SEARCH · Search bioRxiv

Results for “Epidemiology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43Linked to original sources

bioRxiv2021

It ain't what you do, it's what drives why you do it: how the basis of growers' decision making affects the effectiveness of disease control

While the spread of plant disease depends strongly on biological factors driving transmission, it also has a human dimension. Disease control depends on decisions made by individual growers, who are in turn influenced by a broad range of factors. Despite this, human behaviour has rarely been included in plant epidemic models. Considering Cassava Brown Streak Disease, we model how the perceived increase in profit due to disease management influences participation in clean seed systems (CSS). Our models are rooted in game theory, with growers making strategic decisions based on the expected profitability of different control strategies. We find that both the information used by growers to assess profitability and the perception of economic and epidemiological parameters influence long-term participation in the CSS. Over-estimation of infection risk leads to lower participation in the CSS, as growers perceive that paying for the CSS will be futile. Additionally, even though good disease management can be achieved through the implementation of CSS, and a scenario where all controllers use the CSS is achievable when growers base their decision on the average of their entire strategy, CBSD is rarely eliminated from the system. These results are robust to stochastic and spatial effects. Our work highlights the importance of including human behaviour in plant disease models, but also the significance of how that behaviour is included. 1 Author SummaryModels of plant disease epidemics rarely account for the behaviour of growers undertaking management decisions. However, such behaviour is likely to have a large impact on disease spread. Growers may choose to participate in a control scheme based on the perceived economic advantages, acting to maximise their own profit. Yet if many growers participate in a control scheme, their participation will lower the probability of others becoming infected and consequently disincentivise them from participating themselves. How these dynamics play out will alter the course of the epidemic. We incorporate these economic considerations into an epidemic model of Cassava Brown Streak Disease using two broad approaches, which vary in the amount of information provided to growers. We also consider the effect of grower misperception of economic and epidemiological parameters. Our work shows that both the inclusion of grower behaviour, and its means of inclusion, affect disease dynamics, and highlights the importance of including grower decision-making in plant epidemic models.

ecology↗

bioRxiv2021

Human pathogenic RNA viruses establish non-competing lineages by occupying independent niches

Many pathogenic viruses are endemic among human populations and can cause a broad variety of diseases, some potentially leading to devastating pandemics. How virus populations maintain diversity and what selective pressures drive population turnover, is not thoroughly understood. We conducted a large-scale phylodynamic analysis of 27 human pathogenic RNA viruses spanning diverse life history traits in search of unifying trends that shape virus evolution. For most virus species, we identify multiple, co-circulating lineages with low turnover rates. These lineages appear to be largely noncompeting and likely occupy semi-independent epidemiological niches that are not regionally or seasonally defined. Typically, intra-lineage mutational signatures are similar to inter-lineage signatures. The principal exception are members of the family Picornaviridae, for which mutations in capsid protein genes are primarily lineage-defining. The persistence of virus lineages appears to stem from limited outbreaks within small communities so that only a minor fraction of the global susceptible population is infected at any time. As disparate communities become increasingly connected through globalization, interaction and competition between lineages might increase as well, which could result in changing selective pressures and increased diversification and/or pathogenicity. Thus, in addition to zoonotic events, ongoing surveillance of familiar, endemic viruses appears to merit global attention with respect to the prevention or mitigation of future pandemics. SignificanceNumerous pathogenic viruses are endemic in humans and cause a broad variety of diseases, but what is their potential of causing new pandemics? We show that most human pathogenic RNA viruses form multiple, co-circulating lineages with low turnover rates. These lineages appear to be largely noncompeting and occupy distinct epidemiological niches that are not regionally or seasonally defined, and their persistence appears to stem from limited outbreaks in small communities so that a minor fraction of the global susceptible population is infected at any time. However, due to globalization, interaction and competition between lineages might increase, potentially leading to increased diversification and pathogenicity. Thus, endemic viruses appear to merit global attention with respect to the prevention of future pandemics.

