A mathematical, classical stratification modeling approach to disentangling the impact of weather on infectious diseases: A case study using spatio-temporally disaggregated Campylobacter surveillance data for England and Wales.

Disentangling the impact of the weather on transmission of infectious diseases is crucial for health protection, preparedness and prevention. Because weather factors are co-incidental and partly correlated, we have used geography to separate out the impact of individual weather parameters on other seasonal variables using campylobacteriosis as a case study. Campylobacter infections are found worldwide and are the most common bacterial food-borne disease in developed countries, where they exhibit consistent but country specific seasonality. We developed a novel conditional incidence method, based on classical stratification, exploiting the long term, high-resolution, linkage of approximately one-million campylobacteriosis cases over 20 years in England and Wales with local meteorological datasets from diagnostic laboratory locations. The predicted incidence of campylobacteriosis increased by 1 case per million people for every 5° (Celsius) increase in temperature within the range of 8°-15°. Limited association was observed outside that range. There were strong associations with day-length. Cases tended to increase with relative humidity in the region of 75-80%, while the associations with rainfall and wind-speed were weaker. The approach is able to examine multiple factors and model how complex trends arise, e.g. the consistent steep increase in campylobacteriosis in England and Wales in May-June and its spatial variability. This transparent and straightforward approach leads to accurate predictions without relying on regression models and/or postulating specific parameterisations. A key output of the analysis is a thoroughly phenomenological description of the incidence of the disease conditional on specific local weather factors. The study can be crucially important to infer the elusive mechanism of transmission of campylobacteriosis; for instance, by simulating the conditional incidence for a postulated mechanism and compare it with the phenomenological patterns as benchmark. The findings challenge the assumption, commonly made in statistical models, that the transformed mean rate of infection for diseases like campylobacteriosis is a mere additive and combination of the environmental variables.

Dyrk1a gene dosage in glutamatergic neurons has key effects in cognitive deficits observed in mouse models of MRD7 and Down syndrome.

Perturbation of the excitation/inhibition (E/I) balance leads to neurodevelopmental diseases including to autism spectrum disorders, intellectual disability, and epilepsy. Loss-of-function mutations in the DYRK1A gene, located on human chromosome 21 (Hsa21,) lead to an intellectual disability syndrome associated with microcephaly, epilepsy, and autistic troubles. Overexpression of DYRK1A, on the other hand, has been linked with learning and memory defects observed in people with Down syndrome (DS). Dyrk1a is expressed in both glutamatergic and GABAergic neurons, but its impact on each neuronal population has not yet been elucidated. Here we investigated the impact of Dyrk1a gene copy number variation in glutamatergic neurons using a conditional knockout allele of Dyrk1a crossed with the Tg(Camk2-Cre)4Gsc transgenic mouse. We explored this genetic modification in homozygotes, heterozygotes and combined with the Dp(16Lipi-Zbtb21)1Yey trisomic mouse model to unravel the consequence of Dyrk1a dosage from 0 to 3, to understand its role in normal physiology, and in MRD7 and DS. Overall, Dyrk1a dosage in postnatal glutamatergic neurons did not impact locomotor activity, working memory or epileptic susceptibility, but revealed that Dyrk1a is involved in long-term explicit memory. Molecular analyses pointed at a deregulation of transcriptional activity through immediate early genes and a role of DYRK1A at the glutamatergic post-synapse by deregulating and interacting with key post-synaptic proteins implicated in mechanism leading to long-term enhanced synaptic plasticity. Altogether, our work gives important information to understand the action of DYRK1A inhibitors and have a better therapeutic approach.

bigSCale: an analytical framework for big-scale single-cell data.

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin (Reln)-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets.

Environmental limits of Rift Valley fever revealed using ecoepidemiological mechanistic models.

