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bioRxiv2022

MGTdb: A web service and database for studying the global and local genomic epidemiology of bacterial pathogens

Multilevel genome typing (MGT) enables the genomic characterization of bacterial isolates and the relationships among them. The MGT system describes an isolate using multiple multilocus sequence typing (MLST) schemes, referred to as levels. Thus, for a new isolate, sequence types (STs) assigned at multiple precisely defined levels can be used to type isolates at multiple resolutions. The MGT designation for isolates is stable, and assignment is faster than existing approaches. MGTs utility has been demonstrated in multiple species. This paper presents a publicly accessible web service called MGTdb, which enables the assignment of MGT sequence types to isolates, along with their storage, retrieval and analysis. The MGTdb web service enables upload of genome data as sequence reads or alleles, which are processed and assigned MGT identifiers. Additionally, any newly sequenced isolates deposited in NCBI Sequence Read Archive are also regularly retrieved (currently daily), processed, assigned MGT and made publicly available in MGTdb. Interactive visualisation tools are presented to assist analysis, along with capabilities to download publicly available isolates and assignments for use with external software. MGTdb is currently available for Salmonella enterica serovars Typhimurium and Enteritidis, and Vibrio cholerae. We demonstrate the usability of MGTdb through three case studies to study the long-term national surveillance of S. Typhimurium, and the local epidemiology and outbreaks of S. Typhimurium, and the global epidemiology of V. cholerae. Thus, MGTdb enables epidemiological and microbiological investigations at multiple levels of resolution for all publicly available isolates of these pathogens. Database URLhttps://mgtdb.unsw.edu.au

bioinformatics↗

bioRxiv2022

A Re-evaluation of phylogenomic data reveals that current understanding in wheat blast population biology and epidemiology is obfuscated by oversights in population sampling

Wheat blast, caused by the Triticum lineage of Pyricularia oryzae (PoT), is a serious disease that first emerged in Brazil and quickly spread to neighboring countries. The recent appearance of this disease in Bangladesh and Zambia highlights a need to understand the population biology and epidemiology of the disease so as to mitigate pandemic outbreaks. Current knowledge in these areas is largely based on analyses of wheat blast isolates collected in Brazil, and their comparison with isolates from non-wheat, endemic grasses. Those studies concluded that wheat blast is caused by a highly diverse P. oryzae population that lacks host specificity and, as a result, undergoes extensive gene flow with populations infecting non-wheat hosts. Additionally, based on genetic similarity between wheat blast and isolates infecting Urochloa species, it was proposed that the disease originally emerged via a host jump from this grass, and the widespread use of Urochloa as a pasture grass likely plays a central role in wheat blast epidemiology. Inconsistencies with earlier phylogenetic studies prompted us to re-analyze the Brazilian data in the context of a comprehensive, global, phylogenomic dataset. We now show that the seminal studies failed to sample the P. oryzae populations normally found on endemic grasses and, instead, repeatedly sampled PoT and P. oryzae Lolium (PoL) members that happened to be present in these hosts. The resulting lack of accurate and representative information about the grass-infecting populations in Brazil means that current conclusions about wheat blasts evolution, population biology and epidemiology are unsubstantiated and could be equivocal.

microbiology↗

bioRxiv2023

Epidemiological evaluation and identification of the insect vector of soybean stay-green associated virus

In recent years, the emergence of soybean stay-green syndrome (SGS), also referred to as "zhengqing", in the Huang-Huai-Hai region of China has resulted in significant yield losses, with some areas experiencing a complete reduction in seed yield. SGS is a phenomenon characterized by the delayed senescence of soybean, resulting in stay-green leaves, flat pods, and stunted seed development at harvest. Our group was the first to identify a distinct geminivirus, named soybean stay-green associated geminivirus (SoSGV), as the causative agent of SGS by fulfilling Kochs postulate. To further understand the epidemiology of SoSGV, in this study, we collected 368 stay-green samples from 17 regions in 8 provinces including the Huang-Huai-Hai region and surrounding areas of China. The results showed that 228 samples tested positive for SoSGV (61.96%), and 96.93% of these positive samples showed severe pod deflation. Our epidemiological assessment reveals SGS caused by the SoSGV is prevalent in the fields, and it is undergoing geographical expansion and genetic differentiation. Additionally, we determined the other natural hosts grown in the Huang-Huai-Hai region of China. By capturing insects in the field and conducting laboratory vector transmission tests, we confirmed that the common brown leafhopper (Orosius orientalis) is the transmitting vector of SoSGV. With a better understanding of the epidemiology of SoSGV and its transmission, we can develop more effective strategies for managing and mitigating its impact on soybean yields.

