Biology subjects

Davidson, J.

Publications and source records attributed to Davidson, J..

At least 19 recordsLinked to original sources

bioRxiv2025

Intrinsic strain-specific behaviour predicts emergent collective aggregation in heterogeneous C. elegans groups

Collective animal behaviour research to date typically specifies members of the group as identical individuals, even though within group heterogeneity is commonplace. We exploit the tractable C. elegans study system to explicitly define and manipulate heterogeneity to investigate how individuals with different behavioural phenotypes interact and aggregate in heterogeneous group settings. Using controlled mixing experiments between pairs of strains that have defined aggregation tendencies, we apply a quantitative behavioural analysis framework and show that individuals maintain their intrinsic movement patterns and interaction rules regardless of group composition. Notably, neither behavioural differences nor distant genetic relatedness between strains lead to a modulation of individual behaviour; instead, distinct strains behave and coexist without influencing each others intrinsic behavioural tendencies. Using a simulation model, we further show that aggregation in mixed C. elegans groups can be accurately predicted from strain-specific individual-level parameters measured in homogeneous settings. Our integrated approach provides a generalised framework for understanding collective behaviour in diverse heterogeneous systems, which may offer insights into population-level consequences of phenotypic variation and broader ecological processes.

animal behavior and cognition↗

bioRxiv2024

Prenatal VEGF Nano-Delivery Reverses Congenital Diaphragmatic Hernia-Associated Pulmonary Abnormalities

RationaleCongenital diaphragmatic hernia (CDH) results in lung hypoplasia. In severe cases, tracheal occlusion (TO) can be offered to promote lung growth. However the benefit is limited, and novel treatments are required to supplement TO. Vascular endothelial growth factor (VEGF) is downregulated in animal models of CDH and could be a therapeutic target, but its role in human CDH is not known. ObjectivesTo investigate whether VEGF supplementation could be a suitable treatment for CDH-associated lung pathology. MethodsFetal lungs from CDH patients were used to determine pulmonary morphology and VEGF expression. A novel human ex vivo model of fetal lung compression recapitulating CDH features was developed and used to determine the effect of exogenous VEGF supplementation (Figure 1A). A nanoparticle-based approach for intra-pulmonary delivery of VEGF was developed by conjugating it on functionalized nanodiamonds (ND-VEGF) and was tested in experimental CDH in vivo. O_FIG O_LINKSMALLFIG WIDTH=138 HEIGHT=200 SRC="FIGDIR/small/581170v1_fig1.gif" ALT="Figure 1"> View larger version (77K): org.highwire.dtl.DTLVardef@2ba882org.highwire.dtl.DTLVardef@4413d2org.highwire.dtl.DTLVardef@17155aborg.highwire.dtl.DTLVardef@1af7c73_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1C_FLOATNO (A) Schematic of the study design based on the analysis of the early-stage CDH fetal lung sections to assess early hypoplasia and VEGF impairment. In parallel, a human compression-based CDH model will be developed to validate the CDH phenotype and test a therapeutical approach to rescue lung hypoplasia. (B) H&E analysis of 18 and 22 pcw post-mortem CDH human lung tissue reveals impaired epithelial development compared to control healthy tissue at matching developmental stages. Scale bar 100m. (C) Morphometric analysis of CDH and healthy lung tissue at 18-22 pcw reveals decreased values of volume densities of air space (Vair%) and corresponding higher values of volume densities of alveolar septa (Vsep%) in CDH tissues compared to healthy tissue at the same developmental stages. A similar trend can be observed for the mean linear intercept of air space (Lma%) and its corresponding mean linear intercept of septal thickness (Lmw%). (D) Histologic analysis of VEGFA, KDR, Ki67 and NKX2-1 markers in normal and CDH fetal lung tissue at 18 and 22 pcw. Scale bar 100m. (E) Quantification of epithelial VEGFA and KDR expression reported in D shows a significant decrease for both markers in CDH compared to healthy samples. Correspondingly, the percentage of Ki67-positive epithelial cells is significantly lower in CDH compared to healthy samples, with no significant differences in the number of NKX2-1-positive cells. ***<p=0.001. (F) Immunofluorescence analysis of ECAD in normal and CDH fetal lung tissue at 18 and 22 pcw. Scale bar 100m. (G) Quantification of epithelial nuclear density based on results in Figure F shows no significant differences between CDH and healthy tissue. C_FIG Measurements and Main ResultsVEGF expression was downregulated in distal pulmonary epithelium of human CDH fetuses in conjunction with attenuated cell proliferation. The compression model resulted in impaired branching morphogenesis similar to CDH and downregulation of VEGF expression in conjunction with reduced proliferation of terminal bud epithelial progenitors; these could be reversed by exogenous supplementation of VEGF. Prenatal delivery of VEGF with the ND-VEGF platform in CDH fetal rats resulted in lung growth and pulmonary arterial remodelling that was complementary to that achieved by TO alone with appearances comparable to healthy controls. ConclusionsThis innovative approach could have a significant impact on the treatment of CDH.

