National Center for Epidemiology

Abstract Bacterial communities associated with animals show complex spatial and temporal variation. The main driving forces behind this variation are still to be deciphered. Differences in microbiome composition could be caused by stochastic changes, such as random gain and loss of microbiome components, as well as deterministic factors, such as variation in temperature (or other abiotic factors), diet, or the availability of microbes with the potential to colonize the hosts in the surrounding environment. Here we investigated seasonal variation in the microbiome of Hydra polyps and the bacterioplankton surrounding them to test the hypothesis that the contribution of environmental microorganisms to host‐associated microbial communities varies seasonally. Sampling was performed for two consecutive years in three distinct temperate water bodies in Eastern Hungary: a shallow lake, a deep lake, and a river. We found that the microbiomes of polyps differed from their surrounding environment and varied seasonally. The similarity of polyp and water microbiomes changed seasonally in a population‐specific way: microbial communities associated with polyps became markedly more similar to that of their surrounding environment during the summer in the shallow lake habitat, but not in the other populations. Our results suggest that environmental and host‐associated microbiomes change independently during most of the year, but high temperature increases the impact of environmental microbiome on host‐associated microbial communities.

Sensitive quantification of adeno-associated virus (AAV) neutralizing antibodies (NAbs) is essential for gene therapy success. Conventional cell-based transduction inhibition assays often encounter matrix-induced artifacts resulting from variable serum content across dilutions, which artificially inflate transduction baselines and mask partial neutralization. To address this challenge, we developed the constant serum concentration (CSC) assay, which maintains constant serum levels across dilutions to stabilize assay baselines and enhance NAb detection sensitivity. Using human sera across multiple AAV serotypes, we demonstrated that CSC reclassified up to 21.7% of samples classified as non-neutralizing by a conventional variable serum concentration (VSC) assay format. This improved sensitivity was validated using monoclonal antibody and multi-species serum test benchmarks and enhanced the reliability of seronegative control pool selection. Importantly, CSC detected persistent seropositivity in preclinical seroreversion models up to one year longer than a conventional VSC assay. Since even low-level neutralizing antibodies can significantly impact gene therapy efficacy, these findings have direct implications for optimizing AAV redosing strategies and refining patient stratification. By addressing fundamental limitations in NAb quantification while maintaining procedural simplicity, the CSC assay provides crucial insights into antibody persistence with translational relevance across species and clinical settings.

G protein-coupled receptors (GPCRs) are pivotal in biological processes and represent a significant class of drug targets, with 516 approved drugs acting on 121 GPCRs. Many GPCRs, particularly orphan receptors, remain underexplored, emphasizing the need for innovative investigative tools. Fluorescent ligands provide a powerful means to characterize GPCRs including their functional mechanisms and spatial organization, bridging fundamental research and drug discovery. This review presents recent advances (2018-2024) in fluorescent probe development for Class A GPCRs, analyzing over 120 newly developed probes covering 60 GPCRs. We examine their distribution across receptor subclasses, comparing pre-2018 data with contemporary findings and identifying previously uncharted GPCRs that now have fluorescent ligands. Notably, novel probes have been developed for 12 new receptor subtypes and 6 orphan receptors such as GPR6, GPR52, GPR84, MAS1, MRGPRX2, and MRGPRX4. Advances in GPCR structural biology, driven by cryo-EM and AlphaFold technologies, have significantly enhanced probe development, facilitating the design of selective fluorescent ligands across aminergic, peptidergic, lipid, nucleotide, alicarboxylic, melatonin, protein, and orphan GPCRs. These innovations support a broad range of applications, from single-molecule imaging and in vivo bioimaging to diagnostics and fluorescence-guided surgery. By integrating fluorescence-based approaches with structural and pharmacological insights, this field continues to refine polypharmacology profiling, optimize drug-receptor interactions, and accelerate GPCR-targeted drug discovery.

Abstract Predicting whether single amino acid variants (SAVs) in proteins lead to pathogenic outcomes is a critical challenge in molecular biology and precision medicine. Experimental determination of all possible mutation effects is infeasible, and while state-of-the-art tools such as AlphaMissense show promise, their diagnostic performance is insufficient and they are often difficult to run locally. We developed pLM-SAV, a simple yet effective predictor that leverages protein language models (pLMs). Δ-embeddings, computed as the difference between wild-type and mutant sequence embeddings, are used as input for a convolutional neural network. To prevent data leakage, we trained our model on a well-characterized, labeled set of Eff10k and evaluated it on a non-homologous subset of ClinVar data. Our results demonstrate that this approach performs exceptionally well on the Eff10k test folds and reasonably on ClinVar test sets. Notably, pLM-SAV excels in resolving ambiguous predictions by AlphaMissense. We also found that an ensemble method, REVEL, outperforms both AlphaMissense and pLM-SAV, thus, we integrated these REVEL- enhanced predictions into our widely used AlphaMissense web application. Our results demonstrate that an SAV predictor trained on labeled data can achieve high predictive performance. Unlike previous methods such as VESPA, pLM-SAV uses no handcrafted features or substitution matrices, relying solely on pLM-derived representations. We anticipate that incorporating delta-embeddings into other mutation effect predictors or mutant structure prediction methods will further enhance their accuracy and utility in diverse biological contexts. Availability and Implementation Freely available at https://doi.org/10.5281/zenodo.15502498 and https://alphamissense.hegelab.org.