evolutionary biology↗

bioRxiv2021

Diverse and rapidly evolving viral strategies modulate arthropod vector gene expression

Vector-borne viral diseases threaten human and wildlife worldwide. Vectors are often viewed as a passive syringe injecting the virus, however to survive, replicate and spread, viruses must manipulate vector biology. While most vector-borne viral research focuses on vectors transmitting a single virus, in reality vectors often carry diverse viruses. Yet how viruses affect the vectors remains poorly understood. Here we focused on the varroa mite, an emergent parasite that vectors over 20 honey bee viruses, and has been responsible for colony collapses worldwide, as well as changes in global viral populations. Co-evolution of the varroa and the viral community makes it possible to investigate whether viruses affect vector gene expression, and whether these interactions affect viral epidemiology. Using a large set of available varroa transcriptomes we identified how abundances of individual viruses affect the vectors transcriptional network. Perhaps surprisingly, we found no evidence of competition between viruses, but rather that some virus abundances are positively correlated. Furthermore, we found a strong correlation between the extent to which a virus interacts with the vectors gene expression and co-occurrence with other viruses, suggesting that interactions with the vector affect epidemiology. We experimentally validated this observation by silencing candidate genes using RNAi and found that reduction in varroa gene expression was accompanied by a change in viral load. Combined, the meta-transcriptomic analysis and experimental results shed light on the mechanism by which viruses interact with each other and with their vector to shape the disease course.

evolutionary biology↗

bioRxiv2022

Optimized phylogenetic clustering of HIV-1 sequence data for public health applications

Clusters of genetically similar infections suggest rapid transmission and may indicate priorities for public health action or reveal underlying epidemiological processes. However, clusters often require user-defined thresholds and are sensitive to non-epidemiological factors, such as non-random sampling. Consequently the ideal threshold for public health applications varies substantially across settings. Here, we show a method which selects optimal thresholds for phylogenetic (subset tree) clustering based on population. We evaluated this method on HIV-1 pol datasets (n = 14,221 sequences) from four sites in USA (Tennessee, Seattle), Canada (Northern Alberta) and China (Beijing). Clusters were defined by tips descending from an ancestral node (with a minimum bootstrap support of 95%) through a series of branches, each with a length below a given threshold. Next, we used pplacer to graft new cases to the fixed tree by maximum likelihood. We evaluated the effect of varying branch-length thresholds on cluster growth as a count outcome by fitting two Poisson regression models: a null model that predicts growth from cluster size, and an alternative model that includes mean collection date as an additional covariate. The alternative model was favoured by AIC across most thresholds, with optimal (greatest difference in AIC) thresholds ranging 0.007-0.013 across sites. The range of optimal thresholds was more variable when re-sampling 80% of the data by location (IQR 0.008 - 0.016, n = 100 replicates). Our results use prospective phylogenetic cluster growth and suggest that there is more variation in effective thresholds for public health than those typically used in clustering studies.

bioinformatics↗

bioRxiv2022

Xeno-monitoring of molecular drivers of artemisinin and partner drug resistance in P. falciparum populations in malaria vectors across Cameroon

