Biology subjects

Smith, D. L.

Publications and source records attributed to Smith, D. L..

At least 19 recordsLinked to original sources

bioRxiv2026

Widespread detection of Polyethylene glycol reveals chronic human exposure through pharmaceutical drugs

Polyethylene glycol (PEG) is a synthetic polymer ubiquitous in pharmaceuticals, personal care products, food additives, and industrial manufacturing. Despite its widespread use and potential importance as an exposure chemical, the prevalence of PEG exposure and its excretion in human populations remain largely uncharacterized. Moreover, PEG detected in human biofluids is frequently assumed to arise from analytical contamination during sample preparation, potentially obscuring its contribution to the human exposome and confounding metabolic phenotyping studies. Here, we show that PEG is as component of the human xenobiotic exposome and is further metabolized into PEG hydoxy acid and diacid metabolites in humans. We further find that PEG exposure is associated with alterations in microbiome composition and short-chain fatty acid metabolism, suggesting its biological impact of its exposure. We identify PEG exposure in approximately 2.3% of publicly available metabolomics data files and provide a reusable 85,484 candidate PEG and PEGylated MS/MS spectral library for future use for the metabolomic community. Together, these findings establish PEG signal in human biofluids can reflect genuine exposure, and that PEG exposure is neither metabolically inert nor biologically silent.

biochemistry↗

bioRxiv2026

Competing forms of protein-protein association and DNA binding exhibited by BrxC from the BREX phage restriction system

Bacteriophage exclusion (BREX) defense systems restrict phage infection via inhibition of phage DNA replication, while also modifying and protecting the bacterial genome. Type I BREX systems encode six conserved proteins, including a site-specific DNA methyltransferase. Host methylation requires a subset of BREX proteins, whereas phage restriction generally requires them all, suggesting that distinct but overlapping complexes mediate these activities. Full details of the mechanism and regulation of BREX remains to be understood. Here, we characterize the behavior and structures of the conserved BrxC AAA+ ATPase protein. BrxC forms multiple competing assemblages - various self-associating multimers, as well as a complex with BrxB-PglZ - that can be uncoupled via distinct point mutations, leading to differing effects on host methylation versus phage restriction. BrxCs self-association, as well as its ability to bind DNA, is regulated by ATP binding and hydrolysis; BrxA and BrxB appear to also regulate those behaviors. These collective results suggest that BrxC may play a key role in controlling the two activities of BREX, with BrxB, BrxC and PglZ forming a core complex, and the equilibrium among competing assemblies containing those proteins modulating the balance between idling and activated restrictive states.

biochemistry↗

bioRxiv2026

Loss of T73T75 phosphorylation on PP2A-B56Par1 advances mitotic entry and reduces S. pombe cell size

Mitosis is triggered when the rising activity of CDK1-Cyclin B, amplified by the CDK1/Cdc25/Wee1 feedback loop, overcomes inhibitory signalling from Wee1 and counteracting phosphatases. CDK-opposing phosphatases PP1, PP2A-B55 and PP2A-B56 are regulators of mitosis. A screen for differentially phosphorylated sites in a{Delta} PP1dis2 genetic background in Schizosaccharomyces pombe identified phosphorylation of T73 or T75 in the regulatory B56Par1 subunit. The B56Par1.T73T75 phosphorylation is directly mediated by CDK1-Cyclin B, and a phospho-mimetic mutation increased PP2A-B56Par1 phosphatase activity. Blocking B56Par1.T73T75 phosphorylation reduced cell length in unperturbed divisions from 14 to 12 {micro}m, with no other detectable phenotypes. Therefore, blocking phosphorylation at T73T75 alone prematurely unlocked amplification of the CDK1/Cdc25/Wee1 feedback loop, advancing cells into mitosis. Signalling from T73T75 reveals for the first time that timely mitotic commitment in unperturbed cycles is mediated by PP2A-B56.

cell biology↗

bioRxiv2025

UFMylation orchestrates chromatin engagement of core NHEJ components to promote DNA double-strand break repair