microbiology↗

bioRxiv2023

Catching a wave: on the suitability of traveling-wave solutions in epidemiological modeling

Ordinary differential equation models such as the classical SIR model are widely used in epidemiology to study and predict infectious disease dynamics. However, these models typically assume that populations are homogeneously mixed, ignoring possible variations in disease prevalence due to spatial heterogeneity. To address this issue, reaction-diffusion models have been proposed as an alternative approach to modeling spatially continuous populations in which individuals move in a diffusive manner. In this study, we explore the conditions under which such spatial structure must be explicitly considered to accurately predict disease spread, and when the assumption of homogeneous mixing remains adequate. In particular, we derive a critical threshold for the diffusion coefficient below which disease transmission dynamics exhibit spatial heterogeneity. We validate our analytical results with individual-based simulations of disease transmission across a two-dimensional continuous landscape. Using this framework, we further explore how key epidemiological parameters such as the probability of disease establishment, its maximum incidence, and its final epidemic size are affected by incorporating spatial structure into SI, SIS, and SIR models. We discuss the implications of our findings for epidemiological modeling and identify design considerations and limitations for spatial simulation models of disease dynamics.

bioinformatics↗

bioRxiv2023

Old foe, new host: epidemiology, genetic diversity and pathogenic characterization of maize streak virus in rice fields from Burkina Faso.

Rice is of critical significance regarding food security worldwide including in Africa. Only two viruses impacting rice production in Africa have been deeply investigated for decades: the rice yellow mottle virus (Solemoviridae) and the rice stripe necrosis virus (Benyviridae). Using viral metagenomics, we aimed at exploring the diversity of viruses circulating in Burkina Faso rice fields. We performed an epidemiological survey in this country between 2016 and 2019 involving 57 small farmers rice fields under two production systems (rainfed lowlands and irrigated areas). More than 2700 rice samples were collected without a priori (not based on symptom observation) following a regular scheme. In addition, wild and cultivated (maize and sugarcane) Poaceae growing nearby rice fields were also collected. Unexpectedly, metagenomics detected maize streak virus (MSV, Geminiviridae) in analyzed rice samples. Further molecular analyses using RCA-PCR showed that MSV is widely distributed and highly prevalent in both rainfed lowlands and irrigated rice areas. MSV-A and MSV-G strains were identified. MSV-G, exclusively identified so far in wild grasses, was the most prevalent strain while MSV-A, known to cause severe symptoms in maize, was sporadically identified. No genetic differentiation was detected between MSV isolates either infecting wild or cultivated plant species. Using infectious clones in experimental conditions, we confirmed the pathogenicity of both MSV strains on rice. Thus, in addition to contribute to the epidemiological surveillance of rice production in Africa, our results illuminate new epidemiological and pathogenic aspects of one of the most studied plant viruses with significant economic consequences in Africa. FundingFrench National Research Agency < > program (ANR-10-LABX-001-01), Agropolis Fondation (ANR-16-IDEX-006), French National Research Agency "young researchers" program (ANR-20-CE35-0008-01), CGIAR Research Program on Rice Agri-food Systems (RICE), Cooperation and cultural action department of the French Embassy (SCAC) in Burkina Faso.

pathology↗

bioRxiv2024

Genomic epidemiology of Candida auris introduction and outbreaks in the United Kingdom