BackgroundMonitoring of drug resistance in Plasmodium populations is crucial for malaria control. This has primarily been performed in humans and rarely in mosquitoes where parasites genetic recombination occurs. Here, we characterized the Plasmodium spp populations in wild Anopheles vectors by analyzing the genetic diversity of the P. falciparum kelch13 and mdr1 gene fragments implicated in artemisinin and partner drug resistance across Cameroon in three major malaria vectors. MethodsAnopheles mosquitoes were collected across nine localities in Cameroon and dissected into the head/thorax (H/T) and abdomen (Abd) after species identification. A TaqMan assay was performed to detect Plasmodium infection. Fragments of the Kelch 13 and mdr1 genes were amplified in P. falciparum positive samples and directly sequenced to assess their drug resistance polymorphisms and genetic diversity profile. ResultsThe study revealed a high Plasmodium infection rate in the major Anopheles vectors across Cameroon. Notably, An. funestus vector recorded the highest sporozoite (8.02%) and oocyst (14.41%) infection rates. A high P. falciparum sporozoite rate (80.08%) alongside epidemiological signatures of significant P. malariae (15.94%) circulation were recorded in these vectors. Low genetic diversity with six (A578S, R575I, G450R, L663L, G453D, N458D) and eight (H53H, V62L, V77E, N86Y, G102G, L132I, H143H, Y184F) point mutations were observed in the k13 and mdr1 backbones respectively. Remarkably, the R575I (4.44%) k13 and Y184F (64.2%) mdr1 mutations were the predominant variants in the P. falciparum populations. ConclusionThe emerging signal of the R575I polymorphism in the Pfk13 propeller backbone entails the regular surveillance of molecular markers to inform evidence-based policy decisions. Moreover, the high frequency of the 86N184F allele highlights concerns on the plausible decline in efficacy of artemisinin-combination therapies (ACTs); further implying that parasite genotyping from mosquitoes can provide a more relevant scale for quantifying resistance epidemiology in the field.

genomics↗

bioRxiv2022

An intergeneric recombinant geminivirus causes soybean stay-green disease

Soybean is one of the most valuable legume crops in the world with high nutritional value. Recently, the outbreak of soybean stay-green syndrome has swept the soybean production in the Huang-Huai-Hai region of China, resulting in huge yield losses, which has become an epidemic and prominent problem in soybean production. However, the cause of the stay-green syndrome remains obscure. Here, we report a novel intergeneric recombinant geminivirus which causes soybean stay-green symptoms. Viral small RNA-based screening identified a new recombinant geminvirus from field soybean stay-green samples. The complete genome sequence of the virus contains 2762 nucleotide (nt) and appears to be an intergeneric recombinant virus in which protein coding for coat protein (V1) is similar to member of genus Mastrevirus, whereas proteins coding for V2, C2, C3 are most similar to those of viruses in the Maldovirus genus, and C1 and C4 are most similar to virus in genus Begomovirus. Inoculation of the infectious clone of the recombinant geminivirus through Agrobacterium rhizogenes causes typical soybean stay-green syndrome which resembles field symptoms including delayed leaf senescence, flat pods and abnormal seeds. The recombinant geminivirus can be detected in seed coat but not in cotyledon and embryo, thus failing to be transmitted by seeds. Moreover, the genome variation and epidemiological dynamic analysis were also carried out to help the continuous epidemiological surveillance of this emerging geminivirus. Collectively, this new geminivirus is tentatively named soybean stay-green associated virus (SoSGV). Our determination of the causal agent of soybean stay-green disease will bolster efforts to develop effective management strategies to control this prevalent disease in the field.

microbiology↗

bioRxiv2022

Variational phylodynamic inference using pandemic-scale data

The ongoing global pandemic has sharply increased the amount of data available to researchers in epidemiology and public health. Unfortunately, few existing analysis tools are capable of exploiting all of the information contained in a pandemic-scale data set, resulting in missed opportunities for improved surveillance and contact tracing. In this paper, we develop the variational Bayesian skyline (VBSKY), a method for fitting Bayesian phylodynamic models to very large pathogen genetic data sets. By combining recent advances in phylodynamic modeling, scalable Bayesian inference and differentiable programming, along with a few tailored heuristics, VBSKY is capable of analyzing thousands of genomes in a few minutes, providing accurate estimates of epidemiologically relevant quantities such as the effective reproduction number and overall sampling effort through time. We illustrate the utility of our method by performing a rapid analysis of a large number of SARS-CoV-2 genomes, and demonstrate that the resulting estimates closely track those derived from alternative sources of public health data.

evolutionary biology↗

bioRxiv2022

Target-enrichment sequencing yields valuable genomic data for difficult-to-culture bacteria of public health importance