DNA double-strand breaks (DSBs) are highly cytotoxic lesions whose misrepair can lead to genomic instability, cancer and developmental disorders. Through systematic screening of understudied ubiquitin-like modifiers (UBLs), we identify UFM1 as a previously unrecognised regulator of non-homologous end-joining (NHEJ). Using a structure-guided chemical biology strategy, we develop a photo-crosslinkable UFM1 probe and, together with high-resolution NMR, uncover non-canonical UFM1-binding regions in core NHEJ components, including XRCC4. Mechanistically, proximity-dependent proteomics reveals Ku70 as a key UFMylation substrate, establishing a functional axis in which XRCC4 engages UFMylated Ku70 to promote the chromatin assembly of NHEJ factors. Perturbation of UFM1 signalling, via UFSP2 depletion or a hypomorphic UBA5 allele in patient-derived fibroblasts, impairs these processes, linking UFMylation defects to altered regulation of DSB repair. Our findings define a complete UFM1 signalling module in genome maintenance and uncover a molecular connection between hereditary UFMylation disorders and dysregulated DSB repair pathways.

molecular biology↗

bioRxiv2025

Mosquito Dispersal in Context

Mosquito dispersal plays an important role in mosquito ecology and mosquito-borne pathogen transmission. While reaction-diffusion and patch-based models with simple flux assumptions for emigration have played a predominant role in modeling mosquito dispersal, mosquito behavioral ecology - in particular, the process of searching for resources - is usually ignored by diffusion-based models. We thus set out to analyze mosquito movement using highly mimetic models, to see what we could learn from a different approach. Here, we present two behavioral state microsimulation models, in which mosquitoes are in behavioral states and search for required resources, which are distributed on a landscape. Models of this sort are laborious and challenging to work with, so we developed ramp.micro, an R package to build, solve, analyze, and visualize behavioral state microsimulation models for mosquitoes. Mosquito population dispersal is an emergent feature in these complex systems, so we developed new methods to describe and understand it. We show that population structure might not be revealed by a crude analysis of observed mosquito movement patterns, unless it can somehow account for sequences of flights for mosquitoes in behavioral states trying to accomplish a goal. We also show that even when resources are distributed randomly and uniformly, mosquito populations tend to form highly spatially structured communities. We also show that some heterogeneity in mosquito population densities is attributed to features of a network defined by searching and the spatial distribution of resources. These models highlight the importance of understanding mosquito behavioral states and resource availability in understanding mosquito population dispersal, and they point to the importance of local context. Motivated by these dynamics, spatial models for mosquito ecology and mosquito-borne pathogen transmission would benefit from considering resource availability as a factor affecting mosquito movement and dispersal. Author summaryWe develop highly realistic population dynamic models for mosquito behavioral ecology where mosquitoes move around on landscapes made up of resources located at points in space. The mosquitoes are in behavioral states - blood feeding, egg laying, or sugar feeding - and they end each search at a point where the resource they need can be found. Even with simple assumptions, mosquito populations can be highly structured. Because mosquitoes tend to leave areas that lack a resource, and they tend to stay in areas that have all required resources, the scarcest resources end up determining the structure of mosquito populations.

ecology↗

bioRxiv2024

Structure and rational engineering of the PglX methyltransferase and specificity factor for BREX phage defence

AO_SCPLOWBSTRACTC_SCPLOWBacteria have evolved a broad range of systems that provide defence against their viral predators, bacteriophages. Bacteriophage Exclusion (BREX) systems recognize and methylate 6 bp non-palindromic motifs within the host genome, and prevent replication of non-methylated phage DNA that encodes these same motifs. How BREX recognizes cognate motifs has not been fully understood. We have characterised BREX from pathogenic Salmonella and generated the first X-ray crystallographic structures of the conserved BREX protein, PglX. The PglX N-terminal domain encodes the methyltransferase, whereas the C-terminal domain is for motif recognition. We also present the structure of PglX bound to the phage-derived DNA mimic, Ocr, an inhibitor of BREX activity. Our analyses propose modes for DNA-binding by PglX and indicate that larger BREX complexes are required for methyltransferase activity and defence. Through rational engineering of PglX, we broadened both the range of phages targeted, and the host motif sequences that are methylated by BREX. Our data demonstrate that PglX is the sole specificity factor for BREX activity, providing motif recognition for both phage defence and host methylation.

microbiology↗

bioRxiv2023

Small but significant genetic differentiation among populations of Phyllachora maydis in the midwestern United States revealed by microsatellite (SSR) markers.

