Biology subjects

Peace, A.

Publications and source records attributed to Peace, A..

8 recordsLinked to original sources

bioRxiv2024

A Genome-Wide Arrayed CRISPR Screen Reveals PLSCR1 as an Intrinsic Barrier to SARS-CoV-2 Entry

Interferons (IFNs) play a crucial role in the regulation and evolution of host-virus interactions. Here, we conducted a genome-wide arrayed CRISPR knockout screen in the presence and absence of IFN to identify human genes that influence SARS-CoV-2 infection. We then performed an integrated analysis of genes interacting with SARS-CoV-2, drawing from a selection of 67 large-scale studies, including our own. We identified 28 genes of high relevance in both human genetic studies of COVID-19 patients and functional genetic screens in cell culture, with many related to the IFN pathway. Among these was the IFN-stimulated gene PLSCR1. PLSCR1 did not require IFN induction to restrict SARS-CoV-2 and did not contribute to IFN signaling. Instead, PLSCR1 specifically restricted spike-mediated SARS-CoV-2 entry. The PLSCR1-mediated restriction was alleviated by TMPRSS2 over-expression, suggesting that PLSCR1 primarily restricts the endocytic entry route. In addition, recent SARS-CoV-2 variants have adapted to circumvent the PLSCR1 barrier via currently undetermined mechanisms. Finally, we investigate the functional effects of PLSCR1 variants present in humans and discuss an association between PLSCR1 and severe COVID-19 reported recently.

immunology↗

bioRxiv2022

Using agent-based models to predict pollen deposition in a dioecious crop

Pollination involves complex interactions between plants and pollinators, and variation in plant or pollinator biology can lead to variability in pollination services that are difficult to predict. Models that effectively predict pollination services could enhance the ability to conserve plant-pollinator mutualisms in natural systems and increase crop yields in managed systems. However, while most pollination models have focused either on effects of plant or pollination biology, few models have integrated plant-pollinator interactions. Moreover, crop management causes variation in plant-pollinator interactions and pollination services, but management is rarely considered in pollination models. Here we used extensive datasets for kiwifruit (Actinidia chinensis var. deliciosa) to develop an agent-based model to track insect-provided pollination services with variation in crop cultivars, pollinator traits, and orchard layouts. This allowed us to predict pollination outcomes in a dioecious crop under a range of management scenarios. Our sensitivity analysis indicated that flower density and the proportion of female flowers are the most important factors in successful pollination, both of which growers control via cultivar selection and cultural management practices. Our analysis also indicated that economically viable pollination services and crop yields are attained with [~]60% female flowers and a peak foraging activity of 6 to 8 bees per 1,000 open flowers with diminishing returns for additional pollinators. The quality of pollination service varied across simulated orchard layouts, highlighting the potential use of this model as a framework to screen novel orchard configurations. More broadly, linking complex plant and pollinator interactions in pollination models can help identify factors that may improve crop yields and provide a framework for identifying factors important to pollination in natural ecosystems. HIGHLIGHTS- We develop a model using extensive empirical datasets to predict pollen deposition based on the interactions between flowers and pollinators in a dioecious crop system - We conducted a thorough sensitivity analysis, and analysis of the effect of stochastic variance between model runs, which can be used to inform future design of stochastic agent-based models - Our model effectively predicted the outcomes of varying management regimes of orchard layouts and pollinator introductions on pollination in a dioecious crop - Our model can be extended for other functionally dioecious crops or plant communities where managers want to understand how their decisions impact pollination

ecology↗

bioRxiv2020

Genome-scale identification of SARS-CoV-2 and pan-coronavirus host factor networks

