Biology subjects

Shah, S.

Publications and source records attributed to Shah, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Coordinated changes in thymic stromal and hematopoietic cells that define the perinatal to juvenile transition

T cells in the perinatal thymus have distinct phenotypes and functions that may be instructed by age-specific features of the microenvironment. We evaluated molecular and cellular profiles of thymic stromal cells, including thymic epithelial cells (TECs), mesenchyme, endothelium, and hematopoietic antigen presenting cells (hAPCs), from birth through one-month of age in mice. Single-cell transcriptional profiling, flow cytometry, and immunohistochemistry revealed coordinated stromal changes accompanied by altered thymocyte differentiation at defined transitional ages during the shift from perinatal growth to juvenile homeostasis, which was mirrored in humans. These analyses link diminished IGF2 expression by mesenchymal cells with activation of the RB pathway in TECs at the transition. Moreover, a coordinated increase in type I interferon signaling in stroma across the transition is associated with altered antigen processing and presentation signatures in TECs and hAPCs. Collectively, these datasets provide a resource to interrogate thymic stroma across the perinatal to juvenile transition.

immunology↗

bioRxiv2025

Executive Functions in relation to Autonomic Control: An Overview of Neuropsychological Evaluation Methods

Executive functions are a set of cognitive processes essential for cognitive control and coordination, enabling the achievement of objectives. These functions include mental exploration of ideas, reasoning, logical conclusion drawing, discipline, decision making, thoughtful consideration before action, tackling unforeseen challenges, resisting temptations, and maintaining focus. Numerous neuropsychological tests assess executive functions in relation to different autonomic control pathways that regulate involuntary physiological processes. The complexity of the autonomic nervous system and the challenges in measuring it alongside cognitive assessments are significant. Issues such as subject movement, environmental changes, and time-consuming protocols further complicate this measurement. There is a notable lack of research on suitable neuropsychological tests for assessing executive functions across diverse autonomic regulatory states. This paper reviews the most frequently used neuropsychological instruments in this context, aiming to guide the research community towards optimal tasks and administration protocols for concurrent autonomic nervous system measurement. The diversity of current executive function tests presents both opportunities and challenges. Some tests are better suited for simultaneous neurophysiological measurements due to their design, duration, and cognitive load, while others may interfere with or be influenced by such monitoring. This variability can lead to inconsistencies in findings and complicate result interpretation and comparison across studies of brain disorders. A significant drawback of using different tasks is the difficulty in comparing outcomes and conducting meta-analyses. Standardizing a smaller selection of tasks with consistent protocols would enhance research reliability, facilitate robust comparisons, and improve the overall quality of meta-analyses. To achieve this standardization, it is essential to first survey and describe the current landscape of executive function assessments in conjunction with autonomic nervous system measurements. ObjectiveThis paper aims to comprehensively analyze current instruments utilized in the assessment of executive functions, elucidating their advantages, limitations, and implications for future standardization initiatives. By systematically examining the most prevalent tools for evaluating executive functions in conjunction with autonomic nervous system measurements within clinical and experimental research settings, this review seeks to provide valuable insights for enhancing methodological consistency and advancing research in this area. MethodsWe searched for articles published using the PubMed database with the following terms: (neuropsychological test OR neuropsychological evaluation OR neuropsychological measure*) AND (executive functions OR EF OR executive function) AND (autonomic OR ANS OR parasympathetic OR PNS OR vagal OR "heart rate variability" OR HRV OR sympathetic OR HPA OR electrodermal OR RSA) Only the healthy population was chosen. There was no language restriction. Results62 articles fulfilled all the inclusion criteria. The 5 neuropsychological tests most frequently used to evaluate executive functions in relation to autonomic regulation were: O_LITrail Making Test (TMT) B C_LIO_LIThe n-back Task including 2-back Task C_LIO_LIWisconsin Card Sorting Test C_LIO_LIStroop Test and its variants C_LIO_LIWechsler Adult Intelligence Scale (WAIS)-Working Memory Composite C_LI The domains of executive functions most frequently assessed are: cognitive flexibility, working memory, and inhibitory control/selective attention. ConclusionThese findings offer valuable insights for future research directions and the development of standardized assessment protocols for executive functions, tailored to diverse socio-demographic profiles.