Phyllachora maydis Maubl, the causal pathogen of tar spot of corn (Zea mays L.), has emerged recently in the United States and Canada. Studies related to its genetic diversity and population structure are limited and are necessary to improve our understanding of this pathogens biology, ecology, epidemiology, and evolutionary potential within this region. This study developed and used 13 microsatellites (SSR markers) to assess the genetic population structure, diversity, gene flow and reproductive mode of 181 P. maydis samples across five states in the Midwest U.S. The polymorphic information content (PIC) of loci ranged from 0.32 to 0.72 per locus, indicating their high utility for assessing the dynamics of P. maydis populations. Analysis of molecular variance (AMOVA) detected a significantly low, but statistically significant genetic differentiation (FST = 0.15) among populations, where 85% of the variance resided within populations. P. maydis populations were highly diverse (He = 0.55), with moderate gene flow (Nm = 2.80), and showed evidence of sexual recombination ([r]d; p = > 0.001). Structure analysis showed the samples were not geographically structured but rather grouped into two genetic clusters (k =2) of severe genetic admixture suggesting possible long-distance dispersal of aerial spores or infected corn materials among the five Midwest states. Both principal coordinate analysis (PCoA) and discriminate analysis of principal component (DAPC) supported the STRUCTURE analysis of the two clusters. These 13 highly polymorphic molecular markers could be used for future investigations of this pathogens population dynamics within the U.S., and possibly populations outside.

pathology↗

bioRxiv2023

MGSurvE: A framework to optimize trap placement for genetic surveillance of mosquito population

Genetic surveillance of mosquito populations is becoming increasingly relevant as genetics-based mosquito control strategies advance from laboratory to field testing. Especially applicable are mosquito gene drive projects, the potential scale of which leads monitoring to be a significant cost driver. For these projects, monitoring will be required to detect unintended spread of gene drive mosquitoes beyond field sites, and the emergence of alternative alleles, such as drive-resistant alleles or non-functional effector genes, within intervention sites. This entails the need to distribute mosquito traps efficiently such that an allele of interest is detected as quickly as possible - ideally when remediation is still viable. Additionally, insecticide-based tools such as bednets are compromised by insecticide-resistance alleles for which there is also a need to detect as quickly as possible. To this end, we present MGSurvE (Mosquito Gene SurveillancE): a computational framework that optimizes trap placement for genetic surveillance of mosquito populations such that the time to detection of an allele of interest is minimized. A key strength of MGSurvE is that it allows important biological features of mosquitoes and the landscapes they inhabit to be accounted for, namely: i) resources required by mosquitoes (e.g., food sources and aquatic breeding sites) can be explicitly distributed through a landscape, ii) movement of mosquitoes may depend on their sex, the current state of their gonotrophic cycle (if female) and resource attractiveness, and iii) traps may differ in their attractiveness profile. Example MGSurvE analyses are presented to demonstrate optimal trap placement for: i) an Aedes aegypti population in a suburban landscape in Queensland, Australia, and ii)an Anopheles gambiae population on the island of Sao Tome, Sao Tome and Principe. Further documentation and use examples are provided in projects documentation. MGSurvE is freely available as an open-source Python package on pypi (https://pypi.org/project/MGSurvE/). It is intended as a resource for both field and computational researchers interested in mosquito gene surveillance. Author summaryMosquito-borne diseases such as malaria and dengue fever continue to pose a major health burden throughout much of the world. The impact of currently-available tools, such as insecticides and antimalarial drugs, is stagnating, and gene drive-modified mosquitoes are considered a novel tool that could contribute to continuing reductions in disease transmission. Gene drive approaches are unique in the field of vector control in that they involve transgenes that could potentially spread on a wide scale, and consequently, surveillance is expected to be a major cost driver for the technology. This is needed to monitor for unintended spread of intact drive alleles, and the emergence of alternative alleles such as homing-resistance alleles and non-functional effector genes. Additionally, surveillance of insecticide-resistance alleles is of interest to support the impact of insecticide-based tools such as bednets. Here, we present MGSurvE, a computational framework that optimizes trap placement for genetic surveillance of mosquito populations in order to minimize the time to detection for an allele of interest. MGSurvE has been tailored to various features of mosquito ecology, and is intended as a resource for researchers to optimize the efficiency of limited surveillance resources.

