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Results for “Spatio-Temporal Analysis”

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PubMed2026

Estimating the impact of parvovirus B19 outbreaks on congenital anomalies and fetal outcomes in Wales.

OBJECTIVES: Parvovirus B19 (B19V) is a common infection that can cause complications in pregnancy. Outbreaks of B19V in Europe and the UK were recorded in 2024. We aimed to describe the epidemiology of maternal parvovirus in Wales and to investigate associated fetal outcomes widely and in 2024 specifically. STUDY DESIGN: A retrospective observational study. METHODS: All cases of maternal B19V reported to the Congenital Anomaly Register Information Service (CARIS) were analysed. Maternal risk factors included gestational age at the time of infection and maternal age. Spatio-temporal analysis was performed to look for clusters. Poisson regression was used to model incidence of maternal B19V over time. Fetal outcomes were tested for association with risk factors using linear regression and Fisher's exact test. Outcomes and congenital anomalies were descriptively analysed. RESULTS: Between 1998 and 2025, there were 79 cases of maternal B19V across 81 fetuses, mostly reported in South Wales (74/81, 91.3%). There were 24 (29.6%) cases of at least one confirmed congenital anomaly and 57 (70.3%) cases reporting no anomalies; 53 (93%) of these cases had a positive outcome. Congenital anomalies were associated with worse fetal outcomes. Excluding terminations, the overall fetal survival rate was 88%. No association between maternal risk factors and fetal outcome was identified. There was an increase in cases in 2024 with an increase in fetal losses. CONCLUSIONS: The 2024 European B19V outbreak led to an increase in maternal cases and negative fetal outcomes in Wales.

Humans↗

PubMed2026

Spatiotemporal genomic analysis and risk assessment of the plasmids carrying blaOXA-48-like genes based on a large-scale international dataset.

BACKGROUND: The spread of OXA-48-like carbapenemases represents a major public health challenge. Although previous studies have investigated OXA-48-like carbapenemases risk factors, nosocomial dissemination, and plasmid dynamics, an integrated plasmid-centered framework combining complete plasmid mining, transmission-unit analysis, phylogenetic reconstruction, and machine learning-based risk assessment remains limited. METHODS: We systematically collected 747 complete plasmid sequences carrying blaOXA-48-like genes from the NCBI database, establishing the largest collections of complete plasmid sequences to date. Using an integrative framework of population genomics, phylogenetic dating, and machine learning, this study aimed to characterize the dissemination patterns, plasmid replicon diversity, transmission units, mobile genetic elements, co-resistance profiles, and risk classification of these plasmid. RESULTS: Plasmids carrying blaOXA-48-like genes were detected across 50 countries on six continents, with blaOXA-48 predominating in Europe, blaOXA-181 in South Asia, and blaOXA-232 largely in Asia. IncL and ColKP3/IncX3 replicons, together with Tn1999.2 and other MGEs, were central drivers of plasmid maintenance and spread. Sixteen transmission units were defined, with AA068_Cluster3 estimated to have originated in the Netherlands around 2005 before expanding to Europe, the Middle East, Asia, and North America. Co-resistance analyses revealed frequent modules involving aminoglycoside and quinolone resistance, with qnrS1 and aph(3'')-Ib most prevalent. Notably, high-risk transposon structures were often identified in non-clinical environments, underscoring their cross-ecological transmission potential. Machine learning-based classification models showed good internal performance for predefined composite-risk categories, with plasmid mobility, clinical/non-clinical source composition, and host background contributing to the classification results. CONCLUSIONS: This study provides a large-scale plasmid-centered genomic analysis of publicly available complete plasmid sequences carrying blaOXA-48-like genes, integrating transmission-unit inference, phylogeographic reconstruction, mobile genetic element and co-resistance profiling, and composite genomic risk stratification. This gene-centered framework may support future One Health-oriented antimicrobial resistance surveillance and prioritization of plasmids with higher dissemination and resistance potential.

Plasmids↗

PubMed2026

GenOT: generative optimal transport enables spatiotemporal interpolation and generation in cross-platform spatial transcriptomics.

Spatial transcriptomics technologies have revolutionized the analysis of spatial gene expression, yet integrating spatial information and generating data across heterogeneous samples remain challenging. We present GenOT, a generative framework combining multi-scale graph self-supervised contrastive learning with optimal transport barycenter theory for efficient cross-slice and cross-platform spatiotemporal interpolation. The core innovation of GenOT lies in introducing an optimal transport barycenter-based interpolation algorithm, which mathematically models spatial distribution differences across heterogeneous samples to reconstruct spatiotemporal gene expression dynamics. Extensive evaluations demonstrate that GenOT consistently outperforms existing approaches in spatial domain identification, cross-platform interpolation, and developmental trajectory reconstruction.

