Unraveling the epidemiology of Mycobacterium bovis using whole-genome sequencing combined with environmental and demographic data.

When studying the dynamics of a pathogen in a host population, one crucial question is whether it transitioned from an epidemic (i.e., the pathogen population and the number of infected hosts are increasing) to an endemic stable state (i.e., the pathogen population reached an equilibrium). For slow-growing and slow-evolving clonal pathogens such as Mycobacterium bovis, the causative agent of bovine (or animal) and zoonotic tuberculosis, it can be challenging to discriminate between these two states. This is a result of the combination of suboptimal detection tests so that the actual extent of the pathogen prevalence is often unknown, as well as of the low genetic diversity, which can hide the temporal signal provided by the accumulation of mutations in the bacterial DNA. In recent years, the increased availability, efficiency, and reliability of genomic reading techniques, such as whole-genome sequencing (WGS), have significantly increased the amount of information we can use to study infectious diseases, and therefore, it has improved the precision of epidemiological inferences for pathogens such as M. bovis. In this study, we use WGS to gain insights into the epidemiology of M. bovis in Cameroon, a developing country where the pathogen has been reported for decades. A total of 91 high-quality sequences were obtained from tissue samples collected in four abattoirs, 64 of which were with complete metadata. We combined these with environmental, demographic, ecological, and cattle movement data to generate inferences using phylodynamic models. Our findings suggest M. bovis in Cameroon is slowly expanding its epidemiological range over time; therefore, endemic stability is unlikely. This suggests that animal movement plays an important role in transmission. The simultaneous prevalence of M. bovis in co-located cattle and humans highlights the risk of such transmission being zoonotic. Therefore, using genomic tools as part of surveillance would vastly improve our understanding of disease ecology and control strategies.

SCoVMod - a spatially explicit mobility and deprivation adjusted model of first wave COVID-19 transmission dynamics.

Background: Mobility restrictions prevent the spread of infections to disease-free areas, and early in the coronavirus disease 2019 (COVID-19) pandemic, most countries imposed severe restrictions on mobility as soon as it was clear that containment of local outbreaks was insufficient to control spread. These restrictions have adverse impacts on the economy and other aspects of human health, and it is important to quantify their impact for evaluating their future value. Methods: Here we develop Scotland Coronavirus transmission Model (SCoVMod), a model for COVID-19 in Scotland, which presents unusual challenges because of its diverse geography and population conditions. Our fitted model captures spatio-temporal patterns of mortality in the first phase of the epidemic to a fine geographical scale. Results: We find that lockdown restrictions reduced transmission rates down to an estimated 12\% of its pre-lockdown rate. We show that, while the timing of COVID-19 restrictions influences the role of the transmission rate on the number of COVID-related deaths, early reduction in long distance movements does not. However, poor health associated with deprivation has a considerable association with mortality; the Council Area (CA) with the greatest health-related deprivation was found to have a mortality rate 2.45 times greater than the CA with the lowest health-related deprivation considering all deaths occurring outside of carehomes. Conclusions: We find that in even an early epidemic with poor case ascertainment, a useful spatially explicit model can be fit with meaningful parameters based on the spatio-temporal distribution of death counts. Our simple approach is useful to strategically examine trade-offs between travel related restrictions and physical distancing, and the effect of deprivation-related factors on outcomes.

A Cross-Sectional, Population-Based, Seroepidemiological Study of Rift Valley Fever in Cameroonian Cattle Populations.

Rift Valley fever (RVF) is an important emerging zoonoses causing abortion and neonatal deaths in livestock and hemorrhagic fever in humans. It is typically characterized by acute epidemics with abortion storms often preceding human disease and these events have been associated with the El Niño weather cycles. Outside of areas that experience epidemics, little is known about its epidemiology. Here, we present results from a serological study using biobank samples from a study of cattle conducted in 2013 at two sites in Cameroon. A total of 1,458 cattle from 100 herds were bled and sera screened using a commercially available RVF ELISA. The overall design-adjusted animal-level apparent seroprevalence of RVF exposure for the Northwest Region (NWR) of Cameroon was 6.5% (95% CI: 3.9-11.0) and for the Vina Division (VIN) of the Adamawa Region was 8.2% (95% CI: 6.2-11.0). The age-stratified serological results were also used to estimate the force of infection, and the age-independent estimates were 0.029 for the VIN and 0.024 for the NWR. The effective reproductive number was ~1.08. Increasing age and contact with wild antelope species were associated with an increased risk of seropositivity, while high altitudes and contact with buffalo were associated with a reduced risk of seropositivity. The serological patterns are more consistent with an endemical stability rather than the more typical epidemic patterns seen in East Africa. However, there is little surveillance in livestock for abortion storms or in humans with fevers in Cameroon, and it is, therefore, difficult to interpret these observations. There is an urgent need for an integrated One Health approach to understand the levels of human- and livestock-related clinical and asymptomatic disease and whether there is a need to implement interventions such as vaccination.