bioinformatics↗

bioRxiv2023

Uncovering the Environmental Conditions Required for Phyllachora maydis Infection and Tar Spot Development on Corn in the United States for Use as Predictive Models for Future Epidemics

Phyllachora maydis is a fungal pathogen causing tar spot of corn (Zea mays L.), a new and emerging, yield-limiting disease in the United States. Since being first reported in Illinois and Indiana in 2015, P. maydis can now be found across much of the corn growing of the United States. Knowledge of the epidemiology of P. maydis is limited but could be useful in developing tar spot prediction tools. The research presented here aims to elucidate the environmental conditions necessary for the development of tar spot in the field and the creation of predictive models to anticipate future tar spot epidemics. Extended periods (30-day windowpanes) of moderate ambient temperature were most significant for explaining the development of tar spot. Shorter periods (14- to 21-day windowpanes) of moisture (relative humidity, dew point, number of hours with predicted leaf wetness) were negatively correlated with tar spot development. These weather variables were used to develop multiple logistic regression models, an ensembled model, and two machine learning models for the prediction of tar spot development. This work has improved the understanding of P. maydis epidemiology and provided the foundation for the development of a predictive tool for anticipating future tar spot epidemics.

plant biology↗

bioRxiv2022

Acarbose suppresses symptoms of mitochondrial disease in a mouse model of Leigh Syndrome

Mitochondrial diseases represent a spectrum of disorders caused by impaired mitochondrial function ranging in severity from mortality during infancy to progressive adult-onset disease. Mitochondrial dysfunction is also recognized as a molecular hallmark of the biological aging process. Rapamycin, a drug that increases lifespan and health during normative aging also increases survival and reduces neurological symptoms in a mouse model of the severe mitochondrial disease Leigh Syndrome. The Ndufs4 knockout (Ndufs4-/-) mouse lacks the complex I subunit NDUFS4 and shows rapid onset and progression of neurodegeneration mimicking patients with Leigh Syndrome. Here we show that another drug that extends lifespan and delays normative aging in mice, acarbose, also suppresses symptoms of disease and improves survival of Ndufs4-/- mice. Unlike rapamycin, acarbose rescues disease phenotypes independently of mTOR inhibition. Furthermore, rapamycin and acarbose have additive effects in delaying neurological symptoms and increasing maximum lifespan in Ndufs4-/- mice. We find that acarbose remodels the intestinal microbiome and alters the production of short chain fatty acids. Supplementation with tributyrin, a source of butyric acid, recapitulates some effects of acarbose on lifespan and disease progression. This study provides the first evidence that alteration of the gut microbiome may impact severe mitochondrial disease and provides further support for the model that biological aging and severe mitochondrial disorders share underlying common mechanisms.

biochemistry↗

bioRxiv2021

Pre-existing partner-drug resistance facilitates the emergence and spread of artemisinin resistance: a consensus modelling study

