Biology subjects

Hays, M.

Publications and source records attributed to Hays, M..

7 recordsLinked to original sources

bioRxiv2026

Electrical stimulation precisely reproduces naturalistic spiking activity in complete and intermixed neural populations in the primate retina

Neurostimulation technologies have the potential to restore complex brain functions by evoking naturalistic patterns of neural activity. However, faithfully mimicking the brains natural neural code in diverse neuron types remains an unsolved challenge. Here we exploit focal electrical stimulation and recording to reproduce natural visual signals at cellular resolution in two intermixed and oppositely-tuned neural populations in the isolated macaque retina. We calibrated and delivered electrical stimulation sequences to precisely mimic recorded visually-evoked responses to natural images in complete populations of ~50 ON and OFF parasol cells uniformly sampling ~4{degrees} x 4{degrees} of visual angle. Distinct and opposing visually-evoked response patterns in the two intermixed populations were closely replicated spike-by-spike in 5 retinal preparations using electrical stimulation, reproducing spike trains with 51 {+/-} 17% lower variability than repeated presentations of the same visual stimulus. Focal electrical stimulation also replicated traveling waves of neural activity in response to visual motion, and highly structured artificial response patterns. These findings demonstrate for the first time that neurostimulation can match or exceed biological signaling fidelity in large, complete and intermixed neural populations.

bioengineering↗

bioRxiv2024

Spatiotemporal Patterns of Gene Expression During Development of a Complex Colony Morphology

Clonal communities of single celled organisms, such as bacterial or fungal colonies and biofilms, are spatially structured, with subdomains of cells experiencing differing environmental conditions. In the development of such communities, cell specialization is not only important to respond and adapt to the local environment but has the potential to increase the fitness of the clonal community through division of labor. Here, we examine colony development in a yeast strain (F13) that produces colonies with a highly structured "ruffled" phenotype in the colony periphery and an unstructured "smooth" phenotype in the colony center. We demonstrate that in the F13 genetic background deletions of transcription factors can either increase (dig1{Delta}, sfl1{Delta}) or decrease (tec1{Delta}) the degree of colony structure. To investigate the development of colony structure, we carried out gene expression analysis on F13 and the three deletion strains using RNA-seq. Samples were taken early in colony growth (day2), which precedes ruffled phenotype development in F13, and from the peripheral and central regions of colonies later in development (day5), at which time these regions are structured and unstructured (respectively) in F13. We identify genes responding additively and non-additively to the genotype and spatiotemporal factors and cluster these genes into a number of different expression patterns. We identify clusters whose expression correlates closely with the degree of colony structure in each sample and include genes with known roles in the development of colony structure. Individual deletion of 26 genes sampled from different clusters identified 5 with strong effects on colony morphology (BUD8, CIS3, FLO11, MSB2 and SFG1), all of which eliminated or greatly reduced the structure of the F13 outer region.

genetics↗

bioRxiv2023

Identification of host factor for Rift valley fever Phlebovirus

BackgroundRift Valley fever phlebovirus (RVFV) is a zoonotic pathogen that causes Rift Valley fever (RVF) in livestock and humans. Currently, there is no licensed human vaccine or antiviral drug to control RVF. Although multiple species of animals and humans are vulnerable to RVFV infection, host factors affecting susceptibility are not well understood. MethodologyTo identify the host factors or genes essential for RVFV replication, we conducted a CRISPR-Cas9 knock-out screen in human A549 cells. We then validated the putative genes using siRNA-mediated knockdowns and CRISPR-Cas9-mediated knockout studies, respectively. The role of a candidate gene in the virus replication cycle was assessed by measuring intracellular viral RNA accumulation, and the virus titers by plaque assay or TCID50 assay. FindingsWe identified approximately 900 genes with potential involvement in RVFV infection and replication. Further evaluation of the effect of six genes on viral replication using siRNA-mediated knockdowns found that silencing two genes (WDR7 and LRP1) significantly impaired RVFV replication. For further analysis, we focused on the WDR7 gene since the role of LRP1 in RVFV replication was previously described in detail. Knock-out A549 cell lines were generated and used to dissect the effect of WRD7 on RVFV and another bunyavirus, La Crosse encephalitis virus (LACV). We observed significant effects of WDR7 knock-out cells on both intracellular RVFV RNA levels and viral titers. At the intracellular RNA level, WRD7 affected RVFV replication at a later phase of its replication cycle (24h) when compared to LACV which was affected an earlier replication phase (12h). ConclusionIn summary, we have identified WDR7 as an essential host factor for the replication of two relevant bunyaviruses, RVFV and LACV. Future studies will investigate the mechanistic role by which WDR7 facilitates Phlebovirus replication. Authors SummaryRift Valley fever phlebovirus is a high consequence pathogen that infects multiple animal species and also humans. Currently, there are no control measures available to treat RVF in humans and to prevent the incursion of Rift Valley fever virus into non-endemic countries. RVFV poses a significant threat to animal and human health in countries where it is endemic. RVFV replication depends on the hosts machinery to complete its replication cycle. Therefore, one way to control virus replication is to disrupt the interaction between the virus and the host proteins important for replication. In this study, we identified a host factor, the WDR7 gene, that is critical for RVFV replication. The identification of this host factor is important as it can potentially lead to the development of antiviral strategies to control Rift Valley fever in both humans and animals.

microbiology↗

bioRxiv2022

Paths to adaptation under fluctuating nitrogen starvation: The spectrum of adaptive mutations in Saccharomyces cerevisiae is shaped by transposons and microhomology-mediated recombination

