Biology subjects

Fox, D. M.

Publications and source records attributed to Fox, D. M..

10 recordsLinked to original sources

bioRxiv2026

Host control of Mycobacterium tuberculosis infection is not influenced by the gut microbiome

Tuberculosis (TB) is a life-threatening disease with heterogenous presentation. Approximately one-quarter of the global population is infected with Mycobacterium tuberculosis (Mtb), yet a much smaller fraction develops active TB disease. Host genetics, immune system function, and environmental factors have all been implicated in susceptibility to Mtb, yet no one factor fully explains TB heterogeneity. Strikingly, many of these same factors are linked to gut microbiome composition, which is intimately linked to systemic development of the immune system. Antibiotic treated mouse models suggest that increased gut microbiota diversity is protective against Mtb infection. In contrast, Helicobacter hepaticus colonization is correlated with exacerbated Mtb burden. However, antibiotics can have both microbial and nonmicrobial targets and studies to date have not deconvoluted these effects. Focused testing of specific microbiome members has been impossible without a gnotobiotic model for Mtb. Here, we develop the first gnotobiotic mouse model for Mtb infection and test how microbial diversity in the gut microbiome impacts host susceptibility to Mtb. Surprisingly, after intranasal challenge with Mtb, germ-free wild type mice had no difference in lung burden when compared to mice born with either a defined gut microbiome community (OMM-12) or a diverse, conventional microbiota. H. hepaticus gut colonization of OMM-12 and conventional mice also did not impact Mtb burden in the lungs in this controlled setting. H. hepaticus colonization of the gut did perturb lung immune responses associated with TB infection control. CD4+ T cells were decreased, CD8+ T cells were increased, and IL-6 production was decreased. While the gut microbiome may yet play a role in immune compromised mouse models or human disease, comparing drastically different gut microbiotas in gnotobiotically controlled C57BL/6 mice did not yield any evidence of alteration in Mtb lung burden. The hosts unique immune response to Mtb may in part make the pathogen resistant to immune disruption caused by gut microbiome changes.

microbiology↗

bioRxiv2025

Mucosal delivery of influenza antigens using a replication deficient adenovirus supports broadly reactive antibody responses and heterologous viral immunity in the respiratory tract of animals

Systemically administered influenza vaccines provide strain-limited protection, while influenza infection of the respiratory epithelium supports development of lung resident memory B and T cells and more broadly reactive antibody responses. To test whether local antigen delivery is critical for establishing broad immunity, we directly compared respiratory tract and systemic delivery of influenza antigens to mice and hamsters using a replication-deficient adenovirus serotype 5 vector (Ad5[E1-,E2b-,E3-]). Both immunization routes elicited antibody responses in the lower respiratory tract and antigen-specific B and T cells in the draining lymph node. However, only intranasal immunization established lung-resident memory B and T cells, induced IgA responses in the upper respiratory tract directly at the site of viral entry and supported generation of IgA and IgG antibodies that bound antigenically drifted and distantly related influenza strains, including those of avian origin. Intranasal immunization accelerated viral clearance following heterologous virus challenge and was associated with limited pulmonary inflammation and fibrosis. Thus, intranasal immunization with the immunologically stealthy Ad5[E1-,E2b-,E3-] platform supports respiratory and systemic immunity to divergent influenza strains in the absence of overt lung immunopathology, suggesting that local antigen delivery may be key to development of more broadly protective "universal" flu vaccines.

immunology↗

bioRxiv2021

RNA folding using quantum computers

The 3-dimensional fold of an RNA molecule is largely determined by patterns of intramolecular hydrogen bonds between bases. Predicting the hydrogen bonding network from the sequence, also referred to as RNA secondary structure prediction or RNA folding, is a nondeterministic polynomial-time (NP)-complete computational problem. The structure of the molecule is strongly predictive of its functions and biochemical properties, and therefore the ability to accurately predict the structure is a crucial tool for biochemists. Many methods have been proposed to efficiently sample possible secondary structure patterns. Classic approaches employ dynamic programming, and recent studies have explored approaches inspired by evolutionary algorithms. This work demonstrates leveraging quantum computing hardware to predict the secondary structure of RNA. A Hamiltonian written in the form of a Binary Quadratic Model (BQM) is derived to drive the system toward maximizing the number of base pairs while simultaneously maximizing the average length of the stems. An Adiabatic Quantum Computer (AQC) is compared to a Replica Exchange Monte Carlo (REMC) algorithm programmed with the same objective function, with the AQC being shown to be highly competitive at rapidly identifying low energy solutions. The method proposed in this study was compared to three algorithms from literature and was found to have the highest success rate.

