Biology subjects

Ma, H.

Publications and source records attributed to Ma, H..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Neuron-astrocyte Coupling in Lateral Habenula Mediates Depressive-like Behaviors

The lateral habenular (LHb) neurons and astrocytes have been strongly implicated in depression etiology but it was not clear how the two dynamically interact during depression onset. Here, using multi-brain-region calcium photometry recording in freely-moving mice, we discover that stress induces a unique, bimodal neuronal response and a most rapid astrocytic response in the LHb. LHb astrocytic calcium requires the 1A-adrenergic receptor, and depends on a recurrent neural network between the LHb and locus coeruleus (LC). Through the gliotransmitter glutamate and ATP/Adenosine, LHb astrocytes mediate the second-wave activation of local LHb neurons as well as release of norepinephrine (NE). Activation or inhibition LHb astrocytic calcium signaling facilitates or prevents stress-induced depressive-like behaviors respectively. These results identify a stress-induced positive feedback loop in the LHb-LC axis, with astrocytes being a critical signaling relay. The identification of this prominent neuron-glia interaction may shed light on stress management and depression prevention.

neuroscience↗

bioRxiv2024

Probing Biomass Precursor Synthesis as a Key Factor in Microbial Adaptation to Unadapted Carbon Sources

Industrial microorganisms often face challenges in utilizing renewable substrates such as methanol, formate, and xylose. We present findings that the proportion of biomass precursors that must be synthesized from unadapted carbon sources is a critical determinant of the evolutionary driving force and minimal substrate requirements, using a new computational framework, AdaptUC. We predict metabolic engineering strategies for Adaptive Laboratory Evolution (ALE). These strategies enable microorganisms to co-utilize an adapted co-substrate and an unadapted carbon source or, in some cases, rely exclusively on the unadapted source. AdaptUC was validated through experimental records and literature, confirming its effectiveness in identifying gene knockout strategies. Case studies in Escherichia coli and Corynebacterium glutamicum highlight superior strategies with higher driving forces and reduced substrate requirements. This method has the potential to transform industrial biosynthesis by enabling more efficient use of renewable carbon sources. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/619944v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@36fe02org.highwire.dtl.DTLVardef@5e73fdorg.highwire.dtl.DTLVardef@110ffdaorg.highwire.dtl.DTLVardef@10d45dc_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

Omega-3 fatty acid normalizes postsynaptic density proteins via miRNAs regulation in hippocampus and prevents DEHP-induced impairment of learning and memory in mice

AbstractsDEHP is the most widely used plasticizer in many products. However, growing evidence has indicated that DEHP may induce neurotoxicity. DEHP exposure affects mircoRNAs (miRNAs) expression in brain. A growing body of evidence suggests that nutrients and other bioactive food components prevent neurotoxicity through regulation of miRNA expression. Due to the increasing concern about the risks of DEHP to human health, we explored the neuroprotective effect of Omega-3 fatty acid (Omega-3FA) on subchronic DEHP-induced neurotoxicity in mice, and the potential involved miRNAs and their targets in the protective action of Omega-3FA against DEHP-induced neurotoxicity. Omega-3FA protected against the DEHP-induced impairment of learning and memory and alleviated the thinning of postsynaptic density (PSD) thickness in hippocampal synapses. We observed that there are fourteen up or down regulated miRNAs associated PSD in DEHP exposure which were normalized by Omega-3FA treatment. Protein targets in PSD of these differentially expressed miRNAs were predicted. Furthermore, the expression levels of protein mGluR5, Homer1, and NMDAR2B were carried out via Western blot, for further verifying PSD associated miRNAs targets are involved in neuroprotection of Omega-3FA against DEHP. These findings suggested that Omega-3FA protected DEHP-induced impairment of learning and memory as well as synaptic structure alteration in the hippocampus by regulating the expression of PSD associated miRNAs and their targets. Thus, Omega-3FA should be included in diet to prevent or suppress neurotoxicity caused by continuous exposure to DEHP.

neuroscience↗

bioRxiv2024

Connectomic Organization of the Suprachiasmatic Nucleus

The suprachiasmatic nucleus (SCN), the mammalian master clock, is a special structure dedicated to the time computation. However, a connectomic understanding of the nucleus as a whole is lacking. Using serial section electron microscopy, we reconstructed multiscale and multimodal SCN communication networks. Intra-SCN synaptic network consists of 9,566 morphologically similar neurons and 4.3 million synapses, organized into multiscale circuitries that interact with SCN-traversing axon fascicles. Strikingly, SCN neurons engage in unique soma-soma ephaptic interaction, forming 2,038 electrotonic integrative units with the largest overlapping the light-responsive area (LRA). SCNs paracrine modality contains 47,396 m3 dense core vesicles, with notable scarcity in the LRA, suggesting cross-modal coordination and functional integration. These distinct network features provide comprehensive insights into the system architecture of the mammalian circadian clock.