There are many mechanisms that give rise to genomic change: while point mutations are often emphasized in genomic analyses, evolution acts upon many other types of genetic changes that can result in less subtle perturbations. Changes in chromosome structure, DNA copy number, and novel transposon insertions all create large genomic changes, which can have correspondingly large impacts on phenotypes and fitness. In this study we investigate the spectrum of adaptive mutations that arise in a population under consistently fluctuating nitrogen conditions. We specifically contrast these adaptive alleles and the mutational mechanisms that create them, with mechanisms of adaptation under batch glucose limitation and constant selection in low, non-fluctuating nitrogen conditions. We observe that retrotransposon activity accounts for a substantial number of adaptive events, along with microhomology-mediated mechanisms of insertion, deletion, and gene conversion. In addition to loss of function alleles, which are often exploited in genetic screens, we identify adaptive gain of function alleles and alleles acting through as-of-yet unclear mechanisms. Taken together, our findings emphasize that how selection (fluctuating vs. non-fluctuating) is applied also shapes adaptation, just as the selective pressure (nitrogen vs. glucose) does itself. Fluctuating environments can activate different mutational mechanisms, shaping adaptive events accordingly. Experimental evolution, which allows a wider array of adaptive events to be assessed, is thus a complementary approach to both classical genetic screens and natural variation studies to characterize the genotype-to-phenotype-to-fitness map.

evolutionary biology↗

bioRxiv2020

Focal Electrical Stimulation of Human Retinal Ganglion Cells

Vision restoration with retinal implants that electrically stimulate retinal ganglion cells (RGCs), which transmit visual information to the brain, is limited by indiscriminate activation of many cells and cell types. Recent work in isolated macaque retina has demonstrated that direct electrical stimulation of RGCs can be performed with single-cell, single-spike resolution. However, the fidelity of epiretinal stimulation has not been examined in the human retina. Here, electrical activation of the major RGC types was examined using large-scale, multi-electrode recording and stimulation in the human retina ex vivo and compared directly to results from macaque. Targeted activation with single-cell, single-spike resolution was often possible without activating overlying axon bundles, at low stimulation current levels similar to those in macaque. Distinct cell types could be identified and targeted based on their distinct electrical signatures. Simulation based on these measurements revealed that a novel, dynamic stimulation approach would produce a nearly optimal evoked visual signal. These results indicate that high-fidelity control of spiking in human RGCs is achievable with extracellular stimulation and that the macaque retina is an accurate model for vision restoration with epiretinal implants.

neuroscience↗

bioRxiv2020

Natural variation in an essential host gene contributes to parasitic plasmid resistance in Saccharomyces cerevisiae

Ongoing antagonistic coevolution with selfish genetic elements (SGEs) can drive the evolution of host genomes. Here, we investigated whether natural variation allows some Saccharomyces cerevisiae strains to suppress 2-micron (2) plasmids, multicopy nuclear parasites that have co-evolved with budding yeasts. To quantitatively measure plasmid stability, we developed a new method, Single-Cell Assay for Measuring Plasmid Retention (SCAMPR) that measures copy number heterogeneity and 2 plasmid loss in live cells. Next, in a survey of 52 natural S. cerevisiae isolates we identified three strains that lack endogenous 2 plasmids and reproducibly inhibit mitotic plasmid stability. Thus, their lack of endogenous 2 plasmids is genetically determined, rather than the result of stochastic loss. Focusing on one isolate (Y9 ragi strain), we determined that plasmid restriction is heritable and dominant. Using bulk segregant analysis, we identified a high-confidence Quantitative Trait Locus (QTL) for mitotic plasmid instability on Y9 chromosome V. We show that a single amino acid change in MMS21 is associated with increased 2-micron instability. MMS21 is an essential gene, encoding a SUMO E3 ligase and a member of the Smc5/6 complex, which is involved in sister chromatid cohesion, chromosome segregation, and DNA repair. Our analyses leverage natural variation to uncover a novel means by which budding yeasts can overcome a highly successful genetic parasite.

evolutionary biology↗

bioRxiv2018

Data-driven multiscale modeling reveals the role of metabolic coupling for the spatio-temporal growth dynamics of yeast colonies

MotivationMulticellular entities, such as mammalian tissues or microbial biofilms, typically exhibit complex spatial arrangements that are adapted to their specific functions or environments. These structures result from intercellular signaling as well as from the interaction with the environment that allow cells of the same genotype to differentiate into well-organized communities of diversified cells. Despite its importance, our understanding on how cell-cell and metabolic coupling produce functionally optimized structures is still limited.\n\nResultsHere, we present a data-driven spatial framework to computationally investigate the development of one multicellular structure, yeast colonies. Using experimental growth data from homogeneous liquid media conditions, we develop and parameterize a dynamic cell state and growth model. We then use the resulting model in a coarse-grained spatial model, which we calibrate using experimental time-course data of colony growth. Throughout the model development process, we use state-of-the-art statistical techniques to handle the uncertainty of model structure and parameterization. Further, we validate the model predictions against independent experimental data and illustrate how metabolic coupling plays a central role in colony formation.\n\nAvailabilityExperimental data and a computational implementation to reproduce the results are available at http://research.cs.aalto.fi/csb/software/multiscale/code.zip.\n\nContactjukka.intosalmi@aalto.fi, alexander.skupin@uni.lu

bioinformatics↗