Biology subjects

Reiner, A.

Publications and source records attributed to Reiner, A..

14 recordsLinked to original sources

bioRxiv2026

Chromatin architecture and physical constriction cooperate in phenotype switching and cancer cell dissemination

Phenotypic plasticity is a prominent cancer feature that contributes to metastatic potential and resistance to therapy across multiple cancer types. Cancer cell state transitions have been attributed to transcriptional programs, such as the AP1/TEAD-regulated gene network driving the mesenchymal-like (MES) phenotype. In addition, during dissemination, tumor cells are subjected to variable loads of physical mechanical pressure and constriction across transited tissue, which are thought to impact nuclear molecular crowding. How the interplay between mechanical pressure, global 3D nuclear architecture and transcriptional programs contributes to MES identity and metastatic adaptation remains unclear. Using cutaneous melanoma as a model for early dissemination, we integrate in vitro and in vivo epigenomic profiling with nanoscale imaging of cell lines and patient samples to investigate chromatin organization features underlying the MES phenotype. We find that in MES cells, CTCF is relocated from domain boundaries to regulatory regions of EMT-like genes, leading to reduced insulation, extended topological associated domains (TADs) and increased inter-domain contacts, and de novo formation of chromatin hubs. This conformational rewiring, along with loss of heterochromatin, supports nuclear deformability during invasion and dissemination. Conversely, physical constriction of melanocytic cells induces MES-like chromatin features--including CTCF repositioning and heterochromatin loss-- and promotes metastasis in vivo. Similarly, pharmacological inhibition of the heterochromatin mark H3K9me3 triggers MES characteristics and increases invasiveness. These results demonstrate that metastatic competency involves both epigenetic and structural nuclear reprogramming, enabling shifts in gene networks and physical adaptability. Our findings reveal mechanistic links between nuclear architecture and aggressive tumor behavior, identifying potential biomarkers and therapeutic targets to intercept metastatic progression.

cancer biology↗

bioRxiv2025

Localization of Mutant Huntingtin with HTT Exon1 P90 C-terminal Neoepitope Antibodies in Relation to Regional and Neuronal Vulnerability in Forebrain in Q175 Mice and Human Huntington's Disease

BackgroundRecent evidence suggests that accumulation of mutant exon 1 protein (HTT1a) may be critical to HD pathogenesis, but the relation of this to differential regional and cellular vulnerability in HD is unknown. ObjectiveWe assessed the contribution of the accumulation of the mutant huntingtin HTT1a to the regional and cellular variation in HD brain pathology by determining if more vulnerable regions and neuron types were relatively enriched. MethodsWe performed immunolabeling using the novel monoclonal antibodies 11G2 and 1B12 against the C-terminal proline 90 (P90) neoepitope of huntingtin HTT1a, which detect accumulation of monomeric, oligomeric and aggregated mutant HTT1a, on forebrain of Q175 and R6/2 mice and human HD cases. ResultsDiffuse nuclear and aggregate immunolabeling increased in abundance in Q175 with age, with striatal projection neurons showing immunolabeling earlier than cortical neurons, and only neuropil immunolabeling prominent in pallidal regions. Nonetheless, some regions less affected in HD, such as hippocampus, were rich in mutant HTT1a as well. In humans, striatal immunolabeling was sparser than in mouse, and mainly in the neuropil, but sparser in striatal target areas. In human HD cortex, the P90 antibodies detected predominantly neuropil aggregates, which appeared to, in part, localize to dendrites. Immunostaining in mouse and human could be blocked with HTT1a target peptide, demonstrating antibody specificity. ConclusionsOur results indicate that mutant HTT1a burden appears to partly account for overall differential forebrain regional vulnerability in HD, but additional factors may contribute to vulnerability differences among forebrain regions and between specific neuron types. Plain Language SummaryHuntingtons disease (HD) is caused by a mutant gene that is passed from one generation to the next. The mutant gene causes production of a mutant variant of an otherwise valuable protein called huntingtin. This mutant protein is thought to gradually damage neurons in the brain, leading to such extensive loss in a part of the brain called the basal ganglia that movement is impaired. The disability is eventually so severe, it proves fatal. It has been a mystery as to why the mutant protein might cause brain damage, but more so to some brain areas than others. One important recent clue has emerged from studies of the abnormal huntingtin protein that cells with the mutation make. Namely, rather than make a huntingtin protein of full size, as occurs normally, cells instead make only an abbreviated form of the huntingtin protein, but one that contains the abnormality. We hypothesized that if this mutant fragment is particularly toxic and the cause of the neuron damage in HD, then those brain regions that are most injured in the disease should accumulate more of this mutant fragment early in disease. We evaluated this hypothesis by examining accumulation of this mutant fragment, using a staining method selective for the fragment, in histological specimens from the brains of humans with HD and mice engineered to possess the same mutant gene as in the human disease. We found to a large extent that it is the case that those brain regions that showed the most disease-related damage, such as the basal ganglia, also accumulated the mutant huntingtin protein fragment the most. This fragment thus does appear to be toxic for neurons. Our work suggests that therapeutic efforts for HD should be directed at preventing its production or accumulation.