The COVID-19 pandemic has claimed the lives of more than one million people worldwide. The causative agent, SARS-CoV-2, is a member of the Coronaviridae family, which are viruses that cause respiratory infections of varying severity. The cellular host factors and pathways co-opted by SARS-CoV-2 and other coronaviruses in the execution of their life cycles remain ill-defined. To develop an extensive compendium of host factors required for infection by SARS-CoV-2 and three seasonal coronaviruses (HCoV-OC43, HCoV-NL63, and HCoV-229E), we performed parallel genome-scale CRISPR knockout screens. These screens uncovered multiple host factors and pathways with pan-coronavirus and virus-specific functional roles, including major dependency on glycosaminoglycan biosynthesis, SREBP signaling, and glycosylphosphatidylinositol biosynthesis, as well as an unexpected requirement for several poorly characterized proteins. We identified an absolute requirement for the VTT-domain containing protein TMEM41B for infection by SARS-CoV-2 and all other coronaviruses. This human Coronaviridae host factor compendium represents a rich resource to develop new therapeutic strategies for acute COVID-19 and potential future coronavirus spillover events. HIGHLIGHTSGenome-wide CRISPR screens for SARS-CoV-2, HCoV-OC43, HCoV-NL63, and HCoV-229E coronavirus host factors. Parallel genome-wide CRISPR screening uncovered host factors and pathways with pan-coronavirus and virus-specific functional roles. Coronaviruses co-opt multiple biological pathways, including glycosaminoglycan biosynthesis, SREBP signaling, and glycosylphosphatidylinositol biosynthesis and anchoring, among others. TMEM41B - a poorly understood factor with roles in autophagy and lipid mobilization - is a critical pan-coronavirus host factor.

microbiology↗

bioRxiv2020

Functional interrogation of a SARS-CoV-2 host protein interactome identifies unique and shared coronavirus host factors

The ongoing SARS-CoV-2 pandemic has devastated the global economy and claimed nearly one million lives, presenting an urgent global health crisis. To identify host factors required for infection by SARS-CoV-2 and seasonal coronaviruses, we designed a focused high-coverage CRISPR-Cas9 library targeting 332 members of a recently published SARS-CoV-2 protein interactome. We leveraged the compact nature of this library to systematically screen four related coronaviruses (HCoV-229E, HCoV-NL63, HCoV-OC43 and SARS-CoV-2) at two physiologically relevant temperatures (33 {degrees}C and 37 {degrees}C), allowing us to probe this interactome at a much higher resolution relative to genome scale studies. This approach yielded several new insights, including unexpected virus and temperature specific differences in Rab GTPase requirements and GPI anchor biosynthesis, as well as identification of multiple pan-coronavirus factors involved in cholesterol homeostasis. This coronavirus essentiality catalog could inform ongoing drug development efforts aimed at intercepting and treating COVID-19, and help prepare for future coronavirus outbreaks. HIGHLIGHTSFocused CRISPR screens targeting host factors in the SARS-CoV-2 interactome were performed for SARS-CoV-2, HCoV-229E, HCoV-NL63, and HCoV-OC43 coronaviruses. Focused interactome CRISPR screens achieve higher resolution compared to genome-wide screens, leading to the identification of critical factors missed by the latter. Parallel CRISPR screens against multiple coronaviruses uncover host factors and pathways with pan-coronavirus and virus-specific functional roles. The number of host proteins that interact with a viral bait protein is not proportional to the number of functional interactors. Novel SARS-CoV-2 host factors are expressed in relevant cell types in the human airway.

microbiology↗

bioRxiv2020

Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop

Mutualistic plant-pollinator interactions are critical for the functioning of both non-managed and agricultural systems. Mathematical models of plant-pollinator interactions can help understand key determinants in pollination success. However, most previous models have not addressed pollinator behavior and plant biology combined. Information generated from such a model can inform optimal design of crop orchards and effective utilization of managed pollinators like honey bees, and help generate hypotheses about the effects of management practices and cultivar selection. We expect that honey bee density per flower and male to female flower ratio will influence fruit yield. To test the relative importance of these effects, both singly and simultaneously, we utilized a delay differential equation model combined with Latin hypercube sampling for sensitivity analysis. Empirical data obtained from historical records and collected in kiwifruit orchards in New Zealand were used to parameterize the model. We found that, at realistic bee densities, the optimal orchard had 65-75% female flowers, and the most benefit was gained from the first 6-8 bees/1000 flowers, with diminishing returns thereafter. While bee density significantly impacted fruit production, plant-based parameters-flower density and male:female flower ratio-were the most influential. The predictive model provides strategies for improving crop management.

plant biology↗

bioRxiv2020

A Combination of Two Human Monoclonal Antibodies Limits Fetal Damage by Zika Virus in Macaques