Vector-borne diseases (VBDs) of humans and domestic animals are a significant component of the global burden of disease and a key driver of poverty. The transmission cycles of VBDs are often strongly mediated by the ecological requirements of the vectors, resulting in complex transmission dynamics, including intermittent epidemics and an unclear link between environmental conditions and disease persistence. An important broader concern is the extent to which theoretical models are reliable at forecasting VBDs; infection dynamics can be complex, and the resulting systems are highly unstable. Here, we examine these problems in detail using a case study of Rift Valley fever (RVF), a high-burden disease endemic to Africa. We develop an ecoepidemiological, compartmental, mathematical model coupled to the dynamics of ambient temperature and water availability and apply it to a realistic setting using empirical environmental data from Kenya. Importantly, we identify the range of seasonally varying ambient temperatures and water-body availability that leads to either the extinction of mosquito populations and/or RVF (nonpersistent regimens) or the establishment of long-term mosquito populations and consequently, the endemicity of the RVF infection (persistent regimens). Instabilities arise when the range of the environmental variables overlaps with the threshold of persistence. The model captures the intermittent nature of RVF occurrence, which is explained as low-level circulation under the threshold of detection, with intermittent emergence sometimes after long periods. Using the approach developed here opens up the ability to improve predictions of the emergence and behaviors of epidemics of many other important VBDs.

A new mouse model of ARX dup24 recapitulates the patients' behavioral and fine motor alterations.

The aristaless-related homeobox (ARX) transcription factor is involved in the development of GABAergic and cholinergic neurons in the forebrain. ARX mutations have been associated with a wide spectrum of neurodevelopmental disorders in humans, among which the most frequent, a 24 bp duplication in the polyalanine tract 2 (c.428_451dup24), gives rise to intellectual disability, fine motor defects with or without epilepsy. To understand the functional consequences of this mutation, we generated a partially humanized mouse model carrying the c.428_451dup24 duplication (Arxdup24/0) that we characterized at the behavior, neurological and molecular level. Arxdup24/0 males presented with hyperactivity, enhanced stereotypies and altered contextual fear memory. In addition, Arxdup24/0 males had fine motor defects with alteration of reaching and grasping abilities. Transcriptome analysis of Arxdup24/0 forebrains at E15.5 showed a down-regulation of genes specific to interneurons and an up-regulation of genes normally not expressed in this cell type, suggesting abnormal interneuron development. Accordingly, interneuron migration was altered in the cortex and striatum between E15.5 and P0 with consequences in adults, illustrated by the defect in the inhibitory/excitatory balance in Arxdup24/0 basolateral amygdala. Altogether, we showed that the c.428_451dup24 mutation disrupts Arx function with a direct consequence on interneuron development, leading to hyperactivity and defects in precise motor movement control and associative memory. Interestingly, we highlighted striking similarities between the mouse phenotype and a cohort of 33 male patients with ARX c.428_451dup24, suggesting that this new mutant mouse line is a good model for understanding the pathophysiology and evaluation of treatment.

Increased H3K9 methylation and impaired expression of Protocadherins are associated with the cognitive dysfunctions of the Kleefstra syndrome.

Kleefstra syndrome, a disease with intellectual disability, autism spectrum disorders and other developmental defects is caused in humans by haploinsufficiency of EHMT1. Although EHMT1 and its paralog EHMT2 were shown to be histone methyltransferases responsible for deposition of the di-methylated H3K9 (H3K9me2), the exact nature of epigenetic dysfunctions in Kleefstra syndrome remains unknown. Here, we found that the epigenome of Ehmt1+/- adult mouse brain displays a marked increase of H3K9me2/3 which correlates with impaired expression of protocadherins, master regulators of neuronal diversity. Increased H3K9me3 was present already at birth, indicating that aberrant methylation patterns are established during embryogenesis. Interestingly, we found that Ehmt2+/- mice do not present neither the marked increase of H3K9me2/3 nor the cognitive deficits found in Ehmt1+/- mice, indicating an evolutionary diversification of functions. Our finding of increased H3K9me3 in Ehmt1+/- mice is the first one supporting the notion that EHMT1 can quench the deposition of tri-methylation by other Histone methyltransferases, ultimately leading to impaired neurocognitive functioning. Our insights into the epigenetic pathophysiology of Kleefstra syndrome may offer guidance for future developments of therapeutic strategies for this disease.

Mouse models of 17q21.31 microdeletion and microduplication syndromes highlight the importance of Kansl1 for cognition.

