Biology subjects

Aitchison, J. D.

Publications and source records attributed to Aitchison, J. D..

26 records · Page 2Linked to original sources

bioRxiv2020

Dengue activates mTORC2 signaling to counteract apoptosis and maximize viral replication

The mechanistic target of rapamycin (mTOR) functions in at least two distinct complexes: mTORC1, which regulates cellular anabolic-catabolic homeostasis, and mTORC2, which is an important regulator of cell survival and cytoskeletal maintenance. mTORC1 has been implicated in the pathogenesis of flaviviruses including dengue, where it contributes to the establishment of a pro-viral autophagic state. In contrast, the role of mTORC2 in viral pathogenesis is unknown. In this study, we explore the consequences of a physical protein-protein interaction between dengue non-structural protein 5 (NS5) and host cell mTOR proteins during infection. Using shRNA to differentially target mTORC1 and mTORC2 complexes, we show that mTORC2 is required for optimal dengue replication. Furthermore, we show that mTORC2 is activated during viral replication, and that mTORC2 counteracts virus-induced apoptosis, promoting the survival of infected cells. This work reveals a novel mechanism by which the dengue flavivirus can promote cell survival to maximize viral replication.

microbiology↗

bioRxiv2020

A Genome-wide CRISPR-Cas9 Screen Identifies Host Factors Essential for Optimal Plasmodium Liver Stage Development.

Prior to initiating symptomatic malaria, a single Plasmodium sporozoite infects a hepatocyte and develops into thousands of merozoites, in part by scavenging host resources. We show that host microtubules dynamically reorganize around the developing liver stage (LS) parasite. Using a genome-wide CRISPR-Cas9 screen, we identified host regulators of cytoskeleton organization, vesicle trafficking, ER/Golgi stress and lipid biogenesis that regulate Plasmodium LS development. These novel regulators of infection, including Centromere Protein J (CENPJ), led us to interrogate how microtubule organizing centers (MTOCs) are regulated during infection. Foci of {gamma}-tubulin localized to the parasite periphery; depletion of CENPJ exacerbated this re-localization and increased infection. Further, we show that the Golgi acts as a non-centrosomal MTOC by organizing {gamma}-tubulin and stimulating microtubule nucleation at the parasite periphery. Collectively, we show that the Plasmodium LS recruits the host Golgi to form MT mediated conduits along which host organelles are recruited to the PVM, to support liver stage development. Our findings suggest many host-targeted pharmacological inhibitors may inhibit LS infection.

cell biology↗

bioRxiv2020

A system-level gene regulatory network model for Plasmodium falciparum

Many of the gene regulatory processes of Plasmodium falciparum, the deadliest malaria parasite, remain poorly understood. To develop a comprehensive guide for exploring this organisms gene regulatory network, we generated a system-level model of Plasmodium falciparum gene regulation using a well-validated, machine-learning approach for predicting interactions between transcription regulators and their targets. The resulting network accurately predicts expression levels of transcriptionally coherent gene regulatory programs in independent transcriptomic data sets from parasites collected by different research groups in diverse laboratory and field settings. Thus, our results indicate that our gene regulatory model has predictive power and utility as a hypothesis-generating tool for illuminating clinically relevant gene regulatory mechanisms within Plasmodium falciparum. Using the set of regulatory programs we identified, we also investigated correlates of artemisinin resistance based on gene expression coherence. We report that resistance is associated with incoherent expression across many regulatory programs, including those controlling genes associated with erythrocyte-host engagement. These results suggest that parasite populations with reduced artemisinin sensitivity are more transcriptionally heterogenous. This pattern is consistent with a model where the parasite utilizes bet-hedging strategies to diversify the population, rendering a subpopulation more able to navigate drug treatment.

systems biology↗

bioRxiv2020

ODELAM: Rapid sequence-independent detection of drug resistance in clinical isolates of Mycobacterium tuberculosis

Antimicrobial-resistant Mycobacterium tuberculosis (Mtb) causes over 200,000 deaths each year. Current assays of antimicrobial resistance need knowledge of mutations that confer drug resistance, or long periods of culture time to test growth under drug pressure. We present ODELAM (One-cell Doubling Evaluation of Living Arrays of Mycobacterium), a time-lapse microscopy-based method that observes individual cells growing into microcolonies. ODELAM enables rapid quantitative measures of growth kinetics in as little as 30 hours under a wide variety of environmental conditions. We show the utility of ODELAM by identifying ofloxacin resistance in clinical isolates of Mtb and benchmark its performance with standard MIC assays. In one clinical isolate, ODELAM identified ofloxacin heteroresistance and identifies the presence of drug resistant colony forming units (CFU) at 1 per 1000 CFUs in as little as 48 hours. ODELAM is a powerful new tool that can rapidly evaluate Mtb drug resistance in a laboratory setting.

