bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genome-wide temporal gene expression reveals a post-reproductive shift in the nematodeC. briggsae
Authors: Berg Wouter van den , Gupta Bhagwati P 
Published: June 2024

ABSTRACTC. briggsaeoffers a robust system for comparative investigations of genetic pathways that affect physiological processes. One key process, reproduction, significantly impacts longevity due to its high energetic cost, which limits resources for somatic maintenance. Long-lived mutants often exhibit reproductive impairments, and studies inC. eleganshave demonstrated that germline mutations and complete germline removal can promote longevity, underscoring the link between reproduction and aging. We are interested in identifying genes and biological processes affected during the reproductive and post-reproductive periods inC. briggsae. To achieve this, we conducted whole-genome transcriptome profiling on animals at various adult stages. analysis of differentially expressed (DE) genes revealed that the majority were downregulated during the reproductive period. Interestingly, this trend reversed post-reproduction, with three-quarters of the genes upregulated—a phenomenon we termed the ‘reproductive shift’. A similar analysis inC. elegansalso showed a downregulation bias during the reproductive period, but the reproductive shift was absent. Further examination ofC. briggsaeDE genes showed enrichment in processes related to the matrisome, muscle development and function during the reproductive period. Post-reproductive downregulated genes were enriched in DNA damage repair, stress response, and immune response. Additionally, terms related to fatty acid metabolism, catabolism, and transcriptional regulation exhibited complex patterns, with different biological processes being up or downregulated between the reproductive and post-reproductive stages. Overall, our transcriptomic data provides a valuable resource for cross-sectional comparative studies of reproductive and post-reproductive changes in nematodes. Additionally, the findings prompt similar studies in other animal models thereby advancing our understanding of genetic pathways affecting reproduction and aging.
An organoid co-culture model for probing systemic anti-tumor immunity in lung cancer
Authors: Li Kaiyi , Liu Chang , Li Chao , Zhang Ting , Zhao Tian , Zhang Dong , Wu Hainan , Liu Yuhan , Wang Shuai , Yang Yingshun , Lin Baobao , Wang Wenyan , Wang Jun , Sui Xizhao , Chen Xiaofang , Liu Peng 
Published: June 2024

AbstractDeciphering the interactions between tumor micro- and systemic immune macro-environment is essential for developing more effective cancer diagnosis and treatment strategies. Here, we established a gel-liquid interface (GLI) co-culture of lung cancer organoids (LCOs) and paired peripheral blood mononuclear cells (PBMCs), featuring with enhanced interactions of immune cells and tumor organoids, to mimic thein vivosystemic anti-tumor immunity induced by immune checkpoint inhibitors (ICI). The co-culture model recapitulates thein vivoICI-induced T cell recruitment and subsequent tumor regression, predicting the clinical results precisely. We demonstrated that circulating tumor-reactive T cells, which are effector memory-like with high expression levels ofGNLY, CD44andCD9,can serve as an indicator of the immunotherapy efficacy. Interestingly, enhanced inflammatory signaling in blood T cells is accompanied with prompted exhaustion and compromised anti-tumor function, when encountering with organoids. Our findings suggest that the GLI co-culture can be used for developing diagnostic strategies for precision immunotherapies as well as understanding the underlying mechanisms.Summary figure
ProToDeviseR: an automated protein topology scheme generator
Authors: Petrov Petar B. , Izzi Valerio 
Published: June 2024

MotivationAmino acid sequence characterization is a fundamental part of virtually any protein analysis, and creating concise and clear protein topology schemes is of high importance in proteomics studies. Although numerous databases and prediction servers exist, it is challenging to incorporate data from various, and sometimes contending, resources into a publication-ready scheme.ResultsHere, we present the Protein Topology Deviser R package (ProToDeviseR) for the automatic generation of protein topology schemes from database accession numbers, raw results from multiple prediction servers, or a manually prepared table of features. The application offers a graphical user interface, implemented in R Shiny, hosting an enhanced version of Pfam’s domains generator for the rendering of visually appealing schemes. Results show that ProToDeviseR can easily and quickly generate topology schemes by interrogating UniProt or NCBI GenPept databases and elegantly combine features from various resources.AvailabilitySource code (https://github.com/izzilab/protodeviser) is available under GPLv3 license; the tool is also accessible for online use (https://matrinet.shinyapps.io/protodeviser/), without the need of installation.
Cell-type-specific cholinergic control of granular retrosplenial cortex with implications for angular velocity coding across brain states
Authors: Jedrasiak-Cape Izabela , Rybicki-Kler Chloe , Brooks Isla , Ghosh Megha , Brennan Ellen K.W. , Kailasa Sameer , Ekins Tyler G. , Rupp Alan , Ahmed Omar J. 
Published: June 2024

