Biology subjects

Neal, M. L.

Publications and source records attributed to Neal, M. L..

15 recordsLinked to original sources

bioRxiv2025

Single-cell profiling reveals that dynamic lung immune responses distinguish protection from susceptibility to tuberculosis

The mechanisms that underlie protective immunity to Mycobacterium tuberculosis (Mtb) remain incompletely defined. To identify immune correlates associated with protection, we performed single-cell RNA sequencing of lung immune cells after aerosol Mtb infection of naive mice and mice with contained Mtb infection (CoMtb), a model of naturally acquired resistance, across multiple time points, mouse strains, and Mtb strains. Across conditions, protection was associated with distinct temporal patterns of immune activation, cell recruitment, and resolution. Early after challenge, CoMtb mice exhibited rapid, transient recruitment and activation of CD4 T cells, macrophages, NK, and NKT cells, accompanied by short-lived bursts of type I and II interferon signaling, increased oxidative phosphorylation, and enhanced chemokine-mediated cell-cell communication. In contrast, primary infection elicited delayed but sustained interferon and neutrophil responses and higher bacterial burdens. These data indicate that protection involves dynamically coordinated immune pathways rather than the magnitude of any single response. Transcriptional features of CoMtb overlapped with those observed in nonhuman primates following intravenous BCG vaccination, including enrichment of activated tissue-resident CD4 T cells and innate effector populations. Together, these findings support a model in which effective immunity to Mtb depends on the timing and coordination of immune activation, providing a framework for vaccine strategies that reproduce protective lung immune dynamics.

immunology↗

bioRxiv2025

Functional insights into the photoactive yellow protein family from homologs, multidomain proteins and inferred pyp operons

Photoactive Yellow Protein (PYP) is a model system for functional protein dynamics and a prototype of the PAS domain superfamily. It is a bacterial photoreceptor that triggers a range of responses in different bacteria: phototaxis, biosynthesis of photo-protective pigments, and light regulation of biofilm formation. An important gap in knowledge on PYP is the signal transduction chain that guides the initial signal from the photoreceptor to various biological responses. Here we report an expanded set of 984 PYP homologs, providing information on sequence conservation and variation. We analyze this set of PYPs using two bioinformatics approaches to identify candidate proteins that are functionally related to PYP. First, we identified 153 multi-domain proteins containing PYP and analyzed the domain composition of these proteins. Specific preferences for N- or C-terminal placement of the PYP domain were observed. Second, we identified 113 predicted multi-gene operons containing the pyp gene. These two approaches yielded multiple candidates for proteins in the signal transduction chain associated with PYP, particularly histidine kinase (implying phosphorylation), methyl accepting chemotaxis protein (implying phototaxis), and GGDEF and EAL proteins (implying a role of c-di-GMP and biofilm formation). Some of these candidates were present only in multi-domain proteins and others only in pyp operons. Overexpression of the PYP domain from the MCP-fusion protein from Nitrincola alkalilacustris yielded a protein with an absorbance maximum of 447 nm and an overall photocycle rate of 0.5 seconds. Our results provide a clear basis for future experimental work on identifying signal transduction partners of PYP.

microbiology↗

bioRxiv2025

A Conditional Cas9 System for Stage-Specific Gene Editing in P. falciparum

The malaria parasite has a complex lifecycle involving various host cell environments in both human and mosquito hosts. The parasite must tightly regulate gene expression at each stage in order to adapt to its current environment while continuing development. However, it is challenging to study gene function and regulation of essential genes across the parasites multi-host lifecycle. Thus, we adapted a recently developed a single-plasmid dimerizable Cre recombinase system for rapamycin-controllable expression of Cas9, allowing for conditional introduction of mutations. We explored rates of gene deletion using varying repair template lengths, showing functionality of donor templates under 250bp for homology-directed repair. As a proof of concept, we conditionally disrupted two uncharacterized genes in blood and gametocyte stages, identifying new stage-specific phenotypes. ImportanceAs progress towards eliminating malaria has stalled, there is a pressing need for new antimalarials and vaccines. Genes essential to multiple stages of development represent ideal candidates for both antimalarials and vaccines. However, much of the parasite genome remains uncharacterized. Conditional gene perturbation approaches are needed in order to study gene function across the lifecycle. Currently available tools are limited in their ability to perturb genes at the scale required for large screens. We describe a tool that allows for conditional introduction of desired mutations by controlling Cas9 with the DiCre-loxP system. We demonstrate the accessibility of this approach by designing gRNA-donor pairs that can be commercially synthesized. This toolkit provides a scalable system for identifying new drug and vaccine candidates targeting multiple stages of the parasite lifecycle