bioengineering↗

bioRxiv2023

Modulation of hepatic transcription factor EB activity during cold exposure uncovers direct regulation of bis(monoacylglycerol)phosphate lipids by Pla2g15

Cold exposure is a selective environmental stress that elicits a rapid metabolic shift to maintain energy homeostasis. In response to cold exposure, the liver rewires the metabolic state shifting from glucose to lipid catabolism. By probing the liver lipids in cold exposure, we observed that the lysosomal bis(monoacylglycero)phosphate (BMP) lipids were rapidly increased during cold exposure. BMP lipid changes occurred independently of lysosomal abundance but were dependent on the lysosomal transcriptional regulator transcription factor EB (TFEB). Knockdown of TFEB in hepatocytes decreased BMP lipid levels and led to cold intolerance in mice. We assessed TFEB binding sites of lysosomal genes and determined that the phospholipase Pla2g15 regulates BMP lipid catabolism. Knockdown of Pla2g15 in mice increased BMP lipid levels, ablated the cold-induced rise, and improved cold tolerance. Knockout of Pla2g15 in mice and hepatocytes led to increased BMP lipid levels, that were decreased with re-expression of Pla2g15. Mutation of the catalytic site of Pla2g15 ablated the BMP lipid breakdown. Together, our studies uncover TFEB regulation of BMP lipids through Pla2g15 catabolism.

biochemistry↗

bioRxiv2023

Genomic DNA extraction optimization and validation for genome sequencing using the marine gastropod Kellet's whelk

Next-generation sequencing technologies, such as Nanopore MinION, Illumina Hiseq and Novaseq, and PacBio Sequel II, hold immense potential for advancing genomic research on non-model organisms, including the vast majority of marine species. However, application of these technologies to marine invertebrate species is often impeded by challenges in extracting and purifying their genomic DNA due to high polysaccharide content and other secondary metabolites. In this study, we help resolve this issue by developing and testing DNA extraction protocols for Kellets whelk (Kelletia kelletii), a subtidal gastropod with ecological and commercial importance, by comparing four DNA extraction methods commonly used in marine invertebrate studies. We identified an optimized protocol that balances efficiency, cost, and DNA extraction quality; the Salting out protocol. We validated the protocol using an independent set of tissue samples, then applied it to extract high-molecular-weight (HMW) DNA from over three thousand Kellets whelk tissue samples. The protocol demonstrated scalability and, with added clean-up, suitability for RAD-seq, GT-seq, as well as whole genome sequencing using both long read (ONT MinION) and short read (Illumina Novaseq) sequencing platforms. Our findings offer a robust and versatile DNA extraction and clean-up protocol for supporting genomic research efforts on non-model marine organisms, to help mediate the under-representation of invertebrates in genomic studies.

genomics↗

bioRxiv2023

Social structure and individuals' behavior shaped by group composition in long-term tracking of rats

Rodents serve as an important model for examining both individual and collective behavior. Dominance within rodent social structures can determine access to critical resources, such as food and mating opportunities. Yet, many aspects of the intricate interplay between individual behaviors and the resulting group social hierarchy, especially its evolution over time, remain unexplored. In this study, we utilized an automated tracking system that continuously monitored groups of male rats for over 250 days to enable an in-depth analysis of individual behavior and the overarching group dynamic. We describe the evolution of social structures within a group and additionally investigate how past behaviors influence the emergence of new social hierarchies when group composition and experimental area changes. Notably, we find that conventional individual and pairwise tests exhibit a weak correlation with group behavior, highlighting their limited accuracy in predicting behavioral outcomes in a collective context. These results emphasize the context-dependence of social behavior as an emergent property of interactions within a group and highlight the need to measure and quantify social behavior in more naturalistic environments.