neuroscience↗

bioRxiv2025

Glycaemic variability underlies myocyte dysfunction and myocardial injury risk in diabetes

Heart disease is the leading cause of morbidity and mortality in individuals with diabetes, due largely to risks associated with ischaemic injuries such as myocardial infarction (MI). We use human population genetic data to demonstrate that current biomarkers of hyperglycaemia do not account for risk of post-MI mortality in diabetes patients. This study therefore systematically evaluates glycaemic stress underpinning cardiovascular risk in diabetes. Using in vivo and in vitro models, we demonstrate that glycaemic variability rather than hyperglycaemia alone is a dominant risk factor for heart muscle dysfunction and myocardial injury sensitivity in diabetes. These findings provide new preclinical models for mechanistic and drug discovery studies and inform strategies for managing cardiovascular outcomes in patients with diabetes.

cell biology↗

bioRxiv2025

CARDBiomedBench: A Benchmark for Evaluating Large Language Model Performance in Biomedical Research

BackgroundsBiomedical research requires sophisticated understanding and reasoning across multiple specializations. While large language models (LLMs) show promise in scientific applications, their capability to safely and accurately support complex biomedical research remains uncertain. MethodsWe present CARDBiomedBench, a novel question-and-answer benchmark for evaluating LLMs in biomedical research. For our pilot implementation, we focus on neurodegenerative diseases (NDDs), a domain requiring integration of genetic, molecular, and clinical knowledge. The benchmark combines expert-annotated question-answer (Q/A) pairs with semi-automated data augmentation, drawing from authoritative public resources including drug development data, genome-wide association studies (GWAS), and Summary-data based Mendelian Randomization (SMR) analyses. We evaluated seven private and open-source LLMs across ten biological categories and nine reasoning skills, using novel metrics to assess both response quality and safety. ResultsOur benchmark comprises over 68,000 Q/A pairs, enabling robust evaluation of LLM performance. Current state-of-the-art models show significant limitations: models like Claude-3.5-Sonnet demonstrates excessive caution (Response Quality Rate: 25% [95% CI: 25% {+/-} 1], Safety Rate: 76% {+/-} 1), while others like ChatGPT-4o exhibits both poor accuracy and unsafe behavior (Response Quality Rate: 37% {+/-} 1, Safety Rate: 31% {+/-} 1). These findings reveal fundamental gaps in LLMs ability to handle complex biomedical information. ConclusionCARDBiomedBench establishes a rigorous standard for assessing LLM capabilities in biomedical research. Our pilot evaluation in the NDD domain reveals critical limitations in current models ability to safely and accurately process complex scientific information. Future iterations will expand to other biomedical domains, supporting the development of more reliable AI systems for accelerating scientific discovery.

bioinformatics↗

bioRxiv2025

Molecular hallmarks of excitatory and inhibitory neuronal resilience and resistance to Alzheimer's disease

BackgroundA significant proportion of individuals maintain healthy cognitive function despite having extensive Alzheimers disease (AD) pathology, known as cognitive resilience. Understanding the molecular mechanisms that protect these individuals can identify therapeutic targets for AD dementia. This study aims to define molecular and cellular signatures of cognitive resilience, protection and resistance, by integrating genetics, bulk RNA, and single-nucleus RNA sequencing data across multiple brain regions from AD, resilient, and control individuals. MethodsWe analyzed data from the Religious Order Study and the Rush Memory and Aging Project (ROSMAP), including bulk (n=631) and multi-regional single nucleus (n=48) RNA sequencing. Subjects were categorized into AD, resilient, and control based on {beta}-amyloid and tau pathology, and cognitive status. We identified and prioritized protected cell populations using whole genome sequencing-derived genetic variants, transcriptomic profiling, and cellular composition distribution. ResultsTranscriptomic results, supported by GWAS-derived polygenic risk scores, place cognitive resilience as an intermediate state in the AD continuum. Tissue-level analysis revealed 43 genes enriched in nucleic acid metabolism and signaling that were differentially expressed between AD and resilience. Only GFAP (upregulated) and KLF4 (downregulated) showed differential expression in resilience compared to controls. Cellular resilience involved reorganization of protein folding and degradation pathways, with downregulation of Hsp90 and selective upregulation of Hsp40, Hsp70, and Hsp110 families in excitatory neurons. Excitatory neuronal subpopulations in the entorhinal cortex (ATP8B1+ and MEF2Chigh) exhibited unique resilience signaling through neurotrophin (modulated by LINGO1) and angiopoietin (ANGPT2/TEK) pathways. We identified MEF2C, ATP8B1, and RELN as key markers of resilient excitatory neuronal populations, characterized by selective vulnerability in AD. Protective rare variant enrichment highlighted vulnerable populations, including somatostatin (SST) inhibitory interneurons, validated through immunofluorescence showing co-expression of rare variant associated RBFOX1 and KIF26B in SST+ neurons in the dorsolateral prefrontal cortex. The maintenance of excitatory-inhibitory balance emerges as a key characteristic of resilience. ConclusionsWe identified molecular and cellular hallmarks of cognitive resilience, an intermediate state in the AD continuum. Resilience mechanisms include preservation of neuronal function, maintenance of excitatory/inhibitory balance, and activation of protective signaling pathways. Specific excitatory neuronal populations appear to play a central role in mediating cognitive resilience, while a subset of vulnerable SST interneurons likely provide compensation against AD-associated dysregulation. This study offers a framework to leverage natural protective mechanisms to mitigate neurodegeneration and preserve cognition in AD.