bioinformatics↗

bioRxiv2021

Genome-wide, bidirectional CRISPR screens identify mucins as critical host factors modulating SARS-CoV-2 infection

SARS-CoV-2 can cause a range of symptoms in infected individuals, from mild respiratory illness to acute respiratory distress syndrome. A systematic understanding of the host factors mediating viral infection or restriction is critical to elucidate SARS-CoV-2 host-pathogen interactions and the progression of COVID-19. To this end, we conducted genome-wide CRISPR knockout and activation screens in human lung epithelial cells with endogenous expression of the SARS-CoV-2 entry factors ACE2 and TMPRSS2. These screens uncovered proviral and antiviral host factors across highly interconnected host pathways, including components implicated in clathrin transport, inflammatory signaling, cell cycle regulation, and transcriptional and epigenetic regulation. We further identified mucins, a family of high-molecular weight glycoproteins, as a prominent viral restriction network. We demonstrate that multiple membrane-anchored mucins are critical inhibitors of SARS-CoV-2 entry and are upregulated in response to viral infection. This functional landscape of SARS-CoV-2 host factors provides a physiologically relevant starting point for new host-directed therapeutics and suggests interactions between SARS-CoV-2 and airway mucins of COVID-19 patients as a host defense mechanism.

genetics↗

bioRxiv2021

VISUAL CORTICAL AREA MT IS REQUIRED FOR DEVELOPMENT OF THE DORSAL STREAM AND ASSOCIATED VISUOMOTOR BEHAVIOURS

The middle temporal (MT) area of the extrastriate visual cortex has long been studied in adulthood for its distinctive physiological properties and function as a part of the dorsal stream, yet interestingly possesses a similar maturation profile as the primary visual cortex (V1). Here we examined whether an early-life lesion of MT altered the dorsal stream development and the behavioural precision of reaching to grasp sequences. We observed permanent changes in the anatomy of cortices associated with both reaching (PE and MIP) and grasping (AIP), as well as in reaching and grasping behaviours. In addition, we observed a significant impact on the anatomy of V1 and the direction sensitivity of V1 neurons in the lesion projection zone. These findings indicate that area MT is a crucial node for the development of the primate vision, impacting both V1 and areas in the dorsal visual pathway known to mediate visually guided manual behaviours. TeaserThe early life loss of visual area MT leads to significant anatomical, physiological and behavioural changes.

neuroscience↗

bioRxiv2021

mRNA codon optimization on quantum computers

Reverse translation of polypeptide sequences to expressible mRNA constructs is a NP-hard combinatorial optimization problem. Each amino acid in the protein sequence can be represented by as many as six codons, and the process of selecting the combination that maximizes probability of expression is termed codon optimization. This work investigates the potential impact of leveraging quantum computing technology for codon optimization. An adiabatic quantum computer (AQC) is compared to a standard genetic algorithm (GA) programmed with the same objective function. The AQC is found to be competitive in identifying optimal solutions and future generations of AQCs may be able to outperform classical GAs. The utility of gate-based systems is also evaluated using a simulator resulting in the finding that while current generations of devices lack the hardware requirements, in terms of both qubit count and connectivity, to solve realistic problems, future generation devices may be highly efficient.

bioinformatics↗

bioRxiv2020

Screening a library of FDA-approved and bioactive compounds for antiviral activity against SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has emerged as a major global health threat. The COVID-19 pandemic has resulted in over 80 million cases and 1.7 million deaths to date while the number of cases continues to rise. With limited therapeutic options, the identification of safe and effective therapeutics is urgently needed. The repurposing of known clinical compounds holds the potential for rapid identification of drugs effective against SARS-CoV-2. Here we utilized a library of FDA-approved and well-studied preclinical and clinical compounds to screen for antivirals against SARS-CoV-2 in human pulmonary epithelial cells. We identified 13 compounds that exhibit potent antiviral activity across multiple orthogonal assays. Hits include known antivirals, compounds with anti-inflammatory activity, and compounds targeting host pathways such as kinases and proteases critical for SARS-CoV-2 replication. We identified seven compounds not previously reported to have activity against SARS-CoV-2, including B02, a human RAD51 inhibitor. We further demonstrated that B02 exhibits synergy with remdesivir, the only antiviral approved by the FDA to treat COVID-19, highlighting the potential for combination therapy. Taken together, our comparative compound screening strategy highlights the potential of drug repurposing screens to identify novel starting points for development of effective antiviral mono- or combination therapies to treat COVID-19.