animal behavior and cognition↗

bioRxiv2022

The use of a graph database is a complementary approach to a classical similarity search for identifying commercially available fragment merges

AO_SCPLOWBSTRACTC_SCPLOWFragment screening using X-ray crystallography can yield rich structural data to help guide the optimization of low-molecular-weight compounds into more potent binders. Fragment merging, whereby substructural motifs from partially overlapping fragments are incorporated into a single larger compound, represents a potentially powerful and efficient approach for increasing potency. Searching commercial catalogues provides one useful way to quickly and cheaply identify follow-up compounds for purchase and further screening, and circumvents the challenge of synthetic accessibility. The Fragment Network is a graph database that provides a novel way to explore the chemical space surrounding fragment hits. We use an iteration of the database containing >120 million catalogue compounds to find fragment merges for four XChem fragment screening campaigns. Retrieved molecules were filtered using a pipeline of 2D and 3D filters and contrasted against a traditional fingerprint-based similarity search. The two search techniques were found to have complementary results, identifying merges in different regions of chemical space. Both techniques were able to identify merges that are predicted to replicate the interactions made by the parent fragments. This work demonstrates the use of the Fragment Network to increase the yield of fragment merges beyond that of a classical catalogue search, thus increasing the likelihood of finding promising follow-up compounds. We present a pipeline that is able to systematically exploit all known fragment hits by performing large-scale enumeration of all possible fragment pairs for merging.

bioinformatics↗

bioRxiv2022

Stochastic dynamics of social patch foraging decisions

Animals typically forage in groups. Social foraging can help animals avoid predation and decrease their uncertainty about the richness of food resources. Despite this, theoretical mechanistic models of patch foraging have overwhelmingly focused on the behavior of single foragers. In this study, we develop a mechanistic model that accounts for the behavior of individuals foraging together and departing food patches following an evidence accumulation process. Each individuals belief about patch quality is represented by a stochastically accumulating variable which is coupled to others belief to represent the transfer of information. We consider a cohesive group, and model information sharing by considering both intermittent pulsatile coupling (only communicate decision to leave) and continuous diffusive coupling (communicate throughout the evidence accumulation process). We find that foraging efficiency under pulsatile coupling has a stronger dependence on the coupling strength parameter compared to diffusive. Despite employing minimal information transfer, pulsatile coupling can still provide similar or higher foraging efficiency compared to diffusive coupling. Conversely, since diffusive coupling is more robust to parameter choices, it performs better when individuals have heterogeneous departure criteria and social information weighting. Efficiency is measured by a reward rate function that balances the amount of energy accumulated against the time spent in a patch, computed by solving an ordered first passage time problem for the patch departures of each individual. Using synthetic data we show that we can distinguish between the two modes of communication and identify the model parameters. Our model establishes a social patch foraging framework to parse and identify deliberative decision strategies, to distinguish different forms of social communication, and to allow model fitting to real world animal behavior data.

animal behavior and cognition↗

bioRxiv2022

Real-time dynamic single-molecule protein sequencing on an integrated semiconductor device

Proteins are the main structural and functional components of cells, and their dynamic regulation and post-translational modifications (PTMs) underlie cellular phenotypes. Next-generation DNA sequencing technologies have revolutionized our understanding of heredity and gene regulation, but the complex and dynamic states of cells are not fully captured by the genome and transcriptome. Sensitive measurements of the proteome are needed to fully understand biological processes and changes to the proteome that occur in disease states. Studies of the proteome would benefit greatly from methods to directly sequence and digitally quantify proteins and detect PTMs with single-molecule sensitivity and precision. However current methods for studying the proteome lag behind DNA sequencing in throughput, sensitivity, and accessibility due to the complexity and dynamic range of the proteome, the chemical properties of proteins, and the inability to amplify proteins. Here, we demonstrate single-molecule protein sequencing on a compact benchtop instrument using a dynamic sequencing by stepwise degradation approach in which single surface-immobilized peptide molecules are probed in real-time by a mixture of dye-labeled N-terminal amino acid recognizers and simultaneously cleaved by aminopeptidases. By measuring fluorescence intensity, lifetime, and binding kinetics of recognizers on an integrated semiconductor chip we are able to annotate amino acids and identify the peptide sequence. We describe the expansion of the number of recognizable amino acids and demonstrate the kinetic principles that allow individual recognizers to identify multiple amino acids in a highly information-rich manner that is sensitive to adjacent residues. Furthermore, we demonstrate that our method is compatible with both synthetic and natural peptides, and capable of detecting single amino acid changes and PTMs. We anticipate that with further development our protein sequencing method will offer a sensitive, scalable, and accessible platform for studies of the proteome.