Genomic data contribute invaluable information to the epidemiological investigation of pathogens of public health importance. However, whole genome sequencing (WGS) of bacteria typically relies on culture, which represents a major hurdle for generating such data for a wide range of species for which culture is challenging. In this study, we assessed the use of culture-free target-enrichment sequencing as a method for generating genomic data for two bacterial species: 1) Bacillus anthracis, which causes anthrax in both people and animals and whose culture requires high level containment facilities; and 2) Mycoplasma amphoriforme, a fastidious emerging human respiratory pathogen. We obtained high quality genomic data for both species directly from clinical samples, with sufficient coverage (>15X) for confident variant calling over at least 80% of the baited genomes for over two thirds of the samples tested. Higher qPCR cycle threshold (Ct) values (indicative of lower pathogen concentrations in the samples), pooling libraries prior to capture, and lower captured library concentration were all statistically associated with lower capture efficiency. The Ct value had the highest predictive value, explaining 52% of the variation in capture efficiency. Samples with Ct values [≤] 30 were over 6 times more likely to achieve the threshold coverage than those with a Ct > 30. We conclude that target-enrichment sequencing provides a valuable alternative to standard WGS following bacterial culture and creates opportunities for an improved understanding of the epidemiology and evolution of many clinically important pathogens for which culture is challenging. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Scripts used in this study can be accessed on GitHub at https://github.com/tristanpwdennis/bactocap. All sequence data generated during this study have been deposited in the European Nucleotide Archive (ENA) Sequence Read Archive (SRA) under project accession numbers PRJEB46822 (B. anthracis) and PRJEB50216 (M. amphoriforme). Accession numbers for individual samples, along with metadata, laboratory parameters and sequence quality metrics, are available at the University of Glasgows data repository, Enlighten, at http://dx.doi.org/10.5525/gla.researchdata.1249.

molecular biology↗

bioRxiv2022

Close-kin mark-recapture methods to estimate demographic parameters of mosquitoes

Close-kin mark-recapture (CKMR) methods have recently been used to infer demographic parameters such as census population size and survival for fish of interest to fisheries and conservation. These methods have advantages over traditional mark-recapture methods as the mark is genetic, removing the need for physical marking and recapturing that may interfere with parameter estimation. For mosquitoes, the spatial distribution of close-kin pairs has been used to estimate mean dispersal distance, of relevance to vector-borne disease transmission and novel biocontrol strategies. Here, we extend CKMR methods to the life history of mosquitoes and comparable insects. We derive kinship probabilities for mother-offspring, father-offspring, full-sibling and half-sibling pairs, where an individual in each pair may be a larva, pupa or adult. A pseudo-likelihood approach is used to combine the marginal probabilities of all kinship pairs. To test the effectiveness of this approach at estimating mosquito demographic parameters, we develop an individual-based model of mosquito life history incorporating egg, larva, pupa and adult life stages. The simulation labels each individual with a unique identification number, enabling close-kin relationships to be inferred for sampled individuals. Using the dengue vector Aedes aegypti as a case study, we find the CKMR approach provides unbiased estimates of adult census population size, adult and larval mortality rates, and larval life stage duration for logistically feasible sampling schemes. Considering a simulated population of 3,000 adult mosquitoes, estimation of adult parameters is accurate when ca. 40 adult females are sampled biweekly over a three month period. Estimation of larval parameters is accurate when adult sampling is supplemented with ca. 120 larvae sampled biweekly over the same period. The methods are also effective at detecting intervention-induced increases in adult mortality and decreases in population size. As the cost of genome sequencing declines, CKMR holds great promise for characterizing the demography of mosquitoes and comparable insects of epidemiological and agricultural significance. Author summaryClose-kin mark-recapture (CKMR) methods are a genetic analogue of traditional mark-recapture methods in which the frequency of marked individuals in a sample is used to infer demographic parameters such as census population size and mean dispersal distance. In CKMR, the mark is a close-kin relationship between individuals (parents and offspring, siblings, etc.). While CKMR methods have mostly been applied to aquatic species to date, opportunities exist to apply them to insects and other terrestrial species. Here, we explore the application of CKMR to mosquitoes, with Aedes aegypti, a primary vector of dengue, chikungunya and yellow fever, as a case study. By analyzing simulated Ae. aegypti populations, we find the CKMR approach provides unbiased estimates of adult census population size, adult and larval mortality rates, and larval life stage duration, and may be informative of intervention impact. Optimal sampling schemes are compatible with Ae. aegypti ecology and field studies. This study represents the first theoretical exploration of the application of CKMR to an insect species, and demonstrates its potential for characterizing the demography of insects of epidemiological and agricultural importance.

