Inference for a spatio-temporal model with partial spatial data : African horse sickness virus in Morocco

African horse sickness virus (AHSV) is a vector-borne virus spread by midges (Culicoides spp.). The virus causes African horse sickness (AHS) disease in some species of equid. AHS is endemic in parts of Africa, previously emerged in Europe and in 2020 caused outbreaks for the first time in parts of Eastern Asia. Here we analyse a unique historic dataset from the 1989-1991 emergence of AHS in Morocco in a naïve population of equids. Sequential Monte Carlo and Markov chain Monte Carlo techniques are used to estimate parameters for a spatial-temporal model using a transmission kernel. These parameters allow us to observe how the transmissibility of AHSV changes according to the distance between premises. We observe how the spatial specificity of the dataset giving the locations of premises on which any infected equids were reported affects parameter estimates. Estimations of transmissibility were similar at the scales of village (location to the nearest 1.3 km) and region (median area 99 km ), but not province (median area 3000 km ). This data-driven result could help inform decisions by policy makers on collecting data during future equine disease outbreaks, as well as policies for AHS control. [Abstract copyright: Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

Re‐parameterization of a mathematical model of African horse sickness virus using data from a systematic literature search

African horse sickness (AHS) is a vector-borne disease transmitted by Culicoides spp., endemic to sub-Saharan Africa. There have been many examples of historic and recent outbreaks in the Middle East, Asia and Europe. However, not much is known about infection dynamics and outbreak potential in these naive populations. In order to better inform a previously published ordinary differential equation model, we performed a systematic literature search to identify studies documenting experimental infection of naive (control) equids in vaccination trials. Data on the time until the onset of viraemia, clinical signs and death after experimental infection of a naive equid and duration of viraemia were extracted. The time to viraemia was 4.6 days and the time to clinical signs was 4.9 days, longer than the previously estimated latent period of 3.7 days. The infectious periods of animals that died/were euthanized or survived were found to be 3.9 and 8.7 days, whereas previous estimations were 4.4 and 6 days, respectively. The case fatality was also found to be higher than previous estimations. The updated parameter values (along with other more recently published estimates from literature) resulted in an increase in the number of host deaths, decrease in the duration of the outbreak and greater prevalence in vectors

Ecological and Genomic Attributes of Novel Bacterial Taxa That Thrive in Subsurface Soil Horizons.

While most bacterial and archaeal taxa living in surface soils remain undescribed, this problem is exacerbated in deeper soils, owing to the unique oligotrophic conditions found in the subsurface. Additionally, previous studies of soil microbiomes have focused almost exclusively on surface soils, even though the microbes living in deeper soils also play critical roles in a wide range of biogeochemical processes. We examined soils collected from 20 distinct profiles across the United States to characterize the bacterial and archaeal communities that live in subsurface soils and to determine whether there are consistent changes in soil microbial communities with depth across a wide range of soil and environmental conditions. We found that bacterial and archaeal diversity generally decreased with depth, as did the degree of similarity of microbial communities to those found in surface horizons. We observed five phyla that consistently increased in relative abundance with depth across our soil profiles: Chloroflexi, Nitrospirae, Euryarchaeota, and candidate phyla GAL15 and Dormibacteraeota (formerly AD3). Leveraging the unusually high abundance of Dormibacteraeota at depth, we assembled genomes representative of this candidate phylum and identified traits that are likely to be beneficial in low-nutrient environments, including the synthesis and storage of carbohydrates, the potential to use carbon monoxide (CO) as a supplemental energy source, and the ability to form spores. Together these attributes likely allow members of the candidate phylum Dormibacteraeota to flourish in deeper soils and provide insight into the survival and growth strategies employed by the microbes that thrive in oligotrophic soil environments.IMPORTANCE Soil profiles are rarely homogeneous. Resource availability and microbial abundances typically decrease with soil depth, but microbes found in deeper horizons are still important components of terrestrial ecosystems. By studying 20 soil profiles across the United States, we documented consistent changes in soil bacterial and archaeal communities with depth. Deeper soils harbored communities distinct from those of the more commonly studied surface horizons. Most notably, we found that the candidate phylum Dormibacteraeota (formerly AD3) was often dominant in subsurface soils, and we used genomes from uncultivated members of this group to identify why these taxa are able to thrive in such resource-limited environments. Simply digging deeper into soil can reveal a surprising number of novel microbes with unique adaptations to oligotrophic subsurface conditions

BioModels—15 years of sharing computational models in life science

Computational modelling has become increasingly common in life science research. To provide a platform to support universal sharing, easy accessibility and model reproducibility, BioModels (https://www.ebi.ac.uk/biomodels/), a repository for mathematical models, was established in 2005. The current BioModels platform allows submission of models encoded in diverse modelling formats, including SBML, CellML, PharmML, COMBINE archive, MATLAB, Mathematica, R, Python or C++. The models submitted to BioModels are curated to verify the computational representation of the biological process and the reproducibility of the simulation results in the reference publication. The curation also involves encoding models in standard formats and annotation with controlled vocabularies following MIRIAM (minimal information required in the annotation of biochemical models) guidelines. BioModels now accepts large-scale submission of auto-generated computational models. With gradual growth in content over 15 years, BioModels currently hosts about 2000 models from the published literature. With about 800 curated models, BioModels has become the world’s largest repository of curated models and emerged as the third most used data resource after PubMed and Google Scholar among the scientists who use modelling in their research. Thus, BioModels benefits modellers by providing access to reliable and semantically enriched curated models in standard formats that are easy to share, reproduce and reuse

SARS-CoV-2 infection in UK university students: lessons from September-December 2020 and modelling insights for future student return.