microbiology↗

bioRxiv2019

Plasmodium secretion induces hepatocyte lysosome exocytosis and promotes parasite entry

The invasion of a suitable host hepatocyte by Plasmodium sporozoites is an essential step in malaria infection. We demonstrate that in infected hepatocytes, lysosomes are redistributed away from the nucleus, and surface exposure of lysosomal-associated membrane protein (LAMP1) is increased. Lysosome exocytosis in infected cells occurs independently of sporozoite traversal. Instead, a sporozoite-secreted factor is sufficient for the process. Knockdown of the SNARE proteins involved in lysosome-plasma membrane fusion reduces lysosome exocytosis and Plasmodium infection. In contrast, promoting fusion between the lysosome and plasma membrane dramatically increases infection. Our work demonstrates new parallels between Plasmodium sporozoite entry of hepatocytes and infection by the excavate pathogen, Trypanosoma cruzi and raises the question of whether convergent evolution has shaped host cell invasion by divergent pathogens.

cell biology↗

bioRxiv2017

ESCRT-III acts in scissioning new peroxisomes from the ER

Dynamic control of peroxisome proliferation is integral to the peroxisomes many functions. A breakdown in the ability of cells to form peroxisomes is linked to many human health issues, including defense against infectious agents, cancer, aging, heart disease, obesity and diabetes, and forms the basis of a spectrum of peroxisomal genetic disorders that cause severe neuropathologies. The ER serves as a source for preperoxisomal vesicles (PPVs) that mature into peroxisomes during de novo peroxisome biogenesis and to support growth and division of existing peroxisomes. However, the mechanism of PPV formation and release from the ER remains poorly understood. Here we show that the evolutionarily ancient endosomal sorting complexes required for transport (ESCRT)-III are peroxisome biogenesis factors that function to cleave PPVs budding from the ER into the cytosol. Using comprehensive morphological and genetic assays of peroxisome formation and function we find that absence of ESCRT-III proteins impedes de novo peroxisome formation and results in an aberrant peroxisome population in vivo. Using a cell-free PPV budding assay we show that ESCRT-III proteins Vps20 and Snf7 are required to release PPVs from the ER. ESCRT-III is therefore a positive effector of membrane scission for vesicles budding both away from and towards the cytosol, a finding that has important implications for the evolutionary timing of emergence of peroxisomes and the rest of the internal membrane architecture of the eukaryotic cell.

cell biology↗

bioRxiv2017

An indicator cell assay for blood-based diagnostics

We have established proof of principle for the Indicator Cell Assay Platform (iCAP), a broadly applicable tool for blood-based diagnostics that uses specifically-selected, standardized cells as biosensors, relying on their innate ability to integrate and respond to diverse signals present in patients blood. To develop an assay, indicator cells are exposed in vitro to serum from case or control subjects and their global differential response patterns are used to train reliable, cost-effective disease classifiers based on a small number of features. In a feasibility study, the iCAP detected pre-symptomatic disease in a murine model of amyotrophic lateral sclerosis (ALS) with 94% accuracy (p-Value=3.81E-6) and correctly identified samples from a murine Huntingtons disease model as non-carriers of ALS. In a preliminary human disease assay, the iCAP detected early stage Alzheimers disease with 72% cross-validated accuracy (p-Value=3.10E-3). For both assays, iCAP features were enriched for disease-related genes, supporting the assays relevance for disease research.

systems biology↗

bioRxiv2016

Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced REgulation And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAMs enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.\n\nAuthor SummaryThe integration of gene regulatory and metabolic network models is an important goal in computational biology, in order to develop methods that can identify the underlying mechanistic links in biological networks and advance metabolic engineering techniques. In this paper, we develop a framework called Integrated Deduced REgulation And Metabolism (IDREAM) that can improve our ability to predict phenotypes of microorganisms, and particularly it can address the challenges in evaluating phenotypic consequence of perturbing transcriptional regulation of metabolism in a eukaryotic cell. We compare the predictive performance of an IDREAM S. cerevisiae model with a PROM model using a TRN available from the YEASTRACT database. IDREAM outperforms PROM using any of three popular yeast metabolic models and across three experimental growth conditions, making it possible to identify subtle synthetic growth defects, and a new role for Oaf1 in the regulation of acetyl-CoA biosynthesis.

systems biology↗