Spatial Transcriptomics↗

PubMed2025

Unveiling the Dynamics of SARS-CoV-2 Gamma and Delta Waves in Paraná, Brazil - Delta Displacing a Persistent Gamma Through Alternative Routes of Dispersal.

The Gamma and Delta variants of concern (VOCs) of SARS-CoV-2 drove the second and third wave in Brazil and significantly intensified the number of cases and deaths. In this study, we investigate the timeline and origins of the Gamma and Delta variants using a spatiotemporal analysis based on 1508 genomes collected between March and September 2021 from health administrative regions in Paraná state, Brazil. Our findings indicate that community transmission of Gamma-P.1 began in late 2020, with substantial contributions from the Northeast and North regions. In contrast, our analysis of the Delta-AY.101 genomes underscored the crucial role of Paraná in national-level transmission dynamics beginning in late March 2021. At a local level, the movement estimates inferred from the monophyletic clades showed that the Curitiba health region was the primary source for Gamma-P.1, with a substantial contribution from Londrina. This health-region also emerged as an important hub for Delta-AY.101. Our phylogeographical GLM analysis demonstrates that air travel fluxes and population size at the origin of locations were the strongest predictors of shaping SARS-CoV-2 dispersal dynamics within Paraná. In addition, viral load analysis suggests that Gamma-P.1 and Delta-AY.101 may have maintained a similarly high transmissibility potential throughout the evaluated months, providing insights into the prolonged co-circulation dynamics. Our study underscores the relevance of understanding SARS-CoV-2 introductions and regional circulation contributions at the country level to enhance public health preparedness and strengthen local surveillance programs.

Brazil↗

PubMed2026

Spatiotemporal patterns of Rift Valley fever virus in Africa: a retrospective genomic epidemiology and phylodynamic modelling study.

BACKGROUND: Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic pathogen causing outbreaks in humans and ruminants across Africa and the Arabian Peninsula. Originally restricted to the Great Rift Valley, RVFV has expanded geographically, prompting its classification by WHO as a pathogen of pandemic potential. We investigated the evolutionary and spatial dynamics of RVFV across Africa. METHODS: We used genomic data generated at the International Livestock Research Institute Nairobi genomic laboratory (BioProject PRJNA1106221) and combined with publicly available datasets retrieved from the National Center for Biotechnology (NCBI) GenBank nucleotide database. In retrieving RVFV genome sequences from the NCBI GenBank, we applied the search terms "Rift Valley fever virus segment L AND 6404[SLEN]", "Rift Valley fever virus segment M AND 3885[SLEN]", and "Rift Valley fever virus segment S AND 1520:1690[SLEN]" for L (Large), M (Medium), and S (Small) segments, respectively. For sequences without additional spatiotemporal information, we searched PubMed to extract the associated sequence metadata. We performed molecular clock analysis, phylogenetic inference, phylodynamic modelling (continuous phylogeographic reconstruction), and landscape phylogeography on the three RVFV genome segments (L, M, and S). We aimed to assess evolutionary rates, dispersal patterns, and environmental drivers. Focus was placed on lineage C, the most widely distributed variant. FINDINGS: The global dataset used in this study consisted of large (n=236), medium (n=237), and small (n=247), which were further filtered to exclude potential reassortants and vaccine strains. Genome sequences retrieved from NCBI GenBank database comprised large (n=180), medium (n=184), and small (n=202). The genome sequences from retrospective human and livestock isolates comprised large (n=56), medium (n=53), and small (n=45) collected in Burundi (2018), Kenya (2007, 2018, 2019, 2021, and 2022), and Rwanda (2018 and 2022). Our dataset revealed that RVFV exhibited low overall genetic diversity. Lineage C, however, showed evidence of active evolution, with substitution rates ranging from 3·58 × 10-4 to 9·76 × 10-4 substitutions per site per year. This lineage probably originated in Zimbabwe in the mid-1970s and has since expanded across eastern and southern Africa. Phylogeographic reconstructions revealed rapid spread, with diffusion coefficients exceeding 50 000 km2 per year. INTERPRETATION: Lineage C appears capable of establishing endemic transmission in new regions, with ongoing diversification observed during interepidemic periods. These observations reinforce the value of continuous genomic surveillance, particularly during cryptic transmission phases when adaptive mutations might emerge. Although further evidence is needed, observed trends in climate variability and land-use change point to the potential benefit of targeted surveillance in settings that could be at increased risk, including urban centres and wetlands. FUNDING: This work was supported by the German Federal Ministry for Economic Cooperation and Development, the Rockefeller Foundation, and the Africa Centres for Disease Control and Prevention.