microbiology↗

bioRxiv2020

Mapping the neural circuitry of predator fear in the nonhuman primate

In rodents, innate and learned fear of predators depends on the medial hypothalamic defensive system, a conserved brain network that lies downstream of the amygdala. However, it remains unknown whether this network is involved in primate fear. Here we demonstrate that visually evoked predator fear recruits a homologous medial hypothalamic defense system in the nonhuman primate

neuroscience↗

bioRxiv2019

Chemical precision glyco-mutagenesis by glycosyltransferase engineering in living cells

Studying posttranslational modifications classically relies on experimental strategies that oversimplify the complex biosynthetic machineries of living cells. Protein glycosylation contributes to essential biological processes, but correlating glycan structure, underlying protein and disease-relevant biosynthetic regulation is currently elusive. Here, we engineer living cells to tag glycans with editable chemical functionalities while providing information on biosynthesis, physiological context and glycan fine structure. We introduce a non-natural substrate biosynthetic pathway and use engineered glycosyltransferases to incorporate chemically tagged sugars into the cell surface glycome of the living cell. We apply the strategy to a particularly redundant yet disease-relevant human glycosyltransferase family, the polypeptide N-acetylgalactosaminyl transferases. This approach bestows a gain-of-function modification on cells where the products of individual glycosyltransferases can be selectively characterized or manipulated at will.

synthetic biology↗

bioRxiv2017

Mechanisms of generation of membrane potential resonance in a neuron with multiple resonant ionic currents

Neuronal membrane potential resonance (MPR) is associated with subthreshold and network oscillations. A number of voltage-gated ionic currents can contribute to the generation or amplification of MPR, but how the interaction of these currents with linear currents contributes to MPR is not well understood. We explored this in the pacemaker PD neurons of the crab pyloric network. The PD neuron MPR is sensitive to blockers of H- (IH) and calcium-currents (ICa). We used the impedance profile of the biological PD neuron, measured in voltage clamp, to constrain parameter values of a conductance-based model using a genetic algorithm and obtained many optimal parameter combinations. Unlike most cases of MPR, in these optimal models, the values of resonant- (fres) and phasonant- (f{varphi}=0) frequencies were almost identical. Taking advantage of this fact, we linked the peak phase of ionic currents to their amplitude, in order to provide a mechanistic explanation the dependence of MPR on the ICa gating variable time constants. Additionally, we found that distinct pairwise correlations between ICa parameters contributed to the maintenance of fres and resonance power (QZ). Measurements of the PD neuron MPR at more hyperpolarized voltages resulted in a reduction of fres but no change in QZ. Constraining the optimal models using these data unmasked a positive correlation between the maximal conductances of IH and ICa. Thus, although IH is not necessary for MPR in this neuron type, it contributes indirectly by constraining the parameters of ICa.\n\nAuthor SummaryMany neuron types exhibit membrane potential resonance (MPR) in which the neuron produces the largest response to oscillatory input at some preferred (resonant) frequency and, in many systems, the network frequency is correlated with neuronal MPR. MPR is captured by a peak in the impedance vs. frequency curve (Z-profile), which is shaped by the dynamics of voltage-gated ionic currents. Although neuron types can express variable levels of ionic currents, they may have a stable resonant frequency. We used the PD neuron of the crab pyloric network to understand how MPR emerges from the interplay of the biophysical properties of multiple ionic currents, each capable of generating resonance. We show the contribution of an inactivating current at the resonant frequency in terms of interacting time constants. We measured the Z-profile of the PD neuron and explored possible combinations of model parameters that fit this experimentally measured profile. We found that the Z-profile constrains and defines correlations among parameters associated with ionic currents. Furthermore, the resonant frequency and amplitude are sensitive to different parameter sets and can be preserved by co-varying pairs of parameters along their correlation lines. Furthermore, although a resonant current may be present in a neuron, it may not directly contribute to MPR, but constrain the properties of other currents that generate MPR. Finally, constraining model parameters further to those that modify their MPR properties to changes in voltage range produces maximal conductance correlations.

biophysics↗