Biology subjects

Cohen, S.

Publications and source records attributed to Cohen, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2020

A broad exome study of the genetic architecture of asthma reveals novel patient subgroups

IntroductionAsthma risk is a complex interplay between genetic susceptibility and environment. Despite many significantly-associated common variants, the contribution of rarer variants with potentially greater effect sizes has not been as extensively studied. We present an exome-based study adopting 24,576 cases and 120,530 controls to assess the contribution of rare protein-coding variants to the risk of early-onset or all-comer asthma. MethodsWe performed case-control analyses on three genetic units: variant-, gene- and pathway-level, using sequence data from the Scandinavian Asthma Genetic Study and UK Biobank participants with asthma. Cases were defined as all-comer asthma (n=24,576) and early-onset asthma (n=5,962). Controls were 120,530 UK Biobank participants without reported history of respiratory illness. ResultsVariant-level analyses identified statistically significant variants at moderate-to-common allele frequency, including protein-truncating variants in FLG and IL33. Asthma risk was significantly increased not only by individual, common FLG protein-truncating variants, but also among the collection of rare-to-private FLG protein-truncating variants (p=6.8x10-7). This signal was driven by early-onset asthma and did not correlate with circulating eosinophil levels. In contrast, a single splice variant in IL33 was significantly protective (p=8.0x10-10), while the collection of remaining IL33 protein-truncating variants showed no class effect (p=0.54). A pathway-based analysis identified that protein-truncating variants in loss-of-function intolerant genes were significantly enriched among individuals with asthma. ConclusionsAccess to the full allele frequency spectrum of protein-coding variants provides additional clarity about the potential mechanisms of action for FLG and IL33. Beyond these two significant drivers, we detected a significant enrichment of protein-truncating variants in loss-of-function intolerant genes.

genomics↗

bioRxiv2020

Adaptive current-flow models of ECT: Explaining individual static impedance, dynamic impedance, and brain current delivery

BackgroundImprovements in electroconvulsive therapy (ECT) outcomes have followed refinement in device electrical output and electrode montage. The physical properties of the ECT stimulus, together with those of the patients head, determine the impedances measured by the device and govern current delivery to the brain and ECT outcomes. ObjectiveHowever, the precise relations among physical properties of the stimulus, patient head anatomy, and patient-specific impedance to the passage of current are long-standing questions in ECT research and practice. MethodsWe developed anatomical MRI-derived models of transcranial electrical stimulation (tES) that included changes in tissue conductivity due to local electrical current flow. These "adaptive" models simulate ECT both during therapeutic stimulation using high (~1 A) current and when dynamic impedance is measured, as well as prior to stimulation when low (~1 mA) current is used to measure static impedance. We modeled two scalp layers: a superficial scalp layer with adaptive conductivity that increases with electric field up to a subject specific maximum [Formula], and a deep scalp layer with a subject-specific fixed conductivity ({sigma}DS). ResultsWe demonstrate that variation in these scalp parameters explain clinical data on subject-specific static impedance and dynamic impedance, their imperfect correlation across subjects, their relationships to seizure threshold, and the role of head anatomy. Adaptive tES models demonstrate that current flow changes local tissue conductivity which in turn shapes current delivery to the brain in a manner not accounted for in fixed tissue conductivity models. ConclusionsOur predictions that variation in individual skin properties, rather than other aspects of anatomy, largely govern the relationship between static impedance, dynamic impedance, and current delivery to the brain, are themselves subject to assumptions about tissue properties. Broadly, our novel pipeline for tES models is important in ongoing efforts to optimize devices, personalize interventions, and explain clinical findings.

bioengineering↗

bioRxiv2020

Chromatin accessibility profiles of castration-resistant prostate cancers reveal novel subtypes and therapeutic vulnerabilities

In castration-resistant prostate cancer (CRPC), the loss of androgen receptor (AR)-dependence due to lineage plasticity, which has become more prevalent, leads to clinically highly aggressive tumors with few therapeutic options and is mechanistically poorly defined. To identify the master transcription factors (TFs) of CRPC in a subtype-specific manner, we derived and collected 29 metastatic human prostate cancer organoids and cell lines, and generated ATAC-seq, RNA-seq and DNA sequencing data. We identified four subtypes and their master TFs using novel computational algorithms: AR-dependent; Wnt-dependent, driven by TCF; neuroendocrine, driven by ASCL1 and NEUROD1 and stem cell-like (SCL), driven by the AP-1 family. The transcriptomic signatures of these four subtypes enabled the classification of 370 patients. We find that AP-1 co-operates with the inhibitable YAP/TAZ/TEAD pathway in the SCL subtype, the second most common group of CRPC tumors after AR-dependent. Together, this molecular classification reveals new drug targets and can potentially guide therapeutic decisions.

