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At least 19 recordsLinked to original sources
PubMed2026

Strengthening supply chains for pathogen genomic surveillance in Asia.

INTRODUCTION: While pathogen genomics using next-generation sequencing (NGS) has been recommended by the WHO as an essential tool for national communicable disease surveillance programmes, procurement and supply chain management (PSM) systems for this new technology are still evolving. To assess the status of PSM systems for pathogen genomics, we examined perspectives from end-users and manufacturers across South and Southeast Asia. METHODS: Between 2022 and 2023, a cross-sectional survey was conducted among institutional partners supporting pathogen genomics among primarily low- and middle-income countries in South and Southeast Asia. This was complemented by qualitative interviews with the major regional NGS manufacturers. A PSM framework was employed to assess sales, procurement, production, distribution and post-sales support. Analyses are expressed as proportions and means or medians for continuous variables. RESULTS: A total of 42 partners across 13 countries, 3 genomics manufacturers and 22 laboratory personnel contributed data to this assessment. PSM challenges were reported by all countries and for all sequencing platforms. High costs of equipment and consumables were identified by 85% of respondents. Long equipment purchasing lead times and reagent re-supply times were reported by 69% and 77% of countries, respectively, with reagent resupply times averaging 8 weeks (IQR 6.2-9.0). Additional barriers included customs clearance, variability of import procedures, taxes and duties. Manufacturers reported a range of strategies to respond to PSM bottlenecks, including establishing regional hubs, distributor networks and financing schemes. CONCLUSION: Coordinated national and regional efforts are required to improve PSM systems for pathogen genomic sequencing to enhance timely early disease detection and response capacity in South and Southeast Asia.

Humans↗
PubMed2026

Tree Killer, Qu'est-ce Que C'est? Insights From Forest Pathogen Genomes.

Forests are central to planetary health but are increasingly challenged by emerging diseases driven by climate change, global trade, and anthropogenic disturbance. Despite the apparent resilience of long-lived, genetically diverse tree hosts, forest ecosystems have repeatedly experienced landscape-level pathogen-driven transformations. Advances in genomics, transcriptomics, and functional biology have transformed our understanding of how fungal and oomycete pathogens interact with their hosts across a continuum of lifestyles, from saprotrophy and necrotrophy to biotrophy. Here, we synthesize insights from comparative and population genomics and functional studies across diverse forest pathosystems to examine the traits that characterize successful tree pathogens. We highlight how lifestyle plasticity, adaptations to woody tissues, vector-mediated transmission, and biotrophic stealth enable pathogens to colonize perennial hosts and persist over long temporal scales. We further examine how genome plasticity, hybridization, and horizontal gene transfer generate adaptive potential that often outpaces host evolutionary responses under current environmental change. Finally, we discuss emerging genomic tools, including biosurveillance, machine learning-based classification, and genome editing, that are beginning to link genotype to phenotype and inform assessments of disease risk. By integrating genomic, ecological, and evolutionary perspectives, this review outlines general principles governing forest pathogen success and identifies priorities for future research aimed at improving understanding, early detection, and management of forest diseases in a changing world.

Trees↗
PubMed2025

ATAC-seq for Characterizing Host and Pathogen Genome Accessibility During Virus Infection.

Chromatin regulation provides a mechanism through which cells dynamically and rapidly regulate their gene expression profiles, playing a pivotal role in diverse biological processes and disease states. The Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method that enables genome-wide detection of accessible chromatin regions, providing information on nucleosome positioning and the epigenetic regulation of the chromatin structure. ATAC-seq has been used in various biological contexts, and several reports have demonstrated its application to studying infections with viral or bacterial pathogens. The ability to characterize changes in viral or bacterial genome accessibility during infections provides insights into both pathogen replication and host defense mechanisms. Viral genomes undergo dynamic changes in their structural landscape to facilitate replication and evade host immune responses. Additionally, host cells encode DNA sensors, which are specialized proteins that bind to viral genomes to initiate innate immune responses and sometimes, to suppress viral gene expression. ATAC-seq enables the systematic detection of key structural changes on the viral genome mediated by either viral or host proteins, offering mechanistic insights into virus-host interactions. Here, we describe an ATAC-seq method optimized for studying changes in chromatin accessibility in both host and viral genomes. We have previously applied this method to demonstrate a systematic decrease in the genome accessibility of herpes simplex virus type I (HSV-1) enabled by a host antiviral factor, the interferon-gamma inducible protein 16 (IFI16) during infection of human fibroblasts. This protocol can be adapted to various biological contexts involving the introduction of foreign DNA, making it a valuable tool for a broad range of research endeavors.