Koolen-de Vries syndrome (KdVS) is a multi-system disorder characterized by intellectual disability, friendly behavior, and congenital malformations. The syndrome is caused either by microdeletions in the 17q21.31 chromosomal region or by variants in the KANSL1 gene. The reciprocal 17q21.31 microduplication syndrome is associated with psychomotor delay, and reduced social interaction. To investigate the pathophysiology of 17q21.31 microdeletion and microduplication syndromes, we generated three mouse models: 1) the deletion (Del/+); or 2) the reciprocal duplication (Dup/+) of the 17q21.31 syntenic region; and 3) a heterozygous Kansl1 (Kans1+/-) model. We found altered weight, general activity, social behaviors, object recognition, and fear conditioning memory associated with craniofacial and brain structural changes observed in both Del/+ and Dup/+ animals. By investigating hippocampus function, we showed synaptic transmission defects in Del/+ and Dup/+ mice. Mutant mice with a heterozygous loss-of-function mutation in Kansl1 displayed similar behavioral and anatomical phenotypes compared to Del/+ mice with the exception of sociability phenotypes. Genes controlling chromatin organization, synaptic transmission and neurogenesis were upregulated in the hippocampus of Del/+ and Kansl1+/- animals. Our results demonstrate the implication of KANSL1 in the manifestation of KdVS phenotypes and extend substantially our knowledge about biological processes affected by these mutations. Clear differences in social behavior and gene expression profiles between Del/+ and Kansl1+/- mice suggested potential roles of other genes affected by the 17q21.31 deletion. Together, these novel mouse models provide new genetic tools valuable for the development of therapeutic approaches.

Seasonality and the effects of weather on Campylobacter infections.

BACKGROUND: Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. METHODS: To investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses. RESULTS: The increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas. CONCLUSIONS: The association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored.

A comparison of weather variables linked to infectious disease patterns using laboratory addresses and patient residence addresses.

BACKGROUND: To understand the impact of weather on infectious diseases, information on weather parameters at patient locations is needed, but this is not always accessible due to confidentiality or data availability. Weather parameters at nearby locations are often used as a proxy, but the accuracy of this practice is not known. METHODS: Daily Campylobacter and Cryptosporidium cases across England and Wales were linked to local temperature and rainfall at the residence postcodes of the patients and at the corresponding postcodes of the laboratory where the patient's specimen was tested. The paired values of daily rainfall and temperature for the laboratory versus residence postcodes were interpolated from weather station data, and the results were analysed for agreement using linear regression. We also assessed potential dependency of the findings on the relative geographic distance between the patient's residence and the laboratory. RESULTS: There was significant and strong agreement between the daily values of rainfall and temperature at diagnostic laboratories with the values at the patient residence postcodes for samples containing the pathogens Campylobacter or Cryptosporidium. For rainfall, the R-squared was 0.96 for the former and 0.97 for the latter, and for maximum daily temperature, the R-squared was 0.99 for both. The overall mean distance between the patient residence and the laboratory was 11.9 km; however, the distribution of these distances exhibited a heavy tail, with some rare situations where the distance between the patient residence and the laboratory was larger than 500 km. These large distances impact the distributions of the weather variable discrepancies (i.e. the differences between weather parameters estimated at patient residence postcodes and those at laboratory postcodes), with discrepancies up to ±10 °C for the minimum and maximum temperature and 20 mm for rainfall. Nevertheless, the distributions of discrepancies (estimated separately for minimum and maximum temperature and rainfall), based on the cases where the distance between the patient residence and the laboratory was within 20 km, still exhibited tails somewhat longer than the corresponding exponential fits suggesting modest small scale variations in temperature and rainfall. CONCLUSION: The findings confirm that, for the purposes of studying the relationships between meteorological variables and infectious diseases using data based on laboratory postcodes, the weather results are sufficiently similar to justify the use of laboratory postcode as a surrogate for domestic postcode. Exclusion of the small percentage of cases where there is a large distance between the residence and the laboratory could increase the precision of estimates, but there are generally strong associations between daily weather parameters at residence and laboratory.

Conditional depletion of intellectual disability and Parkinsonism candidate gene ATP6AP2 in fly and mouse induces cognitive impairment and neurodegeneration.