BackgroundCandida auris is a globally emerging fungal pathogen that causes nosocomial invasive infections, particularly in intensive care units (ICU). Four prominent genetic clades originating from distinct geographic regions have been identified: South Asia (Clade I), East Asia (Clade II), Africa (Clade III) and South America (Clade IV) with each clade presenting differing antifungal resistance profiles. We aimed to elucidate the epidemiology of this infection in the United Kingdom (UK) 2014 - 2019 using genomic approaches. MethodsGenome sequences from 24 isolates from six patients in four London hospitals were combined with genome sequences from 183 additional outbreak isolates from nine UK hospitals. These data were used to assess the numbers and timings of C. auris lineage introductions into the UK and to infer subsequent patterns of inter- and intra-hospital transmission. FindingsWe found evidence for at least three introductions of C. auris into the UK, one from Clade I and one from Clade III. The evolutionary rate of C. auris Clade I and Clade III were estimated at 2.764 x 10-4 and 3.186 x 10-4 substitutions per polymorphic site per year, respectively, with entry into the UK as 2013 and 2016 for Clades I and III respectively. We observed temporal and geographical evidence for multiple transmission events between hospitals and identified local within-hospital patient-to-patient transmission events. InterpretationThese data confirm that C. auris is a newly emerged infection in the UK with at least three original introductions into this country. Our analysis shows that hospital outbreaks are linked and confirms that transmission amongst patients has occurred, explaining local hospital outbreaks. Our findings argue that enhanced surveillance of C. auris infection within the UK is necessary in order to protect healthcare and to curtail expansion of this emerging infection. FundingThis work was supported by a Wellcome Trust Institutional Strategic Support Fund Springboard Fellowship, and by the Medical Research Council (MR/R015600/1), the Natural Environment Research Council (NE/P001165/1) and the Wellcome Trust (219551/Z/19/Z). Research in contextSince its first description in 2009, Candida auris has spread across the globe. For this study, authors considered all publications describing whole genome sequences of isolates within the UK up until 2020 to assess the genomic epidemiology of this fungal pathogen. This study adds value to the current understanding of C. auris epidemiology by undertaking the first analysis to assess transmission between and within hospitals using genomic data. We also provide the first in-depth temporal analysis to estimate likely times of introduction into the UK. These results have clinical implications, encouraging hospitals to identify yeast upon admission and to assess multiple isolates from single patients, which may harbour much diversity in terms of genetics and drug resistance.

genomics↗

bioRxiv2024

Prior exposure to pathogens augments host heterogeneity in susceptibility and has key epidemiological consequences

Pathogen epidemics are key threats to human and wildlife health. Across systems, host protection from pathogens following initial exposure is often incomplete, resulting in recurrent epidemics through partially-immune hosts. Variation in population-level protection has important consequences for epidemic dynamics, but how acquired protection influences inter{-}individual heterogeneity in susceptibility and its epidemiological consequences remains understudied. We experimentally investigated whether prior exposure (none, low-dose, or high{-}dose) to a bacterial pathogen alters host heterogeneity in susceptibility among songbirds. Hosts with no prior pathogen exposure had little variation in protection, but heterogeneity in susceptibility was significantly augmented by prior pathogen exposure, with the highest variability detected in hosts given high-dose prior exposure. An epidemiological model parameterized with experimental data found that heterogeneity in susceptibility from prior exposure more than halved epidemic sizes compared with a homogeneous population with identical mean protection. However, because infection-induced mortality was also greatly reduced in hosts with prior pathogen exposure, reductions in epidemic size were smaller than expected in hosts with prior exposure. These results highlight the importance of variable protection from prior exposure and/or vaccination in driving population-level heterogeneity and epidemiological dynamics.

microbiology↗

bioRxiv2024

Characterising Staphylococcus aureus genomic epidemiology with Multilevel Genome Typing.

Staphylococcus aureus is a major source of both hospital and community acquired infections, and is the leading source of skin and soft tissue infections worldwide. Advances in whole genome sequencing (WGS) technologies have recently generated large volumes of S. aureus WGS data. The timely classification of S. aureus WGS data with genomic typing technologies has the potential to describe detailed genomic epidemiology at large and small scales. In this study, a multilevel genome typing (MGT) scheme comprised of 8 levels of multilocus sequence typing schemes of increasing resolution was developed for S. aureus and used to analyse 50,481 publicly available genomes. Application of MGT to S. aureus epidemiology was showcased in three case studies. Firstly, the population structure of the globally disseminated sequence type ST8 were described by MGT2, which was compared with Spa typing. Secondly, MGT was used to characterise MLST ST8 - PFGE USA300 isolates that colonised multiple body sites of the same patient. Unique STs from multiple MGT levels were able to group isolates of the same patient, and the highest resolution MGT8 separated isolates within a patient that varied in predicted antimicrobial resistance. Lastly, MGT was used to describe the transmission of MLST ST239 - SCCmec III throughout a single hospital. MGT STs were able to describe both isolates that had spread between wards and also isolates that had colonised different reservoirs within a ward. The S. aureus MGT describes large- and small-scale S. aureus genomic epidemiology with scalable resolutions using stable and standardised ST assignments. The S. aureus MGT database is online (https://mgtdb.unsw.edu.au/staphylococcus) and is capable of tracking new and existing clones to facilitate the design of new strategies to reduce the global burden of S. aureus related diseases.