cancer biology↗

bioRxiv2020

CoRhythMo: A Computational Framework for Modeling Biobehavioral Rhythms from Mobile and Wearable Data Streams

This paper presents CoRhythMo, the first computational framework for modeling biobehavioral rhythms - the repeating cycles of physiological, psychological, social, and environmental events - from mobile and wearable data streams. The framework incorporates four main components: mobile data processing, rhythm discovery, rhythm modeling, and machine learning. We use a dataset of smartphone and Fitbit data collected from 138 college students over a semester to evaluate the frameworks ability to 1) model biobehavioral rhythms of students, 2) measure the stability of their rhythms over the course of the semester, 3) model differences between rhythms of students with different health status, and 4) predict the mental health status in students using the model of their biobehavioral rhythms. Our evaluation provides evidence for the feasibility of using CoRhythMo for modeling and discovering human rhythms and using them to assess and predict different life and health outcomes.

bioinformatics↗

bioRxiv2020

BLM-dependent Break-Induced Replication handles DSBs in transcribed chromatin upon impaired RNA:DNA hybrids dissolution.

Transcriptionally active loci are particularly prone to breakage and mounting evidence suggest that DNA Double-Strand Breaks arising in genes are handled by a dedicated repair pathway, Transcription-Coupled DSB Repair (TC-DSBR), that entails R-loops accumulation and dissolution. Here, we uncovered a critical function of the Bloom RecQ DNA helicase (BLM) in TC-DSBR in human cells. BLM is recruited in a transcription dependent-manner at DSBs where it fosters resection, RAD51 binding and accurate Homologous Recombination repair. However, in a R-loop dissolution-deficient background BLM switches from promoting Homologous Recombination to promoting Break-Induced Replication (BIR), which strongly impairs cell viability. Altogether our work unveils a role for BLM in BIR at DSBs in active chromatin, and highlights the toxic potential of RNA:DNA hybrids that accumulate at these transcription-associated DSBs.

molecular biology↗

bioRxiv2020

Critical role for cold shock protein YB-1 in cytokinesis

High levels of the cold shock protein Y-box-binding protein-1, YB-1, are tightly correlated with increased cell proliferation and cancer progression. However, the precise mechanism by which YB-1 regulates proliferation is unknown. Here, we found that YB-1 depletion in several cell lines resulted in cytokinesis failure, multinucleation and an increase in G1 transit time. Rescue experiments indicated that YB-1 was required for completion of cytokinesis. Using confocal imaging of cells undergoing cytokinesis both in vitro and in zebrafish embryos, we found that YB-1 was critical for microtubule organization during cytokinesis. Using mass spectrometry we identified multiple novel phosphorylation sites on YB-1. We show that phosphorylation of YB-1 at multiple serine residues was essential for its function during cytokinesis. Using atomistic modelling we show how multiple phosphorylations alter YB-1 conformation, allowing it to interact with protein partners. Our results establish phosphorylated YB-1 as a critical regulator of cytokinesis, defining for the first time precisely how YB-1 regulates cell division. SUMMARYY-box-binding protein-1, YB-1, is essential for cell division, but it is not clear how it functions. Using live imaging and confocal microscopy we show that YB-1 functions only in the last step of division, specifically being required to initiate cytokinesis.

cell biology↗

bioRxiv2020

Role of Specialized mSWI/SNF Complexes in Prostate Cancer Lineage Plasticity

Advanced prostate cancer initially responds to hormonal treatment, but ultimately becomes resistant and requires more potent therapies. One mechanism of resistance observed in [~]10% of these patients is through lineage plasticity, which manifests in a partial or complete small cell or neuroendocrine prostate cancer (NEPC) phenotype. Here, we investigate the role of the mammalian SWI/SNF (mSWI/SNF) chromatin remodeling complex in NEPC. Using large patient datasets, patient-derived organoids and cancer cell lines, we identify mSWI/SNF subunits that are deregulated in NEPC and demonstrate that SMARCA4 (BRG1) overexpression is associated with aggressive disease. We also show that SWI/SNF complexes interact with different lineage-specific factors in NEPC compared to prostate adenocarcinoma. These data suggest a role for mSWI/SNF complexes in therapy-related lineage plasticity, which may be relevant for other solid tumors.