neuroscience↗

bioRxiv2025

Chd4 remodels chromatin to control retinal cell type specification and lineage termination

During development, neural progenitor cells modify their output over time to produce different types of neurons and glia in chronological sequences. Previous studies have shown that epigenetic processes play a crucial role in regulating neural progenitor potential, but the underlying mechanisms are not well understood. Here, we hypothesized that nucleosome remodelling would regulate the competence transitions of retinal progenitors. We generated retina-specific conditional knockouts (cKOs) in the key nucleosome remodelling enzyme Chd4. Chd4 cKOs overproduced early-born retinal ganglion and amacrine cells. Postnatally, later-born rod photoreceptors were drastically underproduced. Concomitantly, progenitors failed to be exhausted at late phases of development and ultimately overproduced Muller glia. To determine how Chd4 regulates the genome, we used cut&run-seq to reveal Chd4 genome occupancy, and ATAC-seq experiments to visualize nucleosome remodelling. These data revealed that genome accessibility was significantly increased at [~]10,000 regulatory elements and [~]4,000 genes in the Chd4 cKO. Together, these results suggest that Chd4 restricts the genome to repress progenitor identity and promote rod photoreceptor production. Accordingly, multiplexed single-cell transcriptomics demonstrated that deletion of Chd4 led to markedly divergent gene expression profiles. However, despite overproduction of early fates and underproduction of later-born rods, the perinatal transition between early and late progenitor competence was not altered as determined by birthdating experiments and transcriptomic signatures. Taken together, our data suggest that Chd4-dependent chromatin remodelling regulates cell fate specification, and is also required to terminate retinal neurogenesis, but that it does not regulate the progenitor competence windows that restrict early- vs. late-cell-type production. Key findings1) Chd4 cKOs exhibit a strong shift in neurogenesis, with early-born neurons overproduced and late-born neurons underproduced. 2) We present an epigenetic atlas that combines the occupancy of NuRD proteins such as Chd4 and Mbd3, with nucleosome remodelling data and transcriptomic correlates. 3) We show that NuRD regulates the competence transition that terminates the retinal lineage but not earlier competence transitions, showing for the first time that the epigenetic mechanisms governing retinal competence transitions may vary.

developmental biology↗

bioRxiv2024

CEBPA repression by MECOM blocks differentiation to drive aggressive leukemias

Acute myeloid leukemias (AMLs) have an overall poor prognosis with many high-risk cases co-opting stem cell gene regulatory programs, yet the mechanisms through which this occurs remain poorly understood. Increased expression of the stem cell transcription factor, MECOM, underlies one key driver mechanism in largely incurable AMLs. How MECOM results in such aggressive AML phenotypes remains unknown. To address existing experimental limitations, we engineered and applied targeted protein degradation with functional genomic readouts to demonstrate that MECOM promotes malignant stem cell-like states by directly repressing pro-differentiation gene regulatory programs. Remarkably and unexpectedly, a single node in this network, a MECOM-bound cis-regulatory element located 42 kb downstream of the myeloid differentiation regulator CEBPA, is both necessary and sufficient for maintaining MECOM-driven leukemias. Importantly, targeted activation of this regulatory element promotes differentiation of these aggressive AMLs and reduces leukemia burden in vivo, suggesting a broadly applicable differentiation-based approach for improving therapy.