microbiology↗

bioRxiv2024

The Evolution and Epidemiology of H3N2 Canine Influenza Virus After 20 Years in Dogs

The H3N2 canine influenza virus (CIV) emerged from an avian reservoir in Asia around 2004. As the virus has now been circulating entirely among dogs for 20 years, we here update our understanding of the evolution of virus in its new host. As a host-switched virus, H3N2 CIV will also reveal any host-adaptive changes arising during thousands of infections within its new host, and our analysis showed that the virus has evolved at a constant rate. CIV was first introduced into North America in 2015 from Korea, and we specifically examined the epidemiology of the virus among dogs in North America since then, including local outbreaks, regional die-outs, and repeated reintroduction from Asia. The H3N2 CIV now appears endemic only in China after dying out in South Korea around 2017. Virus lineages circulating in China appear to have seeded the most recent US outbreaks - with 2 or 3 introductions into North America during the past 3 years. Combining clinical reports, diagnostic testing data, and analysis of viral genomes we show that the virus spreads rapidly among dogs in kennels and shelters in different regions - likely dying out locally after all those animals become infected and immune. The overall epidemic therefore requires longer-distance dispersal of virus to initiate outbreaks in new locations. Patterns of spread in the USA may select viruses most adapted to those dense populations, which may lack the properties required for efficient long-distance transfers to other dog populations that would keep the virus in prolonged circulation. IMPORTANCEViruses occasionally jump into new hosts to cause epidemics and may spread widely due to movement of humans or animals, or their viruses, with profound consequences for global health. The emergence and epidemiology of new epidemic viruses in companion animals provides a model for understanding disease dynamics and evolution. The H3N2 canine influenza virus arose from an avian virus, and infected dogs provide many opportunities for human exposure. H3N2 CIV transmission is dominated by fast-moving outbreaks within dense populations in animal shelters or kennels, while sustaining the epidemic likely requires movement of virus to more distant dog populations. Viral spread within North Americahas only been sustained for a few years at a time after which the virus dies out. The epidemiological and evolutionary dynamics of this virus in this structured host population shows how an acute respiratory pathogen can emerge and spread in a new host and population.

microbiology↗

bioRxiv2024

Widely dispersed clonal expansion of multi-fungicide-resistant Aspergillus fumigatus limits genomic epidemiology prospects