neuroscience↗

bioRxiv2025

A Bayesian Approach for Identifying Driver Mutations within Oncogenic Pathways through Mutual Exclusivity

Distinguishing driver mutations from the large background of passenger mutations remains a major challenge in cancer genomics. Evidence-based approaches to nominate driver mutations are often limited by the availability of experimental or clinical validation for specific variants. As clinical sequencing becomes integrated into patient care, computational methods provide powerful opportunities to analyze expanding genomic datasets and identify functional candidates beyond the current knowledge base. Among various analytical frameworks, mutual exclusivity, the observation that mutations in two or more genes tend not to co-occur within the same tumor, has been particularly attractive. Building on this principle, we propose BayesMAGPIE, a refined version of a statistical method, MAGPIE, developed previously for identifying driver genes within oncogenic pathways. The new method introduces two key innovations. First, it incorporates information on mutation type using a Bayesian hierarchical modeling framework, enabling the distinction between potential differences in functional effects among variants within the same gene, thereby improving the accuracy of driver identification. Second, it models gene-specific driver frequencies with a Dirichlet prior which effectively controls the sparsity of the inferred driver set and aligns with the biological expectation that most tumor types are driven by a small number of genes. We evaluate BayesMAGPIE through extensive simulation studies to assess its estimation bias and accuracy in driver identification, and benchmark its performance against MAGPIE using TCGA data from eight cancer types.

bioinformatics↗

bioRxiv2025

Atypical plume-like events drive glutamate accumulation in metabolic stress conditions

Neural glutamate homeostasis plays a key role in health and disease. In ischemic conditions, such as stroke, this homeostasis is severely disrupted since energy depletion and ion imbalances lead to more glutamate release and less uptake. We here used the fluorescent glutamate sensor SF-iGluSnFR(A184V) to probe the effects of chemical ischemia on extracellular glutamate dynamics in situ, using organotypic slice cultures from mouse cortex. SF-iGluSnFR imaging reported spontaneous glutamate release events, which indicate synchronous network activity, similar to calcium signals detected with GCaMP6f. In addition, glutamate imaging revealed local, asynchronous release events, which were atypically large and long-lasting and showed plume-like characteristics. Under baseline conditions plumes occurred with low frequency, were independent of network activity, and persisted in the presence of TTX. Plume induction was strongly favored by blocking glutamate uptake with TFB-TBOA, whereas blocking ionotropic glutamate receptors (iGluRs) suppressed plumes. Upon inducing chemical ischemia plumes became more pronounced and overly abundant, which resulted in large-scale accumulation of extracellular glutamate. Similar plumes were recently also observed in models of cortical spreading depression and migraine. We therefore propose that plumes represent a more general phenomenon induced by glutamate uptake dysfunction, which may contribute to glutamate-related excitotoxicity in various neurodegenerative and neurological disorders.