cancer biology↗

bioRxiv2024

Long-read sequencing of hundreds of diverse brains provides insight into the impact of structural variation on gene expression and DNA methylation

Structural variants (SVs) drive gene expression in the human brain and are causative of many neurological conditions. However, most existing genetic studies have been based on short-read sequencing methods, which capture fewer than half of the SVs present in any one individual. Long-read sequencing (LRS) enhances our ability to detect disease-associated and functionally relevant structural variants; however, its application in large-scale genomic studies has been limited by challenges in sample preparation and high costs. Here, we leverage a new scalable wet-lab protocol and computational pipeline for whole-genome Oxford Nanopore Technologies sequencing and apply it to neurologically normal control samples from the North American Brain Expression Consortium (NABEC) (European ancestry) and Human Brain Collection Core (HBCC) (African or African admixed ancestry) cohorts. Through this work, we present a publicly available long-read resource from 351 human brain samples (median N50: 27 Kbp and at an average depth of ~40x genome coverage). We discover approximately 234,905 SVs and produce locally phased assemblies that cover 95% of all protein-coding genes in GRCh38. To resolve cis-regulatory effects, we develop ASM-LR, a method for allele-specific methylation analysis from long-read data, revealing both strong and subtle regulatory effects, including numerous novel methylation QTLs masked in unphased models. Our results highlight the power of haplotype-resolved methylation to uncover regulatory mechanisms and establish a foundational resource for exploring how genetic variation shapes gene expression and epigenetic architecture across diverse ancestries.

genomics↗

bioRxiv2024

Quantification of CAR T cell performance against acute myeloid leukemia using Bayesian inference

Chimeric Antigen Receptor (CAR) T-cell therapy has transformed cancer immunotherapy by genetically engineering T-cells to target tumor antigens. Acute myeloid leukemia (AML) presents unique challenges due to resistance mechanisms, especially in patients with TP53 loss mutations. The complex dynamics of CAR T-cell expansion remain poorly understood. The field lacks validated quantitative frameworks to systematically evaluate different CAR T-cell target constructs, such as CD33, CD123, and CD371, against resistant AML variants. We address this gap by combining mathematical modeling with in vitro assay data and Bayesian inference. We select, train, and validate a two-compartment deterministic mathematical model that describes the nonlinear dynamics of target AML and CAR T cells, accounting for expansion, killing, and exhaustion. Using Bayesian inference, we train and select the best-performing functional form for CAR T expansion and then validate it on unseen data. Our framework selects a CAR T-cell expansion model that accounts for handling time and T-cell self-interference, highlighting that expansion is a dynamic process in which target-cell handling time and T-cell crowding negatively affect T-cell expansion. Analysis of posterior parameter distributions reveals target-antigen-specific responses against TP53-deficient AML. For instance, CD33-targeting CARs have reduced attack rates against TP53-deficient cells, while CD123- and CD371-targeting CARs show moderately increased attack rates; however, the former exhibit higher death rates, and the latter have increased handling times, impeding efficacy. This target-dependent form of resistance challenges the assumption of uniform performance and reveals a unifying nonlinear expansion model for integrated, yet antigen-specific, preclinical predictions of efficacy. Short SummaryWe identified the target antigen-specific expansion properties and the efficacy of CAR T cells against TP53 wild-type and deficient AML by integrating experimental data from cytolytic assays, mechanistic mathematical modeling, and Bayesian inference.

cancer biology↗

bioRxiv2024

Single-cell spatial atlas of high-grade serous ovarian cancer unveils MHC class II as a key driver of spatial tumor ecosystems and clinical outcomes

The tumor microenvironment (TME) is a complex network of interactions between malignant and host cells, yet its orchestration in advanced high-grade serous ovarian carcinoma (HGSC) remains poorly understood. We present a comprehensive single-cell spatial atlas of 280 metastatic HGSCs, integrating high-dimensional imaging, genomics, and transcriptomics. Using 929 single-cell maps, we identify distinct spatial domains associated with phenotypically heterogeneous cellular compositions, and demonstrate that immune cell co-infiltration at the tumor-stroma interface significantly influences clinical outcomes. To uncover the key drivers of the tumor ecosystem, we developed CEFIIRA (Cell Feature Importance Identification by RAndom forest), which identified tumor cell-intrinsic MHC-II expression as a critical predictor of prolonged survival, independent of clinicomolecular profiles. Validation with external datasets confirmed that MHC-II-expressing cancer cells drive immune infiltration and orchestrate spatial tumor-immune interactions. Our atlas offers novel insights into immune surveillance mechanisms across HGSC clinicomolecular groups, paving the way for improved therapeutic strategies and patient stratification.

