Virus Evolution

The increasing incidence of H5N1 influenza virus transmission from animal species to humans has heightened concerns about an imminent H5N1 pandemic. Prior studies using recombinant hemagglutinin and neuraminidase proteins have reported age-dependent cross-reactivity to H5N1, attributed to immune imprinting from an individual's first influenza virus exposure. However, whether this pattern holds when using whole inactivated virus (WIV), capturing antibodies against diverse viral proteins, and is stable over time remains unknown. We therefore aimed to determine whether H5N1 cross-reactivity of pre-existing antibodies to whole virus follows an age-dependent or imprinting-specific pattern, and whether this pattern is stable over a five-year period. To this end, we measured serum antibody levels in adolescents, adults and seniors by ELISA using whole inactivated H5N1 virus as antigen rather than purified proteins. Detectable, albeit generally low, levels of H5N1-reactive antibodies were present in most individuals, irrespective of age. Comparison of antibody levels against H5N1 with those to five historical influenza virus strains revealed a consistent positive correlation between H5N1-reactive antibodies and responses to the H1N1pdm09 strain A/California/7/2009 (CA), across all age groups. Using unbiased clustering of antibody titers against H5N1, CA, and the H3N2 strain A/Perth/16/2009 (PE), we identified seven distinct age-transcending antibody profiles. These profiles covered individuals with varying titers to all three included viruses but also identified individuals with high anti-CA levels, yet low anti-H5N1 levels and vice versa. Moreover, despite stable antibody levels over a five-year interval in the study population, individual antibody levels and profiles fluctuated considerably over this period. Taken together, our results confirm the presence of H5N1-reactive antibodies in human sera and their association with previously circulating strains. However, they also caution against inferring antibody levels against a new strain based solely on responses to antigenically related strains and highlight the limitations of extrapolating immune status from single timepoint measurements.

Phage D29 infects Mycobacterium smegmatis mc2 155 and has a non-canonical lysis cassette that encodes two endolysin proteins (Lysin A and Lysin B) and a single two transmembrane domain (TMD) protein, LysA2a similar to F1 cluster phage LysF1a. A 1TMD LysF1b homolog, LysA2b, is encoded by a gene found downstream of the tape measure. Exogenous expression of both LysA2 proteins in tandem is a cytotoxic to M. smegmatis. Deletion of lysA2a produces phages that are lysis competent with a 10-minute triggering delay and 30% plaque size reduction. Deletion of lysA2b results in severe lysis defects manifest by 70% reduced plaque size, delayed lysis timing and reduced burst size. Deletion of both lysA2 genes results in phages that are viable and show lysis phenotypes like the lysF1b deletion. Genetic complementation of lysA2b deleted phage with the lysF1b gene fully complements the lysis phenotypes but alters the triggering time to that of an F1 cluster phage. Energy poisons trigger lysis prematurely in all phages with lysA2 gene deletions. Lysis recovery mutants (LRM) isolated from phages lacking the lysA2b genes generate wild type plaque size and have point mutations that map to TMD1 or the C-terminal region of the lysA2a gene. LRMs isolated from phages lacking both lysA2 genes show premature lysis and have mutations that all map to residue C31 of a novel lipoprotein (gene 64). Deletion of gene 64 does not change wild type D29 lysis phenotypes or rescue the lysis defects of any of the lysA2 mutants. A fitness/competition assay shows that loss of the lysA2 genes imposes a substantial competitive fitness cost. These finding support a lysis regulatory network model where the 2TMD protein is maintained in an inactive state until activated by its cognate 1TMD lysis regulator and the lipoprotein has accessory function that may enhance lysis efficiency.

H5N1 clade 2.3.4.4b avian influenza A viruses pose a significant threat to wild animal populations, domesticated animals, and potentially, the human population. For H5N1s to infect and transmit among mammalian species, mutations for improved utilization of mammalian receptors and enhanced replication at the lower temperatures of the upper respiratory tract need to be acquired. A human H1N1pdm09-like virus was compared to H5N1 genotypes B3.13 and D1.1 for replication at 33{o}C, 37{o}C, and 39{o}C - temperatures consistent with the upper and lower respiratory tract in humans, and dairy cow udder tissue. All H5N1 viruses had increased plaque sizes on MDCK cells at 37{o}C and 39{o}C compared to H1N1pdm09. In primary, differentiated human nasal and bronchial epithelial cultures, all H5N1 viruses show restricted infectious virus production compared to H1N1 at 33{o}C. While H5N1 D1.1 also showed restricted replication at 37{o}C and 39{o}C, the H5N1 B3.13 replicated to nearly equivalent titers as H1N1pdm09. All H5N1 viruses demonstrated similar cell tropism in cells from the upper and lower respiratory tract, infecting more ciliated than non-ciliated cells relative to H1N1pdm09. H1N1, H5N1 B3.13 D1.1 infection induced similar innate immune factors, with nasal epithelial cells producing higher levels compared to bronchial epithelial cells. These data suggest that genotype B3.13 and D1.1 H5N1 viruses show different temperature dependent replication patterns compared to H1N1pdm09.