neuroscience↗

bioRxiv2024

Vispro improves imaging analysis for Visium spatial transcriptomics

Spatial transcriptomics (ST) enables the comprehensive analysis of gene expression while preserving the spatial context of tissues. The histological images accompanying ST data provide spatially cohesive information that is often challenging to capture through gene expression alone. However, analyzing such images is challenging due to the presence of fiducial markers and background regions, which can obscure important features and complicate downstream analysis. To address these challenges, we developed Vispro, an end-to-end, fully automated image processing tool tailored for 10x Visium data. Vispro integrates four key modules of fiducial marker detection, fiducial marker removal and image restoration, tissue region detection, and segmentation of disconnected tissue areas. We demonstrated that Vispro enhances the quality of ST images and improves the performance of downstream analyses, including tissue segmentation, cell segmentation, image registration, and histology-based gene imputation.

bioinformatics↗

bioRxiv2024

TET2 contributes to gluconeogenesis and pathology of type 2 diabetes

The control of gluconeogenesis is critical for glucose homeostasis and the pathology of type 2 diabetes (T2D). Here, we uncover a novel function of TET2 in the regulation of gluconeogenesis. In mice, both fasting and a high-fat diet (HFD) stimulate the expression of TET2, and TET2 knockout impairs glucose production. Mechanistically, FBP1, a rate-limiting enzyme in gluconeogenesis, is positively regulated by TET2 in liver cells. TET2 is recruited by HNF4, contributing to the demethylation of FBP1 promoter and activating its expression in response to glucagon stimulation. Moreover, metformin treatment increases the phosphorylation of HNF4 on Ser313, which prevents its interaction with TET2, thereby decreasing the expression level of FBP1 and ameliorating the pathology of T2D. Collectively, we identify an HNF4-TET2-FBP1 axis in the control of gluconeogenesis, which contributes to the therapeutic effect of metformin on T2D and provides a potential target for the clinical treatment of T2D.

cell biology↗

bioRxiv2024

Unveiling allopolyploidization-driven genome duplications through progressive analysis of deep genome skimming data

Whole-genome duplication (WGD) events are widespread across the Web of Life (WoL). Given the prevalence of WGDs in the polyploid Prunus (Rosaceae), this economically- and agriculturally-important angiosperm lineage provides an excellent model for exploring this mode of reticulation. We used the polyploid Prunus to demonstrate a progressive strategy for analyzing Deep Genome Skimming (DGS) data in the presence of WGDs. Phylogenomic discordance analyses indicated that allopolyploidization, rather than Incomplete Lineage Sorting (ILS), played a dominant role in the origin and dynamics of polyploid Prunus. This study underscores how a progressive strategy to identify WGD events at different depths in a phylogenetic tree reveals the nuances of evolutionary mechanisms driving allopolyploidization. We inferred that the continued uplift of the Himalayas from the Middle to Late Miocene drove the rapid diversification of the Eastern Asia endemic Maddenia clade, by facilitating frequent hybridization and allopolyploidization, specifically introgression between the Himalayas-Hengduan and the Central-Eastern China clades.

systems biology↗

bioRxiv2024

BRD4 phosphorylation regulates the structure of chromatin nanodomains

The interplay between chromatin structure and phase-separating proteins is an emerging topic in cell biology with implications for understanding disease states. Here, we investigate the functional relationship between bromodomain protein 4 (BRD4) and chromatin architecture. By combining molecular dynamics simulations with live-cell imaging, we demonstrate that BRD4, when mutated at specific N-terminus sites, significantly impacts nucleosome nanodomain (NN) organization and dynamics. Our findings reveal that enhanced chromatin binding activity of BRD4 condenses NNs, while both loss or gain of BRD4 chromatin binding reduced diffusion of single nucleosomes, suggesting a role for BRD4 in the regulation of nanoscale chromatin architecture and the chromatin microenvironment. These observations shed light on the nuanced regulation of chromatin structure by BRD4, offering insights into its role in maintaining the nuclear architecture and transcriptional activity.

