Biology subjects

Li, D.

Publications and source records attributed to Li, D..

At least 289 records · Page 16Linked to original sources

bioRxiv2024

Circular RNA circASH1L(4,5) protects microRNA-129-5p from target-directed microRNA degradation in human skin wound healing

Both circular RNAs (circRNA) and microRNAs (miRNA) have emerged to play important roles in health and disease. To understand their function in tissue repair, we profiled circRNA, linear RNA, and miRNA expression dynamics in human wound-edge keratinocytes across the wound healing process. Our investigation spotlighted circASH1L(4,5) and its engagement with miR-129-5p, both of which levels were increased with wound repair. Unlike conventional miRNA sponging, circASH1L enhanced miR-129 stability and silencing activity by protecting this miRNA from target-directed miRNA degradation (TDMD) triggered by NR6A1 mRNA. TGF-{beta} signaling, pivotal in wound healing, fostered circASH1L expression while suppressing NR6A1, thus enhancing the miR-129 abundance at the post-transcriptional level. Functionally, circASH1L and miR-129 enhanced keratinocyte migration and proliferation, crucial for re-epithelialization of human wounds. Collectively, our study uncovers circRNAs novel role as shields for miRNAs and sheds light on the physiological importance of regulated miRNA degradation in human skin wound healing.

molecular biology↗

bioRxiv2024

BET inhibitors as a therapeutic intervention in gastrointestinal gene signature-positive castration-resistant prostate cancer.

A subgroup of castration-resistant prostate cancer (CRPC) aberrantly expresses a gastrointestinal (GI) transcriptome governed by two GI-lineage-restricted transcription factors, HNF1A and HNF4G. In this study, we found that expression of GI transcriptome in CRPC correlates with adverse clinical outcomes to androgen receptor signaling inhibitor treatment and shorter overall survival. Bromo- and extra-terminal domain inhibitors (BETi) downregulated HNF1A, HNF4G, and the GI transcriptome in multiple CRPC models, including cell lines, patient-derived organoids, and patient-derived xenografts, while AR and the androgen-dependent transcriptome were largely spared. Accordingly, BETi selectively inhibited growth of GI transcriptome-positive preclinical models of prostate cancer. Mechanistically, BETi inhibited BRD4 binding at enhancers globally, including both AR and HNF4G bound enhancers while gene expression was selectively perturbed. Restoration of HNF4G expression in the presence of BETi rescued target gene expression without rescuing BRD4 binding. This suggests that inhibition of master transcription factors expression underlies the selective transcriptional effects of BETi. SIGNIFICANCEGI transcriptome expression in CRPC is regulated by the HNF1A-HNF4G-BRD4 axis and correlates with worse clinical outcomes. Accordingly, BET inhibitors significantly reduce tumor cell growth in multiple GI-transcriptome-positive preclinical models of CRPC. Our studies point that expression of GI transcriptome could serve as a predictive biomarker to BETi therapy response.

cancer biology↗

bioRxiv2024

Highly Dynamic and Sensitive NEMOer Calcium Indicators for Imaging ER Calcium Signals in Excitable Cells

Endoplasmic/sarcoplasmic reticulum (ER/SR) sits at the heart of the calcium (Ca2+) signaling machinery, yet current genetically encoded Ca2+ indicators (GECIs) lack the ability to detect elementary Ca2+ release events from ER/SR, particularly in muscle cells. Here we report a set of organellar GECIs, termed NEMOer, to efficiently capture ER Ca2+ dynamics with increased sensitivity and responsiveness. Compared to G-CEPIA1er, NEMOer indicators exhibit dynamic ranges that are an order of magnitude larger, which enables up to 5-fold more sensitive detection of Ca2+ oscillation in both non-excitable and excitable cells. The ratiometric version further allows super-resolution monitoring of local ER Ca2+ homeostasis and dynamics. Notably, the NEMOer-f variant enabled the inaugural detection of Ca2+ blinks, elementary Ca2+ releasing signals from the SR of cardiomyocytes, as well as in vivo spontaneous SR Ca2+ releases in zebrafish. In summary, the highly dynamic NEMOer sensors expand the repertoire of organellar Ca2+ sensors that allow real-time monitoring of intricate Ca2+ dynamics and homeostasis in live cells with high spatiotemporal resolution.

synthetic biology↗

bioRxiv2024

N-acetylation of α-synuclein enhances synaptic vesicle clustering mediated by α-synuclein and lysophosphatidylcholine

Post-translational modifications (PTMs) of -synuclein (-syn) such as acetylation and phosphorylation play important yet distinct roles in regulating -syn conformation, membrane binding, and amyloid aggregation. However, how PTMs regulate -syn function in presynaptic terminals remains unclear. Previously, we reported that -syn clusters synaptic vesicles (SV)1, and neutral phospholipid lysophosphatidylcholine (LPC) can mediate this clustering2. Here, based on our previous findings, we further demonstrate that N-terminal acetylation, which occurs under physiological conditions and is irreversible in mammalian cells, significantly enhances the functional activity of -syn in clustering SVs. Mechanistic studies reveal that this enhancement is caused by the N-acetylation-promoted insertion of -syns N-terminus and increased intermolecular interactions on the LPC-containing membrane. Our work demonstrates that N-acetylation fine-tunes -syn-LPC interaction for mediating -syns function in SV clustering.