Motivation: The Interactive Tree of Life (iTOL) is widely used to display and annotate phylogenetic trees, but managing its format-sensitive annotation files impede reproducible high-throughput analyses. Among the maintained Python packages and versions evaluated, none combined template generation, taxonomic monophyly assessment and iTOL batch operations. Results: PyiTOL validates inputs, generates 31 iTOL template schemas (22 accepted by the live batch uploader), performs LCA-based monophyly classification with nested-monophyly detection, sampling-completeness states and polyphyletic subgroup decomposition, plus API upload and session replay. On a topology-constructed benchmark, all calls matched prespecified labels for 4,389 groups; on a 700-genome tree, binary mono/non-mono calls agreed with ETE4 for 409 genera; 17,294 GTDB R232 genera were processed in about 17 s. Availability and Implementation: PyiTOL 1.0.3 (Python [≥]3.10; Linux, macOS and Windows) is MIT-licensed at https://github.com/ZengZichao/PyiTOL and archived with test data at Zenodo (https://doi.org/10.5281/zenodo.22106806).

The 17th Ebola outbreak in the Democratic Republic of the Congo, announced on 15 May 2026, was attributed to Bundibugyo ebolavirus (BDBV). Although case isolation is the main control strategy, its effectiveness is compromised when patients escape isolation facilities before recovery. Between 14 May and 17 June 2026, 175 individuals reportedly left isolation facilities without formal discharge across Ituri Province. We assessed how this "isolation leakage" affects community transmission. We refined the SEIHFR framework to distinguish undetected community infections, detected but not-yet-isolated cases, isolated individuals, leakage, funeral-associated transmission, and removals. Using Bayesian inference, we fitted the model to daily Ituri surveillance data, escapee counts, and isolation census records. We estimated the leakage rate, reporting and detection probabilities, and the transmission rate, while fixing other parameters based on the BDBV literature. The model reproduced confirmed cases, deaths, discharges, and escapees. We estimated R_0=3.67 (95% HDI: 2.0-5.7), a leakage rate of {rho} {approx} 0.034 day^-1 (0.022-0.051), and high contact-tracing-driven detection (p_d {approx} 0.91-0.99). Leakage increased the detection-dependent reproduction number [R](p_d) from approximately 3.2 to above 5. Eliminating leakage reduced cumulative infections by about one-third, from 1,120 to 764, while the minimum detection level required for control increased from p_d [≥] 0.73 without leakage to p_d [≥] 0.87 at the fitted leakage rate. Shortening time to isolation prevented the most infections (73.4%; 59-84), followed by reducing leakage (29.7%; 14-52) and re-isolating escapees (12.6%; 6-24). Delaying leakage reduction until week 4 reduced its benefit from about 27% to below 2%. Isolation leakage represents a major transmission pathway that has until now gone largely unmeasured. While rapid initiation of isolation is highly beneficial, it cannot compensate for permeable isolation; therefore, early, community-driven efforts to control leakage, embedded within a multilayered response, are critical.