biophysics↗

bioRxiv2021

Uncertainty drives deviations in normative foraging decision strategies

Nearly all animals forage, as it is essential to acquire energy for survival through efficient search and resource harvesting. Patch exploitation is a canonical foraging behavior, but a systematic treatment of how animals cope with uncertainty is lacking. To address these shortcomings, we develop a normative theory of patch foraging decisions, proposing mechanisms by which foraging behaviors emerge in the face of uncertainty. Our model foragers statistically and sequentially infer patch resource yields using Bayesian updating based on their resource encounter history. A decision to leave a patch is triggered when the certainty of the patch type or the estimated yield of the patch fall below a threshold. The timescale over which uncertainty in resource availability persists strongly impacts behavioral variables like patch residence times and decision rules determining patch departures. When patch depletion is slow, as in habitat selection, departures are characterized by a reduction of uncertainty, suggesting the forager resides in a low-yielding patch. Uncertainty leads patch-exploiting foragers to overharvest (underharvest) patches with initially low (high) resource yields in comparison to predictions of the marginal value theorem. These results extend optimal foraging theory and motivate a variety of behavioral experiments investigating patch foraging behavior.

animal behavior and cognition↗

bioRxiv2021

The dominant axes of lifetime behavioral variation in honey bees

Insect colonies are decentralized systems that employ task allocation, whereby individuals undertake different roles to fulfil colony needs, such as honey bee "nurses", "nest workers", and "foragers". However, the extent to which individuals can be well-classified by discrete "roles", how they change behavior from day-to-day, over entire lifetimes, and with environmental conditions, is poorly understood. Using long-term automated tracking of over 4,200 individually-identified bees Apis mellifera, we use behavioral metrics to quantify and compare behavior. We show that individuals exhibit behavioral variation along two dominant axes that represent nest substrate use and movement within the nest. Across lifetimes, we find that individuals differ in foraging onset, and that certain bees exhibit lifelong consistencies in their movement patterns. Furthermore, we examine a period of sudden nectar availability where the honey stores tripled over 6 days, and see that the colony exhibits a distributed shift in activity that did not require a large-scale colony reorganization. Our quantitative approach shows how collective units differ over days and lifetimes, and how sources of variation and variability contribute to the colonys robust yet flexible response.

animal behavior and cognition↗

bioRxiv2020

Current population structure and pathogenicity patterns of Ascochyta rabiei in Australia