BackgroundArtemisinin-resistant genotypes have now emerged a minimum of five times on three continents despite recommendations that all artemisinins be deployed as artemisinin combination therapies (ACTs). Widespread resistance to the non-artemisinin partner drugs in ACTs has the potential to limit the clinical and resistance benefits provided by combination therapy. MethodsUsing a consensus modelling approach with three individual-based mathematical models of Plasmodium falciparum transmission, we evaluate the effects of pre-existing partner-drug resistance and ACT deployment on artemisinin resistance evolution. We evaluate settings where dihydroartemisinin-piperaquine (DHA-PPQ), artesunate-amodiaquine (ASAQ), or artemether-lumefantrine (AL) are deployed as first-line therapy. We use time until 0.25 artemisinin resistance allele frequency (the establishment time) as the primary outcome measure. FindingsHigher frequencies of pre-existing partner-drug resistant genotypes lead to earlier establishment of artemisinin resistance. Across all scenarios and pre-existing frequencies of partner-drug resistance explored, a 0.10 increase in partner-drug resistance frequency on average corresponded to 0.7 to 5.0 years loss of artemisinin efficacy. However, the majority of reductions in time to artemisinin establishment were observed after the first increment from 0.0 to 0.10 partner-drug resistance genotype frequency. InterpretationPartner-drug resistance in ACTs facilitates the early emergence of artemisinin resistance and is a major public health concern. Higher grade partner-drug resistance has the largest effect, with piperaquine-resistance accelerating early emergence of artemisinin-resistant alleles the most. Continued investment in molecular surveillance of partner-drug resistant genotypes to guide choice of first-line ACT is paramount. FundingBill and Melinda Gates Foundation; Wellcome Trust.

genetics↗

bioRxiv2020

Principled simulation of agent-based models in epidemiology

After more than a century of sustained work by mathematicians, biologists, epidemiologists, probabilists, and other experts, dynamic models have become a vital tool for understanding and describing epidemics and disease transmission systems. Such models fulfill a variety of crucial roles including data integration, estimation of disease burden, forecasting trends, counterfactual evaluation, and parameter estimation. These models often incorporate myriad details, from age and social structure to inform population mixing patterns, commuting and migration, and immunological dynamics, among others. This complexity can be daunting, so many researchers have turned to stochastic simulation using agent-based models. Developing agent-based models, however, can present formidable technical challenges. In particular, depending on how the model updates state, unwanted or even unnoticed approximations can be introduced into a simulation model. In this article, we present computational methods for approximating continuous time discrete event stochastic processes based on a discrete time step to speed up complicated simulations which also converges to the true process as the time step goes to zero. Our stochastic models is constructed via hazard functions, and only those hazards which are dependent on the state of other agents (such as infection) are approximated, whereas hazards governing dynamics internal to an agent (such as immune response) are simulated exactly. By partitioning hazards as being either dependent or internal, a generic algorithm can be presented which is applicable to many models of contagion processes, with natural areas of extension and optimization. Author summaryStochastic simulation of epidemics is crucial to a variety of tasks in public health, encompassing intervention evaluation, trend forecasting, and estimation of epidemic parameters, among others. In many situations, due to model complexity, time constraints, unavailability or unfamiliarity with existing software, or other reasons, agent-based models are used to simulate epidemic processes. However, many simulation algorithms are ad hoc, which may introduce unwanted or unnoticed approximations. We present a method to build approximate, agent-based models from mathematical descriptions of stochastic epidemic processes which will improve simulation speed and converge to exact simulation techniques in limiting cases. The simplicity and generality of our method should be widely applicable to various problems in mathematical epidemiology and its connection to other methods developed in chemical physics should inspire future work and elaboration.

ecology↗

bioRxiv2020

A cell non-autonomous mechanism of yeast chronological aging regulated by caloric restriction and one-carbon metabolism

