) and 2023 (n = 1 029/quarter). However, notifications dramatically declined between March 2020 and September 2021 during the COVID-19 pandemic (n = 208/quarter) highlighting the impact of travel and social distancing restrictions on transmission. S. sonnei diagnoses were more affected by lockdown restrictions than S. flexneri, most likely due to a combination of species-specific characteristics and host attributes. Azithromycin resistance continued to be associated with epidemics of sexually transmissible S. flexneri (adult males = 45.6% vs. adult females = 8.7%) and S. sonnei (adult males = 59.5% vs. adult females = 14.6%). We detected resistance to ciprofloxacin in S. sonnei from adult male cases not reporting travel at a higher frequency (79.4%) than in travel-associated cases (61.7%). Extensively drug-resistant Shigella species associated with sexual transmission among men almost exclusively had ESBL encoded by blaCTX-M-27, whereas those associated with returning travellers had blaCTX-M-15. Given the increasing incidence of infections and AMR, we recommend that enhanced surveillance is used to better understand the impact of travel and sexual transmission on the acquisition and spread of MDR and XDR Shigella species.

Potential applications of microbial genomics in nuclear non-proliferation.

As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as "characteristic communities of microorganisms" found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.

Combined visualization of genomic and epidemiological data for outbreaks.

In epidemiological investigations, pathogen genomics can provide insights and test epidemiological hypotheses that would not have been possible through traditional epidemiology. Tools to synthesize genomic analysis with other types of data are a key requirement of genomic epidemiology. We propose a new 'phylepic' visualization that combines a phylogenomic tree with an epidemic curve. The combination visually links the molecular time represented in the tree to the calendar time in the epidemic curve, a correspondence that is not easily represented by existing tools. Using an example derived from a foodborne bacterial outbreak, we demonstrated that the phylepic chart communicates that what appeared to be a point-source outbreak was in fact composed of cases associated with two genetically distinct clades of bacteria. We provide an R package implementing the chart. We expect that visualizations that place genomic analyses within the epidemiological context will become increasingly important for outbreak investigations and public health surveillance of infectious diseases.

Genomic analysis of Vibrio cholerae O1 isolates from cholera cases, Europe, 2022.

BackgroundThe number of cholera cases reported to the World Health Organization (WHO) in 2022 was more than double that of 2021. Nine countries of the WHO European Region reported 51 cases of cholera in 2022 vs five reported cases in 2021.AimWe aimed to confirm that the Vibrio cholerae O1 isolates reported by WHO European Region countries in 2022 belonged to the seventh pandemic El Tor lineage (7PET). We also studied their virulence, antimicrobial resistance (AMR) determinants and phylogenetic relationships.MethodsWe used microbial genomics to study the 49 V. cholerae O1 isolates recovered from the 51 European cases. We also used > 1,450 publicly available 7PET genomes to provide a global phylogenetic context for these 49 isolates.ResultsAll 46 good-quality genomes obtained belonged to the 7PET lineage. All but two isolates belonged to genomic Wave 3 and were grouped within three sub-lineages, one of which, Pre-AFR15, predominated (34/44). This sub-lineage, corresponding to isolates from several countries in Southern Asia, the Middle East and Eastern or Southern Africa, was probably a major contributor to the global upsurge of cholera cases in 2022. No unusual AMR profiles were inferred from analysis of the AMR gene content of the 46 genomes.ConclusionReference laboratories in high-income countries should use whole genome sequencing to assign V. cholerae O1 isolates formally to the 7PET or non-epidemic lineages. Periodic collaborative genomic studies based on isolates from travellers can provide useful information on the circulating strains and their evolution, particularly as concerns AMR.

NanoMGT: Marker gene typing of low complexity mono-species metagenomic samples using noisy long reads.

Rapid advancements in sequencing technologies have led to significant progress in microbial genomics, yet challenges persist in accurately identifying microbial strain diversity in metagenomic samples, especially when working with noisy long-read data from platforms like Oxford Nanopore Technologies (ONT). In this article, we introduce NanoMGT, a tool designed to enhance marker gene typing in low-complexity mono-species samples, leveraging the unique properties of long reads. NanoMGT excels in its ability to accurately identify mutations amidst high error rates, ensuring the reliable detection of multiple strain-specific marker genes. Our tool implements a novel scoring system that rewards mutations co-occurring across different reads and penalizes densely grouped, likely erroneous variants, thereby achieving a good balance between sensitivity and precision. A comparative evaluation of NanoMGT, using a simulated multi-strain sample of seven bacterial species, demonstrated superior performance relative to existing tools and the advantages of using a threshold-based filtering approach to calling minority variants in ONT's sequencing data. NanoMGT's potential as a post-binning tool in metagenomic pipelines is particularly notable, enabling researchers to more accurately determine specific alleles and understand strain diversity in microbial communities. Our findings have significant implications for clinical diagnostics, environmental microbiology, and the broader field of genomics. The findings offer a reliable and efficient approach to marker gene typing in complex metagenomic samples.

Combining short- and long-read sequencing unveils geographically structured diversity in Borrelia miyamotoi.

Borrelia miyamotoi is an emerging Ixodes tick-borne human pathogen in the Northern hemisphere. The aim of the current study was to compare whole genome sequences of B. miyamotoi isolates from different continents. Using a combination of Illumina and PacBio platforms and a novel genome assembly and plasmid typing pipeline, we reveal that the 21 sequenced B. miyamotoi isolates and publically available B. miyamotoi genomes from North America, Asia, and Europe form genetically distinct populations and cluster according to their geographical origin, where distinct Ixodes species are endemic. We identified 20 linear and 17 circular plasmid types and the presence of specific plasmids for isolates originating from different continents. Linear plasmids lp12, lp23, lp41, and lp72 were core plasmids found in all isolates, with lp41 consistently containing the vmp expression site. Our data provide insights into the genetic basis of vector competence, virulence, and pathogenesis of B. miyamotoi.