Funder: Isaac Newton Institute for Mathematical Sciences; Id: http://dx.doi.org/10.13039/501100005347Funder: Wellcome Trust; Id: http://dx.doi.org/10.13039/100004440Funder: Medical Research Council; Id: http://dx.doi.org/10.13039/501100000265Funder: UKRIFunder: University of Nottingham; Id: http://dx.doi.org/10.13039/501100000837In this paper, we present work on SARS-CoV-2 transmission in UK higher education settings using multiple approaches to assess the extent of university outbreaks, how much those outbreaks may have led to spillover in the community, and the expected effects of control measures. Firstly, we found that the distribution of outbreaks in universities in late 2020 was consistent with the expected importation of infection from arriving students. Considering outbreaks at one university, larger halls of residence posed higher risks for transmission. The dynamics of transmission from university outbreaks to wider communities is complex, and while sometimes spillover does occur, occasionally even large outbreaks do not give any detectable signal of spillover to the local population. Secondly, we explored proposed control measures for reopening and keeping open universities. We found the proposal of staggering the return of students to university residence is of limited value in terms of reducing transmission. We show that student adherence to testing and self-isolation is likely to be much more important for reducing transmission during term time. Finally, we explored strategies for testing students in the context of a more transmissible variant and found that frequent testing would be necessary to prevent a major outbreak.This work was supported by EPSRC grant no EP/R014604/1. The authors would also like to thank the Virtual Forum for Knowledge Exchange in Mathematical Sciences (V-KEMS) for the support during the workshop Unlocking higher education Spaces – What Might Mathematics Tell Us? where work on this paper was undertaken. K.J.B. acknowledges support from a University of Nottingham Anne McLaren Fellowship. E.L.F. acknowledges support via K.J.B.’s fellowship and the Nottingham BBSRC Doctoral Training Partnership. M.L.T. was supported by the UK Engineering and Physical Sciences Research Council (grant no. EP/N509620/1). E.B.-P., E.J.N., L.D., J.R.G. and M.J.T. were supported by UKRI through the JUNIPER modelling consortium (grant no. MR/V038613/1). E.M.H., L.D. and M.J.T. were supported by the Medical Research Council through the COVID-19 Rapid Response Rolling Call (grant no. MR/V009761/1). H.B.S. is funded by the Wellcome Trust and the Royal Society (grant no. 202562/Z/16/Z). J.E. is partially funded by the UK Engineering and Physical Sciences Research Council (grant no. EP/T004878/1)

Influence of setting-dependent contacts and protective behaviours on asymptomatic SARS-CoV-2 infection amongst members of a UK university

We survey 62 users of a university asymptomatic SARS-CoV-2 testing service on details of their activities, protective behaviours and contacts in the 7 days prior to receiving a positive or negative SARS-CoV-2 PCR test result in the period October 2020-March 2021. The resulting data set is novel in capturing very detailed social contact history linked to asymp-tomatic disease status during a period of significant restriction on social activities. We use this data to explore 3 questions: (i) Did participation in university activities enhance infection risk? (ii) How do contact definitions rank in their ability to explain test outcome during periods of social restrictions? (iii) Do patterns in the protective behaviour help explain discrepancies between the explanatory performance of different contact measures? We classify activities into settings and use Bayesian logistic regression to model test outcome, computing posterior model probabilities to compare the performance of models adopting different contact definitions. Associations between protective behaviours, participant characteristics and setting are explored at the level of individual activities using multiple correspondence analysis (MCA). We find that participation in air travel or non-university work activities was associated with a positive asymptomatic SARS-CoV-2 PCR test, in contrast to participation in research and teaching settings. Intriguingly, logistic regression models with binary measures of contact in a setting performed better than more traditional contact numbers or person contact hours (PCH). The MCA indicates that patterns of protective behaviours vary between setting, in a manner which may help explain the preference for any participation as a contact measure. We conclude that linked PCR testing and social contact data can in principle be used to test the utility of contact definitions, and the investigation of contact definitions in larger linked studies is warranted to ensure contact data can capture environmental and social factors influencing transmission risk

Hematopoietic stem cell gene therapy for adenosine deaminase-deficient severe combined immunodeficiency leads to long-term immunological recovery and metabolic correction