Abstract Background Non-O1, non-O139 Vibrio cholerae is an uncommon cause of pneumonia, particularly following freshwater exposure. Non-O1, non-O139 Vibrio cholerae was identified from bronchoalveolar lavage through culture and quantitative polymerase chain reaction (qPCR) in Hungary. Epidemiological investigation traced the source of infection in a designated bathing site in a lake in Central Hungary, where non-O1,non-O139 Vibrio cholerae was isolated from surface water. Methods We conducted whole-genome sequencing and comparative genomic analysis on a clinical isolate (N=1) and three phenotypically distinct environmental isolates (N=3). In addition, we reviewed the available literature on pulmonary infections associated with Vibrio cholerae . Results Core genome multilocus sequence typing (cgMLST) revealed that the clinical and environmental isolates clustered together with zero allelic differences. Multilocus sequence typing (MLST) identified a new sequence type (ST1605), representing a novel combination of known allele variants. In silico analysis of antibiotic resistance genes identified the presence of bla CARB-7. Both the clinical and environmental isolates exhibited identical virulence gene profiles, reinforcing the hypothesis that the infection was acquired from the local water source. Conclusions This study represents the first investigation of a primary pulmonary Vibrio cholerae infection in Europe following a near-drowning event. While Vibrio vulnificus and Vibrio metschnikovii have been implicated in similar pneumonia cases, the precise virulence mechanisms of these species remain poorly understood. Although non-O1, non-O139 Vibrio cholerae infections linked to recreational water exposure are rare in Hungary (1-2 cases annually), this study underscores the importance of ongoing surveillance to detect potential outbreaks and inform public health responses.

Abstract Adeno-associated virus (AAV) gene therapy is often limited by pre-existing neutralizing antibodies (NAbs), yet current assays for NAb detection lack standardization and rarely quantify uncertainty, complicating cross-study comparisons. We present coreTIA (core Transduction Inhibition Assay), a modular experimental protocol combined with a statistically robust analysis pipeline that delivers precise, reproducible NAb titers with quantified uncertainty for every result. coreTIA’s statistical framework enables robust estimation of neutralization even when dilution series are incomplete, helping to reduce repeat testing and minimizing sample volume requirements. Evaluation and refinement of key assay parameters support consistent performance across AAV serotypes. By providing a protocol and analysis suite as an open resource, coreTIA facilitates more consistent and transparent NAb measurement, potentially aiding assay harmonization and regulatory assessment, addressing a key barrier to progress in gene therapy research and development.

The degradation of freshwater ecosystems due to land use changes is one of the major driver of global biodiversity loss and amphibian declines with these impacts varying across different spatial scales. Our study aimed to assess how natural and human-modified land affects smooth newt (Lissotriton vulgaris) abundance in the surrounding waterbodies of Lake Balaton, a highly urbanized area. We conducted aquatic trap surveys at 32 wetland sites during the breeding season and quantified land cover within 250, 500, and 1000-m radius buffer zones. We hypothesized that urban land use, cropland, and proximity to roads and railways would negatively correlate with newt abundance, while wetlands areas (marshes, swamps, periodically flooded grasslands) and natural terrestrial habitats (grasslands, forests and woodlands) would positively correlate, with effects varying across spatial scales. N-mixture models were used to analyse survey data, estimating abundance and examining relationships with covariates. Results revealed that wetland cover within a 500-m buffer zone increased newt abundance, probably due to supporting metapopulation connectivity. In contrast, cropland cover within 250 m and proximity to roads and railways negatively affected newt abundance. Conservation efforts should prioritize providing smooth newts with adequate breeding habitats and reducing disturbances from croplands, roads, and railways.

IntroductionWith 1 in every 8 people living with a mental disorder according to the World Health Organization, the need for appropriate identification and treatment of mental health conditions is paramount. As the majority of people with mental health problems seek help and receive their mental health care from primary care providers (PCPs), PCPs assume an important role in the identification of mental illness.ObjectivesThis study examined mental health literacy and predictors of disorder recognition among primary care providers (PCPs) in Hungary.MethodsHungarian PCPs (n = 208) completed a survey assessing demographics, mental health stigma, and exposure to mental health. Participants read six vignettes describing obsessive-compulsive disorder (OCD) harm/aggression subtype (OCD-Aggression), OCD order/symmetry subtype (OCD-Order), generalized anxiety disorder (GAD), social anxiety disorder (SAD), panic disorder (PD), and major depressive disorder (MDD) and were asked to identify each condition and provide treatment referrals. Descriptive analyses were used to characterize disorder recognition rates, perceived disorder causes, and treatment referrals. Binary logistic regression analyses were conducted to examine the degree to which demographic characteristics, mental health stigma, and exposure to mental health predict accurate disorder recognition.ResultsIdentification rates for each vignette were: OCD-Aggression (27.9%), OCD-Order (75.5%), SAD (34.1%), GAD (76.0%), PD (78.8%), and MDD (91.3%). First-choice treatment referrals were a psychiatrist for OCD-Aggression (63%), OCD-Order (53.8%), and MDD (46.6%), a psychologist/therapist for SAD (58.7%) and GAD (48.6%), and a PCP for PD (39.9%). Anxiolytics (e.g., benzodiazepines) were the most commonly recommended medication for the anxiety disorders. Mislabeling conditions was significantly associated with older age (for GAD, OCD-Aggression, PD and MDD), male gender (for GAD), greater mental health stigma (for OCD-Order), and not having a family member/friend with a mental health condition (for SAD).ConclusionsFindings highlight strengths (e.g., depression recognition) and limitations (e.g., OCD-Aggression) in knowledge of mental health conditions among PCPs in Hungary. Our findings add to the literature by outlying potential intervention targets (e.g., increasing education on appropriate anxiolytic use) to improve mental health literacy in primary care. Future research should investigate the efficacy of psychoeducation interventions, particularly for OCD and anxiety disorders, in improving the mental health literacy of PCPs in Hungary.Disclosure of InterestV. Swisher Grant / Research support from: This work was supported in part by U.S. Student Fulbright Association., D. Ori: None Declared, R. Wernigg: None Declared