biophysics↗

bioRxiv2024

Modulation Of SUDEP By Central Serotonergic Cooperating with Noradrenergic Circuits: A Synergistic-Dependent Manner

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death in refractory epilepsy patients. Despite previous accumulating evidence has shown that seizure-induced respiratory arrest (S-IRA) may play the main contributor to SUDEP as an initiating event preeminent cause of mortality, the specific underlying mechanism of action remains unclear. Based on our previous work, serotonin (5-HT) signaling in the dorsal raphe nucleus (DRN) is strongly implicated in S-IRA in animal models, including the DBA/1 mice, on the meanwhile, norepinephrine (NE) neurons of the locus coeruleus (LC) also plays a vital role in regulating respiratory function on its own. Superficially, monoaminergic neuron, as important neurotransmitters in the central nervous system, have similar modes of action in the maintenance of nervous system balance, and each of them has a regulatory effect on SUDEP. However, it remains to be investigated whether monoaminergic neuron family (NE and 5-HT) are related in the mechanism of regulating SUDEP, what is even more curious is whether the two are intrinsically linked. Thus, we hypothesize neural mechanism of central noradrenergic and serotonergic circuits in modulating SUDEP in a synergistic-dependent manner, this endeavor will culminate in a significant breakthrough in elucidating the precise mechanism of action underlying SUDEP. In our study, we will use chemogenetics, optogenetics, calcium signal recording, and bidirectional tracing to explore the internal mechanism of DR-LC regulating the occurrence of SUDEP, and by specifically injecting 5-HT2AR antagonist Ketanserin (KET) and/or NE-1R antagonist Prazosin into the pre-Botzinger complex (PBC), it was finally elucidate that the DR-LC-PBC network can effectively reduce the incidence of SIRA. We firstly proposed a powerful target for exploring the reduction of the incidence of SUDEP, which has great clinical translation potential.

neuroscience↗

bioRxiv2024

BCAS2 promotes primitive hematopoiesis by sequestering β-catenin within the nucleus

Breast carcinoma amplified sequence 2 (BCAS2), a core component of the hPrP19 complex, plays crucial roles in various physiological and pathological processes. However, whether BCAS2 has functions other than being a key RNA-splicing regulator within the nucleus remains unknown. Here, we show that BCAS2 is essential for primitive hematopoiesis in zebrafish and mouse embryos. The activation of Wnt/{beta}-catenin signal, which is required for hematopoietic progenitor differentiation, is significantly decreased upon depletion of bcas2 in zebrafish embryos and mouse embryonic fibroblasts (MEFs). Interestingly, BCAS2 deficiency has no obvious impact on the splicing efficiency of {beta}-catenin pre-mRNA, while significantly attenuating {beta}-catenin nuclear accumulation. Moreover, we find that BCAS2 directly binds to {beta}-catenin via its coiled-coil domains, thereby sequestering {beta}-catenin within the nucleus. Thus, our results uncover a previously unknown function of BCAS2 in promoting Wnt signaling by enhancing {beta}-catenin nuclear retention during primitive hematopoiesis.

developmental biology↗

bioRxiv2024

An Omni-Mesoscope for multiscale high-throughput quantitative phase imaging of cellular dynamics and high-content molecular characterization

The mesoscope has emerged as a powerful imaging tool in biomedical research, yet its high cost and low resolution have limited its broader application. Here, we introduce the Omni-Mesoscope, a cost-effective high-spatial-temporal, multimodal, and multiplex mesoscopic imaging platform built from cost-efficient off-the-shelf components. This system uniquely merges the capabilities of quantitative phase microscopy to capture live-cell dynamics over a large cell population with highly multiplexed fluorescence imaging for comprehensive molecular characterization. This integration facilitates simultaneous tracking of live-cell morphodynamics across thousands of cells, alongside high-content molecular analysis at the single-cell level. Furthermore, the Omni-Mesoscope offers a mesoscale field of view of approximately 5 mm2 with a high spatial resolution down to 700 nm, enabling the capture of information-rich images with detailed sub-cellular features. We demonstrate such capability in delineating molecular characteristics underlying rare dynamic cellular phenomena, such as cancer cell responses to chemotherapy and the emergence of polyploidy in drug-resistant cells. Moreover, the cost-effectiveness and the simplicity of our Omni-Mesoscope democratizes mesoscopic imaging, making it accessible across diverse biomedical research fields. To further demonstrate its versatility, we integrate expansion microscopy to enhance 3D volumetric super-resolution imaging of thicker tissues, opening new avenues for biological exploration at unprecedented scales and resolutions.