Human infection by Zika virus (ZIKV) during pregnancy can lead to vertical transmission and fetal aberrations, including microcephaly. Prophylactic administration of antibodies can diminish or prevent ZIKV infection in animal models, but whether passive immunization can protect nonhuman primates and their fetuses during pregnancy has not been determined. Z004 and Z021 are neutralizing monoclonal antibodies to domain III of the envelope (EDIII) of ZIKV. Together the two antibodies protect nonpregnant macaques against infection even after Fc modifications to prevent antibody-dependent enhancement in vitro (ADE) and extend their half-lives. Here we report on prophylactic co-administration of the Fc-modified antibodies to pregnant rhesus macaques challenged 3 times with ZIKV during first and second trimester. The two antibodies did not entirely eliminate maternal viremia but limited vertical transmission protecting the fetus from neurologic damage. Thus, maternal passive immunization with two antibodies to EDIII can shield primate fetuses from the harmful effects of ZIKV. Significance statementZika virus (ZIKV) infection during pregnancy can cause fetal abnormalities. Vaccines against ZIKV are under development, but because of potential safety concerns due to disease enhancing antibodies, and the time required by active immunization to induce protective antibodies, there is a need to explore alternative strategies. Recombinant monoclonal antibodies can be modified to prevent enhancement of infection, and thus could be an efficacious and safe alternative to vaccines to confer rapid protection. We show that prophylactic administration of two engineered antibodies, Z004 and Z021, to pregnant macaques partially protects against fetal neurologic damage and limits vertical transmission of ZIKV.

immunology↗

bioRxiv2019

Local control of resource allocation is sufficient to model optimal dynamics in syntrophic systems

Syntrophic systems are common in nature and include forms of obligate mutualisms in which each participating organism or component of an organism obtains from the other an essential nutrient or metabolic product that it cannot provide for itself. Models of how these complementary resources are allocated between partners often assume optimal behavior, but whether mechanisms enabling global control exist in syntrophic systems, and what form they might take, is unknown. Recognizing that growth of plant organs that supply complementary resources, like roots and shoots, can occur autonomously, we present a theory of plant growth in which root-shoot allocation is determined by purely local rules. Each organ uses as much as it can of its locally produced or acquired resource (inorganic nitrogen or photosynthate) and shares only the surplus. Subject to stoichiometric conditions that likely hold for most plants, purely local rules produce the same optimal allocation as would global control, even in a fluctuating environment, with sharing the surplus being the specific mechanism stabilizing syntrophic dynamics. Our local control model contributes a novel approach to plant growth modeling because it assumes a simple mechanism of root:shoot allocation that can be considered a higher-level physiological rule, from which the optimal growth outcome emerges from the systems dynamics, rather than being built into the model. Moreover, our model is general, in that the mechanism of sharing the surplus can readily be adapted to many obligate syntrophic relationships.

plant biology↗

bioRxiv2019

Evidence of adaptive host and vector manipulation by plant viruses revealed through combined meta-analysis and modeling approaches.

A growing number of studies indicate that plant viruses enhance their own transmission by modifying host phenotypes and vector behavior, leading to the hypothesis that such effects are manipulations resulting from virus adaptations. However, few studies have linked putative manipulations with virus components, and the true frequency and magnitude of host and vector manipulation across virus taxa remains unknown. To address this knowledge gap, we performed a meta-analysis to quantify convergence in virus effects on hosts and vectors across taxonomic groups that share transmission mechanism traits, and thereby stand to benefit from similar sequences of vector behavior. We then combined meta-analysis outputs with an epidemiological model to assess consequences of manipulation for virus spread. Overall, transmission mechanism traits strongly predicted the magnitude and nature of virus effects on vector preferences and performance. Models parameterized with meta-analysis data demonstrate that manipulation effects enhance virus spread, and that viruses with long acquisition times and retention durations are under strong selection pressure to manipulate transmission. By combining meta-analysis with epidemiological modeling, our results confirm that host and vector manipulation are important aspects of plant virus ecology and evolution while emphasizing the need to incorporate more pathosystems and transmission mechanism traits in future studies.

ecology↗