microbiology↗

bioRxiv2024

CD4-mediated immunity shapes neutrophil-driven tuberculous pathology

Pulmonary Mycobacterium tuberculosis (Mtb) infection results in highly heterogeneous lesions ranging from granulomas with central necrosis to those primarily comprised of alveolitis. While alveolitis has been associated with prior immunity in human post-mortem studies, the drivers of these distinct pathologic outcomes are poorly understood. Here, we show that these divergent lesion structures can be modeled in C3HeB/FeJ mice and are regulated by prior immunity. Using quantitative imaging, scRNAseq, and flow cytometry, we demonstrate that Mtb infection in the absence of prior immunity elicits dysregulated neutrophil recruitment and necrotic granulomas. In contrast, prior immunity induces rapid recruitment and activation of T cells, local macrophage activation, and diminished late neutrophil responses. Depletion studies at distinct infection stages demonstrated that neutrophils are required for early necrosis initiation and necrosis propagation at chronic stages, whereas early CD4 T cell responses prevent neutrophil feedforward circuits and necrosis. Together, these studies reveal fundamental determinants of tuberculosis lesion structure and pathogenesis, which have important implications for new strategies to prevent or treat tuberculosis.

immunology↗

bioRxiv2024

Automated, image-based quantification of peroxisome characteristics with perox-per-cell

perox-per-cell automates cumbersome, image-based data collection tasks often encountered in peroxisome research. The software processes microscopy images to quantify peroxisome features in yeast cells. It uses off-the-shelf image processing tools to automatically segment cells and peroxisomes and then outputs quantitative metrics including peroxisome counts per cell and spatial areas. In validation tests, we found that perox-per-cell output agrees well with manually-quantified peroxisomal counts and cell instances, thereby enabling high-throughput quantification of peroxisomal characteristics. The software is available at https://github.com/AitchisonLab/perox-per-cell

bioinformatics↗

bioRxiv2024

Deleteome-Tools: Utilizing a compendium of yeast deletion strain transcriptomes to identify co-functional genes

We introduce DeleteomeTools, an R package that leverages the Deleteome compendium of yeast single-gene deletion transcriptomes to predict gene function. Primarily, the package provides functions for identifying similarities between the transcriptomic signatures of deletion strains, thereby associating genes of interest with others that may be functionally related. We describe how our software predicted a novel relationship between the yeast nucleoporin Nup170 and the Ctf18-RFC complex, which was confirmed experimentally, revealing a previously unknown link between nuclear pore complexes and the DNA replication machinery. To assess the packages broader predictive capabilities, we performed a systematic evaluation that tested how well it predicted Gene Ontology (GO) annotations already applied to the subset of genes deleted in Deleteome strains. We show that our package predicted a majority of reported GO:biological process annotations with semantic similarities ranging from moderate to identical. We also discuss how our strategy for quantifying similarity between deletion strains, which relies on differential expression signatures, differs from other approaches that use global expression profiles and why it has the potential to identify functional relationships that might otherwise go undetected.

bioinformatics↗

bioRxiv2023

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and development of drug resistance. Host-based antivirals, while an alternative, may lead to non-specific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR KO screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting SL drug targets of viral infections. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Comparing data from SARS-CoV-2 and influenza infections, we found possible broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