Background: Oral dysbiosis has been associated with oral squamous cell carcinoma (OSCC); however, most microbiome studies rely on 16S ribosomal RNA (rRNA) gene sequencing, limiting species-level taxonomic resolution. Methods: Dental plaque, saliva, and tumor tissue samples from 10 patients with OSCC and dental plaque and saliva samples from 10 healthy controls were analyzed in this exploratory cross-sectional study. DNA was extracted and subjected to shotgun metagenomic sequencing using the Illumina MiSeq platform. Sequence reads were quality filtered with fastp, taxonomically classified using Kraken2 v2.1.3, and species-level abundances were re-estimated with Bracken v2.9 following the removal of human reads and low abundance taxa. Relative abundances were compared using the Mann Whitney U test with the Benjamini Hochberg false discovery rate correction, while the Bray Curtis principal coordinate analysis was used as an exploratory approach to visualize microbial community patterns. Results: Shotgun metagenomic sequencing revealed distinct bacterial community profiles across the oral microenvironment. Dental plaque exhibited the highest taxonomic diversity and relative abundance. The control plaque was enriched in Streptococcus koreensis, Capnocytophaga sp. oral taxon 878, Treponema sp. Marseille Q4132, and Leptotrichia sp. oral taxon 498, whereas the plaque from patients with OSCC showed a higher relative abundance of Pyramidobacter piscolens, Parvimonas parva, and Gemella sanguinis. Salivary samples displayed lower diversity and a more homogeneous composition, predominantly comprising Capnocytophaga endodontalis, Prevotella jejuni, Aggregatibacter aphrophilus, and Gemella sanguinis. The tumor tissue showed relatively higher abundance of Sellimonas catena, Escherichia coli, Solobacterium moorei, and Lacrimispora sp. HJ 01. Conclusions: This exploratory study provides species-level characterization of the oral microbiome across multiple oral microenvironments in OSCC and generates hypotheses for future integrative metagenomic and functional studies investigating the potential contribution of oral bacterial communities to OSCC pathogenesis.

Background: Seasonal influenza, commonly known as flu, is an acute respiratory, highly contagious illness caused by influenza viruses. A clear understanding of influenza seasonality is crucial for guiding prevention and treatment strategies, including decisions on vaccination timing to prevent outbreaks. While well documented in temperate regions, data on influenza epidemiology in tropical areas, particularly sub-Saharan Africa, remain limited. We described the types, subtypes and positivity rate of seasonal influenza in Uganda during 2019-2023. Methods: We abstracted data from the National Influenza database on positive seasonal influenza cases confirmed by Polymerase Chain Reaction. The cases were disaggregated by age group, sex, region, month and year of reporting. Using Microsoft excel, we calculated the influenza positivity rate and disaggregated it by strain, sex, age, region and time. Test positivity rate was computed as the number of positive cases as a percentage of the total samples tested. Results: Among 17,957 individuals tested, the overall positivity rate for seasonal influenza was 5% (936 cases). Positivity was higher among males compared to females (7% vs. 4%), with children aged 5-9 years having the highest positivity rate (16%), while individuals aged 50-54 years had the lowest (1%). The median positivity rate was 4%, with a range of 1-16%. Regionally, the central region reported a positivity rate of 5%, with rates across all regions ranging from 5% to 8%. Over time, there was a gradual decline in positivity rates, decreasing from 16.5% in 2019 to 5.3% in 2023. Seasonal influenza exhibited bimodal peaks, with the primary peak occurring between March and May and a secondary peak from October to December. Influenza A was the predominant strain, accounting for 70% of seasonal influenza cases (669/936). Among the Influenza A subtypes, H3N2 was most common, representing 63% of cases (425/669). Conclusions: The declining seasonal influenza positivity rates from 2019 to 2023 and the predominance of Influenza A and H3N2 highlight the need for sustained surveillance in Uganda. Given Influenza A's high genetic variability and potential for novel strain emergence, monitoring circulating strains, informing vaccine development, and implementing targeted interventions for high-risk groups and regions are critical to controlling and preventing outbreaks.

Background The COVID-19 pandemic substantially altered respiratory pathogen circulation worldwide. However, longitudinal analyses of changes in respiratory pathogen ecology across the pandemic and post-pandemic periods remain limited. Methods We analyzed 19,968 respiratory samples tested with the BioFire(R) FilmArray(R) Respiratory Panel at a hospital in Tokyo, Japan, between January 2020 and March 2026. We evaluated temporal changes in pathogen circulation, age-specific epidemiology, co-detection patterns, pairwise pathogen associations, and clinical parameters. Results At least one respiratory pathogen was detected in 27.8% of tests. Respiratory pathogens resurged asynchronously following the relaxation of COVID-19-related public health measures. Influenza virus circulation remained markedly suppressed until late 2022 before re-emerging in successive large seasonal epidemics, whereas other pathogens, including RSV, human metapneumovirus, and Mycoplasma pneumoniae, exhibited distinct resurgence patterns. Pathogen distributions also varied by age. Human rhinovirus/enterovirus remained predominant among young children, whereas SARS-CoV-2 predominated among older adults. Co-detection occurred in 14.0% of positive specimens and was significantly more frequent in younger patients. Pairwise analysis identified both positive and negative pathogen associations; however, the patterns varied across age groups and study periods. Conclusions Respiratory pathogen circulation changed substantially during the transition from the COVID-19 pandemic to the post-pandemic period, with pathogen-specific, age- and period-dependent patterns. Continued surveillance is warranted to determine how respiratory pathogen circulation will evolve and to inform infection control strategies in the post-pandemic era.