Rift Valley fever virus↗

PubMed2024

Spatiotemporal and genomic analysis of carbapenem resistance elements in Enterobacterales from hospital inpatients and natural water ecosystems of an Irish city.

Carbapenemase-producing Enterobacterales (CPE) is a diverse group of often multidrug-resistant organisms. Surveillance and control of infections are complicated due to the inter-species spread of carbapenemase-encoding genes (CEGs) on mobile genetic elements (MGEs), including plasmids and transposons. Due to wastewater discharges, urban water ecosystems represent a known reservoir of CPE. However, the dynamics of carbapenemase-bearing MGE dissemination between Enterobacterales in humans and environmental waters are poorly understood. We carried out whole-genome sequencing, combining short- and long-sequencing reads to enable complete characterization of CPE isolated from patients, wastewaters, and natural waters between 2018 and 2020 in Galway, Ireland. Isolates were selected based on their carriage of Class A blaKPC-2 (n = 6), Class B blaNDM-5 (n = 12), and Class D blaOXA-48 (n = 21) CEGs. CEGs were plasmid-borne in all but two isolates. OXA-48 dissemination was associated with a 64 kb IncL plasmid (62%), in a broad range of Enterobacterales isolates from both niches. Conversely, blaKPC-2 and blaNDM-5 genes were usually carried on larger and more variable multireplicon IncF plasmids in Klebsiella pneumoniae and Escherichia coli, respectively. In every isolate, each CEG was surrounded by a gene-specific common genetic environment which constituted part, or all, of a transposable element that was present in both plasmids and the bacterial chromosome. Transposons Tn1999 and Tn4401 were associated with blaOXA-48 and blaKPC-2, respectively, while blaNDM-5 was associated with variable IS26 bound composite transposons, usually containing a class 1 integron.IMPORTANCESince 2018, the Irish National Carbapenemase-Producing Enterobacterales (CPE) Reference Laboratory Service at University Hospital Galway has performed whole-genome sequencing on suspected and confirmed CPE from clinical specimens as well as patient and environmental screening isolates. Understanding the dynamics of CPE and carbapenemase-encoding gene encoding mobile genetic element (MGE) flux between human and environmental reservoirs is important for One Health surveillance of these priority organisms. We employed hybrid assembly approaches for improved resolution of CPE genomic surveillance, typing, and plasmid characterization. We analyzed a diverse collection of human (n = 17) and environmental isolates (n = 22) and found common MGE across multiple species and in different ecological niches. The conjugation ability and frequency of a subset of these plasmids were demonstrated to be affected by the presence or absence of necessary conjugation genes and by plasmid size. We characterize several MGE at play in the local dissemination of carbapenemase genes. This may facilitate their future detection in the clinical laboratory.

Humans↗

PubMed2026

Reconstructing the early spatial spread of pandemic respiratory viruses in the United States.

Understanding the geographic spread of emerging respiratory viruses is critical for pandemic preparedness, yet the early spatiotemporal dynamics of the 2009 H1N1 pandemic influenza and severe acute respiratory syndrome coronavirus 2 in the United States remain unclear. While mobility and genomic data have revealed important aspects of pandemic spatial spread, several key questions remain: Did the two pandemics follow similar spatial transmission routes? How rapidly did they spread across the United States? What role did stochastic processes play in early spatial transmission? To address these questions, we integrated high-resolution disease data with a robust, data-efficient inference framework combining air travel, commuting flows, and pathogen superspreading potentials to reconstruct their spatial spread across US metropolitan areas. The two pandemics exhibited distinct transmission pathways across locations; however, both pandemics established local circulation in most metropolitan areas within weeks, driven by several shared transmission hubs. Early spatial spread was more strongly associated with air travel than with commuting, though stochastic dynamics introduced substantial uncertainty in transmission routes, creating challenges for timely detection and control. Simulations indicate that broad wastewater surveillance coverage beyond top transmission hubs coupled with effective infection control may slow initial spatial expansion. Our findings highlight the rapid, stochastic spread of pandemic respiratory pathogens and the difficulties of early outbreak containment.

Humans↗

PubMed2025

Analysis of gene expression within individual cells reveals spatiotemporal patterns underlying Vibrio cholerae biofilm development.