Crosstalk between 6-methyladenine and 4-methylcytosine in Geobacter sulfurreducens exposed to extremely low-frequency electromagnetic field.

4-Methylcytosine (4mC) and 6-methyladenine (6mA) are the most prevalent types of DNA modifications in prokaryotes. However, whether there is crosstalk between 4mC and 6mA remain unknown. Here, methylomes and transcriptomes of Geobacter sulfurreducens exposed to different intensities of extremely low frequency electromagnetic fields (ELF-EMF) were investigated. Results showed that the second adenine of all the 5'-GTACAG-3' motif was modified to 6mA (M-6mA). For the other 6mA (O-6mA), the variation in their distance from the neighboring M-6mA increased with the intensity of ELF-EMF. Moreover, cytosine adjacent to O-6mA has a much higher probability of being modified to 4mC than cytosine adjacent to M-6mA, and the closer an unmodified cytosine is to 4mC, the higher the probability that the cytosine will be modified to 4mC. Furthermore, there was no significant correlation between DNA methylation and gene expression regulation. These results suggest a reference signal that goes from M-6mA to O-6mA to 4mC.

Lung microbiota: implications and interactions in chronic pulmonary diseases.

The lungs, as vital organs in the human body, continuously engage in gas exchange with the external environment. The lung microbiota, a critical component in maintaining internal homeostasis, significantly influences the onset and progression of diseases. Beneficial interactions between the host and its microbial community are essential for preserving the host's health, whereas disease development is often linked to dysbiosis or alterations in the microbial community. Evidence has demonstrated that changes in lung microbiota contribute to the development of major chronic lung diseases, including chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), asthma, and lung cancer. However, in-depth mechanistic studies are constrained by the small scale of the lung microbiota and its susceptibility to environmental pollutants and other factors, leaving many questions unanswered. This review examines recent research on the lung microbiota and lung diseases, as well as methodological advancements in studying lung microbiota, summarizing the ways in which lung microbiota impacts lung diseases and introducing research methods for investigating lung microbiota.

Genomic analysis of Staphylococcus aureus isolates from bacteremia reveals genetic features associated with the COVID-19 pandemic.

Genomic analyses of bacterial isolates are effective to compare the prevalence of antibiotic resistance genes and virulence determinants in different contexts. This study provides a comprehensive genomic description of 339 Staphylococcus aureus strains isolated from patients with bacteremia (2014-2022). Nosocomial acquisition accounted for 56.6% of cases, with vascular catheters being the main infection source (31.8%). Fatality (27.4%), persistent bacteremia (19.5%), and septic emboli (24.2%) were documented. During the COVID-19 pandemic, S. aureus bacteremia episodes increased by 140%. Genetic features in pandemic isolates revealed higher prevalence of methicillin (mecA) and macrolide (msrA and mphC) resistance genes. Additionally, genes encoding clumping factors A and B, involved in fibrinogen binding, were more prevalent. This was linked to extensive macrolide use in COVID-19 accessory therapy and elevated fibrinogen levels in SARS-CoV-2 infection. These findings highlight S. aureus adaptation to COVID-19 selective pressures and the value of whole-genome sequencing in molecular epidemiology studies.

From raw milk cheese to the gut: investigating the colonization strategies of Bifidobacterium mongoliense.

The microbial ecology of raw milk cheeses is determined by bacteria originating from milk and milk-producing animals. Recently, it has been shown that members of the Bifidobacterium mongoliense species may become transmitted along the Parmigiano Reggiano cheese production chain and ultimately may colonize the consumer intestine. However, there is a lack of knowledge regarding the molecular mechanisms that mediate the interaction between B. mongoliense and the human gut. Based on 128 raw milk cheeses collected from different Italian regions, we isolated and characterized 10 B. mongoliense strains. Comparative genomics allowed us to unveil the presence of enzymes required for the degradation of sialylated host-glycans in B. mongoliense, corroborating the appreciable growth on de Man-Rogosa-Sharpe (MRS) medium supplemented with 3'-sialyllactose (3'-SL) or 6'-sialyllactose (6'-SL). The B. mongoliense BMONG18 was chosen, due to its superior ability to utilize 3'-SL and mucin as representative strain, to investigate its behavior when co-inoculated with other bifidobacterial species. Conversely, members of other bifidobacterial species did not appear to benefit from the presence of BMONG18, highlighting a competitive scenario for nutrient acquisition. Transcriptomic data of BMONG18 reveal no significant differences in gene expression when cultivated in a gut simulating medium (GSM), regardless of whether cheese was included or not. Furthermore, BMONG18 was shown to exhibit high adhesion capabilities to HT29-MTX human cells, in line with its colonization ability of a human host.IMPORTANCEFermented foods are nourishments produced through controlled microbial growth that play an essential role in worldwide human nutrition. Research interest in fermented foods has increased since the 80s, driven by growing awareness of their potential health benefits beyond mere nutritional content. Bifidobacterium mongoliense, previously identified throughout the production process of Parmigiano Reggiano cheese, was found to be capable of establishing itself in the intestines of its consumers. Our study underscores molecular mechanisms through which this bifidobacterial species, derived from food, interacts with the host and other gut microbiota members.