Humans↗
PubMed2026

Parallel single-cell host immune profiling and pathogen genomic characterization in Klebsiella-associated sepsis: a pilot study.

OBJECTIVES: Sepsis is a life-threatening syndrome characterized by profound immune dysregulation and substantial biological heterogeneity. Here, we conducted a pilot study to explore host immune remodeling in Klebsiella-associated sepsis by combining single-cell RNA sequencing of peripheral blood mononuclear cells with whole-genome sequencing of the corresponding bloodstream isolates. METHODS: In this prospective observational pilot study, we analyzed peripheral blood mononuclear cells (PBMCs) from two patients with Klebsiella-associated sepsis and two healthy controls (HC) using single-cell RNA sequencing. PBMC composition, differential transcriptional responses, and pathway analysis were assessed across immune subsets. The corresponding bloodstream isolates were characterized by phenotypic antimicrobial susceptibility testing and whole-genome sequencing. RESULTS: Compared to HC, septic patients showed expansion of the myeloid compartment and contraction of the NK/T compartment. High-resolution analysis suggested shifts within lymphoid populations. At the transcriptional level, sepsis was associated with compartment-specific enrichment of interferon-related and host-defence pathways, as well as oxidative phosphorylation, ATP synthesis, and mitochondrial electron transport signatures across multiple PBMC subsets. Classical monocytes exhibited a coordinated decrease in MHC class II-related transcripts. The sepsis-associated isolates were identified as Klebsiella pneumoniae and Klebsiella variicola and were notable for overall antimicrobial susceptibility, limited resistomes, and absence of canonical hypervirulence determinants. CONCLUSION: Our data provide a preliminary description of immune remodeling during Klebsiella-associated sepsis and suggest that severe clinical disease may be associated with isolates lacking classical multidrug-resistance or hypervirulence features. These findings should be interpreted as preliminary and hypothesis-generating and require validation in larger cohorts with detailed clinical severity assessment.

Female↗
PubMed2024

A framework for automated scalable designation of viral pathogen lineages from genomic data.

Pathogen lineage nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango dynamic lineage nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were sequenced. This approach is vulnerable to time-critical delays as well as regional and personal bias. Here we developed a simple heuristic approach for dividing phylogenetic trees into lineages, including the prioritization of key mutations or genes. Our implementation is efficient on extremely large phylogenetic trees consisting of millions of sequences and produces similar results to existing manually curated lineage designations when applied to SARS-CoV-2 and other viruses including chikungunya virus, Venezuelan equine encephalitis virus complex and Zika virus. This method offers a simple, automated and consistent approach to pathogen nomenclature that can assist researchers in developing and maintaining phylogeny-based classifications in the face of ever-increasing genomic datasets.

Animals↗
PubMed2025

How does date-rounding affect phylodynamic inference for public health?

Phylodynamic analyses infer epidemiological parameters from pathogen genome sequences for enhanced genomic surveillance in public health. Pathogen genome sequences and their associated sampling dates are the essential data in every analysis. However, sampling dates are usually associated with hospitalisation or testing and can sometimes be used to identify individual patients, posing a threat to patient confidentiality. To lower this risk, sampling dates are often given with reduced date-resolution to the month or year, which can potentially bias inference. Here, we introduce a practical guideline on when date-rounding biases the inference of epidemiologically important parameters across a diverse range of empirical and simulated datasets. We show that the direction of bias varies for different parameters, datasets, and tree priors, while compounding with lower date-resolution and higher substitution rates. We also find that bias decreases for datasets with longer sampling intervals, implying that our guideline is most applicable to emerging datasets. We conclude by discussing future solutions that prioritise patient confidentiality and propose a method for safer sharing of sampling dates that translates them them uniformly by a random number.