Ascochyta blight disease, caused by the necrotrophic fungus Ascochyta rabiei, is a major biotic constraint to chickpea production in Australia and worldwide. Detailed knowledge of the structure of the pathogen population and its potential to adapt to our farming practices is key to informing optimal management of the disease. This includes understanding the molecular diversity among isolates and the frequency and distribution of the isolates that have adapted to overcome host resistance across agro-geographically distinct regions. Thanks to continuous monitoring efforts over the past six years, a comprehensive collection of A. rabiei isolates was collated from the major Australian production regions. To determine the molecular structure of the entire population, representative isolates from each collection year and growing region have been genetically characterised using a DArTseq genotyping-by-sequencing approach. The genotyped isolates were further phenotyped to determine their pathogenicity levels against a differential set of chickpea cultivars and genotype-phenotype associations were inferred. Overall, the Australian A. rabiei population displayed a far lower genetic diversity (average Neis gene diversity of 0.047) than detected in other populations worldwide. This may be explained by the presence of a single mating-type in Australia, MAT1-2, limiting its reproduction to a clonal mode. Despite the low detected molecular diversity, clonal selection appears to have given rise to a subset of adapted isolates that are highly pathogenic on commonly employed resistance sources, and that are occurring at an increasing frequency. To better understand the mechanisms and patterns of the pathogen adaptation, multi-locus genotype analysis was performed and two hypotheses were proposed on how new genotypes emerge. These were: 1) In a local, within-region evolutionary pathway; or 2) Through inter-region dispersal, most likely due to human activities. Furthermore, a cluster of genetically similar isolates was identified, with a higher proportion of highly aggressive isolates than in the general population, indicating the adaptive evolution of a sub-set of isolates that pose a greater risk to the chickpea industry. The discovery of distinct genetic clusters associated with high and low isolate pathogenicity forms the foundation for the development of a molecular pathotyping tool for the Australian A. rabiei population. Application of such a tool, along with continuous monitoring of the genetic structure of the population will provide crucial information for the screening of breeding material and integrated disease management packages. Data SummaryAn online dataset containing all supporting genotyping and phenotyping data and the code required to reproduce the results, summary tables and plots found in this publication, is publicly available at Zenodo via the following links: https://zenodo.org/record/4311477; DOI: 10.5281/zenodo.4311477 (1).

genomics↗

bioRxiv2020

Evidence of recent increased pathogenicity within the Australian Ascochyta rabiei population

Ascochyta Blight (AB), caused by Ascochyta rabiei (syn Phoma rabiei), is the major endemic foliar fungal disease affecting the Australian chickpea industry, resulting with potential crop loss and management costs. This study was conducted to better understand the risk posed by the Australian A. rabiei population to current resistance sources and to provide informed decision support for chemical control strategies. Recent changes in the pathogenicity of the population were proposed based on disease severity and histopathological observations on a host set. Controlled environment disease screening of 201 isolates on the host set revealed distinct pathogenicity groups, with 41% of all isolates assessed as highly aggressive and a significant increase in the proportion of isolates able to cause severe damage on resistant and moderately resistant cultivars since 2013. In particular, the frequency of highly aggressive isolates on the widely adopted PBA HatTrick cultivar rose from 18% in 2013 to 68% in 2017. In addition, isolates collected since 2016 caused severe disease on Genesis 090, another widely adopted moderately resistant cultivar and on ICC3996, a commonly used resistance source. Of immediate concern was the 10% of highly aggressive isolates able to severely damage the recently released resistant cultivar PBA Seamer (2016). Histopathology studies revealed that the most aggressive isolates were able to germinate, develop appressoria and invade directly through the epidermis faster than lower aggressive isolates on all hosts assessed, including ICC3996. The fungal invasion triggered a common reactive oxygen species (ROS) and hypersensitive response (HR) on all assessed resistant genotypes with initial biochemical and subsequent structural defence responses initiated within 24 hours of inoculation by the most highly aggressive isolates. These responses were much faster on the less resistant and fastest on the susceptible check host, indicating that speed of recognition was correlated with resistance rating. This will inform fungicide application timing so that infected crops are sprayed with prophylactic chemistries prior to invasion and with systemic chemistries after the pathogen has invaded.Competing Interest StatementThe authors have declared no competing interest.View Full Text

plant biology↗

bioRxiv2020

Normative theory of patch foraging decisions

Foraging is a fundamental behavior as animals search for food is crucial for their survival. Patch leaving is a canonical foraging behavior, but classic theoretical conceptions of patch leaving decisions lack some key naturalistic details. Optimal foraging theory provides general rules for when an animal should leave a patch, but does not provide mechanistic insights about how those rules change with the structure of the environment. Such a mechanistic framework would aid in designing quantitative experiments to unravel behavioral and neural underpinnings of foraging. To address these shortcomings, we develop a normative theory of patch foraging decisions. Using a Bayesian approach, we treat patch leaving behavior as a statistical inference problem. We derive the animals optimal decision strategies in both non-depleting and depleting environments. A majority of these cases can be analyzed explicitly using methods from stochastic processes. Our behavioral predictions are expressed in terms of the optimal patch residence time and the decision rule by which an animal departs a patch. We also extend our theory to a hierarchical model in which the forager learns the environmental food resource distribution. The quantitative framework we develop will therefore help experimenters move from analyzing trial based behavior to continuous behavior without the loss of quantitative rigor. Our theoretical framework both extends optimal foraging theory and motivates a variety of behavioral and neuroscientific experiments investigating patch foraging behavior.