BackgroundAspergillus fumigatus is a ubiquitous fungus that causes a range of diseases in animals, including humans. The most lethal manifestation is invasive aspergillosis for which treatment relies on triazoles. Triazole-resistant A. fumigatus can be recovered from decaying plant material and so-called hotspots containing triazole fungicide residues. Although observations have shown clonal isolates between the environment and clinical samples, a direct link between a specific environment and cases of triazole-resistant invasive aspergillus disease in an individual patient has not yet been demonstrated. MethodsTo understand where patients acquire A. fumigatus isolates causing disease, we used a genomic epidemiology approach with 157 Dutch A. fumigatus isolates, based on whole genome sequencing. Isolates were from three well-characterized environmental hotspots and two hospitals between 2016 and 2019. FindingsIn the Dutch dataset, A. fumigatus isolates from six patients showed near-identical genomes compared to five environmental isolates. One environmental isolate matched three probable cases of triazole-resistant invasive aspergillosis, including one fatal case. Patient isolates were recovered up to 34 months later than near-identical environmental isolates. Comparison to over 1{middle dot}2K global publicly available A. fumigatus genomes showed hundreds of clonal groups spread across three continents. In addition, finding variants associated with resistance to non-triazole fungicides such as benzimidazole, succinate dehydrogenase inhibitor and quinone outside inhibitor classes, strongly suggests an exposure history to multiple agricultural fungicides in these environmental hotspots. InterpretationEnvironmental hotspots represent highly selective habitats for multi-fungicide-resistant A. fumigatus, which we can now directly link to probable cases of aspergillus disease, including a triazole-resistant case. However, geographically widely dispersed clonal expansion limits the utility of genomic epidemiology to identify the source of a particular patients isolate. Furthermore, reducing a single class of fungicides in agriculture may not effectively reduce resistance selection when other classes are still in use. FundingNWO.Groen2019.002 Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTriazole fungicides that exhibit activity against Aspergillus fumigatus have been shown to be a major source of resistant aspergillus disease in humans. However, the route of transmission from environmental hotspot to human remains poorly understood. Isolates of A. fumigatus can be recovered from both environmental samples and clinical specimens that harbour the same resistance signature haplotypes, e.g., TR34/L98H and TR46/Y121F/T289A, in the cyp51A-gene. We searched the literature for evidence using high resolution whole genome sequencing (WGS) to link environmental isolates to human infection. We searched PubMed for articles using the search terms Aspergillus fumigatus AND azole resistance AND whole genome sequencing on 15 April 2024. This search retrieved 32 articles describing different evolutionary routes to select for triazole-resistant A. fumigatus or population structure of whole-genome sequenced isolates. Twenty-six articles used whole-genome sequencing, but none focused on identifying clonal groups to identify direct cases of transmission between the environment and clinical cases of aspergillus disease. By using the additional search term transmission, no other records were retrieved. Added value of this studyOur study links triazole-resistant A. fumigatus isolates cultured from three environmental hotspots to cases of aspergillus disease in two hospitals in the Netherlands. Genome comparisons of isolates from environmental hotspots and patients showed multiple near-identical linked genotypes, consistent with a route of transmission from the environment to patients. Although a naive expectation may be a higher probability of matches of the hotspots located in the northwest of the Netherlands with the hospital located in the west of the country, in fact, more patient isolates from the far southeast were linked to the hotspots. Integrating the Dutch data set into a global data set showed 205 clonal groups spread across the Netherlands, Germany, the United Kingdom (UK), the United States of America (USA) and Japan. Our demonstration of a large number of geographically dispersed clonal groups suggests that current sampling is insufficient to definitively identify the source of an individual patients infection. A genetically highly diverse population combined with a wide global distribution of clones can make it impossible to definitively identify the source of an individual patients infection even with much more sampling. Implications of all the available evidenceOur study provides evidence that triazole-resistant A. fumigatus isolates with multi-fungicide resistance profiles cause aspergillus disease in at-risk patients and may contribute to treatment failure and mortality. The risk of infection due to these triazole-resistant isolates is not confined to the geographic vicinity of the environmental hotspot since clonal spread can be detected across great distances. The finding of linked cases without clear transmission routes limits epidemiological studies and underscores the need to better understand the ecology and environmental niches of this fungus. As it is highly unlikely that each patient visited the rural agricultural areas where a hotspot was located, research should address the complex and long-distance transmission routes of resistant isolates, which involves airborne dispersal of conidia or habitats of this fungus outside the agricultural environment. Furthermore, because of the multi-fungicide resistance phenotype of the triazole-resistant A. fumigatus, involving several classes of fungicides, reducing one class of fungicides in the environment may not effectively reduce resistance selection. Effective interventions should instead aim to reduce the burden of environmental resistance by modifying environments that currently favour the massive outgrowth of fungicide-resistant A. fumigatus to limit the escape of aerial spores from these environmental hotspots.

microbiology↗

bioRxiv2024

Population genomics and molecular epidemiology of wheat powdery mildew in Europe

Agricultural diseases are a major threat to sustainable food production. Yet, for many pathogens we know exceptionally little about their epidemiological and population dynamics, and this knowledge gap is slowing the development of efficient control strategies. Here we study the population genomics and molecular epidemiology of wheat powdery mildew, a disease caused by the biotrophic fungus Blumeria graminis forma specialis tritici (Bgt). We sampled Bgt for two consecutive years, 2022 and 2023, from 22 countries in Europe and surrounding regions, and compiled a genomic dataset of 415 Bgt isolates. We found one single epidemic unit in the north of Europe, consisting of a highly homogeneous population. Conversely, the south of Europe hosts smaller local populations which are less interconnected. In addition, we show that the population structure can be largely predicted by the prevalent wind patterns. We identified several loci that were under selection in the recent past, including fungicide targets and avirulence genes. Some of these loci are common between populations, while others are not, suggesting different local selective pressures. We reconstructed the evolutionary history of one of these loci, AvrPm17, coding for an effector recognized by the wheat receptor Pm17. We found evidence for a soft sweep on standing genetic variation. Multiple AvrPm17 haplotypes, which can partially escape recognition by Pm17, spread rapidly throughout the continent upon its introduction in the early 2000s. We also identified a new virulent variant, which emerged more recently and can evade Pm17 resistance altogether. Overall, we highlight the potential of genomic surveillance in resolving the evolutionary and epidemiological dynamics of agricultural pathogens, as well as in guiding control strategies.