neuroscience↗

bioRxiv2025

Detection of HTTex1p by western blot and immunostaining of HD human and mouse brain using neo-epitope antibody P90 highlights impact of CAG repeat expansion on its size, solubility, and response to MSH3 silencing

HTT1a was identified in human and mouse Huntingtons disease brain as the pathogenic exon 1 mRNA generated from aberrant splicing between exon 1 and 2 of HTT that contributes to aggregate formation and neuronal dysfunction.1 Detection of the huntingtin exon 1 protein (HTT1a) has been accomplished with fluorescence-based reporter assays (Meso Scale Discovery, Homogeneous Time Resolved Fluorescence) and immunoprecipitation assays in Huntingtons disease knock-in mice but direct detection in homogenates by gel electrophoresis and western blot assay has been lacking. Subcellular fractions prepared from mouse and human Huntingtons disease brain were separated by gel electrophoresis and probed by western blot with neo-epitope monoclonal antibodies 1B12 and 11G2 directed to the C-terminal eight residues of HTT1a. In caudate putamen of an allelic series of 6 month old Huntingtons disease knock-in mice (Q50, Q80, Q111, Q140 and Q175) HTT1a migration was inversely correlated with CAG repeat length and appeared as a SDS soluble high molecular mass smear in Q111, Q140 and Q175 mice but weakly in Q80 and not in WT mice or Q50 indicating a CAG repeat size threshold for detecting HTT1a. HTT1a immunoreactivity diminished if 1B12 and 11G2 antibodies were preincubated with an eight amino acid peptide containing the C-terminus of HTT1a but not with unrelated peptide sequence. Migration of HTT1a and its high molecular mass smear changed with age in caudate putamen of Q111, Q175 and YAC128 mice. Treating Q111 mice with siRNA to MSH3, a modifier of CAG repeat expansion, significantly reduced levels of the high molecular mass smear indicating that the effects of curbing CAG repeat expansion were quantifiable. A prominent 56-60 kDa doublet detected by 1B12 and 11G2 antibodies in lysates from human Huntingtons disease brain was not blocked by preincubation with C-terminal HTT1a blocking peptide and also appeared in brains of Parkinsons disease patients. 1B12 and 11G2 antibodies did not immunoprecipitate HTT proteins from either Huntingtons disease mouse or human brain lysates using conditions that pulled down full length HTT with anti-HTT antibody 2B7. Altogether these data show that 11G2 and 1B12 antibodies can be used in western blot assays to track and quantify immunoreactive HTT1a levels, solubility, and subcellular localization in Huntingtons disease mouse brain. Abbreviated SummarySapp et al., report that pathogenic exon 1 protein HTT1a is detected in brain of mouse models of Huntingtons disease by direct western blot assay using monoclonal antibodies 11G2 and 1B12. Lowering MSH3 mRNA in the caudate putamen to prevent CAG repeat expansion reduced levels of HTT1a.

neuroscience↗

bioRxiv2024

PinkyCaMP a mScarlet-based calcium sensor with exceptional brightness, photostability, and multiplexing capabilities

Genetically encoded calcium (Ca2+) indicators (GECIs) are widely used for imaging neuronal activity, yet current limitations of existing red fluorescent GECIs have constrained their applicability. The inherently dim fluorescence and low signal-to-noise ratio of red-shifted GECIs have posed significant challenges. More critically, several red-fluorescent GECIs exhibit photoswitching when exposed to blue light, thereby limiting their applicability in all-optical experimental approaches. Here, we present the development of PinkyCaMP, the first mScarlet-based Ca2+ sensor that outperforms current red fluorescent sensors in brightness, photostability, signal-to-noise ratio, and compatibility with optogenetics and neurotransmitter imaging. PinkyCaMP is well-tolerated by neurons, showing no toxicity or aggregation, both in vitro and in vivo. All imaging approaches, including single-photon excitation methods such as fiber photometry, widefield imaging, miniscope imaging, as well as two-photon imaging in awake mice, are fully compatible with PinkyCaMP.

