Biology subjects

Wang, A.

Publications and source records attributed to Wang, A..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Bioactive Flavonoid Extract Suppresses NLRP3 Activation and Inflammation in 2D and 3D Lung Models

Inflammasome activation plays a critical role in lung inflammation, with the NLRP3 (NOD-, LRR-and pyrin domain-containing protein 3) inflammasome serving as a key mediator of inflammatory cytokine release and pyroptotic cell death. This study investigates the effects of a bioactive flavonoid extract (BFE), as a potential modulator of NLRP3-mediated inflammation using THP-1 derived macrophages, A549 lung cells (2D cells), and lung organoids (3D cells). Cells were primed with lipopolysaccharide (LPS), treated with BFE, and then activated with nigericin to induce NLRP3 activation and examine BFEs effects. Markers of inflammation, including presence of ASC specks (3D models), reactive oxygen species production (ROS) (2D models), caspase-1 activity (2D and 3D models), and IL-1{beta} release (2D and 3D models) were measured to assess the extent of inflammasome activation in several treatment conditions. By integrating 2D and 3D lung models, this work provides insight into the NLRP3 inflammasome axis in lung inflammation and explores BFE as a potential therapeutic strategy for inflammasome-driven pulmonary inflammatory processes.

molecular biology↗

bioRxiv2025

Mapping the regulatory effects of common and rare non-coding variants across cellular and developmental contexts in the brain and heart

Whole genome sequencing has identified over a billion non-coding variants in humans, while GWAS has revealed the non-coding genome as a significant contributor to disease. However, prioritizing causal common and rare non-coding variants in human disease, and understanding how selective pressures have shaped the non-coding genome, remains a significant challenge. Here, we predicted the effects of 15 million variants with deep learning models trained on single-cell ATAC-seq across 132 cellular contexts in adult and fetal brain and heart, producing nearly two billion context-specific predictions. Using these predictions, we distinguish candidate causal variants underlying human traits and diseases and their context-specific effects. While common variant effects are more cell-type-specific, rare variants exert more cell-type-shared regulatory effects, with selective pressures particularly targeting variants affecting fetal brain neurons. To prioritize de novo mutations with extreme regulatory effects, we developed FLARE, a context-specific functional genomic model of constraint. FLARE outperformed other methods in prioritizing case mutations from autism-affected families near syndromic autism-associated genes; for example, identifying mutation outliers near CNTNAP2 that would be missed by alternative approaches. Overall, our findings demonstrate the potential of integrating single-cell maps with population genetics and deep learning-based variant effect prediction to elucidate mechanisms of development and disease-ultimately, supporting the notion that genetic contributions to neurodevelopmental disorders are predominantly rare.

genomics↗

bioRxiv2025

A versatile miniature two-photon microscope enabling multicolor deep-brain imaging

Here we present the FHIRM-TPM 3.0, a 2.6 g miniature two-photon microscope capable of multicolor deep-brain imaging in freely behaving mice. The system was integrated with a broadband anti-resonant hollow-core fiber featuring low transmission loss, minimal dispersion from 700-1060 nm, and high tolerance of laser power. By correcting chromatic and spherical aberrations and optimizing the fluorescence collection aperture, we achieved cortical neuronal imaging at depths exceeding 820 m and, using a GRIN lens, hippocampal Ca2+ imaging at single dendritic spine resolution. Moreover, we engineered three interchangeable parfocal objectives, allowing for a tenfold scalable field-of-view up to 1x0.8 mm{superscript 2}, with lateral resolutions ranging from 0.68 to 1.46 m. By multicolor imaging at excitation wavelengths of 780 nm, 920 nm and 1030 nm, we investigated mitochondrial and cytosolic Ca2+ activities relative to the deposition of amyloid plaques in the cortex of awake APP/PS1 transgenic mice. Thus, the FHIRM-TPM 3.0 provides a versatile imaging system suitable for diverse brain imaging scenarios.