ABSTRACTCholinergic receptor activation enables the persistent firing of cortical pyramidal neurons, providing a key cellular basis for theories of spatial navigation involving working memory, path integration, and head direction encoding. The granular retrosplenial cortex (RSG) is important for spatially-guided behaviors, but how acetylcholine impacts RSG neurons is unknown. Here, we show that a transcriptomically, morphologically, and biophysically distinct RSG cell-type – the low-rheobase (LR) neuron – has a very distinct expression profile of cholinergic muscarinic receptors compared to all other neighboring excitatory neuronal subtypes. LR neurons do not fire persistently in response to cholinergic agonists, in stark contrast to all other principal neuronal subtypes examined within the RSG and across midline cortex. This lack of persistence allows LR neuron models to rapidly compute angular head velocity (AHV), independent of cholinergic changes seen during navigation. Thus, LR neurons can consistently compute AHV across brain states, highlighting the specialized RSG neural codes supporting navigation.
CellFM: a large-scale foundation model pre-trained on transcriptomics of 100 million human cells
Authors: Zeng Yuansong , Xie Jiancong , Wei Zhuoyi , Su Yun , Shangguan Ningyuan , Yang Shuangyu , Zhang Chengyang , Li Wenbing , Zhang Jinbo , Fang Nan , Zhang Hongyu , Zhao Huiying , Lu Yutong , Fan Jue , Yu Weijiang , Yang Yuedong 
Published: June 2024

AbstractThe rapid evolution of single-cell sequencing technologies has facilitated precise transcriptomics profiling at the single-cell level, shedding light on the intricate heterogeneity within cellular populations. Despite these advances, the inherent diversity of cells and data challenges such as noise, batch effects, and sparsity, underscores the pressing need for a unified model to learn and represent cellular states effectively. Single-cell Large Language Models (LLMs) have been crafted to bridge this gap yet exhibit limited performance on human cells. This short-fall may stem from the confounding effects of training data from diverse species, partly because of limited cells for the single species. Here, we have compiled a dataset of approximately 100 million human cells sequenced by multiple technolo-gies from human single-cell datasets with various file types deposited in public databases and websites. Leveraging these extensive data cohorts, we developed CellFM, a robust single-cell foundation model with an impressive 800 million parameters, marking an eight-fold increase over the current largest single-species model. To ensure the training of CellFM on the MindSpore AI framework from Huawei, we have integrated RetNet, a Transformer architecture variant with lin-ear complexity for a balance between efficiency and performance, serving as the backbone of our model. Our comprehensive experiments have shown that CellFM outperforms existing models across diverse applications, such as cell annotation, perturbation prediction, and gene function prediction.
Prevention and treatment of noise-induced hearing loss and cochlear synapse degeneration by potassium channel blockersin vivo
Authors: Zhao Hong-Bo , Liu Li-Man , Mei Ling , Quinonez Auraemil T , Roberts Rafael A , Lu Xiaoling 
Published: June 2024