bioinformatics↗

bioRxiv2023

Multiple Receptor Tyrosine Kinases Regulate Dengue Infection of Hepatocytes

Dengue is an arboviral disease causing severe illness in over 500,000 people each year. Currently, there is no way to constrain dengue in the clinic. Host kinase regulators of dengue virus (DENV) infection have the potential to be disrupted by existing therapeutics to prevent infection and/or disease progression. To evaluate kinase regulation of DENV infection, we performed kinase regression (KiR), a machine learning approach that predicts kinase regulators of infection using existing drug-target information and a small drug screen. We infected hepatocytes with DENV in vitro in the presence of a panel of 38 kinase inhibitors then quantified the effect of each inhibitor on infection rate. We employed elastic net regularization on these data to obtain predictions of which of 300 kinases are regulating DENV infection. Thirty-six kinases were predicted to have a functional role. Intriguingly, seven of the predicted kinases - EPH receptor A4 (EPHA4), EPH receptor B3 (EPHB3), EPH receptor B4 (EPHB4), erb-b2 receptor tyrosine kinase 2 (ERBB2), fibroblast growth factor receptor 2 (FGFR2), Insulin like growth factor 1 receptor (IGF1R), and ret proto-oncogene (RET) - belong to the receptor tyrosine kinase (RTK) family, which are already therapeutic targets in the clinic. We demonstrate that predicted RTKs are expressed at higher levels in DENV infected cells. Knockdown of ERBB2, FGFR2 and IGF1R reduces DENV infection in hepatocytes. Finally, we observe differential temporal induction of ERBB2 and IGF1R following DENV infection, highlighting their unique roles in regulating DENV. Collectively, our findings underscore the significance of multiple RTKs in DENV infection and advocate further exploration of RTK-oriented interventions against dengue.

systems biology↗

bioRxiv2022

Distinct immune responses associated with vaccination status and protection outcomes after malaria challenge

Understanding immune mechanisms that mediate malaria protection is critical for improving vaccine development. Vaccination with radiation-attenuated Plasmodium falciparum sporozoites (PfRAS) induces high level of sterilizing immunity against malaria and serves as a valuable tool for the study of protective mechanisms. To identify vaccine-induced and protection-associated responses during malaria infection, we performed transcriptome profiling of whole blood and in-depth cellular profiling of PBMCs from volunteers who received either PfRAS or noninfectious mosquito bites, followed by controlled human malaria infection (CHMI) challenge. In-depth single-cell profiling of cell subsets that respond to CHMI in mock-vaccinated individuals showed a predominantly inflammatory transcriptome response. Whole blood transcriptome analysis revealed that gene sets associated with interferon responses and T and B cell signatures were increased and decreased, respectively, in protected vaccinees as early as one day following CHMI. In contrast, non-protected vaccinees and mock-vaccinated individuals exhibited shared transcriptome changes after CHMI characterized by decreased innate cell signatures and inflammatory responses. Additionally, immunophenotyping data showed different induction profiles of v{delta}2+{gamma}{delta} T cells, CD56+ CD8+ T effector memory (Tem) cells, and non-classical monocytes between protected vaccinees and individuals developing blood-stage parasitemia, following treatment and resolution of infection. Our data provide key insights in understanding immune mechanistic pathways of PfRAS-induced protection and infective CHMI. We demonstrate that protective immunity by PfRAS is associated with early changes in interferon and adaptive immune responses. Author summaryMalaria poses a significant global health threat, causing over half a million deaths annually. Effective vaccines are critically needed to prevent malaria disease. Our incomplete understanding of immune mechanisms that mediate malaria protection is hampering the development of effective vaccines. Irradiated sporozoite vaccines can induce highly sterilizing protection against malaria and are a valuable tool for the analysis of immune protection. Here, we aimed to characterize correlates of immune protection in individuals vaccinated with a suboptimal dose of irradiated sporozoite and subsequently challenged with live malaria parasite. Blood samples were taken before and after malaria challenge, and gene expression and cell type profiles were measured. We observed that the trajectories of immune response after malaria challenge is highly distinct between protected and non-protected vaccinees. We observed early perturbations in interferon response and adaptive immune cells in protected vaccinees whereas inflammatory and innate cell response were unique to non-protected vaccinees. We also observed that the immune profile after malaria challenge was distinctly similar between non-protected vaccinees and mock-vaccinated individuals. Our study sheds light on the dynamics of vaccine-induced immune responses that are associated with protection from malaria after CHMI.

immunology↗

bioRxiv2022

The nucleoporin Nup170 mediates subtelomeric gene silencing through the Ctf18-RFC complex and PCNA

The nuclear pore complex (NPC) physically interacts with chromatin and regulates gene expression. The inner ring nucleoporin Nup170 has been implicated in chromatin organization and the maintenance of gene silencing in subtelomeric regions. To gain insight into how Nup170 regulates this process, we used protein-protein interaction, genetic interaction, and transcriptome correlation analyses to identify the Ctf18-RFC complex, an alternative proliferating cell nuclear antigen (PCNA) loader, as a facilitator of the gene regulatory functions of Nup170. The Ctf18-RFC complex is recruited to a subpopulation of NPCs that lack the nuclear basket proteins Mlp1 and Mlp2. In the absence of Nup170, PCNA levels on DNA are reduced, resulting in the loss of silencing of subtelomeric genes. Increasing PCNA levels on DNA by removing Elg1, which is required for PCNA unloading, rescues subtelomeric silencing defects in nup170{Delta}. The NPC therefore mediates subtelomeric gene silencing by regulating PCNA levels on DNA.