neuroscience↗

bioRxiv2025

Uridine Metabolism as a Targetable Metabolic Achilles' Heel for chemo-resistant B-ALL

Relapse continues to limit survival for patients with B-cell acute lymphoblastic leukemia (B-ALL). Previous studies have independently implicated activation of B-cell developmental signaling pathways and increased glucose consumption with chemo-resistance and relapse risk. Here, we connect these observations, demonstrating that B-ALL cells with active signaling, defined by high expression of phosphorylated ribosomal protein S6 ("pS6+ cells"), are metabolically unique and glucose dependent. Isotope tracing and metabolic flux analysis confirm that pS6+ cells are highly glycolytic and notably sensitive to glucose deprivation, relying on glucose for de novo nucleotide synthesis. Uridine, but not purine or pyrimidine, rescues pS6+ cells from glucose deprivation, highlighting uridine is essential for their survival. Active signaling in pS6+ cells drives uridine production through activating phosphorylation of carbamoyl phosphate synthetase (CAD), the enzyme catalyzing the initial steps of uridine synthesis. Inhibition of signaling abolishes glucose dependency and CAD phosphorylation in pS6+ cells. Primary pS6+ cells demonstrate high expression of uridine synthesis proteins, including dihydroorotate dehydrogenase (DHODH), the rate-limiting catalyst of de novo uridine synthesis. Gene expression demonstrates that increased expression of DHODH is associated with relapse and inferior event-free survival after chemotherapy. Further, the majority of B-ALL genomic subtypes demonstrate activity of DHODH. Inhibiting DHODH using BAY2402232 effectively kills pS6+ cells in vitro, with its IC50 correlated with the strength of pS6 signaling across 14 B-ALL cell lines and patient-derived xenografts (PDX). In vivo DHODH inhibition prolongs survival and decreases leukemia burden in pS6+ B-ALL cell line and PDX models. These findings link active signaling to uridine dependency in B-ALL cells and an associated risk of relapse. Targeting uridine synthesis through DHODH inhibition offers a promising therapeutic strategy for chemo-resistant B-ALL as a novel therapeutic approach for resistant disease.

cancer biology↗

bioRxiv2025

Striatal cell-type specific stability and reorganization underlying agency and habit

Goal-directed behavior is guided by learned action-outcome associations, allowing actions to adapt when outcomes change. With repetition, behavioral control shifts toward habit, enabling more automatic action execution, but reducing flexibility to outcome changes. Here, we used longitudinal, cellular-resolution calcium imaging, chemogenetics, instrumental conditioning, and the outcome devaluation test to ask how dorsomedial striatum D1+ and D2/A2A+ neurons contribute to the formation of goal-directed behavior and habit. DMS D1+ neurons stably encode instrumental actions, carry information about behavioral engagement and organization, and develop and maintain action-reward representational similarity and conjunctive activation with learning. Correspondingly, these neurons are critical for action-outcome learning and goal-directed decision making. In contrast, one ensemble of DMS A2A+ neurons transiently encodes actions during early action-outcome learning and another slowly starts to encode actions as habits form. Similarly, DMS A2A+ neurons transiently mediate action-outcome learning and become dispensable for goal-directed decision making. Thus, action-outcome associations are learned through DMS D1+ and A2A+ neuronal activity but only DMS D1+ neurons maintain support of adaptive, goal-directed decision making. Habit formation is associated with reorganization of A2A+ neuronal encoding. These data reveal a cell-type-specific dissociation between stable v. reorganizing striatal action representations paralleled by persistent v. transient contributions to goal-directed control.

neuroscience↗

bioRxiv2025

Enhancer Dynamics and Spatial Organization Drive Anatomically Restricted Cellular States in the Human Spinal Cord