ATP6AP2, an essential accessory component of the vacuolar H+ ATPase (V-ATPase), has been associated with intellectual disability (ID) and Parkinsonism. ATP6AP2 has been implicated in several signalling pathways; however, little is known regarding its role in the nervous system. To decipher its function in behaviour and cognition, we generated and characterized conditional knockdowns of ATP6AP2 in the nervous system of Drosophila and mouse models. In Drosophila, ATP6AP2 knockdown induced defective phototaxis and vacuolated photoreceptor neurons and pigment cells when depleted in eyes and altered short- and long-term memory when depleted in the mushroom body. In mouse, conditional Atp6ap2 deletion in glutamatergic neurons (Atp6ap2(Camk2aCre/0) mice) caused increased spontaneous locomotor activity and altered fear memory. Both Drosophila ATP6AP2 knockdown and Atp6ap2(Camk2aCre/0) mice presented with presynaptic transmission defects, and with an abnormal number and morphology of synapses. In addition, Atp6ap2(Camk2aCre/0) mice showed autophagy defects that led to axonal and neuronal degeneration in the cortex and hippocampus. Surprisingly, axon myelination was affected in our mutant mice, and axonal transport alterations were observed in Drosophila. In accordance with the identified phenotypes across species, genome-wide transcriptome profiling of Atp6ap2(Camk2aCre/0) mouse hippocampi revealed dysregulation of genes involved in myelination, action potential, membrane-bound vesicles and motor behaviour. In summary, ATP6AP2 disruption in mouse and fly leads to cognitive impairment and neurodegeneration, mimicking aspects of the neuropathology associated with ATP6AP2 mutations in humans. Our results identify ATP6AP2 as an essential gene for the nervous system.

A rate-distortion theory for gene regulatory networks and its application to logic gate consistency.

MOTIVATION: A gene regulatory network in which the modes (activation/inhibition) of the transcriptional regulations are known and in which gene expression assumes boolean values can be treated as a system of linear equations over a binary field, i.e. as a constraint satisfaction problem for an information code. RESULTS: For currently available gene networks, we show in this article that the distortion associated with the corresponding information code is much lower than expected from null models, and that it is close to (when not lower than) the Shannon bound determined by the rate-distortion theorem. This corresponds to saying that the distribution of regulatory modes is highly atypical in the networks, and that this atypicality greatly helps in avoiding contradictory transcriptional actions. Choosing a boolean formalism to represent the gene networks, we also show how to formulate criteria for the selection of gates that maximize the compatibility with the empirical information available on the transcriptional regulatory modes. Proceeding in this way, we obtain in particular that non-canalizing gates are upper-bounded by the distortion, and hence that the boolean gene networks are more canalizing than expected from null models.

Durable resistance to crop pathogens: an epidemiological framework to predict risk under uncertainty.

Increasing the durability of crop resistance to plant pathogens is one of the key goals of virulence management. Despite the recognition of the importance of demographic and environmental stochasticity on the dynamics of an epidemic, their effects on the evolution of the pathogen and durability of resistance has not received attention. We formulated a stochastic epidemiological model, based on the Kramer-Moyal expansion of the Master Equation, to investigate how random fluctuations affect the dynamics of an epidemic and how these effects feed through to the evolution of the pathogen and durability of resistance. We focused on two hypotheses: firstly, a previous deterministic model has suggested that the effect of cropping ratio (the proportion of land area occupied by the resistant crop) on the durability of crop resistance is negligible. Increasing the cropping ratio increases the area of uninfected host, but the resistance is more rapidly broken; these two effects counteract each other. We tested the hypothesis that similar counteracting effects would occur when we take account of demographic stochasticity, but found that the durability does depend on the cropping ratio. Secondly, we tested whether a superimposed external source of stochasticity (for example due to environmental variation or to intermittent fungicide application) interacts with the intrinsic demographic fluctuations and how such interaction affects the durability of resistance. We show that in the pathosystem considered here, in general large stochastic fluctuations in epidemics enhance extinction of the pathogen. This is more likely to occur at large cropping ratios and for particular frequencies of the periodic external perturbation (stochastic resonance). The results suggest possible disease control practises by exploiting the natural sources of stochasticity.

Computing global structural balance in large-scale signed social networks.