Humans↗
PubMed2025

Annotation of RxLR Effectors in Oomycete Genomes.

Pathogens have evolved effector proteins to suppress host immunity and facilitate plant infections. RxLR effectors are small, secreted effector proteins with conserved RxLR and dEER amino acid motifs at the N terminus and highly variable C termini and are commonly found in oomycete species. We provide computational approaches to annotate RxLR candidate effector genes in a genome assembly in FASTA format with an available GFF file. Hidden Markov Modeling (HHM) is used in combination with regular expressions to search for RxLR and EER amino acid patterns.

Oomycetes↗
PubMed2026

Comparative genomics of ESKAPE pathogen species: Integrating pan-genome architecture, antimicrobial resistance, and virulence factor repertoires.

BACKGROUND: ESKAPE pathogens are major causes of hospital-acquired infections and are characterized by extensive antimicrobial resistance (AMR) and diverse virulence mechanisms. Although species-specific pan-genome studies have revealed substantial genomic diversity, the relationships among genome plasticity, resistance burden, and virulence remain incompletely understood across the ESKAPE complex. METHODS: We analyzed 120 high-quality genomes representing six single-species ESKAPE groups (20 genomes per species). Genome quality was assessed using CheckM2. Species-specific pan-genomes were constructed with Roary, AMR genes were identified using AMRFinderPlus, and virulence factors were detected against the VFDB database using DIAMOND. AMR genes were mapped to core and accessory genome compartments through integration of Prokka annotations and Roary outputs. Statistical associations were evaluated using Fisher's exact tests and correlation analyses, with false discovery rate correction applied within each test family. Core-genome maximum-likelihood phylogenies were reconstructed to provide an evolutionary framework. RESULTS: Pan-genome sizes ranged from 4720 to 17,272 genes, with Enterobacter and Pseudomonas possessing the largest accessory genomes. Multidrug resistance (MDR; resistance to ≥3 antimicrobial classes) was detected in 93.3% of strains. After false discovery rate correction, AMR genes remained significantly enriched in the accessory genomes of Enterobacter, Enterococcus, Klebsiella, and Staphylococcus, whereas Acinetobacter and Pseudomonas did not show significant enrichment in either genome compartment. Within-species analyses identified significant positive associations between accessory genome size and AMR class burden in Staphylococcus, Enterococcus, and Enterobacter, whereas the moderate Pearson correlation observed in Pseudomonas was not significant after FDR correction. Virulence factor repertoires varied markedly among species, with Pseudomonas exhibiting the highest burden and Enterococcus the lowest. CONCLUSIONS: ESKAPE pathogens display distinct patterns of resistance and virulence. Accessory genome expansion was associated with higher AMR burden in several species, whereas other species showed no significant association between accessory genome size and AMR burden and no significant enrichment of AMR genes in either genome compartment, highlighting the species-specific nature of AMR evolution.

Virulence Factors↗
PubMed2026

Advancing One Health genomics in Africa: opportunities and challenges for outbreak and antimicrobial resistance control.

SUMMARYAfrica's ongoing struggles with emerging epidemics and antimicrobial resistance (AMR) underscore the urgency of integrating pathogen genomics and surveillance systems into the continent's One Health strategy, particularly given the existing limitations in preparedness and technological resources. This review brings together current evidence on the growth of sequencing infrastructure, the development of regional genomic hubs, and the establishment of governance frameworks, while identifying critical challenges in data integration, bioinformatics capacity, and sustainable financing. Special focus is placed on the lack of African-based genomic data, with our analysis showing that only 1.82% of the global total is available. Case studies illustrate the immense potential and importance of pathogen genomics, giving policymakers a tangible sense of its impact. These examples demonstrate how genomic technologies integrated with artificial intelligence (AI) are transforming outbreak response, AMR surveillance, and stewardship programs by enabling early detection of zoonotic threats, mapping transmission pathways, and guiding vaccine development. However, to fully realize this scientific intel, it is essential to embed One Health pathogen surveillance within strong policy and system frameworks to ensure the translation of technical progress into lasting institutional capacity and sustainable impact. Long-term implementation depends on coordinated investment and advocacy across four interdependent pillars: data architecture, governance and sovereignty, human capital, and technical capacity.