Here, we report the spatial organization of RNA transcription and associated enhancer dynamics in the human spinal cord at single-cell and single-molecule resolution. We expand traditional multiomic measurements to reveal epigenetically poised and bivalent active transcriptional enhancer states that define cell type specification. Simultaneous detection of chromatin accessibility and histone modifications in spinal cord nuclei reveals previously unobserved cell-type specific cryptic enhancer activity, in which transcriptional activation is uncoupled from chromatin accessibility. Such cryptic enhancers define both stable cell type identity and transitions between cells undergoing differentiation. We also define glial cell gene regulatory networks that reorganize along the rostrocaudal axis, revealing anatomical differences in gene regulation. Finally, we identify the spatial organization of cells into distinct cellular organizations and address the functional significance of this observation in the context of paracrine signaling. We conclude that cellular diversity is best captured through the lens of enhancer state and intercellular interactions that drive transitions in cellular state. This study provides fundamental insights into the cellular organization of the healthy human spinal cord.

neuroscience↗

bioRxiv2025

Revealing hidden knowledge in amnestic mice

Alzheimers disease (AD) is a form of dementia in which memory and cognitive decline is thought to arise from underlying neurodegeneration. These cognitive impairments, however, are transient when they first appear and can fluctuate across disease progression. Here, we investigate the neural mechanisms underlying fluctuations of performance in amnestic mice. We trained APP/PS1+ mice on an auditory go/no-go task that dissociated learning of task contingencies (knowledge) from its more variable expression under reinforcement (performance). APP/PS1+ exhibited significant performance deficits compared to control mice. Using large-scale two-photon imaging of 6,216 excitatory neurons in 8 mice, we found that auditory cortical networks were more suppressed, less selective to the sensory cues, and exhibited aberrant higher-order encoding of reward prediction compared to control mice. A small sub-population of neurons, however, displayed the opposite phenotype, reflecting a potential compensatory mechanism. Volumetric analysis demonstrated that deficits were concentrated near A{beta} plaques. Strikingly, we found that these cortical deficits were reversed almost instantaneously on probe (non-reinforced) trials when APP/PS1+ performed as well as control mice, providing neural evidence for intact stimulus-action knowledge despite variable ongoing performance. A biologically-plausible reinforcement learning model recapitulated these results and showed that synaptic weights from sensory-to-decision neurons were preserved (i.e. intact stimulus-action knowledge) despite poor performance that was due to inadequate contextual scaling (i.e. impaired performance). Our results suggest that the amnestic phenotype is transient, contextual, and endogenously reversible, with the underlying neural circuits retaining the underlying stimulus-action associations. Thus, memory deficits commonly observed in amnestic mouse models, and potentially at early stages of dementia in humans, relate more to contextual drivers of performance rather than degeneration of the underlying memory traces.

neuroscience↗

bioRxiv2024

Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina

Most genetic risk variants linked to ocular diseases are non-protein coding and presumably contribute to disease through dysregulation of gene expression, however, deeper understanding of their mechanisms of action has been impeded by an incomplete annotation of the transcriptional regulatory elements across different retinal cell types. To address this knowledge gap, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome and 3D chromatin architecture in human retina, macula, and retinal pigment epithelium (RPE)/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 sub-classes of retinal cells. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the rapid advancements in deep-learning techniques, we developed sequence-based predictors to interpret non-coding risk variants of retina diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases, and provides a resource for studying the gene regulatory programs of the human retina and relevant diseases.