evolutionary biology↗

bioRxiv2024

Deciphering Memory Patterns in Eco-Epidemiological systems through the lens of BaFOMS: A Bayesian Fractional Order Model Selection Method

The evolution of eco-epidemiological systems is significantly influenced by the memory or previous history of the system. These non-Markovian dynamics are effectively modelled using fractional derivatives (FDs), incorporating memory kernels that reflect long-term or short-term memory characteristics in corresponding nonlinear fractional differential evolution equations. We introduce BaFOMS, a framework for identifying and selecting the optimal FD model for eco-epidemiological processes based on historical data. Specifically, we evaluate a class of fractional logistic growth models defined by their time correlation functions and determine the optimal model through Bayesian inference, selecting the one with the highest posterior probability. We also demonstrated BaFOMS efficiency in parameter estimation and forecasting, producing reliable results with quantified uncertainties. The method is shown to be robust across a range of eco-epidemiological datasets, offering computational efficiency and reliable inference about the evolution dynamics.

ecology↗

bioRxiv2024

Molecular epidemiology of carbapenem-resistant hypervirulent Klebsiella pneumoniae: Risk factors and resistance mechanism of ceftazidime/avibactam in China

The high morbidity and mortality rates associated with carbapenem-resistant hypervirulent Klebsiella pneumoniae have become a global public health problem. We analyzed the whole genome sequence and epidemiological data of 81 carbapenem-resistant Klebsiella pneumoniae strains and conducted sensitivity experiments to explore the optimal concentration of carbapenem-resistant Klebsiella pneumoniae. We verified the resistance and virulence genes of carbapenem-resistant Klebsiella pneumoniae using polymerase chain reaction and compared virulence between carbapenem-resistant hypervirulent Klebsiella pneumoniae a ndcarbapenem-resistant-non-hypervirulent Klebsiella pneumoniae through Galleria mellonella assays.The prevalent types of multilocus sequence typing in our carbapenem-resistant Klebsiella pneumoniae strains were ST11 (69.14%, 56/81). ST11-K64-O1/O2v1 has become an epidemic type in our hospital, with drug-resistance genes dominated by blaKPC-2 (90.12%, 73/81). Ceftazidime/avibactam has better antibacterial effects on carbapenem-resistant Klebsiella pneumoniae, and its resistance is mainly mediated by a resistance plasmid containing the blaKPC-2 gene. 52 carbapenem-resistant hypervirulent Klebsiella pneumoniae strains carry the blaKPC-2, with a high detection rate of siderophore. Further research has shown that the genetic environment of the blaKPC-2 contains TnpR_Tn3 and ISKpn27 upstream and ISKpn6 insertion sequences downstream. Galleria mellonella revealed that the survival rate of carbapenem-resistant hypervirulent Klebsiella pneumoniae was lower than that of carbapenem-resistant-non-hypervirulent Klebsiella pneumoniae, and the survival rate of carbapenem-resistant hypervirulent Klebsiella pneumoniae-K64 was lower than that of carbapenem-resistant hypervirulent Klebsiella pneumoniae-K47.The spread of carbapenem-resistant hypervirulent Klebsiella pneumoniae strains is alarming, necessitating molecular monitoring of hypervirulent strains and strengthening the nosocomial infection prevention and control measures. Antibiotics should be used reasonably based on patients infection status and local epidemiological data. ImportanceCarbapenem-resistant Klebsiella pneumonia is a global public health concern. We conducted a molecular epidemiological analysis of 81 carbapenem-resistant hypervirulent Klebsiella pneumoniae strains from our hospital and explored the resistance mechanism of ceftazidime/avibactam. We identified the blaKPC-2 gene to be primarily responsible for carbapenem resistance in our hospital, and ST11-K64 was the dominant clone. A high-risk clone, ST307-K102, was detected, necessitating strengthened surveillance to prevent its spread. This studys findings contribute to the optimization of antimicrobial management and indicate that genomic research can assist with the tracking of hospital infection outbreaks and the improvement of infection-control measures.