Humans↗
PubMed2025

Bayesian Inference of Pathogen Phylogeography using the Structured Coalescent Model.

Over the past decade, pathogen genome sequencing has become well established as a powerful approach to study infectious disease epidemiology. In particular, when multiple genomes are available from several geographical locations, comparing them is informative about the relative size of the local pathogen populations as well as past migration rates and events between locations. The structured coalescent model has a long history of being used as the underlying process for such phylogeographic analysis. However, the computational cost of using this model does not scale well to the large number of genomes frequently analysed in pathogen genomic epidemiology studies. Several approximations of the structured coalescent model have been proposed, but their effects are difficult to predict. Here we show how the exact structured coalescent model can be used to analyse a precomputed dated phylogeny, in order to perform Bayesian inference on the past migration history, the effective population sizes in each location, and the directed migration rates from any location to another. We describe an efficient reversible jump Markov Chain Monte Carlo scheme which is implemented in a new R package StructCoalescent. We use simulations to demonstrate the scalability and correctness of our method and to compare it with existing software. We also applied our new method to several state-of-the-art datasets on the population structure of real pathogens to showcase the relevance of our method to current data scales and research questions.

Bayes Theorem↗
PubMed2025

Incorporating Epidemiological Data into the Genomic Analysis of Partially Sampled Infectious Disease Outbreaks.

Pathogen genomic data are increasingly being used to investigate transmission dynamics in infectious disease outbreaks. Combining genomic data with epidemiological data should substantially increase our understanding of outbreaks, but this is highly challenging when the outbreak under study is only partially sampled, so that both genomic and epidemiological data are missing for intermediate links in the transmission chains. Here, we present a new dynamic programming algorithm to perform this task efficiently. We implement this methodology into the well-established TransPhylo framework to reconstruct partially sampled outbreaks using a combination of genomic and epidemiological data. We use simulated datasets to show that including epidemiological data can improve the accuracy of the inferred transmission links compared with inference based on genomic data only. This also allows us to estimate parameters specific to the epidemiological data (such as transmission rates between particular groups), which would otherwise not be possible. We then apply these methods to two real-world examples. First, we use genomic data from an outbreak of tuberculosis in Argentina, for which data was also available on the HIV status of sampled individuals, in order to investigate the role of HIV coinfection in the spread of this tuberculosis outbreak. Second, we use genomic and geographical data from the 2003 epidemic of avian influenza H7N7 in the Netherlands to reconstruct its spatial epidemiology. In both cases, we show that incorporating epidemiological data into the genomic analysis allows us to investigate the role of epidemiological properties in the spread of infectious diseases.

Humans↗
PubMed2026

Genomic Medicine Sweden: Advancing precision medicine at the national level.