cell biology↗

bioRxiv2024

RNA-ligand interaction scoring via data perturbation and augmentation modeling

RNA-targeting drug discovery is undergoing an unprecedented revolution. Despite recent advances in this field, developing data-driven deep learning models remains challenging due to the limited availability of validated RNA-small molecule interactions and the scarcity of known RNA structures. In this context, we introduce RNAsmol, a novel sequence-based deep learning framework that incorporates data perturbation with augmentation, graph-based molecular feature representation and attention-based feature fusion modules to predict RNA-small molecule interactions. RNAsmol employs perturbation strategies to balance the bias between true negative and unknown interaction space thereby elucidating the intrinsic binding patterns between RNA and small molecules. The resulting model demonstrates accurate predictions of the binding between RNA and small molecules, outperforming other methods with average improvements of [~]8% (AUROC) in 10-fold cross-validation, [~]16% (AUROC) in cold evaluation (on unseen datasets), and [~]30% (ranking score) in decoy evaluation. Moreover, we use case studies to validate molecular binding hotspots in the prediction of RNAsmol, proving the models interpretability. In particular, we demonstrate that RNAsmol, without requiring structural input, can generate reliable predictions and be adapted to many RNA-targeting drug design scenarios.

bioinformatics↗

bioRxiv2024

High-resolution chromosome-level genome provides molecular insights into adaptive evolution in crabs

Crabs thrive in diverse ecosystems, from coral reefs to hydrothermal vents and terrestrial habitats. Here, we report a comprehensive genomic analysis of the mud crab using ultralong sequencing technologies, achieving a high-quality chromosome-level assembly. The refined 1.21 Gb genome, with an impressive contig N50 of 11.45 Mb, offers a valuable genomic resource. Gene family analysis shows expansion in development-related pathways and contraction in metabolic pathways, indicating niche adaptations. Notably, Investigation into Hox gene regulation sheds light on their role in pleopod development, with the Abd-A gene identified as a linchpin. Posttranscriptional regulation involving novel-miR1317 negatively regulates Abd-A levels. Furthermore, the fru genes potential role in ovarian development and the identification of novel-miRNA-35 as a regulator of Spfru2 add complexity to gene regulatory networks. Comparative functional analysis across Decapoda species reveals neofunctionalization of the elovl6 gene in the synthesis of long-chain polyunsaturated fatty acids (LC-PUFA), suggesting its importance in environmental adaptation. These findings contribute significantly to our understanding of crab adaptability and evolutionary dynamics, offering a robust foundation for future investigations.

genomics↗

bioRxiv2024

Deficiency in a special dynein DNAH12 causes male infertility by impairing DNAH1 and DNALI1 recruitment in humans and mice

Asthenoteratozoospermia, a prevalent cause of male infertility, lacks a well-defined etiology. DNAH12 is a special dynein featured by the absence of a microtubule-binding domain, however, its functions in spermatogenesis remain largely unknown. Through comprehensive genetic analyses involving whole-exome sequencing and subsequent Sanger sequencing on infertile patients and fertile controls from six distinct families, we unveiled six biallelic mutations in DNAH12 that co-segregate recessively with male infertility in the studied families. Transmission electron microscopy (TEM) revealed pronounced axonemal abnormalities, including inner dynein arms (IDAs) impairment and central pair (CP) loss in sperm flagella of the patients. Mouse models (Dnah12-/- and Dnah12mut/mut) were generated and recapitulated the reproductive defects in the patients. Noteworthy, DNAH12 deficiency did not show effects on cilium organization and function. Mechanistically, DNAH12 was confirmed to interact with two other IDA components DNALI1 and DNAH1, while disruption of DNAH12 leads to failed recruitment of DNALI1 and DNAH1 to IDAs and compromised sperm development. Furthermore, DNAH12 also interacts with radial spoke head proteins RSPH1, RSPH9, and DNAJB13 to regulate CP stability. Moreover, the infertility of Dnah12-/- mice could be overcome by intracytoplasmic sperm injection (ICSI) treatment. Collectively, DNAH12 plays a crucial role in the proper organization of axoneme in sperm flagella, but not cilia, by recruiting DNAH1 and DNALI1 in both humans and mice. These findings expand our comprehension of dynein component assembly in flagella and cilia and provide a valuable marker for genetic counseling and diagnosis of asthenoteratozoospermia in clinical practice.

genetics↗

bioRxiv2024

Spatially Resolved Tumor Ecosystems and Cell States in Gastric Adenocarcinoma Progression and Evolution