Genetic defects in the purine salvage enzyme adenosine deaminase (ADA) lead to severe combined immunodeficiency (SCID) with profound depletion of T, B, and natural killer cell lineages. Human leukocyte antigen-matched allogeneic hematopoietic stem cell transplantation (HSCT) offers a successful treatment option. However, individuals who lack a matched donor must receive mismatched transplants, which are associated with considerable morbidity and mortality. Enzyme replacement therapy (ERT) for ADA-SCID is available, but the associated suboptimal correction of immunological defects leaves patients susceptible to infection. Here, six children were treated with autologous CD34-positive hematopoietic bone marrow stem and progenitor cells transduced with a conventional gammaretroviral vector encoding the human ADA gene. All patients stopped ERT and received mild chemotherapy before infusion of gene-modified cells. All patients survived, with a median follow-up of 43 months (range, 24 to 84 months). Four of the six patients recovered immune function as a result of engraftment of gene-corrected cells. In two patients, treatment failed because of disease-specific and technical reasons: Both restarted ERT and remain well. Of the four reconstituted patients, three remained off enzyme replacement. Moreover, three of these four patients discontinued immunoglobulin replacement, and all showed effective metabolic detoxification. All patients remained free of infection, and two cleared problematic persistent cytomegalovirus infection. There were no adverse leukemic side effects. Thus, gene therapy for ADA-SCID is safe, with effective immunological and metabolic correction, and may offer a viable alternative to conventional unrelated donor HSCT

Continental-scale patterns of extracellular enzyme activity in the subsoil: an overlooked reservoir of microbial activity

Chemical stabilization of microbial-derived products such as extracellular enzymes (EE) onto mineral surfaces has gained attention as a possibly important mechanism leading to the persistence of soil organic carbon (SOC). While the controls on EE activities and their stabilization in the surface soil are reasonably well-understood, how these activities change with soil depth and possibly diverge from those at the soil surface due to distinct physical, chemical, and biotic conditions remains unclear. We assessed EE activity to a depth of 1 m (10 cm increments) in 19 soil profiles across the Critical Zone Observatory Network, which represents a wide range of climates, soil orders, and vegetation types. For all EEs, activities per mass of soil correlated positively with microbial biomass (MB) and SOC, and all three of these variables decreased logarithmically with depth (p< 0.05). Across all sites, over half of the potential EE activities per mass soil consistently occurred below 20 cm for all measured EEs. Activities per unit MB or SOC were substantially higher at depth (soils below 20 cm accounted for 80% of whole-profile EE activity), suggesting an accumulation of stabilized (i.e. mineral sorbed) EEs in subsoil horizons. The pronounced enzyme stabilization in subsurface horizons was corroborated by mixed-effects models that showed a significant, positive relationship between clay concentration and MB-normalized EE activities in the subsoil. Furthermore, the negative relationships between soil C, N, and P and C-, N-, and P-acquiring EEs found in the surface soil decoupled below 20 cm, which could have also been caused by EE stabilization. This finding suggests that EEs may not reflect soil nutrient availabilities deeper in the soil profile. Taken together, our results suggest that deeper soil horizons hold a significant reservoir of EEs, and that the controls of subsoil EEs differ from their surface soil counterparts.U.S. Department of EnergyOpen access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Ecological and Genomic Attributes of Novel Bacterial Taxa That Thrive in Subsurface Soil Horizons

Soil profiles are rarely homogeneous. Resource availability and microbial abundances typically decrease with soil depth, but microbes found in deeper horizons are still important components of terrestrial ecosystems. By studying 20 soil profiles across the United States, we documented consistent changes in soil bacterial and archaeal communities with depth. Deeper soils harbored communities distinct from those of the more commonly studied surface horizons. Most notably, we found that the candidate phylum Dormibacteraeota (formerly AD3) was often dominant in subsurface soils, and we used genomes from uncultivated members of this group to identify why these taxa are able to thrive in such resource-limited environments. Simply digging deeper into soil can reveal a surprising number of novel microbes with unique adaptations to oligotrophic subsurface conditions.While most bacterial and archaeal taxa living in surface soils remain undescribed, this problem is exacerbated in deeper soils, owing to the unique oligotrophic conditions found in the subsurface. Additionally, previous studies of soil microbiomes have focused almost exclusively on surface soils, even though the microbes living in deeper soils also play critical roles in a wide range of biogeochemical processes. We examined soils collected from 20 distinct profiles across the United States to characterize the bacterial and archaeal communities that live in subsurface soils and to determine whether there are consistent changes in soil microbial communities with depth across a wide range of soil and environmental conditions. We found that bacterial and archaeal diversity generally decreased with depth, as did the degree of similarity of microbial communities to those found in surface horizons. We observed five phyla that consistently increased in relative abundance with depth across our soil profiles: Chloroflexi, Nitrospirae, Euryarchaeota, and candidate phyla GAL15 and Dormibacteraeota (formerly AD3). Leveraging the unusually high abundance of Dormibacteraeota at depth, we assembled genomes representative of this candidate phylum and identified traits that are likely to be beneficial in low-nutrient environments, including the synthesis and storage of carbohydrates, the potential to use carbon monoxide (CO) as a supplemental energy source, and the ability to form spores. Together these attributes likely allow members of the candidate phylum Dormibacteraeota to flourish in deeper soils and provide insight into the survival and growth strategies employed by the microbes that thrive in oligotrophic soil environments