Dissecting the complexity of antibody responses in orthopoxvirus (OPXV) infected individuals is essential for elucidating protective mechanisms and identifying candidate protective immunogens. Here, we profiled the acute humoral response in 51 mpox cases, showing distinct IgG trajectories among multiple antigens alongside the rise of plasma neutralizing activities to plateau within 6 weeks after symptom onset. Utilizing a single-cell transcriptomic and BCR sequencing based antigen-agnostic mAb isolation workflow, we further generated monoclonal antibodies (mAbs) from 254 expanded peripheral B cell clones of 3 patients. We discerned 97 specific mAbs recognizing at least 12 different OPXV proteins via integrated screening approaches, which comprised neutralizing antibodies binding unconventional viral targets and antibodies exhibiting extraordinary in vitro and in vivo anti-OPXV effects. The number of OPXV-specific mAbs recovered per donor reflected the percentage of expanded clones among circulating B cells. More interestingly, we demonstrated that the inferred unmutated common ancestors (UCAs) of neutralizing antibody clones did not necessarily react with OPXV, implying that OPXV neutralizing antibodies might frequently originate from B cells previously activated by unknown antigens. Our work establishes an efficient workflow for antigen-agnostic isolation of pathogen specific mAbs and reveals previously unclarified features of antibody responses induced by acute MPXV infection.

Determining the correct donor species/lineages of grass-to-grass lateral gene transfer (LGT) is vital for deducing specific donor features that could help inform the mechanism of transfer. This requires a dataset spanning a broad range of species to achieve the phylogenetic resolution necessary for precise donor inference. As grass-to-grass LGT often involves the transfer of multi-gene DNA fragments, they can contain additional sequences that allow for accurate orthologous comparisons, such as nuclear DNA of plastid origin (NUPTs). Here we systematically scan for NUPTs in the genomes of four Alloteropsis semialata accessions, whose LGTs have previously been characterised. Using the abundant Panicoideae chloroplast sequences, we reconstruct NUPT phylogenies and infer two lateral acquisitions: one from Paniceae/Digitaria and another from Andropogoneae/Eremochloa adjacent to a previously identified LGT. We then assembled and included an additional 12 Eremochloa chloroplast genomes in the analysis and showed the likely donor was Eremochloa attenuata. Subsequent short-read mapping from E. attenuata to the nuclear region flanking this NUPT showed consistent coverage across the region, including the previously identified LGT, supporting co-transfer. Overall this study highlights the potential for NUPTs to better identify the donors of grass-to-grass LGT.

Alzheimer's disease is characterized by the accumulation and aggregation of amyloid-{beta}(A{beta}), but the molecular mechanisms linking environmental and infectious factors to A$\beta$ conformational changes remain incompletely understood. Herpes simplex virus type 1 (HSV-1) has been proposed as a potential contributor to AD pathology, and interactions between the viral glycoprotein B (gB) and A$\beta$ may influence the conformational behaviour of the peptide. Molecular dynamics (MD) simulations provide atomic-scale information on such interactions, but conventional structural descriptors may not fully capture changes in the organization of residue interaction networks. Here, we introduce a graph-geometric framework based on Forman-Ricci curvature to characterize the evolution of residue interaction networks during MD simulations. Each simulation frame is represented as a residue interaction graph based on C--C contacts, and residue-wise curvature profiles are analysed across time. We apply the framework to A{beta}1-42 in isolation and in complex with HSV-1 gB. Conventional MD analyses indicate stable association of the simulated complex, favourable interaction energetics, and conformational changes in A{beta}, including a transition from -helical structure toward {beta}-turn-rich conformations over the simulated timescale. Forman-Ricci curvature reveals pronounced and spatially localized remodelling of the A{beta} residue interaction network in the complex, with the strongest changes concentrated in the C-terminal region. These regions also exhibit reduced temporal curvature fluctuations and progressively distinct geometric behaviour throughout the simulation. Hierarchical clustering further identifies cooperative groups of residues with coordinated curvature dynamics, including a prominent C-terminal domain. Together, these results demonstrate that Forman-Ricci curvature provides a complementary description of biomolecular dynamics by capturing changes in the geometric organization of residue interaction networks that are not directly represented by conventional structural descriptors. The framework provides a general computational approach for studying network-level structural remodelling in protein molecular dynamics and offers a quantitative perspective on the conformational consequences of HSV-1 gB--A{beta} association.