genomics↗

bioRxiv2024

CSF1R-CAR T cells induce CSF1R signalling and promote cancer cell growth

Chimeric antigen receptor (CAR) T cells have transformed the landscape of cancer therapy and demonstrate unprecedented success in treating relapsed/refractory blood cancers. The mechanism underlaying the interactions and responses of CAR T cells and their targets remain incompletely understood. Previous studies focus on the activation of CAR T cells and attempt to optimise CAR design to increase efficacy, meanwhile ignoring tumours and their responses to CAR ligation. Here, we evaluate the signalling capacity of a second generation CSF1-tageted CSF1R CAR compared with a scFv-targeted CD19-CAR using a SILAC co- culture approach coupled with phosphotyrosine (pY) enrichment and LC-MS/MS. We show that ligation of CSF1R-expressing THP1 cells with CSF1R-CAR T cells induces CSF1R-like signalling in THP1 cells, whereas no target cell signalling response is observed after CD19- CAR/Raji B cell ligation. Using small molecule inhibitors of Lck, actin polymerisation, and CSF1R, we find that CAR-induced CSF1R signalling in THP1 cells depends exclusively on CSF1R kinase activity with no participation from T cell activation. Consistently, CSF1R- CAR T cells promote THP1 growth at low effector-to-target (E:T) ratios but prevent THP1 growth at high E:T ratios. Our data provide evidence for an unintended consequence of CARs; CAR-induced signalling in cancer cells. These data may have broad implications for the choice of CAR antigen for optimal clinical efficacy. One Sentence Summary: CSF1R-CAR activates intracellular signalling cascades in THP1 cells, which promote THP1 cell growth.

cancer biology↗

bioRxiv2024

Rigosertib reverses hypertrophic cardiomyopathy in RAF1-associated Noonan syndrome

BackgroundRASopathies constitute a group of rare genetic disorders caused by mutations in genes that reside along the canonical Ras/MAPK signaling pathway, affecting cell growth and differentiation. These syndromes, which include conditions like Noonan syndrome (NS), are characterized by developmental delays, distinctive facial dysmorphia, and a variety of cardiac defects, notably hypertrophic cardiomyopathy (HCM). Despite their prevalence and impact, therapeutic options for RASopathies remain limited. Rigosertib, a novel dual Ras/MAPK and PI3K/AKT pathway inhibitor, is currently in clinical trials for treatment of melanoma and recessive dystrophic epidermolysis bullosa. Here, we identify rigosertib as a candidate therapy for RAF1-associated HCM. Methods and ResultsOur Drosophila screen of clinically relevant drugs and compounds identified rigosertib as broadly effective across a panel of transgenic RASopathy fly transgenic models, indicating that rigosertib may be effective against multiple disease isoforms. Analysis of a Drosophila model targeting a RAF1L613V transgene to the heart found that rigosertib reduced aspects of cardiac hypertrophy. Rigosertib treatment prevented or regressed cellular hypertrophy in human induced pluripotent stem cell-(iPSC-) derived cardiomyocytes homozygous for the NS-associated RAF1S257L allele. We extended these findings to a mammalian model, using Raf1L613V/+ KI mice to explore the therapeutic implications of rigosertib on RAF1-driven HCM. Longitudinal six-week treatment with rigosertib in these mice resulted in significant improvement in left ventricular chamber dimension and posterior wall thickness, total heart mass, size of individual cardiomyocytes (CMs), as well as reversal of cardiac hypertrophy. Rigosertib treatment also led to normalized fetal gene expression and inhibition of ERK and AKT pathway activities in primary CMs isolated from Raf1L613V/+ mice. Cardiac function, as assessed by echocardiography, showed significant improvement in ejection fraction and fractional shortening, with molecular studies confirming downregulation of hypertrophic markers and signaling pathways. Together with the Drosophila data, these mammalian results support the potential and use for rigosertib to reverse pathological hypertrophy in NS through targeted pathway inhibition in patients. Moreover, in addition to its effects in the heart, rigosertib treatment in mice also significantly improved other NS-associated syndromic features, including increasing bone growth and correcting craniofacial abnormalities. ConclusionsTaken together, our findings suggest rigosertib effectively normalizes and reverses RASopathy-associated HCM as well as other NS-associated syndromic features, supporting its potential for development as a promising treatment for RAF1-associated HCM and, potentially, other RASopathies-dependent pathologies. This study not only highlights the therapeutic potential of rigosertib but also demonstrates the utility of an integrated approach using Drosophila, iPSC and mammalian models to elucidate drug effects across complex biological systems.