ecology↗

bioRxiv2022

The Neisseria meningitidis iron acquisition protein HpuA moonlights as an adhesin and inhibits host cell migration

Neisseria meningitidis can cause meningococcal disease, a rapidly developing and potentially fatal infection. Despite this, it normally resides as a commensal in the nasopharynx of healthy individuals. The mechanisms by which meningococci access deeper tissues remain unknown. Epidemiological data suggest that mucosal disruptions increase the risk of meningococcal disease. We previously investigated whether meningococci inhibit host cell wound repair, enhancing invasive disease risk. Here, using genome sequencing and a collection of closely related household isolates that differ in their ability to inhibit host wound repair, we identify the responsible meningococcal factor. This protein, HpuA, has previously been characterized as part of a bipartite heme acquisition transporter. We constructed mutants to demonstrate that HpuA, but not HpuB, inhibits wound repair, acts as an adhesin for epithelial cells, and promotes cellular invasion. We showed this was not due to iron starvation resulting from the bacteria, differences in growth rate, or manipulation of host haptoglobin. Heterologous expression of HpuA in E. coli mediated adherence to 16HBE cells in an HpuA-dependent manner and conferred an aggregative phenotype onto E. coli, suggesting that HpuA may play a role in the formation of microcolonies on host cells. We also demonstrated that iron supplementation of meningococci restored the inhibition of wound repair in strains lacking HpuA (NZCM112, {Delta}hpuA mutant) to levels seen with the wild type. This was also seen with unrelated carriage strains previously shown not to inhibit wound repair. Iron supplementation also increased adherence and invasion of meningococci for strains lacking HpuA, while not affecting those that expressed HpuA. These findings suggest there may be a second meningococcal protein that inhibits wound repair. Together, these results suggest that HpuA is an important meningococcal virulence factor with multiple moonlighting functions, mediating adherence, invasion, inhibition of wound repair, and bacterial aggregation. Author SummaryNeisseria meningitidis causes meningococcal disease, a potentially fatal and rapidly developing illness that most often occurs in children. Despite this, the bacteria are frequently carried harmlessly as part of the normal airway microflora in healthy people, only rarely causing invasive disease, which involves replication in the bloodstream or central nervous system. It remains unknown precisely how the bacteria reach the deeper tissues from the airways, though some epidemiological evidence suggests that wounds or disruptions to the airways may increase risk. Here, we show that a N. meningitidis protein, HpuA, moonlights from its usual job of acquiring nutrients from the host, to enable the bacteria to adhere to and invade host cells, as well as inhibiting wound closure. Furthermore, we also show that meningococci that lack HpuA acquire the ability to inhibit wound repair when they are supplemented with iron, suggesting that there are additional meningococcal proteins to be discovered that may inhibit wound repair.

microbiology↗

bioRxiv2022

Comparative Genomic Analysis of Salmonella enterica serovar Typhimurium from Passerines Reveals Two Lineages Circulating in Europe, New Zealand, and the United States