Bacteria commonly exist in multicellular, surface-attached communities called biofilms. Biofilms are central to ecology, medicine, and industry. The Vibrio cholerae pathogen forms biofilms from single founder cells that, via cell division, mature into three-dimensional structures with distinct, yet reproducible, regional architectures. To define mechanisms underlying biofilm developmental transitions, we establish a single-molecule fluorescence in situ hybridization (smFISH) approach that enables accurate quantitation of spatiotemporal gene-expression patterns in biofilms at cell-scale resolution. smFISH analyses of V. cholerae biofilm regulatory and structural genes demonstrate that, as biofilms mature, overall matrix gene expression decreases, and simultaneously, a pattern emerges in which matrix gene expression becomes largely confined to peripheral biofilm cells. Both quorum sensing and c-di-GMP-signaling are required to generate the proper temporal pattern of matrix gene expression. Quorum sensing signaling is uniform across the biofilm, and thus, c-di-GMP-signaling alone sets the regional matrix gene expression pattern. The smFISH strategy provides insight into mechanisms conferring particular fates to individual biofilm cells.

Biofilms↗

PubMed2026

Dynamic metabolic modelling of ATP allocation during viral infection.

Viral pathogens, like SARS-CoV-2, hijack the host's macromolecular production machinery, imposing an energetic burden that is distributed across cellular metabolism. To explore the dynamic metabolic tension between the host's survival and viral replication, we developed a computational framework that uses genome-scale models to perform dynamic flux balance analysis of human cell metabolism during virus infections. Relative to previous models, our framework addresses the physiology of viral infections of non-proliferating host cells through two new features. First, by incorporating the lipid content of SARS-CoV-2 biomass, we discovered activation of previously overlooked pathways giving rise to new predictions of possible drug targets. Furthermore, we introduce a dynamic model that simulates the partitioning of resources between the virus and the host cell, capturing the extent to which the competition depletes the human cells from essential ATP. By incorporating viral dynamics into our COMETS framework for spatio-temporal modelling of metabolism, we provide a mechanistic, dynamic and generalizable starting point for bridging systems biology modelling with viral pathogenesis. This framework could be extended to broadly incorporate phage dynamics in microbial systems and ecosystems.

Humans↗

PubMed2026

Scalable, open-access and multidisciplinary data integration pipeline for climate-sensitive diseases.

Climate-sensitive infectious diseases pose an important challenge for human, animal and environmental health and it has been estimated that over half of known human pathogenic diseases can be aggravated by climate change. While climatic and weather conditions are important drivers of transmission of vector-borne diseases, socio-economic, behavioural, and land-use factors as well as the interactions among them impact transmission dynamics. Analysis of drivers of climate-sensitive diseases require rapid integration of interdisciplinary data to be jointly analysed with epidemiological (including genomic and clinical) data. Current tools for the integration of multiple data sources are often limited to one data type or rely on proprietary data and software. To address this gap, we develop a scalable and open-access pipeline for the integration of multiple spatio-temporal datasets that requires only the declaration of the country and temporal range and resolution of the study. The tool is locally deployable and can easily be integrated into existing climate-disease-modelling applications. We demonstrate the utility of the tool for dengue modelling in Vietnam where epidemiological data are legally required to remain local. We include a pipeline for bias correction of climate data to enhance their quality for downstream modelling tasks. The Dengue Advanced Readiness Tools-Pipeline empowers users by simplifying complex download, correction, and aggregation steps, fostering data-driven discovery of relationships between infectious diseases and their drivers in space and time, and enhancing reproducibility in research. Additional modules and datasets can be added to the existing ones to make the pipeline extendable to use cases other than the ones presented here.

automated workflows↗

PubMed2021

Epigenetically regulated digital signaling defines epithelial innate immunity at the tissue level.

To prevent damage to the host or its commensal microbiota, epithelial tissues must match the intensity of the immune response to the severity of a biological threat. Toll-like receptors allow epithelial cells to identify microbe associated molecular patterns. However, the mechanisms that mitigate biological noise in single cells to ensure quantitatively appropriate responses remain unclear. Here we address this question using single cell and single molecule approaches in mammary epithelial cells and primary organoids. We find that epithelial tissues respond to bacterial microbe associated molecular patterns by activating a subset of cells in an all-or-nothing (i.e. digital) manner. The maximum fraction of responsive cells is regulated by a bimodal epigenetic switch that licenses the TLR2 promoter for transcription across multiple generations. This mechanism confers a flexible memory of inflammatory events as well as unique spatio-temporal control of epithelial tissue-level immune responses. We propose that epigenetic licensing in individual cells allows for long-term, quantitative fine-tuning of population-level responses.

Animals↗