The study of evolution between species (phylogenetics) and the study of evolution within a species (population genetics) are highly related, as the same biological mechanisms are fundamental to both fields. Although both have been studied for a long time, their joint study in a unified setting has been prevented by the different time scales they consider and the different data types they employ. A similar discrepancy holds for their whole-genome specializations, comparative genomics and pangenomics. Two active areas in these fields are genome rearrangement studies and graphical pangenomics, respectively. Since the emergence of graphical pangenomics, these have existed as separate fields, despite observations that central data structures representing genomic variants in both fields are highly similar. While there exists a wealth of theoretical results for various rearrangement models in comparative genomics, the application to pangenomic data is hampered by the limitations of rearrangement problem formulations. On the practical side, pangenomes typically contain too many individual genomes for classical problems, such as the often NP-hard parsimony problems, to be solved, or for all-vs-all comparisons using rearrangement distances to be performed. On the theoretical side, some assumptions in the formulation of rearrangement problems, such as the assumption of an underlying tree, are inadequate for many pangenomes. In this work, we propose the Complete Ancestral Reconstruction for Pangenomes (CARP) problem, which overcomes these limitations while retaining intuitive relationships to both classical rearrangement problems and pangenome graphs.

Background National childhood respiratory pathogen spectra are diversifying nearly everywhere - within-country diversity rose in 203 of 204 countries between 1990 and 2023 - yet whether countries are diversifying toward a common spectrum or along divergent paths is unknown. We quantified between-country compositional distance of national pathogen spectra over the same period. Methods We built national pathogen share vectors from Global Burden of Disease Study 2023 lower respiratory infection etiologic attributions (26 pathogens, 204 countries, ages 0-19 years) at five timepoints spanning 1990-2023. Between-country distance was measured as all pairwise Jensen-Shannon divergences (JSD; primary) and Bray-Curtis dissimilarities, with Baselga and Jaccard decompositions; robustness was assessed across metrics, pathogen panels, low-count thresholds and a balanced panel of 107 countries. Results Mean pairwise JSD rose from 0.0084 in 1990 to 0.0283 in 2023 (+238%; trend p = 0.030), peaking in 2021 (+283%) with a partial 2023 pullback. Bray-Curtis dissimilarity rose +120% and the balanced panel +423%. Divergence was entirely balanced variation (share reallocation), with spectrum richness rising from 18.5 to 21.1 of 26 pathogens. Dispersion rose fastest for influenza (coefficient of variation 0.03 to 0.55) and respiratory syncytial virus (0.08 to 0.48). Within-region distance rose in every computable GBD super-region (five of seven): divergence occurs within regions, not between blocs. Conclusions National spectra are re-sorting along country-specific axes as vaccine-preventable dominance recedes at different speeds. Diversification is universal, but convergence is absent: the transition at the etiologic-spectrum level is asynchronous and path-dependent, with implications for empirical treatment policy and pathogen surveillance.

Mosquito-borne diseases pose a growing public health challenge as climate change reshapes vector population dynamics. West Nile virus (WNV), transmitted between birds and Culex mosquitoes, disproportionately affects Maricopa County, Arizona, one of the nation's highest-burden counties, yet whether models that include weather and avian dynamics improve forecast accuracy remains unclear. Using a 15-year weekly time series of mosquito abundance, mosquito infection prevalence, and human cases, we developed four mechanistic model configurations of varying complexity, from mosquito-human dynamics alone to full models incorporating avian dynamics and weather forcing. We fitted each model to the weekly-observed data, generated probabilistic 1- and 2-week-ahead forecast horizons, and evaluated forecasts against a historical baseline. All configurations fit the data equally regardless of weather or avian dynamics. However, models incorporating both birds and weather created more accurate forecasts of mosquito abundance and mosquito infection prevalence, and all configurations outperformed the baseline for forecasting human cases. Forecast accuracy was highest in summer and fall, and ensemble aggregation sometimes outperformed every individual model, stabilizing predictions across the 15-year record. These findings indicate that avian and weather dynamics are most critical for predicting mosquito-specific data, positioning this framework as a scalable tool for public health planning for WNV surveillance under climate change.

