Biology subjects

Ferris, M.

Publications and source records attributed to Ferris, M..

5 recordsLinked to original sources

bioRxiv2026

Diurnal Variations in the Cholinergic System of the Nucleus Accumbens

The nucleus accumbens (NAc) plays a critical role in reward-related behaviors, which exhibit diurnal variations. Cholinergic interneurons (CINs) are the primary source of acetylcholine within the NAc and regulate local dopamine (DA) signaling through nicotinic acetylcholine receptors (nAChRs). Although there are diurnal variations in NAc dynamics, little is known about whether CIN activity and nicotinic signaling also vary across the light/dark cycle. Here, we aimed to determine diurnal variations in the NAc cholinergic system using ex vivo fast-scan cyclic voltammetry and cell-attached electrophysiological recordings in male rodents. We examined time-of-day-dependent differences in nAChR-mediated modulation of DA release, spontaneous CIN firing frequency, and firing patterns. We found that spontaneous CIN firing varied across the light/dark cycle, with increased activity during the dark cycle. Additionally, bath application of nicotine (NIC), mecamylamine (MEC), and dihydro-{beta}-erythroidine (DH{beta}E) reduced CIN firing frequency during the dark cycle, with only MEC decreasing firing frequency in the light cycle. NIC and MEC also altered CIN firing patterns during the dark cycle, whereas DH{beta}E primarily affected firing frequency. Together, these findings demonstrate diurnal variations in NAc CIN activity and reveal time-of-day-dependent differences in the effects of nAChR modulation on spontaneous firing. These results suggest that nicotinic signaling may contribute to diurnal regulation of NAc cholinergic activity, providing insight into mechanisms underlying time-of-day-dependent changes in reward circuitry.

neuroscience↗

bioRxiv2023

Frequent emergence of resistance mutations following complex intra-host genomic dynamics in SARS-CoV-2 patients receiving Sotrovimab

The emergence of the Omicron variant of SARS-CoV-2 represented a challenge to the treatment of COVID-19 with monoclonal antibodies. Only Sotrovimab maintained partial activity, allowing it to be used in high-risk patients infected with the Omicron variant. However, the reports of resistance mutations to Sotrovimab call for efforts to better understand the intra-patient emergence of this resistance. A retrospective genomic analysis was conducted on respiratory samples from immunocompromised patients infected with SARS-CoV-2 who received Sotrovimab at our hospital between December 2021 and August 2022. The study involved 95 sequential specimens from 22 patients (1-12 samples/patient; 3-107 days post-infusion (Ct [≤] 32)). Resistance mutations (in P337, E340, K356, and R346) were detected in 68% of cases; the shortest time to detection of a resistance mutation was 5 days after Sotrovimab infusion. The dynamics of resistance acquisition were highly complex, with up to 11 distinct amino acid changes in specimens from the same patient. In two patients, the mutation distribution was compartmentalized in respiratory samples from different sources. This is the first study to examine the acquisition of resistance to Sotrovimab in the BA.5 lineage, enabling us to determine the lack of genomic or clinical differences between Sotrovimab resistance in BA.5 relative to BA.1/2. Across all Omicron lineages, the acquisition of resistance delayed SARS-CoV-2 clearance (40.67 vs 19.5 days). Close, real-time genomic surveillance of patients receiving Sotrovimab should be mandatory to facilitate early therapeutic interventions.

microbiology↗

bioRxiv2022

Host genetic background is a barrier to vaccine-induced protection against infection