animal behavior and cognition↗

bioRxiv2019

Coral bleaching susceptibility is predictive of subsequent mortality within but not between coral species

Marine heat waves instigated by anthropogenic climate change are causing increasingly frequent and severe coral bleaching events that often lead to widespread coral mortality. While community-wide increases in coral mortality following bleaching events have been documented on reefs around the world, the ecological consequences for conspecific individual colonies exhibiting contrasting phenotypes during thermal stress (e.g. bleached vs. not bleached) are not well understood. Here we describe the ecological outcomes of colonies of the two dominant reef-building coral species in K[a]ne{square}ohe Bay, Hawai{square}i, Montipora capitata and Porites compressa, that exhibited either a bleaching susceptible phenotype (bleached) or resistant phenotype (non-bleached) following the second of two consecutive coral bleaching events in Hawai{square}i in 2015. Conspecific pairs of adjacent bleaching susceptible vs. resistant corals were tagged on patch reefs in two regions of K[a]ne{square}ohe Bay with different seawater residence times and terrestrial influence. The ecological consequences (symbiont recovery and mortality) were monitored for two years following the peak of the bleaching event. Bleaching susceptible corals suffered higher partial mortality than bleaching resistant corals of the same species in the first 6 months following thermal stress. Surprisingly, P. compressa had greater resilience following bleaching (faster pigment recovery and lower post-bleaching mortality) than M. capitata, despite having less resistance to bleaching (higher bleaching prevalence and severity). These differences indicate that bleaching susceptibility of a species is not always a good predictor of mortality following a bleaching event. By tracking the fate of individual colonies of resistant and susceptible phenotypes, contrasting ecological consequences of thermal stress were revealed that were undetectable at the population level. Furthermore, this approach revealed individuals that underwent particularly rapid recovery from mortality, including some colonies over a meter in diameter that recovered all live tissue cover from >60% partial mortality within just one year. These coral pairs continue to be maintained and monitored in the field, serving as a "living library" for future investigations on the ecology and physiology of coral bleaching.

ecology↗

bioRxiv2019

Schistocephalus parasite infection alters sticklebacks' movement ability and thereby shapes social interactions

Parasitism is ubiquitous in the animal kingdom. Although many fundamental aspects of host-parasite relationships have been unravelled, few studies have systematically investigated how parasites affect organismal movement. Here we combine behavioural experiments of Schistocephalus solidus infected sticklebacks with individual-based simulations to understand how parasitism affects individual movement ability and how this in turn influences social interaction patterns. Detailed movement tracking revealed that infected fish swam slower, accelerated slower, turned more slowly, and tended to be more predictable in their movements than did non-infected fish. Importantly, the strength of these effects increased with increasing parasite load (% of body weight), with the behaviour of more heavily infected fish being more impaired. When grouped, pairs of infected fish moved more slowly, were less cohesive, less aligned, and less coordinated than healthy pairs. Mixed pairs exhibited intermediate behaviours and were primarily led by the non-infected fish. These social patterns emerged naturally in model simulations of self-organised groups composed of individuals with different speeds and turning tendency, consistent with changes in mobility and manoeuvrability due to infection. Together, our results demonstrate how infection with a complex life cycle parasite affects the movement ability of individuals and how this in turn shapes social interactions, providing important mechanistic insights into the effects of parasites on host movement dynamics.

animal behavior and cognition↗

bioRxiv2019

A model of tuberculosis clustering in low incidence countries reveals more on-going transmission in the United Kingdom than the Netherlands between 2010 and 2015.