molecular biology↗

bioRxiv2024

Metaproteomics reveals age-specific alterations of gut microbiome in hamsters with SARS-CoV-2 infection

The gut microbiomes pivotal role in health and disease is well-established. SARS-CoV-2 infection often causes gastrointestinal symptoms and is associated with changes of the microbiome in both human and animal studies. While hamsters serve as important animal models for coronavirus research, there exists a notable void in the functional characterization of their microbiomes with metaproteomics. In this study, we present a workflow for analyzing the hamster gut microbiome, including a metagenomics-derived hamster gut microbial protein database and a data-independent acquisition metaproteomics method. Using this workflow, we identified 32419 protein groups from the fecal microbiomes of young and old hamsters infected with SARS-CoV-2. We showed age-specific changes in the expressions of microbiome functions and host proteins associated with microbiomes, providing further functional insight into the dysbiosis and aberrant cross-talks between the microbiome and host in SARS-CoV-2 infection. Altogether this study established and demonstrated the capability of metaproteomics for the study of hamster microbiomes.

microbiology↗

bioRxiv2024

GeneCover: A Combinatorial Approach for Label-free Marker Gene Selection

The selection of marker gene panels is critical for capturing the cellular and spatial hetero-geneity in the expanding atlases of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics data. Most current approaches to marker gene selection operate in a label-based framework, which is inherently limited by its dependency on predefined cell type labels or clustering results. In contrast, existing label-free methods often struggle to identify genes that characterize rare cell types or subtle spatial patterns, and they frequently fail to scale efficiently with large datasets. Here, we introduce geneCover, a label-free combinatorial method that selects an optimal panel of minimally redundant marker genes based on gene-gene correlations. Our method demonstrates excellent scalability to large datasets and identifies marker gene panels that capture distinct correlation structures across the transcriptome. This allows geneCover to distinguish cell states in various tissues of living organisms effectively, including those associated with rare or otherwise difficult-to-identify cell types. We evaluate the performance of geneCover across various scRNA-seq and spatial transcriptomics datasets, comparing it to other label-free algorithms to highlight its utility and potential in diverse biological contexts.

bioinformatics↗

bioRxiv2024

Brain functional connectivity, but not neuroanatomy, captures the interrelationship between sex and gender in preadolescents

Understanding sex differences in the adolescent brain is crucial, as these differences are linked to neurological and psychiatric conditions that vary between males and females. Predicting sex from adolescent brain data may offer valuable insights into how these variations shape neurodevelopment. Recently, attention has shifted toward exploring socially-identified gender, distinct from sex assigned at birth, recognizing its additional explanatory power. This study evaluates whether resting-state functional connectivity (rsFC) or cortical thickness more effectively predicts sex and sex/gender alignment (the congruence between sex and gender) and investigates their interrelationship in preadolescents. Using data from the Adolescent Brain Cognitive Development (ABCD) Study, we employed machine learning to predict both sex (assigned at birth) and sex/gender alignment from rsFC and cortical thickness. rsFC predicted sex with significantly higher accuracy (86%) than cortical thickness (75%) and combining both did not improve the rsFC models accuracy. Brain regions most effective in predicting sex belonged to association (default mode, dorsal attention, and parietal memory) and visual (visual and medial visual) networks. The rsFC sex classifier trained on sex/gender aligned youth was significantly more effective in classifying unseen youth with sex/gender alignment than in classifying unseen youth with sex/gender unalignment. In females, the degree to which their brains rsFC matched a sex profile (female or male), was positively associated with the degree of sex/gender alignment. Lastly, neither rsFC nor cortical thickness predicted sex/gender alignment. These findings highlight rsFCs predictive power in capturing the relationship between sex and gender and the complexity of the interplay between sex, gender, and the brains functional connectivity and neuroanatomy.