cancer biology↗

bioRxiv2024

Epigenetic constraint of cellular genomes evolutionarily links genetic variation to function

Cellular diversity is a product of evolution acting to drive divergent regulatory programs from a common genome. Here, we use cross-cell-type epigenetic conservation to gain insight into the impact of selective constraints on genome function and phenotypic variation. By comparing chromatin accessibility across hundreds of diverse cell-types, we identify 1.4% of the human genome safeguarded by conserved domains of facultative heterochromatin, which we term regions under "cellular constraint". We calculate single-base resolution cellular constraint scores and demonstrate robust prediction of functionally important coding and non-coding loci in a cell-type-, trait-, and disease-agnostic manner. Cellular constraint annotation enhances causal variant identification, drug discovery, and clinical diagnostic predictions. Furthermore, cell-constrained sequences share paradoxical evolutionary signals of positive and negative selection, suggesting a dynamic role in driving human adaptation. Overall, this study demonstrates that evolutionary chromatin dynamics can be leveraged to inform the translation of genetic discoveries into effective biological, therapeutic, and clinical outcomes.

genetics↗

bioRxiv2024

Tailoring a CRISPR/Cas-based Epigenome Editor for Programmable Chromatin Acylation and Decreased Cytotoxicity

CRISPR-based epi-editors can robustly modulate cellular transcription and chromatin structure, but off-target activity and cytotoxicity limit their utility. Here, we engineer the acyl-CoA binding pocket of the human p300 histone acyltransferase to reduce its cytotoxicity and tune its acylation profile when fused to dCas9. We discover a single amino acid substitution (I1417N) that decreases cytotoxicity related to exogenous p300 overexpression yet preserves dCas9-p300 mediated histone acetylation and gene activation. We find that dCas9-p300 I1417N is less perturbative to the transcriptome and proteome of human cells, and that this behavior is driven by favorable stability kinetics. We also develop a crotonylation-biased dCas-p300 variant (I1395G) that selectively deposits histone crotonylation and activates transcription from endogenous promoters at levels comparable to wild-type p300. The p300 variants generated here enhance epi-editing capabilities and demonstrate that engineering of catalytic domains can be a powerful strategy for tailoring enzymatic activities and mitigating effector-driven toxicity in epi-editing.

synthetic biology↗

bioRxiv2024

Lifetime fitness benefits of breeding site fidelity and low costs of inbreeding permit inbreeding tolerance in an avian cooperative breeder

Breeding with relatives often decreases individual fitness but can be mitigated via inbreeding avoidance mechanisms such as dispersal, mate-switching, and kin avoidance. Disentangling the effects of multiple mechanisms is challenging without detailed individual-level data and incomplete without considering all life stages. We leveraged 32 years of data from a population of Florida Scrub-Jays (Aphelocoma coerulescens) to investigate how dispersal and mate choice contribute to inbreeding risk across individuals lifetimes and quantify the associated fitness outcomes. We find that when mating is random, inbreeding is two-fold higher when dispersal is limited, but adding sex-biased dispersal significantly reduces inbreeding risk. Limited movement away from the breeding territory for later pairings (site fidelity) contributes more to higher-than-expected levels of inbreeding than limited natal dispersal. Within observed dispersal constraints, however, inbreeding is lower than expected under random mating, suggesting Florida Scrub-Jays actively avoid mating with relatives, especially first-order kin. Finally, males paired with close relatives and females who move farther for later pairings experience equivalently lower lifetime reproductive success. Breeders who move farther for first pairings have lower survival. Overall, our results show how variation in fitness tradeoffs and mate choice behavior across life stages affects inbreeding in a long-lived, social species.

animal behavior and cognition↗

bioRxiv2024

Reduced Hydrogen Sulfide Bioavailability Contributes to Cardiometabolic Heart Failure with Preserved Ejection Fraction