Structural balance theory affirms that signed social networks (i.e., graphs whose signed edges represent friendly/hostile interactions among individuals) tend to be organized so as to avoid conflictual situations, corresponding to cycles of negative parity. Using an algorithm for ground-state calculation in large-scale Ising spin glasses, in this paper we compute the global level of balance of very large online social networks and verify that currently available networks are indeed extremely balanced. This property is explainable in terms of the high degree of skewness of the sign distributions on the nodes of the graph. In particular, individuals linked by a large majority of negative edges create mostly "apparent disorder," rather than true "frustration."

Decompositions of large-scale biological systems based on dynamical properties.

MOTIVATION: Given a large-scale biological network represented as an influence graph, in this article we investigate possible decompositions of the network aimed at highlighting specific dynamical properties. RESULTS: The first decomposition we study consists in finding a maximal directed acyclic subgraph of the network, which dynamically corresponds to searching for a maximal open-loop subsystem of the given system. Another dynamical property investigated is strong monotonicity. We propose two methods to deal with this property, both aimed at decomposing the system into strongly monotone subsystems, but with different structural characteristics: one method tends to produce a single large strongly monotone component, while the other typically generates a set of smaller disjoint strongly monotone subsystems. AVAILABILITY: Original heuristics for the methods investigated are described in the article. CONTACT: altafini@sissa.it

Mapping the evidence of the effects of environmental factors on the prevalence of antibiotic resistance in the non-built environment: Protocol for a systematic evidence map.

BACKGROUND: Human, animal, and environmental health are increasingly threatened by the emergence and spread of antibiotic resistance. Inappropriate use of antibiotic treatments commonly contributes to this threat, but it is also becoming apparent that multiple, interconnected environmental factors can play a significant role. Thus, a One Health approach is required for a comprehensive understanding of the environmental dimensions of antibiotic resistance and inform science-based decisions and actions. The broad and multidisciplinary nature of the problem poses several open questions drawing upon a wide heterogeneous range of studies. OBJECTIVE: This study seeks to collect and catalogue the evidence of the potential effects of environmental factors on the abundance or detection of antibiotic resistance determinants in the outdoor environment, i.e., antibiotic resistant bacteria and mobile genetic elements carrying antibiotic resistance genes, and the effect on those caused by local environmental conditions of either natural or anthropogenic origin. METHODS: Here, we describe the protocol for a systematic evidence map to address this, which will be performed in adherence to best practice guidelines. We will search the literature from 1990 to present, using the following electronic databases: MEDLINE, Embase, and the Web of Science Core Collection as well as the grey literature. We shall include full-text, scientific articles published in English. Reviewers will work in pairs to screen title, abstract and keywords first and then full-text documents. Data extraction will adhere to a code book purposely designed. Risk of bias assessment will not be conducted as part of this SEM. We will combine tables, graphs, and other suitable visualisation techniques to compile a database i) of studies investigating the factors associated with the prevalence of antibiotic resistance in the environment and ii) map the distribution, network, cross-disciplinarity, impact and trends in the literature.

The evolution of plant pathogens in response to host resistance: factors affecting the gain from deployment of qualitative and quantitative resistance.

Disease resistance genes are valuable natural resources which should be deployed in a way which maximises the gain to crop productivity before they lose efficacy. Here we present a general epidemiological model for plant diseases, formulated to study the evolution of phenotypic traits of plant pathogens in response to host resistance. The model was used to analyse how the characteristics of the disease resistance, and the method of deployment, affect the size and duration of the gain. The gain obtained from growing a resistant cultivar, compared to a susceptible cultivar, was quantified as the increase in green canopy area resulting from control of foliar disease, integrated over many years-termed 'Healthy Area Duration (HAD) Gain'. Previous work has suggested that the effect of crop ratio (the proportion of land area occupied by the resistant crop) on the gain from qualitative (gene-for-gene) resistance is negligible. Increasing the crop ratio increases the area of uninfected host, but the resistance is more rapidly broken; these two effects counteract each other. We tested the hypothesis that similar counteracting effects would occur for quantitative, multi-genic resistance, but found that the HAD Gain increased at higher crop ratios. Then we tested the hypothesis that the gain from quantitative host resistance could differ depending on the life-cycle component (sporulation rate or infection efficiency) constrained by the resistance. For the patho-system considered, a quantitative resistant cultivar that reduced the infection efficiency gave a greater HAD Gain than a cultivar that reduced sporulation rate, despite having equivalent transmission rates.