Salmonella enterica serovar Typhimurium from passerines have caused wild bird mortality and human salmonellosis outbreaks in Europe, Oceania, and North America. Here, we performed comparative genomic analysis to explore the emergence, genetic relationship, and evolution of geographically dispersed passerine isolates. We found that passerine isolates from Europe and the United States clustered to form two lineages (EU and US passerine lineages), which were distinct from major S. Typhimurium lineages circulating in other diverse hosts (e.g., humans, cattle, pigs, chicken, other avian hosts such as pigeons and ducks). Further, passerine isolates from New Zealand clustered to form a sublineage (NZ passerine lineage) of the US passerine lineage. We inferred that the passerine isolates mutated at a rate of 3.2 x 10-7 substitutions/site/year, and the US, EU, and NZ passerine lineages emerged in ca. 1952, 1970, and 1996, respectively. Isolates from the three lineages presented genetic similarity such as lack of antimicrobial resistance genes and accumulation of same virulence pseudogenes. In addition, genetic diversity due to microevolution existed in the three passerine lineages. Specifically, pseudogenization in type 1 fimbrial gene fimC (deletion of G at position 87) was only detected in the US and NZ passerine isolates, while a single-base deletion in type 3 secretion system effector genes (i.e., gogB, sseJ, and sseK2) solely concurred in the EU passerine isolates. These findings provide insights into evolution, host adaptation, and epidemiology of S. Typhimurium in passerines. IMPORTANCEPasserine-associated S. Typhimurium have been linked to human salmonellosis outbreaks in recent years. Here we investigated the phylogenetic relationship of globally distributed passerine isolates and profiled their genomic similarity and diversity. Our study reveals two passerine-associated S. Typhimurium lineages circulating in Europe, Oceania, and North America. Isolates from the two lineages presented phylogenetic and genetic signatures that were distinct from isolates of other hosts. The findings shed light on host adaptation of S. Typhimurium in passerines and are important for source attribution of S. Typhimurium to avian hosts. Further, we found S. Typhimurium definitive phage type (DT) 160 from passerines that caused decade-long human salmonellosis outbreaks in New Zealand and Australia formed a sublineage of the US passerine lineage, suggesting that DT160 may have originated from passerines outside Oceania. Our study demonstrates the importance of whole-genome sequencing and genomic analysis of historical microbial collections to modern day epidemiologic surveillance.

microbiology↗

bioRxiv2022

A re-emerging arbovirus in livestock in China: Early genomic surveillance and phylogeographic analysis

Viruses in livestock represent a great risk to public health due to the close contact of their hosts with humans and the potential long-range transportation though animal trade. Here, we show how to predict outbreaks of potential zoonotic pathogens and use spatially-explicit phylogeographic and phylodynamic approaches to provide estimates of key epidemiological parameters. First, we use metagenomic next generation sequencing (mNGS) to identify a Getah virus (GETV) as the pathogen responsible for a re-emerging swine disease in China. The GETV isolate is able to replicate in a variety of cell lines including human cells and shows high pathogenicity in a mouse model suggesting a potential public health risk. We obtained 16 complete genomes and 78 E2 gene sequences from viral strains collected within China from 2017 to 2021 through large-scale surveillance among livestock, pets and mosquitoes. Moreover, phylogenetic analysis reveals that three major GETV lineages are responsible for the current epidemic in livestock in China. We identify three potential positively selected sites and mutations of interest in E2, which may impact the transmissibility and pathogenicity of the virus. We then reconstruct the evolutionary and dispersal history of the virus and test the impact of several environmental factors on the viral genetic diversity through time and on the dispersal dynamic of viral lineages. Of note, we identify temporal variation in livestock meat consumption as a main predictor of viral genetic diversity through time. Finally, phylogeographic analyses indicate that GETV preferentially circulates within areas associated with relatively higher mean annual temperature and pig population density. Our results highlight the importance of continuous surveillance of GETV among livestock in southern Chinese regions associated with relatively high temperatures, and the need to control mosquitoes in the livestock farms. Our analyses of GETV also provide a baseline for future studies of the molecular epidemiology and early warning of emerging arboviruses in China.