BackgroundHeart failure with preserved ejection fraction (HFpEF) is a significant public health concern with limited treatment options. Dysregulated nitric oxide-mediated signaling has been implicated in HFpEF pathophysiology, however, little is known about the role of endogenous hydrogen sulfide (H2S) in HFpEF. ObjectivesThis study evaluated H2S bioavailability in patients and two animal models of cardiometabolic HFpEF and assessed the impact of H2S on HFpEF severity through alterations in endogenous H2S production and pharmacological supplementation. We also evaluated the effects of the H2S donor, diallyl trisulfide (DATS) in combination with the GLP-1/glucagon receptor agonist, survodutide, in HFpEF. MethodsHFpEF patients and two rodent models of HFpEF ("two-hit" L-NAME + HFD mouse and ZSF1 obese rat) were evaluated for H2S bioavailability. Two cohorts of two-hit mice were investigated for changes in HFpEF pathophysiology: (1) endothelial cell cystathionine-{gamma}-lyase (EC-CSE) knockout; (2) H2S donor, JK-1, supplementation. DATS and survodutide combination therapy was tested in ZSF1 obese rats. ResultsH2S levels were significantly reduced (i.e., 81%) in human HFpEF patients and in both preclinical HFpEF models. This depletion was associated with reduced CSE expression and activity, and increased SQR expression. Genetic knockout of H2S -generating enzyme, CSE, worsened HFpEF characteristics, including elevated E/e ratio and LVEDP, impaired aortic vasorelaxation and increased mortality. Pharmacologic H2S supplementation restored H2S bioavailability, improved diastolic function and attenuated cardiac fibrosis corroborating an improved HFpEF phenotype. DATS synergized with survodutide to attenuate obesity, improve diastolic function, exercise capacity, and reduce oxidative stress and cardiac fibrosis. ConclusionsH2S deficiency is evident in HFpEF patients and conserved across multiple preclinical HFpEF models. Increasing H2S bioavailability improved cardiovascular function, while knockout of endogenous H2S production exacerbated HFpEF pathology and mortality. These results suggest H2S dysregulation contributes to HFpEF and increasing H2S bioavailability may represent a novel therapeutic strategy for HFpEF. Furthermore, our data demonstrate that combining H2S supplementation with GLP-1/glucagon receptor agonist may provide synergistic benefits in improving HFpEF outcomes. HighlightsO_LIH2S deficiency is evident in both human HFpEF patients and two clinically relevant models. C_LIO_LIReduced H2S production by CSE and increased metabolism by SQR impair H2S bioavailability in HFpEF. C_LIO_LIPharmacological H2S supplementation improves diastolic function and reduces cardiac fibrosis in HFpEF models. C_LIO_LITargeting H2S dysregulation presents a novel therapeutic strategy for managing HFpEF. C_LIO_LIH2S synergizes with GLP-1/glucagon agonist and ameliorates HFpEF C_LI

pharmacology and toxicology↗

bioRxiv2024

Brain transcriptomic signatures for mood disorders and suicide phenotypes: an anterior insula and subgenual ACC network postmortem study

Mood disorders affect over ten percent of humans, but studies dissecting the brain anatomical and molecular neurobiological mechanisms underlying mood (dys)functions have not consistently identified the patterns of pathological changes in relevant brain regions. Recent studies have identified pathological changes in the anterior insula (Ant-Ins) and subgenual anterior cingulate (sgACC) brain network in mood disorders, in line with this networks role in regulating mood/affective feeling states. Here, we applied whole-tissue RNA-sequencing measures of differentially expressed genes (DEGs) in mood disorders versus (vs.) psychiatrically unaffected controls (controls) to identify postmortem molecular pathological markers for mood disorder phenotypes. Using data-driven factor analysis of the postmortem phenotypic variables to determine relevant sources of population variances, we identified DEGs associated with mood disorder-related diagnostic phenotypes by combining gene co-expression, differential gene expression, and pathway-enrichment analyses. We found downregulation/under expression of inflammatory, and protein synthesis-related genes associated with psychiatric morbidity (i.e., all co-occurring mental disorders and suicide outcomes/death by suicide) in Ant-Ins, in contrasts to upregulation of synaptic membrane and ion channel-related genes with increased psychiatric morbidity in sgACC. Our results identified a preponderance of downregulated metabolic, protein synthesis, inflammatory, and synaptic membrane DEGs associated with suicide outcomes in relation to a factor representing longevity in the Ant-Ins and sgACC (AIAC) network. Our study revealed a critical brain network molecular repertoire for mood disorder phenotypes, including suicide outcomes and longevity, and provides a framework for defining dosage-sensitive (i.e., downregulated vs. upregulated) molecular signatures for mood disorder phenotypic complexity and pathological outcomes.