Modeling Human TBX5 Haploinsufficiency Predicts Regulatory Networks for Congenital Heart Disease.

Haploinsufficiency of transcriptional regulators causes human congenital heart disease (CHD); however, the underlying CHD gene regulatory network (GRN) imbalances are unknown. Here, we define transcriptional consequences of reduced dosage of the CHD transcription factor, TBX5, in individual cells during cardiomyocyte differentiation from human induced pluripotent stem cells (iPSCs). We discovered highly sensitive dysregulation of TBX5-dependent pathways-including lineage decisions and genes associated with heart development, cardiomyocyte function, and CHD genetics-in discrete subpopulations of cardiomyocytes. Spatial transcriptomic mapping revealed chamber-restricted expression for many TBX5-sensitive transcripts. GRN analysis indicated that cardiac network stability, including vulnerable CHD-linked nodes, is sensitive to TBX5 dosage. A GRN-predicted genetic interaction between Tbx5 and Mef2c, manifesting as ventricular septation defects, was validated in mice. These results demonstrate exquisite and diverse sensitivity to TBX5 dosage in heterogeneous subsets of iPSC-derived cardiomyocytes and predicts candidate GRNs for human CHDs, with implications for quantitative transcriptional regulation in disease.

Households as hotspots of Lassa fever? Assessing the spatial distribution of Lassa virus-infected rodents in rural villages of Guinea.

The Natal multimammate mouse (Mastomys natalensis) is the reservoir host of Lassa virus (LASV), an arenavirus that causes Lassa haemorrhagic fever in humans in West Africa. While previous studies suggest that spillover risk is focal within rural villages due to the spatial behaviour of the rodents, the level of clustering was never specifically assessed. Nevertheless, detailed information on the spatial distribution of infected rodents would be highly valuable to optimize LASV-control campaigns, which are limited to rodent control or interrupting human-rodent contact considering that a human vaccine is not available. Here, we analysed data from a four-year field experiment to investigate whether LASV-infected rodents cluster in households in six rural villages in Guinea. Our analyses were based on the infection status (antibody or PCR) and geolocation of rodents (n = 864), and complemented with a phylogenetic analysis of LASV sequences (n = 119). We observed that the majority of infected rodents were trapped in a few houses (20%) and most houses were rodent-free at a specific point in time (60%). We also found that LASV strains circulating in a specific village were polyphyletic with respect to neighbouring villages, although most strains grouped together at the sub-village level and persisted over time. In conclusion, our results suggest that: (i) LASV spillover risk is heterogeneously distributed within villages in Guinea; (ii) viral elimination in one particular village is unlikely if rodents are not controlled in neighbouring villages. Such spatial information should be incorporated into eco-epidemiological models that assess the cost-efficiency of LASV control strategies.

Sampling time-dependent artifacts in single-cell genomics studies.

Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results, and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention.

Calcium control of gene regulation in rat hippocampal neuronal cultures.

Blockage of GABA-A receptors in hippocampal neuronal cultures triggers synchronous bursts of spikes initiating neuronal plasticity, partly mediated by changes of gene expression. By using specific pharmacological blockers, we have investigated which sources of Ca2+ entry primarily control changes of gene expression induced by 20 microM gabazine applied for 30 min (GabT). Intracellular Ca2+ transients were monitored with Ca2+ imaging while recording electrical activity with patch clamp microelectrodes. Concomitant transcription profiles were obtained using Affymetrix oligonucleotide microarrays and confirmed with quantitative RT-PCR. Blockage of NMDA receptors with 2-amino-5-phosphonovaleric acid (APV) did not reduce significantly somatic Ca2+ transients, which, on the contrary, were reduced by selective blockage of L, N, and P/Q types voltage gated calcium channels (VGCCs). Therefore, we investigated changes of gene expression in the presence of blockers of NMDA receptors and L, N, and P/Q VGCCs. Our results show that: (i) among genes upregulated by GabT, there are genes selectively dependent on NMDA activation, genes selectively dependent on L-type VGCCs and genes dependent on the activation of both channels; (ii) the majority of genes requires the concomitant activation of NMDA receptors and Ca2+ entry through VGCCs; (iii) blockage of N and P/Q VGCCs has an effect similar but not identical to blockage of L-type VGCCs.