AbstractNoise can induce hearing loss. In particularly, noise can induce cochlear synapse degeneration leading to hidden hearing loss, which is the most common type of hearing disorders in the clinic. Currently, there is no pharmacological treatment, particularly, no post-exposure (i.e., therapeutic) treatment available in the clinic. Here, we report that systematic administration of K+channel blockers before or after noise exposure could significantly attenuate NIHL and synapse degeneration. After systematic administration of a general K-channel blocker tetraethylammonium (TEA), the elevation of auditory brainstem response (ABR) thresholds after noise-exposure significantly reduced, and the active cochlear mechanics significantly improved. The therapeutic effect was further improved as the post-exposure administration time extending to 3 days. BK channel is a predominant K+channel in the inner hair cells. Systematic administration of a BK channel blocker GAL-021 after noise exposure also ameliorated hearing loss and improved hearing behavioral responses tested by acoustic startle response (ASR). Finally, both TEA and GAL-021 significantly attenuated noise-induced ribbon synapse degeneration. These data demonstrate that K+-channel blockers can prevent and treat NIHL and cochlear synapse degeneration. Our finding may aid in developing therapeutic strategies for post-exposure treatment of NIHL and synapse degeneration.Significance StatementNoise is a common deafness factor affecting more 100 million people in the United States. So far, there is no pharmacological treatment available. We show here that administration of K+channel blockers after noise exposure could attenuate noise-induced hearing loss and synapse degeneration, and improved behavioral responses. This is the first time to real the K+channel blockers that could treat noise-induced hearing loss and cochlear synaptopathy after noise exposure.
The Molecular Basis of Differentiation Wave Activity in Embryogenesis
Authors: Alicea Bradly , Bastani Surosh , Gordon Natalie K. , Crawford-Young Susan , Gordon Richard 
Published: June 2024

AbstractAs development varies greatly across the tree of life, it may seem difficult to suggest a model that proposes a single mechanism for understanding collective cell behaviors and the coordination of tissue formation. Here we propose a mechanism called differentiation waves, which unify many disparate results involving developmental systems from across the tree of life. We demonstrate how a relatively simple model of differentiation proceeds not from function-related molecular mechanisms, but from so-called differentiation waves. A phenotypic model of differentiation waves is introduced, and its relation to molecular mechanisms is proposed. These waves contribute to a differentiation tree, which is an alternate way of viewing cell lineage and local action of the molecular factors. We construct a model of differentiation wave-related molecular mechanisms (genome, epigenome, and proteome) based onC. elegansbioinformatic data. To validate this approach across different modes of development, we evaluate protein expression across different types of development by comparing the nematodeCaenorhabditis eleganswith several model organisms: fruit flies (Drosophila melanogaster), yeast (Saccharomyces cerevisiae), and mouse (Mus musculus). Inspired by gene regulatory networks, two Models of Interactive Contributions (fully-connected MICs and ordered MICs) are used to suggest potential genomic contributions to differentiation wave-related proteins. This, in turn, provides a framework for understanding differentiation and development.
Probabilistic graph-based model uncovers previously unseen druggable vulnerabilities in major solid cancers
Authors: Zhu Ying , Schmidt Stephanie T. , Zhao Li , Jiang Chunjie , Micco Patrizio Di , Mitsopoulos Costas , Futreal Andrew , Al-Lazikani Bissan 
Published: June 2024

AbstractOver half cancer patients lack safe, effective, targeted therapies despite abundant molecular profiling data. Statistically recurrent cancer drivers have provided fertile ground for drug discovery where they exist. But in rare, complex, and heterogeneous cancers, strong driver signals are elusive. Moreover, therapeutically exploitable molecular vulnerabilities extend beyond classical drivers. Here we describe a novel, integrative, generalizable graph-based, cooperativity-led Markov chain model, A3D3a’s MVP (Adaptive AI-Augmented Drug Discovery and Development Molecular Vulnerability Picker), to identify and prioritize key druggable molecular vulnerabilities in cancer. The algorithm exploits cooperativity of weak signals within a cancer molecular network to enhance the signal of true molecular vulnerabilities. We apply A3D3a’s MVP to 19 solid cancer types and demonstrate that it outperforms standard approaches for target hypothesis generation by >3-fold as benchmarked against cell line genetic perturbation and drug screening data. Importantly, we demonstrate its ability to identify non-driver druggable vulnerabilities and highlight 43 novel or emergent druggable targets for these tumors.
Human TSC2 Mutant Cells Exhibit Aberrations in Early Neurodevelopment Accompanied by Changes in the DNA Methylome
Authors: Chalkley Mary-Bronwen L. , Guerin Lindsey N. , Iyer Tenhir , Mallahan Samantha , Nelson Sydney , Sahin Mustafa , Hodges Emily , Ess Kevin C. , Ihrie Rebecca A. 
Published: June 2024