neuroscience↗

bioRxiv2024

Improving Accuracy of Somatic Mutation Profiling in Large Epidemiologic Studies: Addressing Cases without Matched Normal Samples

Ideally, detection of somatic mutations in a tumor is accomplished using a patient-matched sample of normal cells as the benchmark. In this way somatic mutations can be distinguished from rare germline mutations. In large retrospective studies, archival tissue collection can pose challenges in obtaining samples of normal DNA. In this article we propose a protocol that improves somatic mutation analysis in the absence of a matched normal sample. The method was motivated by the InterMEL study, a large-scale epidemiologic investigation involving multiomic, multi-institutional genomic profiling of 1000 primary melanoma samples. The key insight for accomplishing improved mutation calling is the fact that germline mutations should produce a variant allele frequency (VAF) of around 50%. While a similar VAF of 50% would also be expected for somatic mutations in pure tumor samples, typically the tumor purity is much less than 50%, resulting in a considerably lower VAF. Making use of a technique that can simultaneously estimate both tumor purity and VAF from tumor-only samples we have developed a method for better distinguishing somatic versus germline variants. Based on 137 melanomas from the InterMEL Study with matched normal tissue to provide a gold standard we show that the conventional pipeline using a panel of (unmatched) normal samples has a false positive rate of 15.6% and a false negative rate of 3.5%. Our new technique improves these error rates to 6.4% and 2.1%, respectively.

genomics↗

bioRxiv2024

Spatial Immunophenotyping from Whole-Slide Multiplexed Tissue Imaging Using Convolutional Neural Networks

The multiplexed immunofluorescence (mIF) platform enables biomarker discovery through the simultaneous detection of multiple markers on a single tissue slide, offering detailed insights into intratumor heterogeneity and the tumor-immune microenvironment at spatially resolved single cell resolution. However, current mIF image analyses are labor-intensive, requiring specialized pathology expertise which limits their scalability and clinical application. To address this challenge, we developed CellGate, a deep-learning (DL) computational pipeline that provides streamlined, end-to-end whole-slide mIF image analysis including nuclei detection, cell segmentation, cell classification, and combined immuno-phenotyping across stacked images. The model was trained on over 750,000 single cell images from 34 melanomas in a retrospective cohort of patients using whole tissue sections stained for CD3, CD8, CD68, CK-SOX10, PD-1, PD-L1, and FOXP3 with manual gating and extensive pathology review. When tested on new whole mIF slides, the model demonstrated high precision-recall AUC. Further validation on whole-slide mIF images of 9 primary melanomas from an independent cohort confirmed that CellGate can reproduce expert pathology analysis with high accuracy. We show that spatial immuno-phenotyping results using CellGate provide deep insights into the immune cell topography and differences in T cell functional states and interactions with tumor cells in patients with distinct histopathology and clinical characteristics. This pipeline offers a fully automated and parallelizable computing process with substantially improved consistency for cell type classification across images, potentially enabling high throughput whole-slide mIF tissue image analysis for large-scale clinical and research applications.

bioinformatics↗

bioRxiv2023

Adaptation of a Mutual Exclusivity Framework to Identify Driver Mutations within Biological Pathways