microbiology↗

bioRxiv2025

Enhanced virulence and stress tolerance are signatures of epidemiologically successful Shigella sonnei

Shigellosis is a leading cause of diarrhoeal deaths worldwide, with Shigella sonnei increasingly implicated as a dominant agent. S. sonnei is divided into five monophyletic lineages all sharing a single O-antigen, yet most contemporary infections are caused by just a few clonal sub-lineages within globally dominant Lineage 3 that are quite distinct from the widely used Lineage 2 laboratory strain 53G. Factors underlying the success of these globally dominant lineages remain poorly understood in part due to a lack of complete genome sequences and available animal models. Here, we utilise a novel reference collection of representative Lineage 1, 2 and 3 isolates with complete genome sequences, and find that epidemiologically successful S. sonnei harbour fewer genes encoding putative immunogenic components whilst key virulence-associated regions (such as the type three secretion system and O-antigen) remain highly conserved. Using a zebrafish infection model, we discover that Lineage 3 isolates are most virulent, driven by significantly increased dissemination and a greater neutrophil response. We show that Lineage 3 isolates have increased tolerance to complement-mediated killing and acidic conditions alongside upregulated expression of group four capsule synthesis genes. Consistent with these observations, infection of primary human neutrophils revealed that Lineage 3 isolates are more tolerant of phagosomal killing. Together, our findings link the epidemiological success of S. sonnei to heightened virulence and stress tolerance and highlight zebrafish as a valuable platform to illuminate factors underlying establishment of Shigella epidemiological success.

microbiology↗

bioRxiv2025

Integrating Behavioural Science and Epidemiology to Improve Early Detection of Zoonotic Swine Influenza in the Netherlands

Background and ObjectivesThe Netherlands faces zoonotic disease risks due to its dense human and livestock populations. The 2009 H1N1 outbreak highlighted the pandemic potential of influenza virus reassortment. Effective preparedness requires integrating behavioural and epidemiological models. Human behaviour, shaped by personal, social, and institutional factors, is critical in detecting, intervening, and treating diseases. Using the Theory of Planned Behaviour (TPB), a framework was developed integrating knowledge from the TPB to improve early detection and response, using (zoonotic) swine influenza as a case study. Material and MethodsWithin the framework we defined the desired outcome: timely detection and notification of symptomatic (and hypothetical zoonotic) swine influenza to prevent its spread. Actions, such as symptom recognition and disease reporting, were linked to key drivers extracted from the TPB and disease transmission modelling. Expert elicitation estimated the likelihood of action for different farmer profiles, while disease transmission modelling assessed farm-to-farm spread probabilities. Simulations integrated these probabilities to evaluate intervention effectiveness across different scenarios. ResultsThe framework successfully combined behavioural science and epidemiology, offering nuanced estimates of intervention effectiveness. For early detection, 95% of farmers were estimated to notify their veterinarian within 13 days post-infection. Key factors influencing action included symptom recognition and disease spread extent. The farmer profiles influenced response likelihood, while human infections linked to outbreaks had minimal impact. Farm density and assumptions about transmission probabilities significantly affected the likelihood of spread before notification. Discussion and ConclusionThe framework provides a systematic approach for integrating social and epidemiological insights to support evidence-based policies. The work can be further enhanced by complementing expert judgement with more extensive stakeholder surveys, randomized scenario presentations, and immersive methods. This pragmatic tool aids policymakers in designing targeted interventions for zoonotic disease preparedness.

systems biology↗

bioRxiv2025

Genomic and epidemiologic characteristics of SARS-CoV-2 persistent infections in California, January 2021 - July 2023