Site Specific Relationships between COVID-19 Cases and SARS-CoV-2 Viral Load in Wastewater Treatment Plant Influent.

Wastewater based epidemiology (WBE) has become an important tool during the COVID-19 pandemic, however the relationship between SARS-CoV-2 RNA in wastewater treatment plant influent (WWTP) and cases in the community is not well-defined. We report here the development of a national WBE program across 28 WWTPs serving 50% of the population of Scotland, including large conurbations, as well as low-density rural and remote island communities. For each WWTP catchment area, we quantified spatial and temporal relationships between SARS-CoV-2 RNA in wastewater and COVID-19 cases. Daily WWTP SARS-CoV-2 influent viral RNA load, calculated using daily influent flow rates, had the strongest correlation (ρ > 0.9) with COVID-19 cases within a catchment. As the incidence of COVID-19 cases within a community increased, a linear relationship emerged between cases and influent viral RNA load. There were significant differences between WWTPs in their capacity to predict case numbers based on influent viral RNA load, with the limit of detection ranging from 25 cases for larger plants to a single case in smaller plants. SARS-CoV-2 viral RNA load can be used to predict the number of cases detected in the WWTP catchment area, with a clear statistically significant relationship observed above site-specific case thresholds.

Identifying likely transmissions in Mycobacterium bovis infected populations of cattle and badgers using the Kolmogorov Forward Equations.

Established methods for whole-genome-sequencing (WGS) technology allow for the detection of single-nucleotide polymorphisms (SNPs) in the pathogen genomes sourced from host samples. The information obtained can be used to track the pathogen's evolution in time and potentially identify 'who-infected-whom' with unprecedented accuracy. Successful methods include 'phylodynamic approaches' that integrate evolutionary and epidemiological data. However, they are typically computationally intensive, require extensive data, and are best applied when there is a strong molecular clock signal and substantial pathogen diversity. To determine how much transmission information can be inferred when pathogen genetic diversity is low and metadata limited, we propose an analytical approach that combines pathogen WGS data and sampling times from infected hosts. It accounts for 'between-scale' processes, in particular within-host pathogen evolution and between-host transmission. We applied this to a well-characterised population with an endemic Mycobacterium bovis (the causative agent of bovine/zoonotic tuberculosis, bTB) infection. Our results show that, even with such limited data and low diversity, the computation of the transmission probability between host pairs can help discriminate between likely and unlikely infection pathways and therefore help to identify potential transmission networks. However, the method can be sensitive to assumptions about within-host evolution.

Multilayer and Multiplex Networks: An Introduction to Their Use in Veterinary Epidemiology.

Contact network analysis has become a vital tool for conceptualizing the spread of pathogens in animal populations and is particularly useful for understanding the implications of heterogeneity in contact patterns for transmission. However, the transmission of most pathogens cannot be simplified to a single mode of transmission and, thus, a single definition of contact. In addition, host-pathogen interactions occur in a community context, with many pathogens infecting multiple host species and most hosts being infected by multiple pathogens. Multilayer networks provide a formal framework for researching host-pathogen systems in which multiple types of transmission-relevant interactions, defined as network layers, can be analyzed jointly. Here, we provide an overview of multilayer network analysis and review applications of this novel method to epidemiological research questions. We then demonstrate the use of this technique to analyze heterogeneity in direct and indirect contact patterns amongst swine farms in the United States. When contact among nodes can be defined in multiple ways, a multilayer approach can advance our ability to use networks in epidemiological research by providing an improved approach for defining epidemiologically relevant groups of interacting nodes and changing the way we identify epidemiologically important individuals such as superspreaders.

Mycobacterium bovis genomics reveals transmission of infection between cattle and deer in Ireland.