Despite suppressive antiretroviral therapy, many people with HIV (PWH) retain chronic interferon-associated immune dysregulation. Observational data from the Swiss HIV Cohort Study linked asymptomatic mycobacterial exposure to lower viral set points, reduced interferon-associated activity, and attenuated HIV-specific antibody responses, a pattern sharing features with HIV elite controllers and natural hosts of primate lentiviruses. We therefore examined whether Bacillus Calmette-Guerin (BCG) vaccination could induce a related immune configuration in ART-treated PWH. Using longitudinal systems-level profiling within the BELIEVE trial, we found that BCG reduced constitutive NK cell IFN-{gamma} production and PBMC-mediated direct cytotoxicity without impairing inducible cytokine responses or antibody-dependent cellular cytotoxicity. Multiomic and proteomic analyses showed reduced interferon- and activation-associated programs, while adaptive immune parameters remained largely stable and follow-up revealed no obvious adverse clinical pattern. This configuration, reduced baseline interferon activity coexisting with preserved Fc-dependent effector function, shares selected features with immune states described in natural lentiviral control and provides a rationale for testing BCG in combination with antibody-based HIV interventions.

Background: In 2019, WHO recommended three consecutive reactive serological test results for HIV diagnosis to reduce false-positive diagnoses. Malawi changed from a two-test to a three-test strategy in 2022 as HIV test positivity declined. We assessed diagnostic performance, implementation fidelity, and costs. Methods: We analysed national HIV testing data from Nov 1, 2022, to Oct 31, 2025. Using observed three-test classifications as the reference standard, we reconstructed classifications under the two-test strategy. We estimated positive predictive value (PPV), implementation fidelity, potential false-positive diagnoses prevented, incremental costs, and time to offset testing costs through avoided antiretroviral therapy expenditure. Results: Among 9,885,599 encounters eligible for implementation-fidelity analysis, 99.98% followed a valid three-test pathway. The diagnostic-performance analysis included 9,862,908 encounters, of which 171,351 (1.7%) were classified HIV-positive and 9,138 (0.09%) were inconclusive. Under the two-test strategy, 1,209 inconclusive encounters with a T1+/T2+/T3- sequence would have been classified as HIV-positive. Retesting and reference-laboratory data indicated that 82.5% of these would subsequently be classified as HIV-negative, corresponding to 997 false-positive diagnoses prevented (10.3 per 100 000 three-test non-positive encounters; 95% CI 9.7-10.9). Retesting within 1-2 weeks was associated with the highest odds of potential false-positive classification (adjusted OR 39.37, 95% CrI 30.63-50.61). The incremental cost was US$471 per false-positive diagnosis averted and was offset within 7.30 years. Conclusions: Malawi's transition to a three-test HIV testing strategy prevented false-positive diagnoses and unnecessary antiretroviral therapy at modest cost, supporting broader adoption of WHO guidance in similar settings. Funding: Gates Foundation.

Microorganisms across all domains of life engage in molecular conflict, deploying toxins to inhibit competitors or respond to biological threats. Among these, ribonuclease toxins are particularly widespread and diverse. A substantial fraction is associated with the BECR fold, a compact /{beta} architecture that supports RNase activity despite extensive divergence. Although several canonical members are well characterized, many BECR-fold proteins remain difficult to identify because of low sequence similarity, variation in catalytic residues, and structural elaborations that obscure evolutionary relationships. The growing availability of high-confidence protein structure predictions provides an opportunity to reassess this deeply divergent protein landscape. Here, we integrate iterative profile-HMM searches, profile-similarity networks, structural analyses, active-site mapping, and genomic context to examine BECR proteins across the tree of life. Our analysis resolves an expanded BECR-fold landscape comprising canonical BECR and BECR-like superfamilies, refines the organization of canonical BECR proteins and identifies previously unrecognized families. We further validate BECR-Tox2 as a toxin neutralized by a cognate immunity protein and show that its homologs occur in both Menshen-like anti-phage systems and polymorphic toxin loci. Together, these findings expand and clarify the BECR-fold landscape and provide a framework for identifying and interpreting highly divergent proteins of this fold.