neuroscience↗

bioRxiv2024

Among-Population Differentiation in the Tapeworm Proteome through Prediction of Excretory/Secretory and Transmembrane Proteins in Schistocephalus solidus

BackgroundParasites secrete and excrete a variety of molecules evolve to help establish and sustain infections within hosts. Parasite adaptation to their host may lead to between-population divergence in these excretory and secretory products (ESPs), but few studies have tested for intraspecific variation in helminth proteomes. MethodsSchistocephalus solidus is a cestode that parasitizes three spined stickleback, Gasterosteus aculeatus. We used an ultra-performance liquid chromatography-mass spectrometry protocol to characterize the ESP and whole-body proteome of S. solidus. Specifically, we characterized the proteome of S. solidus at the plerocercoid stage from wild caught stickleback from three lakes on Vancouver Island (British Columbia, Canada) and one lake in Alaska (United States). We tested for differences in proteome composition among the four populations and specifically between ESPs and body tissue. ResultsOverall, we identified 1362 proteins in the total proteome of S. solidus, with 542 of the 1362 proteins detected exclusively in the ESPs. Of the ESP proteins, we found signaling peptides and transmembrane proteins that were previously not detected or characterized in S. solidus. We also found protein spectrum counts greatly varied between all lake populations. ConclusionsThese population-level differences were observed in both ESP and tissue types. Our study suggests that S. solidus can excrete and secrete a wide range of proteins which are distinct among populations. These differences might reflect plastic responses to host genotype differences, or evolved adaptations by Schistocephalus to different local host populations.

evolutionary biology↗

bioRxiv2024

Mechanistic insights into structure-based design of a Lyme disease subunit vaccine

The quality of protective immunity plays a critical role in modulating vaccine efficacy, with native antigens often not able to trigger sufficiently strong immune responses for pathogen killing. This warrants creation of structure-based vaccine design, leveraging high-resolution antigen structures for mutagenesis to improve protein stability and efficient immunization strategies. Here, we investigated the mechanisms underlying structure-based vaccine design using CspZ-YA, a vaccine antigen from Borrelia burgdorferi, the bacteria causing Lyme disease (LD), the most common vector-borne disease in the Northern Hemisphere. Compared to wild-type CspZ-YA, we found CspZ-YAI183Y and CspZ-YAC187S required lower immunization frequency to protect mice from LD-associated manifestations and bacterial colonization. We observed indistinguishable human and mouse antigenicity between wild-type and mutant CspZ-YA proteins after native infection or active immunization. This supports our newly generated, high-resolution structures of CspZ-YAI183Y and CspZ-YAC187S, showing no altered surface epitopes after mutagenesis. However, CspZ-YAI183Y and CspZ-YAC187S favored the interactions between helices H and I, consistent with their elevated thermostability. Such findings are further strengthened by increasing ability of protective CspZ-YA monoclonal antibodies in binding to CspZ-YA at a physiological temperature (37{degrees}C). Overall, this study demonstrated enhanced intramolecular interactions improved long-term stability of antigens while maintaining protective epitopes, providing a mechanism for structure-based vaccine design. These findings can ultimately be extended to other vaccine antigens against newly emerging pathogens for the improvement of protective immunity.

immunology↗

bioRxiv2024

α-Synuclein Strain Dynamics Correlate with Cognitive Shifts in Parkinson's Disease