Novel SARS-CoV-2 variants demonstrating considerable intra-host evolution emerged throughout the pandemic. The persistent infections thought to give rise to these variants, however, have been difficult to identify at scale. This study sought to detect and characterize persistent infection cases in California using routine epidemiologic and genomic surveillance data. We identified 69 persistent infection cases with collection dates between January 2021 and July 2023 ranging from 21 to 400 days in duration, with an average of 44 days. Significant differences were identified in age distribution, sex, hospitalizations, and deaths between persistent infection cases and all sequenced California SARS-CoV-2 cases. Underlying health conditions were identified for the majority of cases with available medical records. The mutations found in these cases were suggestive of positive selection in the Spike receptor binding domain and convergent evolution toward immune evasion and residues observed in previous persistent infections. We describe a 400-day B.1.429 infection that demonstrates substantial intra-host evolution, and a BA.5.11 persistent infection revealing apparent competition between two intra-host viral subpopulations. By establishing a framework for detecting persistent infections, this study lays the groundwork for other public health organizations to monitor and investigate highly divergent SARS-CoV-2 viruses. Author SummaryGenomic surveillance has been used to monitor the evolution and spread of SARS-CoV-2 variants throughout the pandemic. When a new variant emerges, it is often due to the accumulation of mutations during a persistent infection, i.e. in an individual who was unable to clear the virus after an infection. Using genomic and epidemiologic surveillance data, we identify 69 of these persistent infections in California and provide demographic and clinical characteristics of these infections compared to the broader population of SARS-CoV-2 infections. The identification of risk factors for persistent infections provides important insight into the epidemiology of SARS-CoV-2, while the identification of shared mutations between these infections enhances our understanding of SARS-CoV-2 evolution that may result in new variants. Ultimately, our work may help public health labs to better monitor persistent infections in the future, prior to the potential emergence and spread of novel variants into the community.

genomics↗

bioRxiv2018

Epidemiologal investigation of an Acinetobacter baumannii outbreak using Core Genome Multilocus Sequence Typing

Carbapenem-resistant (CR) Acinetobacter baumannii is a serious nosocomial pathogen able to cause a variety of serious, often life-threatening infections and outbreaks. We aimed to investigate the molecular epidemiology of clinical isolates of CR-A. baumannii from an outbreak occurred in the intensive care unit (ICU) of our hospital.\n\nFrom January to April 2017, 13 CR-A. baumannii isolates were collected at the \"L. Spallanzani\" hospital, Rome, Italy; typing was performed by repetitive extragenetic palindromic-based (rep)- PCR-based DiversiLab system and WGS data were used for in silico analysis of traditional MLST types, for identifying resistance genes and for core genome multi locus sequence typing (cgMLST) analysis. Epidemiological data were obtained from hospital records.\n\nStrains were cultured from 7 patients treated in the ICU of our hospital; all isolates showed a multi-drug resistant (MDR) profile, carrying the blaOXA-23 carbapenemase. Typing performed by rep-PCR and MLST showed that the isolates clustered into one group while the cgMLST approach, which uses 2690 gene targets to characterize the gene-by-gene allelic profile of A. baumannii, highlighted the presence of two cluster types. These results allowed us to identify two patients who entered the ICU already colonized by two different strains of CR-A. baumannii; we hypothesize that these two patients could be the source of two separate transmission chains.\n\nOur results show that whole-genome-DNA sequencing by cgMLST is a valuable tool, better suited for prompt epidemiological investigations than traditional typing methods because of its higher discriminatory ability in determining clonal relatedness.

molecular biology↗

bioRxiv2019

The ecological and epidemiological consequences of reproductive interference between the vectors Aedes aegypti and Aedes albopictus

Vector ecology is integral to understanding the transmission of vector-borne diseases, with processes such as reproduction and competition pivotal in determining vector presence and abundance. The arbovirus vectors Aedes aegypti and Aedes albopictus compete as larvae, but this mechanism is insufficient to explain patterns of coexistence and exclusion. Inviable interspecies matings - known as reproductive interference - is another candidate mechanism. Here, we analyse mathematical models of mosquito population dynamics and epidemiology which include two Aedes-specific features of reproductive interference. First, as these mosquitoes use hosts to find mates, reproductive interference will only occur if the same host is visited. Host choice will, in turn, be determined by functional responses to host availability. Second, females can become sterilised after mis-mating with heterospecifics. We find that a species with an affinity for a shared host will suffer more from reproductive interference than a less selective competitor. Costs from reproductive interference can be \"traded-off\" against costs from larval competition, leading to competitive outcomes difficult to predict from empirical evidence. Sterilisations of a self-limiting species can counter-intuitively lead to higher densities than a competitor suffering less sterilisation. We identify that functional responses and reproductive interference mediate a concomitant relationship between vector ecological dynamics and epidemiology. Competitors with opposite functional responses can maintain disease where human hosts are rare, due to vector coexistence facilitated by a reduced cost from reproductive interference. Our work elucidates the relative roles of the competitive mechanisms governing Aedes populations and the associated epidemiological consequences.

ecology↗