Biology subjects

Cohen, Y.

Publications and source records attributed to Cohen, Y..

32 records · Page 2Linked to original sources

bioRxiv2022

S6K1 phosphorylates Cdk1 and MSH6 to regulate DNA repair.

The mTORC1 substrate, S6 Kinase 1 (S6K1), is involved in the regulation of cell growth, ribosome biogenesis, glucose homeostasis and adipogenesis. Accumulating evidence has suggested a role for mTORC1 signaling in the DNA damage response. This is mostly based on the findings that mTORC1 inhibitors sensitized cells to DNA damage. However, a direct role of the mTORC1-S6K1 signaling pathway in DNA repair and the mechanism by which this signaling pathway regulates DNA repair is unknown. In this study, we discovered a novel role for S6K1 in regulating DNA repair through the coordinated regulation of the cell cycle, homologous recombination (HR) DNA repair (HRR) and mismatch DNA repair (MMR) mechanisms. Here we show that S6K1 orchestrates DNA repair by phosphorylation of Cdk1 at serine 39, causing G2/M cell cycle arrest enabling homologous recombination and by phosphorylation of MSH6 at serine 309, enhancing MMR. Moreover, breast cancer cells harboring RPS6KB1 gene amplification show increased resistance to several DNA damaging agents and S6K1 expression is associated with poor survival of breast cancer patients treated with chemotherapy. Our findings reveal an unexpected function of S6K1 in the DNA repair pathway, serving as a tumorigenic barrier by safeguarding genomic stability.

cancer biology↗

bioRxiv2021

Rapid adaptation often occurs through mutations to the most highly conserved positions of the RNA polymerase core enzyme

Mutations to the genes encoding the RNA polymerase core enzyme (RNAPC) and additional housekeeping regulatory genes were found to be involved in rapid adaptation, in the context of numerous evolutionary experiments, in which bacteria were exposed to diverse selective pressures. This provides a conundrum, as the housekeeping genes that were so often mutated in response to these diverse selective pressures tend to be among the genes that are most conserved in their sequences across the bacterial phylogeny. In order to further examine this apparent discrepancy, we characterized the precise positions of the RNAPC involved in adaptation to a large variety of selective pressures. We found that different positions of the RNAPC are involved in adaptation to various stresses, with very little overlap found between stresses. We further found that RNAPC positions involved in adaptation tended to be more evolutionary conserved, were more likely to occur within defined protein domains, and tended to be closer to the complexs active site, compared to all other RNAPC positions. Finally, we could show that this observed trend of higher conservation of positions involved in rapid adaptation extends beyond the RNAPC to additional housekeeping genes. Combined, our results demonstrate that the positions that change most readily in response to well defined selective pressures exerted in lab environments are also those that evolve most slowly in nature. This suggests that such adaptations may not readily occur in nature, due to their antagonistically pleiotropic effects, or that if they do occur in nature, they are highly transient.

evolutionary biology↗

bioRxiv2021

Large-scale cellular-resolution imaging of neural activity in freely behaving mice

Miniaturized microscopes for head-mounted fluorescence imaging are powerful tools for visualizing neural activity during naturalistic behaviors, but the restricted field of view of first-generation miniscopes limits the size of neural populations accessible for imaging. Here we describe a novel miniaturized mesoscope offering cellular-resolution imaging over areas spanning several millimeters in freely moving mice. This system enables comprehensive visualization of activity across entire brain regions or interactions across areas.

neuroscience↗

bioRxiv2021

A novel approach to the empirical characterization of learning in biological systems

Learning to execute precise, yet complex, motor actions through practice is a trait shared by most organisms. Here we develop a novel experimental approach for the comprehensive investigation and characterization of the learning dynamics of practiced motion. Following the dynamical systems framework, we consider a high-dimensional behavioral space in which a trial-by-trial sequence of motor outputs defines a trajectory that converges to a fixed point - the desired motor output. In this scenario, details of the internal dynamics and the trial-by-trial learning mechanism cannot be disentangled from behavioral noise for nonlinear systems or even well estimated for linear systems with many parameters. To overcome this problem, we introduce a novel approach: the sporadic application of systematic target perturbations that span the behavioral space and allow us to estimate the linearized dynamics in the vicinity of the fixed point. The steady-state Lyapunov equation then allows us to identify the noise covariance. We illustrate the method by analyzing sequence-generating neural networks with either intrinsic or extrinsic noise, at time resolutions that span from spike timing to spiking rates. We demonstrate the utility of our approach in experimentally plausible and realizable settings and show that this method can fully characterize the linearized between-trials learning dynamics as well as extract meaningful internal properties of the unknown mechanism that drives the motor output within each trial. We then illustrate how the approach can be extended to nonlinear learning dynamics through a flexible choice of the basis and magnitude of perturbations. Significance statementMovement control ties brain activity to measurable external actions in real time, providing a useful tool for both neuroscientists interested in the emergence of stable behavior and biomedical engineers interested in the design of neural prosthesis and brain-machine interfaces. We approach the question of motor skill learning by introducing artificial errors through a novel perturbative scheme amenable to analytic examination in the linearized regime close to the desired behavior. Numerical simulations then demonstrate how to probe the learning dynamics in both linear and nonlinear systems. These findings stress the usefulness of analyzing responses to deliberately induced errors and the importance of properly designing such perturbation experiments. Our approach provides a novel generic tool for monitoring the acquisition of motor skills.