cell biology↗

bioRxiv2021

SBMate: A Framework for Evaluating Quality of Annotations in Systems Biology Models

The interests in repurposing and reusing systems biology models have been growing in recent years. Semantic annotations play an important role for this, as they provide crucial information on the meanings and functions of models. However, there are a limited number of tools that evaluate the existence or quality of such annotations. In this paper, we introduce SBMate, a python package that would serve as a framework for evaluating the quality of annotations in systems biology models. Three default metrics are provided: coverage, consistency, and specificity. Coverage checks whether annotations exist in a model. Consistency tests if the annotations are appropriate for the given model element. Finally, specificity represents how detailed the annotations are. We analyzed 1,000 curated models from the BioModels repository using the three metrics and discussed the results. Additional metrics can be easily added to extend the current version of SBMate.

systems biology↗

bioRxiv2021

Systems analysis of immune responses to attenuated P. falciparum malaria sporozoite vaccination reveals excessive inflammatory signatures correlating with impaired immunity

Immunization with radiation-attenuated sporozoites (RAS) can confer sterilizing protection against malaria, although the mechanisms behind this protection are incompletely understood. We performed a systems biology analysis of samples from the Immunization by Mosquito with Radiation Attenuated Sporozoites IMRAS) trial, which comprised P. falciparum RAS-immunized (PfRAS), malaria-naive participants whose protection from malaria infection was subsequently assessed by controlled human malaria infection (CHMI). Blood samples collected after initial PfRAS immunization were analyzed to compare immune responses between protected and non-protected volunteers leveraging integrative analysis of whole blood RNA-seq, high parameter flow cytometry, and single cell CITEseq of PBMCs. This analysis revealed differences in early innate immune responses indicating divergent paths associated with protection. In particular, elevated levels of inflammatory responses early after the initial immunization were detrimental for the development of protective adaptive immunity. Specifically, non-classical monocytes and early type I interferon responses induced within 1 day of PfRAS vaccination correlated with impaired immunity. Non-protected individuals also showed an increase in Th2 polarized T cell responses whereas we observed a trend towards increased Th1 and T-bet+ CD8 T cell responses in protected individuals. Temporal differences in genes associated with natural killer cells suggest an important role in immune regulation by these cells. These findings give insight into the immune responses that confer protection against malaria and may guide further malaria vaccine development.

immunology↗

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↗

bioRxiv2018

Model Annotation and Discovery with the Physiome Model Repository

MotivationMathematics and physics based computational models have the potential to help interpret and encapsulate biological phenomena in a computable and reproducible form. Similarly, comprehensive descriptions of such models encoded in computable form help to ensure that such models are accessible, discoverable, and reusable. To this end, researchers have developed tools and standards to encode mathematical models of biological systems enabling reproducibility and reuse; tools and guidelines to facilitate semantic description of mathematical models; and repositories in which to archive, share, and discover models. Biologists and clinicians can leverage these resources to investigate specific questions and hypotheses.\n\nResultsWe have comprehensively annotated a cohort of models with biological semantics. These annotated models are freely available in the Physiome Model Repository (PMR). To demonstrate the benefits of this approach, we have developed a web-based tool which enables users to discover models relevant to their work, with a particular focus on epithelial transport. In helping a user to discover relevant models this tool will provide users with suggestions for similar or alternative models they may wish to explore or utilize in their model based on the models they would like to use. The semantic annotation and the web tool we have developed is a new contribution enabling scientists to discover relevant models in the PMR as candidates for reuse in their own scientific endeavours. We believe that this approach demonstrates how semantic web technologies and methodologies can contribute to biomedical and clinical research.\n\nAvailability and implementationhttps://github.com/dewancse/model-discovery-tool

bioinformatics↗

bioRxiv2018

Harmonizing semantic annotations for computational models in biology

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition, and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current semantic annotation practices among the COmputational Modeling in BIology NEtwork (COMBINE) community and provide a set of recommendations for building a consensus approach to semantic annotation.

scientific communication and education↗