Caloric restriction (CR) improves healthspan and lifespan of organisms ranging from yeast to mammals. Understanding the mechanisms involved will uncover future interventions for aging associated diseases. In budding yeast, Saccharomyces cerevisiae, CR is commonly defined by reduced glucose in the growth medium, which extends both replicative and chronological lifespan (CLS). We found that conditioned media collected from stationary phase CR cultures extended CLS when supplemented into non-restricted (NR) cultures, suggesting a potential cell non-autonomous mechanism of CR-induced lifespan regulation. Chromatography and untargeted metabolomics of the conditioned media, as well as transcriptional responses associated with the longevity effect, pointed to specific amino acids enriched in the CR conditioned media (CRCM) as functional molecules, with L-serine being a particularly strong candidate. Indeed, supplementing L-serine into NR cultures extended CLS through a mechanism dependent on the one-carbon metabolism pathway, thus implicating this conserved and central metabolic hub in lifespan regulation.

cell biology↗

bioRxiv2020

Measuring the accuracy of gridded human population density surfaces: a case study in Bioko Island, Equatorial Guinea

Geospatial datasets of population are becoming more common in models used for health policy. Publicly-available maps of human population in sub-Saharan Africa make a consistent picture from inconsistent census data, and the techniques they use to impute data makes each population map unique. Each mapping model explains its methods, but it can be difficult to know which map is appropriate for which policy work. Gold-standard census datasets, where available, are a unique opportunity to characterize maps by comparing them with truth. We use census data from Bioko Island, in Equatorial Guinea, to evaluate LandScan (LS), WorldPop (WP), and the High-Resolution Settlement Layer (HRSL). Each layer is compared to the gold-standard using statistical measures to evaluate distribution, error, and bias. We investigated how map choice affects burden estimates from a malaria prevalence model. Specific population layers were able to match the gold-standard distribution at different population densities. LandScan was able to most accurately capture highly urban distribution, HRSL matched best at all other lower population densities and WorldPop performed poorly everywhere. Correctly capturing empty pixels is key, and smaller pixel sizes (100 m vs 1 km) improve this. Normalizing areas based on known district populations increased performance. The use of differing population layers in a malaria model showed a disparity in results around transition points between endemicity levels. The metrics in this paper, some of them novel in this context, characterize how these population maps differ from the gold standard census and from each other. We show that the metrics help understand the performance of a population map within a malaria model. The closest match to the census data would combine LandScan within urban areas and the HRSL for rural areas. Researchers should prefer particular maps if health calculations have a strong dependency on knowing where people are not, or if it is important to categorize variation in density within a city.

ecology↗

bioRxiv2020

High-resolution yeast quiescence profiling in human-like media reveals interacting influences of auxotrophy and nutrient availability

Yeast cells survive in stationary phase culture by entering quiescence, which is measured by colony forming capacity upon nutrient re-exposure. Yeast chronological lifespan (CLS) studies, employing the comprehensive collection of gene knockout strains, have correlated weakly between independent laboratories, which is hypothesized to reflect differential interaction between the deleted genes, auxotrophy, media composition and other assay conditions influencing quiescence. This hypothesis was investigated by high-throughput quiescence profiling of the parental prototrophic strain, from which the gene deletion strain libraries were constructed, and all possible auxotrophic allele combinations in that background. Defined media resembling human cell culture media promoted long-term quiescence, and was used to assess effects of glucose, ammonium sulfate, auxotrophic nutrient availability, Target of Rapamycin signaling, and replication stress. Frequent, high-replicate measurements of colony forming capacity from cultures aged past 60 days provided profiles of quiescence phenomena such as gasping and hormesis. Media acidification was assayed in parallel to assess correlation. Influences of leucine, methionine, glucose, and ammonium sulfate metabolism were clarified, and a role for lysine metabolism newly characterized, while histidine and uracil perturbations had less impact. Interactions occurred between glucose, ammonium sulfate, auxotrophy, auxotrophic nutrient limitation, aeration, TOR signaling, and/or replication stress. Weak correlation existed between media acidification and maintenance of quiescence. In summary, experimental factors, uncontrolled across previous genome-wide yeast CLS studies, influence quiescence and interact extensively, revealing quiescence as a complex metabolic and developmental process that should be studied in a prototrophic context, omitting ammonium sulfate from defined media, and employing highly replicable protocols.

genetics↗

bioRxiv2020

Canagliflozin Extends Lifespan in Genetically Heterogeneous Male But Not Female Mice