neuroscience↗

bioRxiv2020

TweetyNet: A neural network that enables high-throughput, automated annotation of birdsong

Songbirds have long been studied as a model system of sensory-motor learning. Many analyses of birdsong require time-consuming manual annotation of the individual elements of song, known as syllables or notes. Here we describe the first automated algorithm for birdsong annotation that is applicable to complex song such as canary song. We developed a neural network architecture, "TweetyNet", that is trained with a small amount of hand-labeled data using supervised learning methods. We first show TweetyNet achieves significantly lower error on Bengalese finch song than a similar method, using less training data, and maintains low error rates across days. Applied to canary song, TweetyNet achieves fully automated annotation of canary song, accurately capturing the complex statistical structure previously discovered in a manually annotated dataset. We conclude that TweetyNet will make it possible to ask a wide range of new questions focused on complex songs where manual annotation was impractical.

animal behavior and cognition↗

bioRxiv2020

Spliceosome-Associated MicroRNAs Identified in Breast Cancer Cells Act on Nuclear Targets and Are Potential Indicators for Tumorigenicity

MicroRNAs (miRNAs) act as negative regulators of gene expression in the cytoplasm. Previous studies identified miRNAs associated with the spliceosome. Here we study three breast-derived cell-lines with increased tumorigenicity (from MCF-10A to MCF-7 and MDA-MB-231) and compared their miRNA sequences at the spliceosome fraction (SF). We report that the SF-miRNAs expression, identity, and pre-miRNA segmental composition vary across these cell-lines. The expression of the majority of the abundant SF-miRNAs (e.g. miR-100, miR-30a, and let-7 members) shows an opposite trend in view of the literature and breast cancer large cohorts. The results suggest that SF-miRNAs act in the nucleus on alternative targets than in the cytoplasm. One such miRNA is miR-7704 whose genomic position overlaps HAGLR, a cancer-related lncRNA. We found an inverse expression of miR-7704 and HAGLR in the tested cell lines. Moreover, inhibition of miR-7704 caused an increase in HAGLR expression. Furthermore, increasing miR-7704 levels attenuated the MDA-MB-231 cell-division rate. While miR-7704 acts as oncomiR in breast cancer patients, it has a tumor-suppressing function in SF, with HAGLR being its nuclear target. Manipulating miR-7704 levels is a potential lead for altering tumorigenicity. Altogether, we report on the potential of manipulating SF-miRNAs as an unexplored route for breast cancer therapeutics.

cancer biology↗

bioRxiv2020

An atlas of robust microbiome associations with phenotypic traits based on large-scale cohorts from two continents

Numerous human conditions are associated with the microbiome, yet studies are inconsistent as to the magnitude of the associations and the bacteria involved, likely reflecting insufficiently employed sample sizes. Here, we collected diverse phenotypes and gut microbiota from 34,057 individuals from Israel and the U.S.. Analyzing these data using a much-expanded microbial genomes set, we derive an atlas of robust and numerous unreported associations between bacteria and physiological human traits, which we show to replicate in cohorts from both continents. Using machine learning models trained on microbiome data, we predict human traits with high accuracy across continents. Subsampling our cohort to smaller cohort sizes yielded highly variable models and thus sensitivity to the selected cohort, underscoring the utility of large cohorts and possibly explaining the source of discrepancies across studies. Finally, many of our prediction models saturate at these numbers of individuals, suggesting that similar analyses on larger cohorts may not further improve these predictions.

genomics↗

bioRxiv2019

Spexin and a novel cichlid-specific spexin paralog both inhibit FSH and LH through a specific galanin receptor (Galr2b) in tilapia