Control of bovine tuberculosis (bTB), caused by Mycobacterium bovis, in the Republic of Ireland costs €84 million each year. Badgers are recognized as being a wildlife source for M. bovis infection of cattle. Deer are thought to act as spillover hosts for infection; however, population density is recognized as an important driver in shifting their epidemiological role, and deer populations across the country have been increasing in density and range. County Wicklow represents one specific area in the Republic of Ireland with a high density of deer that has had consistently high bTB prevalence for over a decade, despite control operations in both cattle and badgers. Our research used whole-genome sequencing of M. bovis sourced from infected cattle, deer and badgers in County Wicklow to evaluate whether the epidemiological role of deer could have shifted from spillover host to source. Our analyses reveal that cattle and deer share highly similar M. bovis strains, suggesting that transmission between these species is occurring in the area. In addition, the high level of diversity observed in the sampled deer population suggests deer may be acting as a source of infection for local cattle populations. These findings have important implications for the control and ultimate eradication of bTB in Ireland.

Free Fatty Acids Rewire Cancer Metabolism in Obesity-Associated Breast Cancer via Estrogen Receptor and mTOR Signaling.

Obesity is a risk factor for postmenopausal estrogen receptor alpha (ERα)-positive (ER+) breast cancer. Molecular mechanisms underlying factors from plasma that contribute to this risk and how these mechanisms affect ERα signaling have yet to be elucidated. To identify such mechanisms, we performed whole metabolite and protein profiling in plasma samples from women at high risk for breast cancer, which led us to focus on factors that were differentially present in plasma of obese versus nonobese postmenopausal women. These studies, combined with in vitro assays, identified free fatty acids (FFA) as circulating plasma factors that correlated with increased proliferation and aggressiveness in ER+ breast cancer cells. FFAs activated both the ERα and mTOR pathways and rewired metabolism in breast cancer cells. Pathway preferential estrogen-1 (PaPE-1), which targets ERα and mTOR signaling, was able to block changes induced by FFA and was more effective in the presence of FFA. Collectively, these data suggest a role for obesity-associated gene and metabolic rewiring in providing new targetable vulnerabilities for ER+ breast cancer in postmenopausal women. Furthermore, they provide a basis for preclinical and clinical trials where the impact of agents that target ERα and mTOR signaling cross-talk would be tested to prevent ER+ breast cancers in obese postmenopausal women. SIGNIFICANCE: These findings show that obesity-associated changes in certain blood metabolites rewire metabolic programs in cancer cells, influence mammary epithelial cell tumorigenicity and aggressiveness, and increase breast cancer risk.

The spread of bovine tuberculosis in Canadian shared pastures: Data, model, and simulations.

Bovine tuberculosis (bTB), caused by Mycobacterium bovis, is a chronic disease typical of cattle. Nonetheless, it can affect many mammals including humans, making it one of the most widespread zoonotic diseases worldwide. In industrialized countries, the main pathways of introduction of bTB into a herd are animal trade and contact with infected wildlife. In addition, for slow-spreading diseases with a long latent period such as bTB, shared seasonal pastures might be a between-herd transmission pathway, indeed farmers might unknowingly send infected animals to the pasture, since clinical signs are rarely evident in early infection. In this study, we developed a dynamic stochastic model to represent the spread of bTB in pastures. This was tailored to Canadian cow-calf herds, as we calibrated the model with data sourced from a recent bTB outbreak in Western Canada. We built a model for a herd with seasonal management, characterized by its partition into a group staying in the main facility and the remaining group(s) moving to summer pastures. We used this model to estimate the time of the first introduction of bTB into the herd. Furthermore, we expanded the model to include herds categorized as high-risk contacts with the index herd, in order to estimate the potential for disease spread on shared pastures. Finally, we explored two control scenarios to be applied to high-risk farms after the outbreak detection. Our results showed that the first introduction likely happened 3 to 5 years prior to the detection of the index herd, and the probability of bTB spreading in pastures was low, but not negligible. Nevertheless, the surveillance system currently in place was effective to detect potential outbreaks.

The spread of mosquito-borne viruses in modern times: A spatio-temporal analysis of dengue and chikungunya.