-Synuclein (-syn) strains can serve as discriminators between Parkinsons disease (PD) and related -synucleinopathies. The relationship between -syn strain dynamics and clinical performance as patients transition from normal cognition (NC) to cognitive impairment (CI) is not known. Here, we show that the biophysical properties and neurotoxicity of -syn strains change as PD cognitive status transitions from NC to mild cognitive impairment (PD-MCI) and dementia (PD-D). Both cross-sectional and longitudinal analyses reveal distinct -syn strains in PD patients correlating to their level of cognitive impairment. Machine learning (ML) was employed to achieve high classification accuracy. The combination of thioflavin T (ThT) maximal fluorescence intensity (mfi), max slope of rise curve (forming rate), lag time (tlag), 20% time (t20), and half-time (t50), dynamic light scattering (DLS) (peak number, [1/2] peak size, [1/2] peak intensity) and neurotoxicity together with demographic variables for model training yielded superior performance (89[~]99% accuracy in the 4- and 2- classification schema) compared to individual features alone in classifying cognitive status. For the longitudinal study, DLS peak number emerged as the strongest predictor of cognitive transition (HR = 0.12, P = 0.002), with the optimal predictive model combining DLS peak number, sex, education, DLS peak 1 size, and DLS peak 2 polydispersity achieving high accuracy (C-index of [~]93%). This study presents evidence that individuals with PD have different -syn strains correlating to their cognitive status and highlights the potential of -syn strain dynamics to guide future diagnosis, management, and stratification of PD patients. One Sentence SummaryDistinct features of -syn strains change with cognitive decline in Parkinsons disease and AI-based analysis incorporating these combined characteristics serves as a powerful tool for PD clinical stratification.

neuroscience↗

bioRxiv2024

Spatial Single-Cell Mapping of Transcriptional Differences Across Genetic Backgrounds in Mouse Brains

Genetic variation can alter organ structure and, in turn, function. Comparative statistical analysis of organs across genetic backgrounds requires spatial, single-cell, atlas-scale data in replicates, which current technologies do not provide at scale. We introduce Atlas-scale Transcriptome Localization using Aggregate Signatures (ATLAS), a scalable tissue mapping method. ATLAS learns transcriptional signatures from scRNAseq data, encodes them in situ with tens of thousands of oligonucleotide probes, and decodes them to infer cell types and imputed transcriptomes. We validated ATLAS in the mouse brain by comparing its cell type inferences with direct MERFISH measurements of marker genes and quantitative comparisons to four other technologies. Using ATLAS, we mapped the central brains of five male and five female C57BL/6J (B6) mice and five male BTBR T+ tf/J (BTBR) mice, an idiopathic model of autism, collectively profiling over 40 million cells across over 400 coronal sections. Our analysis revealed over 40 significant differences in cell type distributions and identified 16 regional composition changes across male-female and B6-BTBR comparisons. ATLAS thus enables systematic comparative studies, facilitating organ-level structure-function analysis of disease models.

genomics↗

bioRxiv2024

D-lactate derived from intestinal bacteria drives lysine D-lactylation to modulate transcription in liver cells

Emerging evidence indicates that the accumulated D-lactate (D-la) from intestinal bacteria induces diverse effects in human intestinal injury diseases. However, its regulatory mechanism and functional consequence remain unclear. Here, we show that the secreted D-la induces lysine D-lactylation (K-Dla) to modulate transcription in host cells. We uncover K-Dla in HepG2 cells stimulated by D-la from E. coli secretions. Then, we confirm the occurrence of D-la-driven K-Dla by four orthogonal approaches. We further validate that the existence of K-Dla in organisms by detecting the mouse liver and human intestinal tissue. Besides, we demonstrate a SCOT1-catalyzed biosynthetic pathway of D-lactyl-CoA, serving as a key donor for K-Dla. Next, we identify the K-Dla landscape with 2895 sites and further suggest the regulation of histone K-Dla in transcription by MNase ChIP-seq and RNA-seq assays. Finally, we show the potential effect of K-Dla on inhibiting the hepatocellular carcinoma cell proliferation. In summary, we report that the secreted D-la can induce K-Dla to regulate transcription, providing a new insight into the function of D-la secreted by gut microbiota and the effect of protein chemical modifications induced by bacterial secretions.

molecular biology↗