Tuberculosis (TB) is a major public health threat, including in low TB incidence countries, through a combination of imported infection and onward transmission. Using data from the Enhanced Tuberculosis Surveillance system in the United Kingdom (UK) and the Netherlands (NL) Tuberculosis Register, we developed a mathematical model of TB importation and transmission in low-incidence settings. We apply this method to compare the effective reproduction number for TB, the contribution of importation and the role of superspreaders in the UK and the NL. We estimate that on average, between 2010 and 2015, a TB case generated 0{middle dot}41(0{middle dot}30,0{middle dot}60) secondary cases in the UK, and 0{middle dot}24(0{middle dot}14,0{middle dot}48) secondary cases in the NL. A majority of cases did not generate any secondary cases. Recent transmission accounted for 26% (21%,36%) of UK cases and 19%(11%,31%) of NL cases. We predict that reducing UK transmission rates to those observed in NL would result in 538(266,818) fewer cases annually in the UK. This methodology reveals common transmission mechanisms across two low-incidence countries and can be applied to other settings. Control policies aimed at limiting spread have a role to play in eliminating TB in low incidence countries.

epidemiology↗

bioRxiv2018

Foraging as an evidence accumulation process

A canonical foraging task is the patch-leaving problem, in which a forager must decide to leave a current resource in search for another. Theoretical work has derived optimal strategies for when to leave a patch, and experiments have tested for conditions where animals do or do not follow an optimal strategy. Nevertheless, models of patch-leaving decisions do not consider the imperfect and noisy sampling process through which an animal gathers information, and how this process is constrained by neurobiological mechanisms. In this theoretical study, we formulate an evidence accumulation model of patch-leaving decisions where the animal averages over noisy measurements to estimate the state of the current patch and the overall environment. Evidence accumulation models belong to the class of drift diffusion processes and have been used to model decision making in different contexts especially in cognitive and systems neuroscience. We solve the model for conditions where foraging decisions are optimal and equivalent to the marginal value theorem, and perform simulations to analyze deviations from optimal when these conditions are not met. By adjusting the drift rate and decision threshold, the model can represent different \"strategies\", for example an increment-decrement or counting strategy. These strategies yield identical decisions in the limiting case but differ in how patch residence times adapt when the foraging environment is uncertain. To account for sub-optimal decisions, we introduce an energy-dependent utility function that predicts longer than optimal patch residence times when food is plentiful. Our model provides a quantitative connection between ecological models of foraging behavior and evidence accumulation models of decision making. Moreover, it provides a theoretical framework for potential experiments which seek to identify neural circuits underlying patch leaving decisions.

animal behavior and cognition↗

bioRxiv2018

A quantitative evaluation of MIRU-VNTR typing against whole-genome sequencing for identifying Mycobacterium tuberculosis transmission: A prospective observational cohort study

SummaryO_ST_ABSBackgroundC_ST_ABSMycobacterial Interspersed Repetitive Unit-Variable Number Tandem Repeat (MIRU-VNTR) typing is widely used in high-income countries for Mycobacterium tuberculosis typing. Whole-genome sequencing (WGS) is known to deliver greater specificity, but no quantitative prospective comparison has yet been undertaken.\n\nMethodsWe studied isolates from the English Midlands, sampled consecutively between 1 January 2012 and 31 December 2015. In addition to routinely performed MIRU-VNTR typing, DNA was extracted from liquid cultures and sequenced using Illumina technology. Demographic and epidemiological data were extracted from the Enhanced Tuberculosis Surveillance system maintained by Public Health England. Closely related samples, defined using a threshold of five single nucleotide variants (SNVs), were compared to samples with identical MIRU-VNTR profiles, with shared epidemiological risk factors, and to those with both characteristics.\n\nFindings1,999 patients were identified for whom at least one M. tuberculosis isolate had been MIRU-VNTR typed and sequenced. Comparing epidemiological risk factors with close genetic relatedness, only coresidence had a positive predictive value of over 5%. Excluding co-resident individuals, 18.6% of patients with identical MIRU-VNTR profiles were within 5 SNVs. Where patients also shared social risk factors and ethnic group, this rose to 48%. Only 8% of MIRU-VNTR linked pairs in lineage 1 were within 5 SNV, compared to 31% in lineage 4.\n\nInterpretationIn the setting studied, MIRU-VNTR typing and epidemiological risk factors are poorly predictive of close genomic relatedness, assessed by SNV. MIRU-VNTR performance varies markedly by lineage.\n\nFundingPublic Health England, National Institute of Health Research Oxford Biomedical Research Centre.

microbiology↗