Since the 1970s, mosquito-borne pathogens have spread to previously disease-free areas, as well as causing increased illness in endemic areas. In particular, dengue and chikungunya viruses, transmitted primarily by Aedes aegypti and secondarily by Aedes albopictus mosquitoes, represent a threat for up to a third of the world population, and are a growing public health concern. In this study, we assess the spatial and temporal factors related to the occurrences of historic dengue and chikungunya outbreaks in 76 nations focused geographically on the Indian Ocean, with outbreak data from 1959 to 2009. First, we describe the historical spatial and temporal patterns of outbreaks of dengue and chikungunya in the focal nations. Second, we use a boosted regression tree approach to assess the statistical relationships of nations' concurrent outbreak occurrences and annual occurrences with their spatial proximity to prior infections and climatic and socio-economic characteristics. We demonstrate that higher population density and shorter distances among nations with outbreaks are the dominant factors that characterize both dengue and chikungunya outbreaks. In conclusion, our analysis provides crucial insights, which can be applied to improve nations' surveillance and preparedness for future vector-borne disease epidemics.

Long-Term Administration of Conjugated Estrogen and Bazedoxifene Decreased Murine Fecal ß-Glucuronidase Activity Without Impacting Overall Microbiome Community.

Conjugated estrogens (CE) and Bazedoxifene (BZA) combination is used to alleviate menopause-associated symptoms in women. CE+BZA undergo first-pass-metabolism in the liver and deconjugation by gut microbiome via ß-glucuronidase (GUS) enzyme inside the distal gut. To date, the impact of long-term exposure to CE+BZA on the gut microbiome or GUS activity has not been examined. Our study using an ovariectomized mouse model showed that CE+BZA administration did not affect the overall cecal or fecal microbiome community except that it decreased the abundance of Akkermansia, which was identified as a fecal biomarker correlated with weight gain. The fecal GUS activity was reduced significantly and was positively correlated with the abundance of Lactobacillaceae in the fecal microbiome. We further confirmed in Escherichia coli K12 and Lactobacillus gasseri ADH that Tamoxifen-, 4-hydroxy-Tamoxifen- and Estradiol-Glucuronides competed for GUS activity. Our study for the first time demonstrated that long-term estrogen supplementation directly modulated gut microbial GUS activity. Our findings implicate that long-term estrogen supplementation impacts composition of gut microbiota and microbial activity, which affects estrogen metabolism in the gut. Thus, it is possible to manipulate such activity to improve the efficacy and safety of long-term administered estrogens for postmenopausal women or breast cancer patients.

Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back.

Infectious diseases in livestock can be transmitted through fomites: objects able to convey infectious agents. Between-farm spread of infections through fomites is mostly due to indirect contacts generated by on-farm visits of personnel that can carry pathogens on their clothes, equipment, or vehicles. However, data on farm visitors are often difficult to obtain because of the heterogeneity of their nature and privacy issues. Thus, models simulating disease spread between farms usually rely on strong assumptions about the contribution of indirect contacts on infection spread. By using data on veterinarian on-farm visits in a dairy farm system, we built a simple simulation model to assess the role of indirect contacts on epidemic dynamics compared to cattle movements (i.e. direct contacts). We showed that including in the simulation model only specific subsets of the information available on indirect contacts could lead to outputs widely different from those obtained with the full-information model. Then, we provided a simple preferential attachment algorithm based on the probability to observe consecutive on-farm visits from the same operator that allows overcoming the information gaps. Our results suggest the importance of detailed data and a deeper understanding of visit dynamics for the prevention and control of livestock diseases.

The Potential Role of Direct and Indirect Contacts on Infection Spread in Dairy Farm Networks.

Animals' exchanges are considered the most effective route of between-farm infectious disease transmission. However, despite being often overlooked, the infection spread due to contaminated equipment, vehicles, or personnel proved to be important for several livestock epidemics. This study investigated the role of indirect contacts in a potential infection spread in the dairy farm network of the Province of Parma (Northern Italy). We built between-farm contact networks using data on cattle exchange (direct contacts), and on-farm visits by veterinarians (indirect contacts). We compared the features of the contact structures by using measures on static and temporal networks. We assessed the disease spreading potential of the direct and indirect network structures in the farm system by using data on the infection state of farms by paratuberculosis. Direct and indirect networks showed non-trivial differences with respect to connectivity, contact distribution, and super-spreaders identification. Furthermore, our analyses on paratuberculosis data suggested that the contributions of direct and indirect contacts on diseases spread are apparent at different spatial scales. Our results highlighted the potential role of indirect contacts in between-farm disease spread and underlined the need for a deeper understanding of these contacts to develop better strategies for prevention of livestock epidemics.

Epidemiological modelling for the assessment of bovine tuberculosis surveillance in the dairy farm network in Emilia-Romagna (Italy).