Spexin (SPX) is a 14 amino acid peptide hormone that has pleiotropic functions across vertebrates, one of which is involvement in the brain-pituitary-gonad axis of fish. SPX(1) has been identified in each class of vertebrates, and a second SPX (named SPX2) has been found in some non-mammalian species. We have cloned two spexin paralogs, designated as Spx1a and Spx1b, from Nile tilapia (Oreochromis niloticus) that have varying tissue distribution patterns. Spx1b is a novel peptide only identified in cichlid fish, and is more closely related to Spx1 than Spx2 homologs as supported by phylogenetic, synteny, and functional analyses. Kisspeptin, Spx, and galanin (Gal) peptides and their corresponding kiss receptors and Gal receptors (Galrs), respectively, are evolutionarily related. Cloning of six tilapia Galrs (Galr1a, Galr1b, Galr2a, Galr2b, Galr type 1, and Galr type 2) and subsequent in vitro second-messenger reporter assays for Gs, Gq, and Gi suggests that Gal and Spx activate Galr1a/Galr2a and Galr2b, respectively. A decrease in plasma follicle stimulating hormone and luteinizing hormone concentrations was observed with injections of Spx1a or Spx1b in vivo. Additionally, application of Spx1a to pituitary slices decreased the firing rate of LH cells, suggesting direct inhibition at the pituitary level. These data collectively suggest an inhibitory mechanism of action against the secretion of gonadotropins for a traditional and a novel spexin paralog in cichlid species.

molecular biology↗

bioRxiv2019

A modular high-density 294-channel μECoG system on macaque vlPFC for auditory cognitive decoding

OBJECTIVEA fundamental goal of the auditory system is to parse the auditory environment into distinct perceptual representations. Auditory perception is mediated by the ventral auditory pathway, which includes the ventrolateral prefrontal cortex (vlPFC) late. Because large-scale recordings of auditory signals are quite rare, the spatiotemporal resolution of the neuronal code that underlies vlPFCs contribution to auditory perception has not been fully elucidated. Therefore, we developed a modular, chronic, high-resolution, multi-electrode array system with long-term viability.\n\nAPPROACHWe molded three separate ECoG arrays into one and implanted this system in a non-human primate. A custom 3D-printed titanium chamber was mounted on left hemisphere. The molded 294-contact ECoG array was implanted subdurally over vlPFC. ECoG activity was recorded while the monkey participated in a \"hearing-in-noise\" task in which they reported hearing a \"target\" vocalization from a background \"chorus\" of vocalizations. We titrated task difficulty by varying the sound level of the target vocalization, relative to the chorus (target-to-chorus ratio, TCr).\n\nMAIN RESULTSWe decoded the TCr and the monkeys behavioral choices from the ECoG signal. We analyzed decoding capacity as a function of neuronal frequency band, spatial resolution, and time from implantation. Over a one-year period, we were successfully able to record ECoG signals. Although we found significant decoding with as few as two electrodes, we found near-perfect decoding with [~]16 electrodes. Decoding further improved when we included more electrodes. Finally, because the decoding capacity of individual electrodes varied on a day-by-day basis, high-density electrode arrays ensure robust decoding in the long term.\n\nSIGNIFICANCEOur results demonstrate the utility and robustness of high-resolution chronic {micro}ECoG recording. We developed a new high-resolution surface electrode array that can be scaled to cover larger cortical areas without increasing the chamber footprint.

neuroscience↗

bioRxiv2019

Transfer of Septin Rings to Cytokinetic Remnants Directs Age-Sensitive ER stress Surveillance Cell Cycle Re-entry

During cell division, cells must actively pass on organelles. Previously, we discovered the endoplasmic reticulum (ER) stress surveillance (ERSU) pathway that ensures the inheritance of functional ER. Activation of the ERSU causes the septin ring to mislocalize, which blocks ER inheritance and cytokinesis. Here, we found that the septin ring mislocalizes to previously utilized cell division sites called cytokinetic remnants (CRMs). The transfer of the septin ring to CRMs requires Nba1, a negative polarity component that normally prevents septin ring formation at CRMs. Furthermore, septin ring movement to CRMs relies on the ERSU component Slt2, which is recruited by binding Bem1. During ER stress, Bem1 also binds the GTP exchange factor Cdc24, without activating Cdc42, a GTPase that normally establishes polarized growth. Failure to translocate septin rings to CRMs delays the cells ability to re-enter cell division when ER homeostasis is re-established. Thus, ER stress considers the history of previous cell cycle for future cell cycle re-entry upon ER stress recovery.