cancer biology↗

bioRxiv2020

Dynamics of oligomer populations formed during the aggregation of Alzheimer's Aβ42 peptide

Oligomeric aggregates populated during the aggregation of the A{beta}42 peptide have been identified as potent cytotoxins linked to Alzheimers disease, but the fundamental molecular pathways that control their dynamics have yet to be elucidated. By developing a general approach combining theory, experiment, and simulation, we reveal in molecular detail the mechanisms of A{beta}42 oligomer dynamics during amyloid fibril formation. Even though all mature amyloid fibrils must originate as oligomers, we find that most A{beta}42 oligomers dissociate to their monomeric precursors without forming new fibrils. Only a minority of oligomers converts into fibrillar species. Moreover, the heterogeneous ensemble of oligomeric species interconverts on timescales comparable to aggregation. Our results identify fundamentally new steps that could be targeted by therapeutic interventions designed to combat protein misfolding diseases.

biophysics↗

bioRxiv2020

DNA damage induced during mitosis undergoes DNA repair synthesis

Understanding the mitotic DNA damage response (DDR) is critical to our comprehension of cancer, premature aging and developmental disorders which are marked by DNA repair deficiencies. In this study we use a micro-focused-laser to induce DNA damage in selected mitotic chromosomes to study the subsequent repair response. Our findings demonstrate that (1) mitotic cells are capable of DNA repair as evidenced by DNA synthesis at damage sites, (2) Repair is attenuated when DNA-PKcs and ATM are simultaneously compromised, (3) Laser damage may permit the observation of previously undetected DDR proteins when damage is elicited by other methods in mitosis, and (4) Twenty five percent of mitotic DNA-damaged cells undergo a subsequent mitosis. Together these findings suggest that mitotic DDR is more complex than previously thought and may involve factors from multiple repair pathways that are better understood in interphase.

cell biology↗

bioRxiv2019

Mass spectrometry reveals the chemistry of formaldehyde cross-linking in structured proteins

Formaldehyde is a widely used fixative in biology and medicine. The current mechanism of formaldehyde cross-linking of proteins is the formation of a methylene bridge that incorporates one carbon atom into the link. Here, we present mass spectrometry data that largely refute this mechanism. Instead, the data reveal that cross-linking of structured proteins mainly involves a reaction that incorporates two carbon atoms into the link. Under MS/MS fragmentation, the link cleaves symmetrically to yield previously unrecognized fragments carrying a modification of one carbon atom. If these characteristics are considered, then formaldehyde cross-linking is readily applicable to the structural approach of cross-linking coupled to mass spectrometry. Using a cross-linked mixture of purified proteins, a suitable analysis identifies tens of cross-links that fit well with their atomic structures. A more elaborate in situ cross-linking of human cells in culture identified 469 intra-protein and 90 inter-protein cross-links, which also agreed with available atomic structures. Interestingly, many of these cross-links could not be mapped onto a known structure and thus provide new structural insights. For example, two cross-links involving the protein {beta}NAC localize its binding site on the ribosome. Also of note are cross-links of actin with several auxiliary proteins for which the structure is unknown. Based on these findings we suggest a revised chemical reaction, which has relevance to the reactivity and toxicity of formaldehyde.

biochemistry↗

bioRxiv2019

Plasma-derived exosomal analysis and deconvolution enables prediction and tracking of melanoma checkpoint blockade response

PurposeImmune checkpoint inhibitors (ICI) have demonstrated promising therapeutic benefit although a majority will not respond. Here we identify and validate predictive biomarkers from plasma-derived exosomes that allow non-invasive monitoring of tumor intrinsic and host immune status and prediction of ICI success.\n\nExperimental DesignTranscriptomic profiling of peripheral blood bulk exosomes and tumors from a discovery cohort of 50 patients with metastatic melanoma treated with ICI was undertaken; a further validation cohort of 30 patients was utilized to validate findings from the discovery cohort. We designed a Bayesian probabilistic model to partition bulk exosomes into tumor-specific and non-tumor-specific proportions.\n\nResultsExosomal RNA signatures exhibit significant correlations with tumor transcriptomes. Exosomal profiles reflect several key biological drivers of ICI resistance or melanoma progression, exhibit significantly differentially expressed genes and pathways, and correlate with and are predictive of clinical response to therapy. Our deconvolution model estimates contributions from tumor and non-tumor sources, enabling more precise interpretation of differentially-expressed genes and pathways. Exosomal RNA-seq mutational information can be used to segregate responders and non-responders.\n\nConclusionsPeripheral blood-derived exosomes can serve as a non-invasive biomarker to jointly probe tumor-intrinsic and immune changes to ICI, and can potentially function as predictive markers of ICI responsiveness and a monitoring tool for tumor persistence and immune activation.\n\nStatement of SignificanceWe use transcriptomic analysis of bulk, non-selected, peripheral blood derived exosomes to reveal both tumor-intrinsic and immune-derived signatures predictive of early response to immune checkpoint inhibitor therapy. We develop a novel computational model to classify exosomal transcripts into tumor and non-tumor components and establish relevance in immune checkpoint blockade therapy. We show that tumor driver load from RNA-seq mutational calls are significantly different between responders and non-responders.