Canagliflozin (Cana) is an inhibitor of the sodium glucose transporter 2 (SGLT2), and is thought to act by blocking renal reuptake and intestinal absorption of glucose. Cana is FDA-approved for treatment of diabetes, and affords protection from cardiovascular and kidney diseases. In the context of the mouse Interventions Testing Program, genetically heterogeneous mice were given chow containing 180 ppm Cana at 7 months of age until their death. Cana extended median survival of male mice by 14%, with p < 0.001 by log-rank test. Cana also increased by 9% the age for 90th percentile survival (p < 0.001 by Wang/Allison test), with parallel effects seen at each of three test sites. Cana did not alter the distribution of inferred cause of death, nor of incidental pathology findings at end-of-life necropsies. No benefits were seen in female mice. The lifespan benefit of Cana is likely to reflect blunting of peak glucose levels, because similar longevity effects are seen in mice given acarbose, a diabetes drug that blocks glucose surges through a distinct mechanism, i.e. slowing breakdown of carbohydrate in the intestine. Interventions that control daily peak glucose levels deserve attention as possible preventive medicines to protect from a wide range of late-life neoplastic and degenerative diseases.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pathology↗

bioRxiv2019

Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology

Mosquitoes are important vectors for pathogens of humans and other vertebrate animals. Some aspects of adult mosquito behavior and mosquito ecology play an important role in determining the capacity of vector populations to transmit pathogens. Here, we re-examine factors affecting the transmission of pathogens by mosquitoes using a new approach. Unlike most previous models, this framework considers the behavioral states and state transitions of adult mosquitoes through a sequence of activity bouts. We developed a new framework for individual-based simulation models called MBITES (Mosquito Bout-based and Individual-based Transmission Ecology Simulator). In MBITES, it is possible to build models that simulate the behavior and ecology of adult mosquitoes in exquisite detail on complex resource landscapes generated by spatial point processes. We also developed an ordinary differential equation model which is the Kolmogorov forward equations for models developed in MBITES under a specific set of simplifying assumptions. While infection of the mosquito and pathogen development are one possible part of a mosquitos state, that is not the main focus. Using extensive simulation using some models developed in MBITES, we show that vectorial capacity can be understood as an emergent property of simple behavioral algorithms interacting with complex resource landscapes, and that relative density or sparsity of resources and the need to search can have profound consequences for mosquito populations capacity to transmit pathogens.

ecology↗

bioRxiv2019

A New Role for Telomerase in Promoting Meiotic Homolog Pairing Fidelity

We report a role for telomerase, beyond its known function of telomeric DNA end extension, in maintaining normal chromosome dynamics during meiosis in Saccharomyces cerevisiae. When telomerase at telomeres was reduced by various genetic means, increased frequencies of crossover and noncrossover recombination events occurred. To investigate the mechanism of this increased meiotic recombination, we examined the kinetics of meiosis events, and tracked the movement of chromosomes in live cells during meiotic prophase. Cytoskeletal forces acting on telomeres during meiosis have been shown to promote active chromosome motion needed to pair homologous chromosomes. Here we show that changes in telomerase interaction with telomeres using a tlc1-11 mutant result in altered meiotic motion. Specifically, reduction in telomerase at telomeres leads to a decreased frequency of high velocity chromosome pulls. In the tlc1-11 mutant, we see earlier synapsis and increased genome-wide recombination for the majority of the cells and lower gamete viability. Notably, homologous pairing is not delayed unlike other telomere binding mutants. Although synapsis initiates earlier, the overall timing of synapsis remains the same, except for a subset of cells that do not exit meiosis I. Together, these results suggest that the strong pulling component of the active chromosome motion promotes homolog pairing fidelity, likely by pulling apart improperly associated regions. Our combined observations are consistent with a model in which telomerase-mediated telomeric anchoring to the nuclear envelope helps engage and properly transmit cytoskeletal forces to chromosomes. Thus, telomerase contributes to efficient chromosome movements leading to normal gamete viability.

cell biology↗