High-throughput sequencing has transformed clinical diagnostics of rare diseases (RD), cancer and infectious diseases by enabling the identification of disease-causing genetic alterations and facilitating individualised treatment and care. In response to these advances, Genomic Medicine Sweden (GMS) was established in 2017 as a national collaborative effort to accelerate implementation of genomics-based precision medicine within Sweden's regionally organized, publicly funded healthcare system. GMS brings together the seven university healthcare regions and their associated medical faculties, in collaboration with healthcare regions across Sweden, Science for Life Laboratory, patient organizations, industry and governmental agencies. Activities are coordinated through national disease-specific expert groups, supported by cross-cutting functions in bioinformatics, health economics, ethics, education and patient engagement. At the operational level, seven Genomic Medicine Centres, embedded at university hospitals, develop and deliver harmonised genomic diagnostics nationwide. The National Genomics Platform provides secure infrastructure for large-scale data storage, analysis, and national and international data sharing. Following initial project-based funding, GMS now receives long-term governmental support. This review describes the national implementation of genomic-based precision diagnostics, discusses challenges and lessons learnt, and highlights key milestones across disease areas, including whole-genome sequencing in RD and paediatric cancer, comprehensive genomic profiling of haematological malignancies and solid tumours, pathogen genomics in microbiology, pharmacogenomic testing and emerging applications of polygenic risk scores in complex diseases. Collectively, these efforts have contributed to more than 500,000 genomic tests being performed within Swedish healthcare between 2017 and 2025. Finally, we outline future diagnostic needs and priority areas to ensure sustainable, scalable and equitable access to precision medicine.

Precision Medicine↗
PubMed2025

Accounting for contact tracing in epidemiological birth-death models.

Phylodynamics bridges the gap between classical epidemiology and pathogen genome sequence data by estimating epidemiological parameters from time-scaled pathogen phylogenetic trees. The models used in phylodynamics typically assume that the sampling procedure is independent between infected individuals. However, this assumption does not hold for many epidemics, in particular for such sexually transmitted infections as HIV-1, for which contact tracing schemes are included in health policies of many countries. We extended phylodynamic multi-type birth-death (MTBD) models with contact tracing (CT), and developed a simulator to generate trees under MTBD and MTBD-CT models. We proposed a non-parametric test for detecting contact tracing in pathogen phylogenetic trees. Its application to simulated data showed that it is both highly specific and sensitive. For the simplest representative of the MTBD-CT family, the BD-CT(1) model, where only the last contact can be notified, we solved the differential equations and proposed a closed form solution for the likelihood function. We implemented a maximum-likelihood program, which estimates the BD-CT(1) model parameters and their confidence intervals from phylogenetic trees. It performed accurate parameter inference on BD and BD-CT(1) simulated data, and detected contact tracing in HIV-1 B epidemics in Zurich and the UK. Importantly, we showed that not accounting for contact tracing when it is present, leads to bias in parameter estimation with the BD model (overestimation of the becoming-non-infectious rate). This bias is also present, but greatly reduced, when the BD-CT(1) model is used on data where multiple contacts can be notified. Our CT test, MTBD-CT tree simulator and BD-CT(1) parameter estimator are freely available at GitHub (evolbioinfo/treesimulator and evolbioinfo/bdct).

Contact Tracing↗
PubMed2026

Genomic characterization and pathogenicity of ruminant Listeria monocytogenes isolates in a murine oral infection model.

Listeria monocytogenes is a major foodborne pathogen; its ruminant isolates display zoonotic characteristics, causing similar clinical signs in humans, including abortion and encephalitis. However, data on whole genome sequencing and pathogenicity of ruminant L. monocytogenes isolates remain sparse. This study aimed to analyze the genotypic characteristics of L. monocytogenes isolates from ruminants with listeriosis. Furthermore, we assessed the in vivo pathogenicity of four ruminant L. monocytogenes isolates, characterized via whole-genome sequencing-based genetic clustering, in orogastrically inoculated mice. The isolate LM18 (serotype 1/2b, ST224, SL6178) had the lowest lethal dose compared to the other three isolates including previous hypervirulence type (serotype 4b, ST1, SL1) and caused secondary bacteremia in lungs, with sustained bacterial loads in the spleen and liver. Genomic (listeria pathogenicity island -1 and -3) and virulence gene (actA and llsX) mutation analyses associated with virulence suggested from well-recognized studies could not elucidate the virulence of the isolates. SSI-1, which only exists in the isolate LM18 (serotype 1/2b, ST224, SL6178), may help L. monocytogenes survive in the gastrointestinal environment, thereby affecting its virulence. Further research should investigate the role of SSI-1 in the pathogenicity of L. monocytogenes. Moreover, additional studies utilizing larger datasets of ruminant isolates are required to validate our genotypic characterization and to obtain a comprehensive picture of further genotypic differences crucial for L. monocytogenes pathogenicity.