cancer biology↗

bioRxiv2019

USP1 deubiquitinates protein kinase Akt to inhibit PI3K-Akt-FoxO signaling

PI3K-Akt-FoxO-mTOR signaling is the central pathway controlling growth and metabolism in all cells. Activation of this pathway requires ubiquitination of Akt prior to its activation by phosphorylation. Here, we found that the deubiquitinating (DUB) enzyme USP1 removes K63-linked polyubiquitin chains on Akt to sustain PI3K-Akt-FoxO signaling low during prolonged starvation. DUB screening platform identified USP1 as a direct DUB for Akt, and USP1 depletion in atrophying muscle increased Akt ubiquitination, PI3K-Akt-FoxO signaling, and glucose uptake during fasting. Co-immunoprecipitation and mass spectrometry identified Disabled-2 (Dab2) and the tuberous sclerosis complex TSC1/TSC2 as USP1 bound proteins. During starvation, Dab2 was essential for Akt recruitment to USP1/UAF1 complex, and for PI3K-Akt-FoxO inhibition. Additionally, to maintain its own protein levels high, USP1 limits TSC1 levels to sustain mTOR-mediated basal protein synthesis rates. This USP1-mediated suppression of PI3K-Akt-FoxO signaling probably contributes to insulin resistance in catabolic diseases and perhaps to malignancies seen with USP1 mutations.

cell biology↗

bioRxiv2019

Genome-wide RNAi screen for context-dependent tumor suppressors identified using in vivo models for neoplasia in Drosophila

Genetic approaches in Drosophila have successfully identified many genes involved in regulation of growth control as well as genetic interactions relevant to the initiation and progression of cancer in vivo. Here, we report on large-scale RNAi-based screens to identify potential tumor suppressor genes that interact with known cancer-drivers: The Epidermal Growth Factor Receptor and the Hippo pathway transcriptional cofactor Yorkie. These screens were designed to identify genes whose depletion drove tissue expressing EGFR or Yki from a state of benign overgrowth into neoplastic transformation in vivo. We also report on an independent screen aimed to identify genes whose depletion suppressed formation of neoplastic tumors in an existing EGFR-dependent neoplasia model. Many of the positives identified here are known to be functional in growth control pathways. We also find a number of novel connections to Yki and EGFR driven tissue growth, mostly unique to one of the two. Thus, resources provided here would be useful to all researchers who study negative regulators of growth in the context of activated EGFR and/or Yki and positive regulators of growth in the context of activated EGFR.

developmental biology↗

bioRxiv2019

Novel lead compounds that target the ribosomal peptidyl transferase center

M. tuberculosis (Mtb) is a pathogenic bacterium that causes tuberculosis, which kills more than 1.5 million people worldwide every year. Strains resistant to available antibiotics pose a significant healthcare problem. The enormous complexity of the ribosome poses a barrier for drug discovery. We have overcome this in a tractable way by using an RNA segment that represents the peptidyl transferase center as a target. By using a novel combination of NMR transverse relaxation times (T2) and computational chemistry approaches, we have obtained improved inhibitors of the Mtb ribosomal PTC. Two phenylthiazole derivatives were predicted by machine learning models as effective inhibitors, and this was confirmed by their IC50 values, which were significantly improved over standard antibiotic drugs.

biochemistry↗

bioRxiv2019

Novel signaling hub of insulin receptor, dystrophin glycoprotein complex and plakoglobin regulates muscle size