Gastric cancer (GC) is a major cause of global cancer mortality with high heterogeneity levels. To explore geospatial interactions in tumor ecosystems, we integrated 1,563 spatial transcriptomic regions-of-interest (ROIs) with 152,423 single-cell expression profiles across 130 GC samples from 70 patients. We observed pervasive expression-based intratumor heterogeneity, recapitulating tumor progression through spatially localized and functionally ordered subgroups with specific immune microenvironments and immune checkpoint profiles. Evolutionary phylogenetic analysis revealed two different evolutionary trajectories (branched evolution and diaspora evolution) associated with distinct molecular subtypes, clinical prognoses, stromal neighborhoods including VWF+ ACKR1+ endothelial cells, and genetic drivers such as SOX9. Spatial analysis of tumor-stromal interfaces across multiple GCs highlighted new ecosystem states not attributable to mere tumor/stroma admixture, landmarked by increased GREM1 expression. Our results provide insights into how the cellular ecosystems of individual GCs are sculpted by tumor intrinsic and extrinsic selective pressures, culminating in individualized patient-specific cancer cartographies.

cancer biology↗

bioRxiv2024

Biophysical Profiling of Red Blood Cells from Thin-film Blood Smears using Deep Learning

Microscopic inspection of thin-film blood smears is widely used to identify red blood cell (RBC) pathologies, including malaria parasitism and hemoglobinopathies, such as sickle cell disease and thalassemia. Emerging research indicates that non-pathologic changes in RBCs can also be detected in images, such as deformability and morphological changes resulting from the storage lesion. In transfusion medicine, cell deformability is a potential biomarker for the quality of donated RBCs. However, a major impediment to the clinical translation of this biomarker is the difficulty associated with performing this measurement. To address this challenge, we developed an approach for biophysical profiling of RBCs based on cell images in thin-film blood smears. We hypothesize that subtle cellular changes are evident in blood smear images, but this information is currently undetectable by human cognition. To test this hypothesis, we developed a deep learning strategy to analyze Giemsa-stained blood smears to assess the subtle morphologies indicative of RBC deformability and storage-based degradation. Specifically, we prepared thin-film blood smears from 27 RBC samples (9 donors evaluated at 3 storage timepoints) and imaged them using high-resolution microscopy. Using this dataset, we trained a convolutional neural network to evaluate image-based morphological features related to cell deformability. The prediction of donor deformability is strongly correlated to the microfluidic scores and can be used to categorize images into specific deformability groups with high accuracy. We also used this model to evaluates differences in RBC morphology resulting from cold storage. Together, our results demonstrate that deep learning models can exceed the limits of human cognition to detect subtle cellular differences in morphology resulting from deformability and cold storage. This result suggests the potential to assess donor blood quality from thin-film blood smears, which can be acquired ubiquitously in clinical workflows.

bioengineering↗

bioRxiv2024

Positive Selection on Rare Variants Underlying the Cold Adaptation of Wild Boar

The wide geographical distribution of Eurasian wild boar (Sus scrofa) offers a natural experiment to study the thermoregulation. Here, we conducted whole-genome resequencing and chromatin profiling experiments on the local populations from cold regions (northern and northeastern Asia) and warm regions (southeastern Asia and southern China). Using genome-wide scans of four methods, we detected candidate genes underlying cold-adaptation with significant enrichment of pathways related to thermogenesis, fat cell development, and adipose tissue regulation. We also found two enhancer variants under positive selection, an intronic variant of IGF1R (rs341219502) and an exonic variant of BRD4 (rs327139795), which showed the highest differentiation between cold and warm region populations of wild boar and domestic pigs. Moreover, these rare variants were absent in outgroup species and warm-region wild boar but nearly fixed in cold-region populations, suggesting their de novo origins in cold-region populations. The experiments of CUT&Tag chromatin profiling showed that rs341219502 of IGF1R is associated with the gain of three novel transcription factors involving regulatory changes in enhancer function, while rs327139795 of BRD4 could result in the loss of a phosphorylation site due to amino acid alteration. We also found three genes (SLCO1C1, PDE3A, and TTC28) with selection signals in both wild boar and native human populations from Siberia, which suggests convergent molecular adaptation in mammals. Our study shows the adaptive evolution of genomic molecules underlying the remarkable environmental flexibility of wild boar.

evolutionary biology↗

bioRxiv2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare event problems, the computational costs and/or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information of transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. We also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

biophysics↗