evolutionary biology↗

bioRxiv2022

Dispersion and Plant Arrangement Condition the Timing and Magnitude of Coffee Rust Infection

One central issue in coffee-leaf rust (Hemileia vastatrix) epidemiology is to understand what determines the intensity and the timing of yearly infections in coffee plantations. However, most experimental and theoretical studies report infection as an average at the plot level, obscuring the role of potentially key factors like rust dispersal or the planting pattern. Here, we first review the rust epidemic patterns of different sites, which reveal large variability in the duration and magnitude of the different epidemiologic phases. We then present a spatially explicit and parametrised model, where the host population is subdivided into discrete patches linked through spore dispersal, modelled as simple diffusion. With this model, we study the role of the planting arrangement, the dispersal intensity and plant-level variables on the maximum average tree infection (MATI) and its timing. Our results suggest that the epidemic timeline can be divided into two phases: a time lag and a growth phase per se. The model shows that the combination of the dispersal magnitude and plant aggregation modifies the MATI and the time to MATI, mainly by preventing some plants from reaching their maximum peak during the epidemic. It also affects the epidemic curves, which can have a stepped, or a rather smooth pattern in plots with otherwise similar conditions. The initial rust infection modulates the time lag before the epidemic and the infected leaf-fall rate drastically changes the MATI. These findings highlight the importance of explicitly considering the spatial aspects of coffee agroecosystems when measuring and managing rust infection, and help us to further understand the spatio-temporal dynamics of ecological systems in general.

systems biology↗

bioRxiv2022

Modelling the spread and mitigation of an emerging vector-borne pathogen:citrus greening in the U.S.

Predictive models, based upon epidemiological principles and fitted to surveillance data, play an increasingly important role in shaping regulatory and operational policies for emerging outbreaks. Data for parameterising these strategically important models are often scarce when rapid actions are required to change the course of an epidemic invading a new region. We provide a flexible toolkit for landscape-scale disease management, which is applicable to a range of emerging pathogens including vector-borne pathogens for both endemic and invading epidemic vectors. We use the toolkit to analyse and predict the spread of Huanglongbing disease or citrus greening in the U.S. We estimate epidemiological parameters using survey data from one region (Texas) and show how to transfer and test parameters to construct predictive spatio-temporal models for another region (California). The models are used to screen effective coordinated and reactive management strategies for different regions.

ecology↗

bioRxiv2022

SOPHIE: viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework

Genomic epidemiology is now widely used for viral outbreak investigations. Still, this methodology faces many challenges. First, few methods account for intra-host viral diversity. Second, maximum parsimony principle continues to be employed, even though maximum likelihood or Bayesian models are usually more consistent. Third, many methods utilize case-specific data, such as sampling times or infection exposure intervals. This impedes study of persistent infections in vulnerable groups, where such information has a limited use. Finally, most methods implicitly assume that transmission events are independent, while common source outbreaks violate this assumption. We propose a maximum likelihood framework SOPHIE (SOcial and PHilogenetic Investigation of Epidemics) based on integration of phylogenetic and random graph models. It infers transmission networks from viral phylogenies and expected properties of inter-host social networks modelled as random graphs with given expected degree distributions. SOPHIE is scalable, accounts for intra-host diversity and accurately infers transmissions without case-specific epidemiological data. SOPHIE code is freely available at https://github.com/compbel/SOPHIE/

bioinformatics↗

bioRxiv2022

Cysteine Restriction-Specific Effects of Sulfur Amino Acid Restriction on Lipid Metabolism