cell biology↗

bioRxiv2019

Hidden neural states underlie canary song syntax

Coordinated skills such as speech or dance involve sequences of actions that follow syntactic rules in which transitions between elements depend on past actions. Canary songs are comprised of repeated syllables, called phrases, and the ordering of these phrases follows long-range rules, where the choice of what to sing depends on song structure many seconds prior. The neural substrates that support these long-range correlations are unknown. Using miniature head-mounted microscopes and cell-type-specific genetic tools, we observed neural activity in the premotor nucleus HVC as canaries explore various phrase sequences in their repertoire. We find neurons that encode past transitions, extending over 4 phrases and spanning up to 3 seconds and 40 syllables. These neurons preferentially encode past actions rather than future actions, can reflect more than a single song history, and occur mostly during the rare phrases that involve history-dependent transitions in song. These findings demonstrate that network dynamics in HVC reflect preceding behavior context relevant to flexible transitions.

neuroscience↗

bioRxiv2019

A geometric representation unveils rule-learning dynamics in primate neurons

Primates can quickly and advantageously adopt new behaviors based on changing stimuli relationships. We studied acquisition of a classification task while recording single neurons in the dorsal-anterior-cingulate-cortex (dACC) and the Striatum. Monkeys performed trial-by-trial classification on a rich set of multi-cue patterns, allowing de-novo learning every few days. To examine neural dynamics during the learning itself, we represent each rule with a spanning set of the space formed by the stimuli features. Because neural preference can be expressed by feature combinations, we can track neural dynamics in geometrical terms in this space, allowing a compact description of neural trajectories by observing changes in either vector-magnitude and/or angle-to- rule. We find that a large fraction of cells in both regions follow the behavior during learning. Neurons in the dACC mainly rotate towards the policy, suggesting an increase in selectivity that approximates the rule; whereas in the Putamen we also find a prominent magnitude increase, suggesting strengthening of confidence. Additionally, magnitude increases in the striatum followed rotation in the dACC. Finally, the neural representation at the end of the session predicted next-day behavior. The use of this novel framework enables tracking of neural dynamics during learning and suggests differential yet complementing roles for these brain regions.

neuroscience↗

bioRxiv2019

Post-decision processing in primate prefrontal cortex influences subsequent choices on an auditory decision-making task

Perceptual decisions do not occur in isolation but instead reflect ongoing evaluation and adjustment processes that can affect future decisions. However, the neuronal substrates of these across-decision processes are not well understood, particularly for auditory decisions. We measured and manipulated the activity of choice-selective neurons in the ventrolateral prefrontal cortex (vlPFC) while monkeys made decisions about the frequency content of noisy auditory stimuli. As the decision was being formed, vlPFC activity was not modulated strongly by the task. However, after decision commitment, vlPFC population activity encoded the sensory evidence, choice, and outcome of the current trial and predicted subject-specific choice biases on the subsequent trial. Consistent with these patterns of neuronal activity, electrical microstimulation in vlPFC tended to affect the subsequent, but not current, decision. Thus, distributed post-commitment representations of graded decision-related information in prefrontal cortex can play a causal role in evaluating past decisions and biasing subsequent ones.

neuroscience↗

bioRxiv2018

Pogz deficiency leads to abnormal behavior, transcription dysregulation and impaired cerebellar physiology

Genes implicated in autism spectrum disorder (ASD) are enriched with chromatin regulators, but the mechanisms leading to the abnormal behavior and cognition are still unclear. Animal models are crucial for studying the effects of mutations on brain function and behavior. We generated conditional knockout mice with brain-specific mutation in Pogz, a heterochromatin regulator recurrently mutated in ASD and other neurodevelopmental disorders, and demonstrated that these mice display phenotypes that resemble the human condition. Pogz deficiency led to smaller brain, growth impairment, motor learning deficits, and increased social interactions that mimic the human overly friendly phenotype. At the molecular level, reporter assay indicated that POGZ functions as a negative regulator of transcription through its interaction with HP1 proteins. In accordance, we found a significant upregulation of gene expression, most notably in the cerebellum. Furthermore, Pogz deficiency was associated with a significant reduction in the firing frequency of simple and complex spikes in cerebellar Purkinje cells with no changes in their intrinsic properties. Overall, our findings support a mechanism linking heterochromatin dysregulation to cerebellar circuit dysfunction and to motor and social abnormalities in ASD.

neuroscience↗