Distinguishing genomic alterations in cancer genes that have functional impact on tumor growth and disease progression from the ones that are passengers and confer no fitness advantage has important clinical implications. Evidence-based methods for nominating drivers are limited by existing knowledge on the oncogenic effects and therapeutic benefits of specific variants from clinical trials or experimental settings. As clinical sequencing becomes a mainstay of patient care, applying computational methods to mine the rapidly growing clinical genomic data holds promise in uncovering novel functional candidates beyond the existing knowledge-base and expanding the patient population that could potentially benefit from genetically targeted therapies. We propose a statistical and computational method (MAGPIE) that builds on a likelihood approach leveraging the mutual exclusivity pattern within an oncogenic pathway for identifying probabilistically both the specific genes within a pathway and the individual mutations within such genes that are truly the drivers. Alterations in a cancer gene are assumed to be a mixture of driver and passenger mutations with the passenger rates modeled in relationship to tumor mutational burden. A limited memory BFGS algorithm is used to facilitate large scale optimization. We use simulations to study the operating characteristics of the method and assess false positive and false negative rates in driver nomination. When applied to a large study of primary melanomas the method accurately identified the known driver genes within the RTK-RAS pathway and nominated a number of rare variants with previously unknown biological and clinical relevance as prime candidates for functional validation.

cancer biology↗

bioRxiv2023

Axons of cortical basket cells originating from dendrites develop higher local complexity than axons emerging from basket cell somata

Neuronal differentiation is regulated by neuronal activity. Here, we analyzed dendritic and axonal growth of Basket cells and non-Basket cells using sparse transfection of channelrhodopsin-YFP and repetitive optogenetic stimulation in slice cultures of rat visual cortex. Neocortical interneurons often display axon-carrying dendrites (AcDs). We found that the AcDs of Basket cells and non-Basket cells were on average their most complex dendrite. Further, the AcD configuration had an influence on Basket cell axonal development. Axons originating from an AcD formed denser arborizations with more terminal endings within the dendritic field of the parent cell. Intriguingly, this occurred already in unstimulated Basket cells, and complexity was not increased further by optogenetic stimulation. However, optogenetic stimulation exerted a growth-promoting effect on axons emerging from Basket cell somata. The axons of non-Basket cells neither responded to the AcD configuration nor to the optogenetic stimulation. The results suggest that the formation of locally dense Basket cell plexuses is regulated by spontaneous activity. Moreover, in the AcD configuration, the AcD and the axon it carries mutually support each others growth. TeaserTextbooks usually draw cortical neurons with axons emerging from the cell body. Axons emerging from dendrites have been considered a caprice of nature until recent work demonstrated that axon-carrying dendrites are neither a rare nor a random phenomenon. Rather, this morphological configuration awards specific functional properties. Here, we discovered a morphogenetic role of the AcD configuration in developing Basket neurons which deliver axo-somatic inhibition to pyramidal neurons. Driven by spontaneous activity, AcD and the axon mutually promote each others growth such that the axon rapidly forms a denser presynaptic terminal field. Basket cells with axons from the cell body achieve the same complexity with technical assistance via an optogenetic stimulation. This way, a dendritic origin accelerates Basket cell axonal development.

neuroscience↗

bioRxiv2022

sDarken: Next generation genetically encoded fluorescent sensors for serotonin

We developed a new family of genetically encoded serotonin (5-HT) sensors (sDarken) on the basis of the native 5-HT1A receptor and circularly permuted GFP. sDarken 5-HT sensors are bright in the unbound state and diminish their fluorescence upon binding of 5-HT. Sensor variants with different affinities for serotonin were engineered to increase the versatility in imaging of serotonin dynamics. Experiments in vitro and in vivo showed the feasibility of imaging serotonin dynamics with high temporal and spatial resolution. As demonstrated here, the designed sensors showed excellent membrane expression, have high specificity, a superior signal-to-noise ratio, detect the endogenous release of serotonin and are suitable for two-photon in vivo imaging.

neuroscience↗

bioRxiv2019

Machine Learning Methods to Identify Genetic Correlates of Radiation-Associated Contralateral Breast Cancer in the WECARE Study