ABSTRACTTuberous Sclerosis Complex (TSC) is a debilitating developmental disorder characterized by a variety of clinical manifestations. While benign tumors in the heart, lungs, kidney, and brain are all hallmarks of the disease, the most severe symptoms of TSC are often neurological, including seizures, autism, psychiatric disorders, and intellectual disabilities. TSC is caused by loss of function mutations in theTSC1orTSC2genes and consequent dysregulation of signaling via mechanistic Target of Rapamycin Complex 1 (mTORC1). While TSC neurological phenotypes are well-documented, it is not yet known how early in neural developmentTSC1/2-mutant cells diverge from the typical developmental trajectory. Another outstanding question is the contribution of homozygous-mutant cells to disease phenotypes and whether such phenotypes are also seen in the heterozygous-mutant populations that comprise the vast majority of cells in patients. Using TSC patient-derived isogenic induced pluripotent stem cells (iPSCs) with defined genetic changes, we observed aberrant early neurodevelopmentin vitro, including misexpression of key proteins associated with lineage commitment and premature electrical activity. These alterations in differentiation were coincident with hundreds of differentially methylated DNA regions, including loci associated with key genes in neurodevelopment. Collectively, these data suggest that mutation or loss ofTSC2affects gene regulation and expression at earlier timepoints than previously appreciated, with implications for whether and how prenatal treatment should be pursued.
Placental extracellular vesicles from early-onset but not late-onset preeclampsia induce a pro-vasoconstrictive and anti-vasodilatory state in resistance arteries
Authors: Lau Sien Yee , Groom Katie , Hisey Colin L. , Chen Qi , Barrett Carolyn , Chamley Larry 
Published: June 2024

AbstractBackgroundThe human placenta releases large numbers of extracellular vesicles (EVs) into the maternal circulation throughout pregnancy. In preeclampsia, a hypertensive disorder of pregnancy, the number of EVs increases and the cargo they carry is altered. We investigated whether human placental EVs from pregnancies complicated by preeclampsia directly alter maternal vascular function, a hallmark of the disorder, and if EVs from early-onset or late-onset variants of preeclampsia have different effects on the vasculature.MethodsMacro-EVs, micro-EVs and nano-EVs were isolated from cultured explants of human placentae from women with early-onset or late-onset preeclampsia, or from normotensive women. EVs were injected intravenously into pregnant mice and either at 30 minutes or 24 hours after injection, the mice were euthanized and the function of second order mesenteric arteries were assessed using wire myography.ResultsPlacental EVs from pregnancies with early-onset preeclampsia enhanced vasoconstriction to PE, AngII, and ET-1 whilst impairing vasodilation to ACh and SNP in a time-dependent fashion, most prominently at 24 hours. In contrast, placental EVs from pregnancies with late-onset preeclampsia induced few differences compared to arteries taken from control mice injected with EVs from women with normotensive pregnancies.ConclusionsTo the best of our knowledge, this is the first comparison of vascular function after exposure to the full range of EVs produced by placentae from women with early-onset and late-onset preeclampsia and normotensive women. Placental EVs from early-onset preeclampsia demonstrated the ability to contribute to the development of the high-resistance haemodynamic profiles of women affected by early-onset preeclampsia.
Expansion of a bacterial operon during cancer treatment ameliorates drug toxicity
Authors: Trepka Kai R. , Kidder Wesley A. , Kyaw Than S. , Halsey Taylor , Olson Christine A. , Ortega Edwin F. , Noecker Cecilia , Upadhyay Vaibhav , Stanfield Dalila , Steiding Paige , Guthrie Benjamin G. H. , Spanogiannopoulos Peter , Dumlao Darren , Turnbaugh Jessie A. , Stachler Matthew D. , Van Blarigan Erin L. , Venook Alan P. , Atreya Chloe E. , Turnbaugh Peter J. 
Published: June 2024