neuroscience↗

bioRxiv2024

A quantitative characterization of the heterogeneous response of glioblastoma U-87 MG cell line to temozolomide

Most cancers are genetically and phenotypically heterogeneous. This includes subpopulations of cells with different levels of sensitivity to chemotherapy, which may lead to treatment failure as the more resistant cells can survive drug treatment and continue to proliferate. While the genetic basis of resistance to many drugs is relatively well characterised, non-genetic factors are much less understood. Here we investigate the role of non-genetic, phenotypic heterogeneity in the response of glioblastoma cancer cells to the drug temozolomide (TMZ) often used to treat this type of cancer. Using a combination of live imaging, machine-learning image analysis and agent-based modelling, we show that even if all cells share the same genetic background, individual cells respond differently to TMZ. We quantitatively characterise this response by measuring the doubling time, lifespan, and motility of cells, and determine how these quantities correlate with each other as well as between the mother and daughter cell. We also show that these responses do not correlate with the cellular level of the enzyme MGMT which has been implicated in the response to TMZ.

cancer biology↗

bioRxiv2024

micronuclAI: Automated quantification of micronuclei for assessment of chromosomal instability.

Chromosomal instability (CIN) is a hallmark of cancer that drives metastasis, immune evasion and treatment resistance. CIN results from chromosome mis-segregation events during anaphase, as excessive chromatin is packaged in micronuclei (MN), that can be enumerated to quantify CIN. Despite recent advancements in automation through computer vision and machine learning, the assessment of CIN remains a predominantly manual and time-consuming task, thus hampering important work in the field. Here, we present micronuclAI, a novel pipeline for automated and reliable quantification of MN of varying size, morphology and location from DNA-only stained images. In micronucleAI, single-cell crops are extracted from high-resolution microscopy images with the help of segmentation masks, which are then used to train a convolutional neural network (CNN) to output the number of MN associated with each cell. The pipeline was evaluated against manual single-cell level counts by experts and against routinely used MN ratio within the complete image. The classifier was able to achieve a weighted F1 score of 0.937 on the test dataset and the complete pipeline can achieve close to human-level performance on various datasets derived from multiple human and murine cancer cell lines. The pipeline achieved a root-mean-square deviation (RMSE) value of 0.0041, an R2 of 0.87 and a Pearsons correlation of 0.938 on images obtained at 10X magnification. We tested the approach in otherwise isogenic cell lines in which we genetically dialed up or down CIN rates, and also on a publicly available image data set (obtained at 100X) and achieved an RMSE value of 0.0159, an R2 of 0.90, and a Pearsons correlation of 0.951. Given the increasing interest in developing therapies for CIN-driven cancers, this method provides an important, scalable, and rapid approach to quantifying CIN on routinely obtained images. We release a GUI-implementation for easy access and utilization of the pipeline.

systems biology↗

bioRxiv2024

Risk-free polio vaccine: Recombinant expression systems for production of stabilised virus-like particles

Polioviruses have caused crippling disease in humans for centuries, prior to the successful development of vaccines in the mid-1900s, which dramatically reduced disease prevalence. Continued use of these vaccines, however, threatens ultimate disease eradication and achievement of a polio-free world. Virus-like particles (VLPs) that lack a viral genome represent a safer potential vaccine, although they require particle stabilization. Using our previously established genetic techniques to stabilize the structural capsid proteins, we demonstrate production of poliovirus VLPs of all three serotypes, from four different recombinant expression systems. We compare the antigenicity, thermostability and immunogenicity of these stabilized VLPs against the current inactivated polio vaccine, demonstrating equivalent or superior immunogenicity. Structural analyses of these recombinant VLPs provide a rational understanding of the stabilizing mutations and the role of potential excipients. Collectively, we have established these poliovirus stabilized VLPs as viable next-generation vaccine candidates for the future.

microbiology↗