Animals↗
PubMed2025

Adjusting the scope of natural killer cells in cancer therapy.

Natural killer (NK) cells have evolved to detect abnormalities in tissues arising from infection with pathogens, genomic damage, or transformation and respond rapidly to the production of potent proinflammatory and cytolytic mediators. While this acute proinflammatory response is highly efficient at orchestrating sterilizing immunity to pathogens in a matter of days, cellular transformation often avoids the innate detection mechanisms of NK cells. When cellular transformation results in malignancy, tumor cells and/or the tumor microenvironment can evolve additional mechanisms to circumvent NK cell responses, and cancer is now a dominant disease burden worldwide. Here, we review recent advances in our understanding of the combined relationship between malignancies and natural killer (NK) cells, learn from recent clinical efforts in therapeutically targeting natural killer (NK) cells in cancer and outline some emerging therapeutic concepts that aim to improve the innate immune response against cancer.

Humans↗
PubMed2025

Monogenic disorders associated with motor speech phenotypes in children and adolescents undergoing clinical exome sequencing.

PURPOSE: Prior studies investigating the genetic architecture of pediatric motor speech disorders (MSDs) have been limited by small sample sizes and an exclusive focus on apraxia. We aimed to identify pathogenic genomic variants associated with MSDs in a large pediatric population referred for exome sequencing (ES). METHODS: We identified pediatric patients with MSDs who had clinical ES between 2012 and 2022. The rate of pathogenic/likely pathogenic (P/LP) findings considered causative of the MSD phenotype was determined and delineated by sex and neurodevelopmental comorbidity. Gene-based burden testing compared the rate of P/LP variants in each gene in MSD cases with a comparison clinical ES cohort. RESULTS: Positive diagnostic results were detected in 527 of 2004 (26.3%) patients with MSDs, with higher diagnostic rates in females and individuals with neurodevelopmental comorbidities. P/LP sequence variants were detected in 262 genes. Gene-based case-referent burden analysis revealed that 30 genes were nominally associated with MSDs, 2 of which (SETBP1 and ADCY5) survived exome-wide correction. CONCLUSION: Over 25% of patients with MSDs were found to harbor P/LP variants in 262 genes, many of which have not previously been associated with MSDs. Potential clinical implications include early implementation of intensive speech therapy for children diagnosed with monogenic causes of MSDs.

Humans↗
PubMed2026

Global vaccine readiness: equity-by-design in pandemic preparedness and response.

INTRODUCTION: COVID-19 showed that rapid vaccine development and roll-out, while lifesaving, can still yield large, avoidable harms when equity is not considered from the outset. Disparities in vaccine timing and coverage, especially in low-resource settings, amplified health and economic burdens, highlighting the need for preparedness frameworks that combine speed with fairness. AREAS COVERED: We synthesize evidence from literature and policy reports regarding global vaccine roll-out, focusing on avertable mortality under alternative sharing scenarios, procurement design, pooled mechanisms such as COVAX, and the role of distributed manufacturing and delivery capacity. We also examine how transparent data-sharing, effective public communication, genomic surveillance, adaptive trial designs, and modeling hubs can support more responsive and equitable vaccine deployment. Across six reflection points, we translate these lessons into practical priorities for future pandemic readiness, including strengthening healthcare infrastructure, equitable procurement, data transparency, and safeguarding public health decision-making from political and commercial distortion. EXPERT OPINION: We argue that equity-by-design is essential if vaccine innovation is to deliver equitable public health impact. This requires geographically distributed manufacturing, transparency, equity-conditioned advance purchase agreements, and pre-agreed, epidemiology-triggered allocation of vaccines. We recommend institutionalizing disaggregated reporting, standardized data-sharing, greater pathogen genomic sequencing capacity, and communication strategies that support public health protection while countering misinformation.

Humans↗