AbstractDose-limiting toxicities remain a major barrier to drug development and therapy, revealing the limited predictive power of human genetics. Herein, we demonstrate the utility of a more comprehensive approach to studying drug toxicity through longitudinal study of the human gut microbiome during colorectal cancer (CRC) treatment (NCT04054908) coupled to cell culture and mouse experiments. 16S rRNA gene sequencing revealed significant shifts in gut microbial community structure during oral fluoropyrimidine treatment across multiple patient cohorts, in mouse small and large intestinal contents, and in patient-derivedex vivocommunities. Metagenomic sequencing revealed marked shifts in pyrimidine-related gene abundance during oral fluoropyrimidine treatment, including enrichment of thepreTAoperon, which is sufficient for the inactivation of active metabolite 5-fluorouracil (5-FU).preTA+bacteria depleted 5-FU in gut microbiota grownex vivoand the mouse distal gut. Germ-free and antibiotic-treated mice experienced increased fluoropyrimidine toxicity, which was rescued by colonization with the mouse gut microbiota,preTA+E. coli, orpreTA-high CRC patient stool. Finally,preTAabundance was negatively associated with fluoropyrimidine toxicity in patients. Together, these data support a causal, clinically relevant interaction between a human gut bacterial operon and the dose-limiting side effects of cancer treatment. Our approach is generalizable to other drugs, including cancer immunotherapies, and provides valuable insights into host-microbiome interactions in the context of disease.One Sentence Summary:Gut microbial enzymes can be used to predict and prevent anticancer drug toxicity.
AGS3-based optogenetic GDI induces GPCR-independent Gβγ signaling and macrophage migration
Authors: Thotamune Waruna , Ubeysinghe Sithurandi , Rajarathna Chathuri , Kankanamge Dinesh , Olupothage Koshala , Chandu Aditya , Copits Bryan A. , Karunarathne Ajith 
Published: June 2024

AbstractG protein-coupled receptors (GPCRs) are efficient Guanine nucleotide exchange factors (GEFs) and exchange GDP to GTP on the Gα subunit of G protein heterotrimers in response to various extracellular stimuli, including neurotransmitters and light. GPCRs primarily broadcast signals through activated G proteins, GαGTP, and free Gβγ and are major disease drivers. Evidence shows that the ambient low threshold signaling required for cells is likely supplemented by signaling regulators such as non-GPCR GEFs and Guanine nucleotide Dissociation Inhibitors (GDIs). Activators of G protein Signaling 3 (AGS3) are recognized as a GDI involved in multiple health and disease-related processes. Nevertheless, understanding of AGS3 is limited, and no significant information is available on its structure-function relationship or signaling regulation in living cells. Here, we employedin silicostructure-guided engineering of a novel optogenetic GDI, based on the AGS3’s G protein regulatory (GPR) motif, to understand its GDI activity and induce standalone Gβγ signaling in living cells on optical command. Our results demonstrate that plasma membrane recruitment of OptoGDI efficiently releases Gβγ, and its subcellular targeting generated localized PIP3 and triggered macrophage migration. Therefore, we propose OptoGDI as a powerful tool for optically dissecting GDI-mediated signaling pathways and triggering GPCR-independent Gβγ signaling in cells andin vivo.
Baikal: Unpaired Denoising of Fluorescence Microscopy Images using Diffusion Models
Authors: Chaudhary Shivesh , Sankarapandian Sivaramakrishnan , Sooknah Matt , Pai Joy , McCue Caroline , Chen Zhenghao , Xu Jun 
Published: June 2024

AbstractFluorescence microscopy is an indispensable tool for biological discovery but image quality is constrained by desired spatial and temporal resolution, sample sensitivity, and other factors. Computational denoising methods can bypass imaging constraints and improve signal-tonoise ratio in images. However, current state of the art methods are commonly trained in a supervised manner, requiring paired noisy and clean images, limiting their application across diverse datasets. An alternative class of denoising models can be trained in a self-supervised manner, assuming independent noise across samples but are unable to generalize from available unpaired clean images. A method that can be trained without paired data and can use information from available unpaired highquality images would address both weaknesses. Here, we present Baikal, a first attempt to formulate such a framework using Denoising Diffusion Probabilistic Models (DDPM) for fluorescence microscopy images. We first train a DDPM backbone in an unconditional manner to learn generative priors over complex morphologies in microscopy images. We then apply various conditioning strategies to sample from the trained model and propose an optimal strategy to denoise the desired image. Extensive quantitative comparisons demonstrate better performance of Baikal over state of the art self-supervised methods across multiple datasets. We highlight the advantage of generative priors learnt by DDPMs in denoising complexFlywingmorphologies where other methods fail. Overall, our DDPM based denoising framework presents a new class of denoising methods for fluorescence microscopy datasets that achieve good performance without collection of paired high-quality images. Github repo:https://github.com/scelesticsiva/denoising/tree/main