Decreasing dietary intake of methionine exerts robust anti-adiposity effects in rodents but modest effects in humans. Since cysteine can be synthesized from methionine, animal diets are formulated by decreasing methionine and eliminating cysteine. Such diets exert both methionine restriction (MR) and cysteine restriction (CR), i.e., sulfur amino acid restriction (SAAR). Contrarily, human diets used in clinical studies did not eliminate cysteine and thus might have exerted only MR. Epidemiological studies positively correlate body adiposity with plasma cysteine but not with methionine, suggesting that CR, but not MR, is responsible for the antiadiposity effects of SAAR in rodents. Whether this is true, and if so, the underlying mechanisms are unknown. Using multiple diets with variable concentrations of methionine and cysteine, we demonstrate that the anti-adiposity effects of SAAR are due to CR. CR increased serinogenesis (serine biosynthesis from non-glucose substrates) by diverting substrates from glyceroneogenesis, essential for fatty acid/triglyceride cycling. Molecular data suggest that the CR results in glutathione depletion, which induces Nrf2 and downstream targets Phgdh (the serine biosynthetic enzyme) and Pepck-M. Using multiple mouse models, we show that the magnitude of SAAR-induced changes in molecular markers depends on dietary fat concentration (60 fat>10% fat), gender (males>females), and age-at-onset (young>adult). Our findings are translationally relevant as we found a negative correlation of plasma serine with triglycerides and metabolic syndrome criteria in a cross-sectional epidemiological study. SAAR-like diets with high polyunsaturated fatty acids increased plasma serine in a short-term human feeding study. Serinogenesis might be a potential target to correct hypertriglyceridemia.

biochemistry↗

bioRxiv2022

The role of the environment in transmission of antimicrobial resistance between humans and animals: a modelling study

BackgroundAntimicrobial resistance can be transmitted between animals and humans both directly or indirectly, through transmission via the environment (such as fomites or sewage). However, there is a lack of understanding of, and quantitative evidence about, the contribution of the environment to AMR epidemiology. In this study we incorporate the transmission of resistance via the environment into a mathematical model to study the potential importance of this form of transmission for human resistance levels and any effects of the impact of interventions to reduce antibiotic consumption in animals. MethodsWe developed a compartmental model of human-animal AMR transmission with an additional environmental compartment. We compared the outcomes of this model under different human-animal-environment transmission scenarios, conducted a sensitivity analysis, and investigated the impact of curtailing antibiotic usage in animals on resistance levels in humans. ResultsOur findings suggest that human resistance levels are most sensitive to both parameters associated with the human compartment (rate of loss of resistance from humans) and parameters associated with the environmental compartment (rate of loss of resistance from the environment and the transmission rate from the environment to humans). The impact of curtailing antibiotic consumption in animals on long term prevalence of AMR in humans was weaker when environmental transmission was assumed to be high. ConclusionsThis study highlights that environment-human sharing of resistance can influence the epidemiology of resistant bacterial infections in humans and reduce the impact of interventions that curtail antibiotic consumption in animals. More data on the types and dynamics of resistance in the environment and frequency of human-environment transmission is crucial to understanding the population dynamics of antibiotic resistance.

microbiology↗

bioRxiv2022

Global predictions for the risk of establishment of Pierce's disease of grapevines

The vector-borne bacterium Xylella fastidiosa is responsible for Pierces disease (PD), a lethal grapevine illness that originated in the Americas. The international plant trade is expanding the geographic range of this pathogen, posing a new threat to viticulture worldwide. To assess the potential incidence of PD, we have built a dynamic epidemiological model based on the response of 36-grapevine varieties to the pathogen in inoculation assays and on the vectors distribution when this information is available. Key temperature-driven epidemiological processes, such as PD symptom development and recovery, are mechanistically modelled. Integrating into the model highresolution spatiotemporal climatic data from 1981 onward and different infectivity (R0) scenarios, we show how the main wine-producing areas thrive mostly in non-risk, transient, or epidemic-risk zones with potentially low growth rates in PD incidence. Epidemic-risk zones with moderate to high growth rates are currently marginal outside the United States. However, a global expansion of epidemic-risk zones coupled with small increments in the disease growth rate is projected for 2050. Our study globally downscales the risk of PD establishment while highlighting the importance of considering climate variability, vector distribution and an invasive criterion in obtaining accurate risk maps to guide policy decision-making in plant health.

plant biology↗