Signaling through the insulin receptor governs central physiological functions related to cell growth and metabolism. Here we show by tandem native protein complex purification approach and super-resolution STED microscopy that insulin receptor activity requires association with the fundamental structural module in muscle, the dystrophin glycoprotein complex (DGC), and the desmosomal component plakoglobin ({gamma}-catenin). The integrity of this high-molecular-mass assembly renders skeletal muscle susceptibility to insulin because DGC-insulin receptor dissociation by plakoglobin downregulation reduced insulin signaling and caused atrophy. Furthermore, impaired insulin receptor function in muscles from diabetic mice reduced plakoglobin-DGC-insulin receptor content on the plasma membrane; however, plakoglobin overexpression alone restored DGC association with the insulin receptor, and stimulated glucose uptake. Our findings establish DGC as a signaling hub, containing plakoglobin as an auxiliary subunit, and provide a possible mechanism for the insulin resistance in Duchenne Muscular Dystrophy, and for the cardiomyopathies seen with plakoglobin mutations.

cell biology↗

bioRxiv2018

GRAM: A generalized model to predict the molecular effect of a non-coding variant in a cell-type specific manner

There has been much effort to prioritize genomic variants with respect to their impact on \"function\". However, function is often not precisely defined: Sometimes, it is the disease association of a variant; other times, it reflects a molecular effect on transcription or epigenetics. Here we coupled multiple genomic predictors to build GRAM, a generalized model, to predict a well-defined experimental target: the expression-modulating effect of a non-coding variant in a cell-specific manner. As a first step, we performed feature engineering: using a LASSO regularized linear model, we found transcription factor (TF) binding most predictive, especially for TFs that are hubs in the regulatory network; in contrast, evolutionary conservation, a popular feature in many other functional-impact predictors, has almost no contribution. Moreover, TF binding inferred from in vitro SELEX is as effective as that from in vivo ChIP-Seq. Second, we implemented GRAM integrating SELEX features and expression profiles. The program combines a universal regulatory score for a variant in a non-coding element with a modifier score reflecting the particular cell type. We benchmarked GRAM on a large-scale MPRA dataset in the GM12878 cell line, achieving a ROC score of [~]0.73; performance on the K562 cell line was similar. Finally, we evaluated the performance of GRAM on targeted regions using luciferase assays in MCF7 and K562 cell lines. We noted that changing the insertion position of the construct relative to the reporter gene gives very different results, highlighting the importance of carefully defining the functional target the model is predicting.\n\nAuthor SummaryNoncoding variants lie outside of protein-coding regions, and are found to have disease associations. However, knowledge on the molecular effect of these non-coding variants in a cell-specific context is very limited. Also, different output between multiple experiment platforms may introduce extra complexity in analyzing the molecular function of these variants. We developed GRAM, a generalized model to predict molecular effect of non-coding variants in multiple cell types for different experimental platforms. We first selected the most informative cell-independent SELEX transcription factor binding score on the variant locus as features and then combine cell-specific gene expression profile to build a multi-step prediction model. GRAM has been successfully tested on both MPRA and Luciferase assay, and on three different cell lines: GM12878, K562 and MCF7, shows high performance.

bioinformatics↗

bioRxiv2017

Reducing Pyrrolysine tRNA Copy Number Improves the Performance of Genetic Code Expansion in Live Cell Imaging of Bioorthogonally Labeled Proteins

Genetic code expansion enables the incorporation of non-canonical amino acids (ncAAs) into expressed proteins. ncAAs are usually encoded by a stop codon that is decoded by an exogenous orthogonal aminoacyl tRNA synthetase and its cognate suppressor tRNA, such as the pyrrolysine synthetase/[Formula] pair. In such systems, stop codon suppression is dependent on the intracellular levels of the exogenous tRNA. Therefore, multiple copies of the tRNAPyl gene (PylT) are encoded to improve ncAA incorporation. However, certain applications in mammalian cells, such as live-cell imaging applications, where labelled tRNA contributes to background fluorescence, can benefit from the use of less invasive minimal expression systems. Accordingly, we studied the effect of tRNAPyl on live-cell fluorescence imaging of bioorthogonally-labelled intracellular proteins. We found that in COS7 cells, a decrease in PylT copy numbers had no measurable effect on protein expression levels. Importantly, reducing PylT copy numbers improved the quality of live-cells images by enhancing the signal-to-noise ratio and reducing an immobile tRNAPyl population. This enabled us to improve live cell imaging of bioorthogonally labelled intracellular proteins, and to simultaneously label two different proteins in a cell. Our results indicate that the number of introduced PylT genes can be minimized according to the transfected cell line, incorporated ncAA, and application.

synthetic biology↗

bioRxiv2017

The Healthy Brain Network Biobank: An open resource for transdiagnostic research in pediatric mental health and learning disorders

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

neuroscience↗