Background: Respiratory syncytial virus (RSV) remains a leading cause of hospitalization in infancy, with severe outcomes influenced by both contact patterns and passive immunity. Non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic suppressed RSV circulation and reduced opportunities for maternal immune boosting, potentially altering protection among newborns. We evaluated whether incorporating time-varying maternal immunity improves the ability of an age-structured transmission model to predict post-pandemic RSV hospitalization patterns in infants. Methods: We analyzed population-based RSV hospitalizations among Ontario (Canada) infants (<1 year) from July 2, 2017 to June 25, 2024, using linked administrative databases. A deterministic compartmental model across seven age classes was calibrated against pre-pandemic data using Latin Hypercube Sampling. We compared a model incorporating time-varying contact rates alone against a specification that additionally included time-varying maternal immunity. Results: Both specifications accurately reproduced pre-pandemic seasonality and macro-level post-pandemic resurgence features. The constant maternal immunity model showed slightly better accuracy in capturing the 2021/22 peak compared to the time-varying maternal immunity specification. However, both qualitatively captured the continued near-absence of RSV and the observed peak was captured within the 95% credible intervals. While both models precisely captured the timing and overwhelming surge of admissions that occurred in 2022/23, they failed to capture the premature peak timing and magnitude in 2023/24. Conclusions: Incorporating time-varying maternal immunity did not improve model accuracy post-pandemic. While maternal protection is essential for evaluating infant immunizations, population-level contact shifts primarily shaped post-pandemic RSV seasonality, indicating that models must account for these mechanisms of RSV transmission dynamics.

Genomic signatures can provide key insight into the evolutionary history and remaining adaptive potential of threatened populations. As demographic decline erodes both diversity and the processes maintaining it, understanding how remaining variation is distributed becomes increasingly important for conserving species like the staghorn coral, Acropora cervicornis, a foundational but critically endangered Caribbean reef-builder. We analyzed 46 high-coverage A. cervicornis genomes from 10 locations across the tropical western Atlantic to evaluate neutral and adaptive structure, genomic diversity, demographic history, inbreeding, and connectivity, and generated a regional haplotype reference panel for future genomic monitoring. Genome-wide analyses recovered recurring regional substructure, but differentiation was modest and partly explained by isolation-by-distance and spatial variation in effective migration. Subpopulations had similar levels of genomic diversity, shared demographic history, and limited evidence of local adaptation. These patterns support interpreting sampled Caribbean populations as a single evolutionarily significant unit (ESU) containing multiple regional management units (MUs), rather than as deeply divergent evolutionary lineages. Despite substantial retained variation and low current inbreeding, estimated contemporary effective population size was small, suggesting an increased vulnerability to the effects of drift as demographic collapse continues, especially if structure is reinforced by isolated management. Together, our findings emphasize the urgent need for interventions that preserve and enhance genomic diversity, including risk-managed assisted gene flow. Supported by the haplotype reference panel developed here, these strategies will require coordinated efforts across regional entities to conserve and restore A. cervicornis as a jointly managed, single ESU.

Background Dengue is a major public health challenge, and predictive models are crucial for early warning systems. However, many current modeling practices rely exclusively on climatic factors or employ complex algorithms that lack the interpretability needed for informed public health decision-making. To address these shortcomings, we developed and validated a multidimensional, interpretable statistical model to predict monthly dengue incidence. Methodology/Principal Findings We used a Generalized Linear Mixed Model (GLMM) with a Negative Binomial distribution to analyze 14 years (2010-2023) of spatiotemporal data from 37 municipalities in Huila, Colombia, an endemic region. The model integrates non-linear and lagged effects of climatic, demographic, and socioeconomic factors. The final model underwent rigorous external validation on an independent test set (2021-2023). Our model demonstrated high predictive discrimination (R2 = 0.743, Spearman's {rho} = 0.657), accurately capturing the timing of epidemic outbreaks. Key findings include the identification of an optimal thermal window for transmission at 27-28{degrees}C, a threshold effect for precipitation above 800 mm, and a saturation dynamic in outbreak autocorrelation. Conclusions/Significance This mechanistically-informed statistical approach provides a robust and transparent tool for epidemiological surveillance, successfully balancing high predictive performance with the explanatory power needed for effective, data-driven public health interventions.