Assessing the performance of a surveillance system for infectious diseases of domestic animals is a challenging task for health authorities. Therefore, it is important to assess what strategy is the most effective in identifying the onset of an epidemic and in minimizing the number of infected farms. The aim of the present work was to evaluate the performance of the bovine tuberculosis (bTB) surveillance system in the network of dairy farms in the Emilia-Romagna (ER) Region, Italy. A bTB-free Region since 2007, ER implements an integrated surveillance strategy based on three components, namely routine on-farm tuberculin skin-testing performed every 3 years, tuberculin skin-testing of cattle exchanged between farms, and post-mortem inspection at slaughterhouses. We assessed the effectiveness of surveillance by means of a stochastic network model of both within-farm and between-farm bTB dynamics calibrated on data available for ER dairy farms. Epidemic dynamics were simulated for five scenarios: the current ER surveillance system, a no surveillance scenario that we used as the benchmark to characterize epidemic dynamics, three additional scenarios in which one of the surveillance components was removed at a time so as to outline its significance in detecting the infection. For each scenario we ran Monte Carlo simulations of bTB epidemics following the random introduction of an infected individual in the network. System performances were assessed through the comparative analysis of a number of statistics, including the time required for epidemic detection and the total number of infected farms during the epidemic. Our analysis showed that slaughterhouse inspection is the most effective surveillance component in reducing the time for disease detection, while routine surveillance in reducing the number of multi-farms epidemics. On the other hand, testing exchanged cattle improved the performance of the surveillance system only marginally.

The dynamic complex of cytochrome c6 and cytochrome f studied with paramagnetic NMR spectroscopy.

The rapid transfer of electrons in the photosynthetic redox chain is achieved by the formation of short-lived complexes of cytochrome b6f with the electron transfer proteins plastocyanin and cytochrome c6. A balance must exist between fast intermolecular electron transfer and rapid dissociation, which requires the formation of a complex that has limited specificity. The interaction of the soluble fragment of cytochrome f and cytochrome c6 from the cyanobacterium Nostoc sp. PCC 7119 was studied using NMR spectroscopy and X-ray diffraction. The crystal structures of wild type, M58H and M58C cytochrome c6 were determined. The M58C variant is an excellent low potential mimic of the wild type protein and was used in chemical shift perturbation and paramagnetic relaxation NMR experiments to characterize the complex with cytochrome f. The interaction is highly dynamic and can be described as a pure encounter complex, with no dominant stereospecific complex. Ensemble docking calculations and Monte-Carlo simulations suggest a model in which charge-charge interactions pre-orient cytochrome c6 with its haem edge toward cytochrome f to form an ensemble of orientations with extensive contacts between the hydrophobic patches on both cytochromes, bringing the two haem groups sufficiently close to allow for rapid electron transfer. This model of complex formation allows for a gradual increase and decrease of the hydrophobic interactions during association and dissociation, thus avoiding a high transition state barrier that would slow down the dissociation process.

Innocent until proven guilty? Stable coexistence of alien rainbow trout and native marble trout in a Slovenian stream.

To understand the consequences of the invasion of the nonnative rainbow trout Oncorhynchus mykiss on the native marble trout Salmo marmoratus, we compared two distinct headwater sectors where marble trout occur in allopatry (MTa) or sympatry (MTs) with rainbow trout (RTs) in the Idrijca River (Slovenia). Using data from field surveys from 2002 to 2009, with biannual (June and September) sampling and tagging from June 2004 onwards, we analyzed body growth and survival probabilities of marble trout in each stream sector. Density of age-0 in September over the study period was greater for MTs than MTa and very similar between MTs and RTs, while density of trout ≥age-1 was similar for MTa and MTs and greater than density of RTs. Monthly apparent survival probabilities were slightly higher in MTa than in MTs, while RTs showed a lower survival than MTs. Mean weight of marble and rainbow trout aged 0+ in September was negatively related to cohort density for both marble and rainbow trout, but the relationship was not significantly different between MTs and MTa. No clear depression of body growth of sympatric marble trout between sampling intervals was observed. Despite a later emergence, mean weight of RTs cohorts at age 0+ in September was significantly higher than weight of both MTs and MTa. The establishment of a self-sustaining population of rainbow trout does not have a significant impact on body growth and survival probabilities of sympatric marble trout. The numerical dominance of rainbow trout in streams at lower altitudes seem to suggest that while the low summer flow pattern of Slovenian streams is favorable for rainbow trout invasion, the adaptation of marble trout to headwater environments may limit the invasion success of rainbow trout in headwaters.