The purpose of this study is to identify germline single nucleotide polymorphisms (SNPs) that optimally predict radiation-associated contralateral breast cancer (RCBC) and to provide new biological insights into the carcinogenic process. Fifty-two women with contralateral breast cancer and 153 women with unilateral breast cancer were identified within the Womens Environmental Cancer and Radiation Epidemiology (WECARE) Study who were at increased risk of RCBC because they were [≤] 40 years of age at first diagnosis of breast cancer and received a scatter radiation dose > 1 Gy to the contralateral breast. A previously reported algorithm, preconditioned random forest regression, was applied to predict the risk of developing RCBC. The resulting model produced an area under the curve of 0.62 (p=0.04) on hold-out validation data. The biological analysis identified the cyclic AMP-mediated signaling and Ephrin-A as significant biological correlates, which were previously shown to influence cell survival after radiation in an ATM-dependent manner. The key connected genes and proteins that are identified in this analysis were previously identified as relevant to breast cancer, radiation response, or both. In summary, machine learning/bioinformatics methods applied to genome-wide genotyping data have great potential to reveal plausible biological correlates associated with the risk of RCBC.

bioinformatics↗

bioRxiv2017

Exome chip meta-analysis elucidates the genetic architecture of rare coding variants in smoking and drinking behavior

BackgroundSmoking and alcohol use behaviors in humans have been associated with common genetic variants within multiple genomic loci. Investigation of rare variation within these loci holds promise for identifying causal variants impacting biological mechanisms in the etiology of disordered behavior. Microarrays have been designed to genotype rare nonsynonymous and putative loss of function variants. Such variants are expected to have greater deleterious consequences on gene function than other variants, and significantly contribute to disease risk.\n\nMethodsIn the present study, we analyzed [~]250,000 rare variants from 17 independent studies. Each variant was tested for association with five addiction-related phenotypes: cigarettes per day, pack years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted single variant tests of all variants, and gene-based burden tests of nonsynonymous or putative loss of function variants with minor allele frequency less than 1%.\n\nResultsMeta-analytic sample sizes ranged from 70,847 to 164,142 individuals, depending on the phenotype. Known loci tagged by common variants replicated, but there was no robust evidence for individually associated rare variants, either in gene based or single variant tests. Using a modified method-of-moment approach, we found that all low frequency coding variants, in aggregate, contributed 1.7% to 3.6% of the phenotypic variation for the five traits (p<.05).\n\nConclusionsThe findings indicate that rare coding variants contribute to phenotypic variation, but that much larger samples and/or denser genotyping of rare variants will be required to successfully identify associations with these phenotypes, whether individual variants or gene- based associations.

genetics↗

bioRxiv2017

TECPR2 a positive regulator of autophagy is implicated in healthy brain ageing

Understanding the healthy brain aging process is key to uncovering the mechanisms leading to pathological age-related neurodegeneration, including progression to Alzheimers disease (AD). Here, we report the first deep whole genome sequencing study aiming to identify variants that are associated specifically to healthy brain aging defined on both clinical and neuropathological level, thus tacking the issue of pathological heterogeneity that often underlies a clinical AD diagnosis. We studied samples from the VITA brain bank and followed an extreme phenotypic ends study design comparing neuropathologically \"healthy\" aging individuals above 80 years of age with pure AD patients of the same age. Focusing on the extreme ends of the phenotypic distribution, and potentially functional variants, we discover a single variant (rs10149146) carried by 53.6% of the \"healthy\" brain elderly individuals in our study (15/28 individuals) and none of the 12 AD cases. This variant lies on the autophagy and cell cycle associated TECPR2 gene. Autophagy dysfunction has been previously implicated in multiple progressive neurodegenerative diseases. An additional non-synonymous variant on the CINP gene (encoding a cell-cycle checkpoint protein) is also found in 46% of healthy controls and absent from all the AD cases. TECPR2 and CINP appear to be \"partner\" genes in terms of regulation and their associated transcription factors have been previously implicated in AD and neurodegeneration. Our study is the first to support the hypothesis that a TECPR2 non-synonymous variant carries a significant neuroprotective effect pointing to key molecules for the involvement of autophagy and cell cycle control in protection from neurodegeneration.

genomics↗