The heterogeneity of immune responses observed in humans is difficult to model in standard inbred laboratory mice. To capture the diversity inherent in mice and better understand how host variation affects BCG-induced immunity against Mycobacterium tuberculosis, 24 unique Collaborative Cross (CC) recombinant inbred mouse strains and the C57BL/6 reference strain were vaccinated with or without BCG, and then challenged with low-dose aerosolized virulent M. tuberculosis. In contrast to standard lab strains, BCG protected only half of the CC strains tested. Furthermore, BCG efficacy is dissociable from inherent susceptibility to TB. As these strains differed primarily in the genes and alleles they inherited from the CC founder strains, we conclude that the host genetic background has a major influence on whether BCG confers protection against M. tuberculosis infection and indicates that host genetics should be considered as an important barrier to vaccine-mediated protection. Importantly, we wished to identify the components of the immune response stimulated by BCG, which were subsequently recalled after Mtb infection and associated with protection. The T cell immune response following BCG vaccination and Mtb challenge was extensively characterized. Although considerable diversity was observed, BCG vaccination had little impact on the composition of T cells recruited and maintained in the lung after infection. Instead, the variability was largely shaped by the genetic background. We developed models to detect vaccine-induced differences, which identified immune signatures associated with BCG-elicited protection against TB. Importantly, even when categorized as susceptible vs. resistant, and protected vs. unprotected, many of the protected CC strains had unique flavors of immunity, indicating multiple paths to protection. Thus, CC mice can be used to define correlates of protection and to identify vaccine strategies that protect a larger fraction of genetically diverse individuals instead of optimizing protection for a single genotype.

immunology↗

bioRxiv2021

Collaborative Cross Founder Expression Analysis (CCFEA)

To understand the role of host genetic variation in infection by SARS-CoV and influenza A virus we developed the Collaborative Cross Founder Expression Analysis (CCFEA), a shiny visualization tool using public RNAseq data from the collaborative cross (CC) founder strains (A/J, C57BL/6J, 129s1/SvImJ, NOD/ShILtJ, NZO/HILtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ) that underwent infection by either virus, linked with genetic analyses to define loci linked to infection, immunity, and disease phenotypes. Individual gene expression data is displayed across founders, viral infections and days post infection. Resource Table O_TBL View this table: org.highwire.dtl.DTLVardef@4a284borg.highwire.dtl.DTLVardef@9b6168org.highwire.dtl.DTLVardef@11831baorg.highwire.dtl.DTLVardef@168e351org.highwire.dtl.DTLVardef@123e9ec_HPS_FORMAT_FIGEXP M_TBL C_TBL

bioinformatics↗

bioRxiv2017

Profiling metabolic flux modes by enzyme cost reveals variable trade-offs between growth and yield in Escherichia coli.

Microbes may maximize the number of daughter cells per time or per amount of nutrients consumed. These two strategies correspond, respectively, to the use of enzyme-efficient or substrate-efficient metabolic pathways. In reality, fast growth is often associated with wasteful, yield-inefficient metabolism, and a general thermodynamic trade-off between growth rate and biomass yield has been proposed to explain this. We studied growth rate/yield trade-offs by using a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM) and by assuming that the growth rate depends directly on the enzyme investment per rate of biomass production. In a comprehensive mathematical model of core metabolism in E. coli, we screened all elementary flux modes leading to cell synthesis, characterized them by the growth rates and yields they provide, and studied the shape of the resulting rate/yield Pareto front. By varying the model parameters, we found that the rate/yield trade-off is not universal, but depends on metabolic kinetics and environmental conditions. A prominent trade-off emerges under oxygen-limited growth, where yield-inefficient pathways support a 2-to-3 times higher growth rate than yield-efficient pathways. EFCM can be widely used to predict optimal metabolic states and growth rates under varying nutrient levels, perturbations of enzyme parameters, and single or multiple gene knockouts.\n\nAuthor SummaryWhen cells compete for nutrients, those that grow faster and produce more offspring per time are favored by natural selection. In contrast, when cells need to maximize the cell number at a limited nutrient supply, fast growth does not matter and an efficient use of nutrients (i.e. high biomass yield) is essential. This raises a basic question about metabolism: can cells achieve high growth rates and yields simultaneously, or is there a conflict between the two goals? Using a new modeling method called Enzymatic Flux Cost Minimization (EFCM), we predict cellular growth rates and find that growth rate/yield trade-offs and the ensuing preference for enzyme-efficient or substrate-efficient metabolic pathways are not universal, but depend on growth conditions such as external glucose and oxygen concentrations.

systems biology↗