biophysics↗

bioRxiv2024

Unraveling the Genetic Comorbidity Landscape of Alzheimer's Disease

Alzheimers disease (AD) has emerged as the most prevalent and complex neurodegenerative disorder among the elderly population. However, the genetic comorbidity etiology for AD remains poorly understood. In this study, we conducted pleiotropic analysis for 41 AD phenotypic comorbidities, identifying ten genetic comorbidities with 16 pleiotropy genes associated with AD. Through biological functional and network analysis, we elucidated the molecular and functional landscape of AD genetic comorbidities. Furthermore, leveraging the pleiotropic genes and reported biomarkers for AD genetic comorbidities, we identified 50 potential biomarkers for AD diagnosis. Our findings deepen the understanding of the occurrence of AD genetic comorbidities and provide new insights for the search for AD diagnostic markers. HighlightsThe present study has focused on the comorbidities associated with Alzheimers disease (AD) by constructing a landscape of these comorbidities at various levels, including diseases, genetics, and pathways. O_LIThe study findings reveal novel and significant pathways that contribute to the etiology of AD and its comorbidities. C_LIO_LIBy exploring pleiotropic genes and reported biomarkers of AD comorbidities, the study has identified several potential diagnostic biomarker candidates for AD. C_LI O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/583453v1_figG1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@2fc040org.highwire.dtl.DTLVardef@f6d801org.highwire.dtl.DTLVardef@1df65a4org.highwire.dtl.DTLVardef@18a307e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic abstract.C_FLOATNO Study pipeline. C_FIG

neuroscience↗

bioRxiv2024

Overexpression of PpGL2 from Prunus persica enhanced soybean drought tolerance

The HD-ZIP transcription factor family plays crucial roles in plant growth and abiotic stress responses. While its diverse functions and regulatory mechanisms are well-documented, its role in conferring abiotic stress tolerance in peaches remains largely unexplored. Here, we report the bioinformatics profile of PpGL2, a member of the HD-ZIP transcription factor family, and its integration into the soybean genome to assess its potential impact on drought tolerance. Localization studies in onion cells revealed nuclear localization of PpGL2-GFP fusion protein, while yeast hybridization experiments demonstrated its transactivation and DNA binding abilities. PpGL2 overexpression under drought conditions led to reduced accumulation of reactive oxygen species and malondialdehyde compared to wild-type, decreased water loss rate, and increased chlorophyll content and relative water content. Additionally, PpGL2 overexpression promoted plant height and root length under drought stress, accompanied by altered transcription levels of stress-related genes across different plant genotypes. Furthermore, PpGL2 overexpression enhanced oxidative tolerance. Therefore, our findings suggest that PpGL2 overexpression holds promise for enhancing soybean drought resistance, offering a novel approach to improving soybean drought resistance.

plant biology↗

bioRxiv2024

Functional architecture of intracellular oscillations in hippocampal dendrites

Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions and report an advancing gradient of dendritic theta phase along the basal-tuft axis, then describe a pre-dominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.

neuroscience↗

bioRxiv2024

Spatial architecture of CD8+ T cells and DC subsets is critical for the response to immune checkpoint inhibitors in melanoma

BackgroundDendritic cells (DCs) are promising targets for cancer immunotherapies owing to their central role in the initiation and the control of immune responses. Their functions encompass a wide range of mechanisms mediated by different DC subsets. Several studies have identified human tumor- associated DC (TA-DC) populations through limited marker-based technologies, such as immunostaining or flow cytometry. However, tumor infiltration, spatial organization and specific functions in response to immunotherapy of each DC subset remain to be defined. MethodsHere, we implemented a multiplexed immunofluorescence analysis pipeline coupled with bio-informatic analyses to decipher the tumor DC landscape and its spatial organization within melanoma patients lesions, and its association with patients response to immune checkpoint inhibitors (ICI). For this aim, we analyze a cohort of 41 advanced melanoma patients treated with anti- PD1 alone or associated with anti-CTLA4. Distance and cell network analyses were performed to gain further insight into the spatial organization of tumor-associated DCs. A Digital Spatial Profiling analysis further characterized ecosystem of tumor-infiltrating DCs. ResultsPlasmacytoid DCs (pDCs) were the most abundant DC population, followed by conventional cDC1 and mature DCs, present in equal proportions. In contrast to CD8+ T cell frequency, and despite varying densities, all DC subsets were associated with a favorable response to ICI. Distance and cell network analyses demonstrated that tumor-infiltrating DCs were largely organized in dense areas with high homotypic connections, except for cDC1 that exhibited a more scattered distribution. We identified four patterns of ecosystems with distinct preferential interactions between DC subsets. Significantly, the proximity and interactions between CD8+ T cells and cDC1 were positively associated with patients response to ICI. ConclusionsOur study unravels the complex spatial organization of DC subsets and their interactions in melanoma patient lesions, shedding light on their pivotal role in shaping the response to ICI. Our discoveries regarding the spatial arrangement of cDC1, especially with CD8+ T cells, provide valuable clues for improving immunotherapeutic strategies in melanoma patients. What is already known on this topicDendritic cells (DCs) are promising targets for cancer immunotherapies owing to their central role in the initiation and the control of immune responses. Although conventional type 1 dendritic cells (cDC1) were proposed to contribute to immunotherapy response, their precise functions and interactions with other immune populations in human cancers are largely unknown. What this study addsThis study provides a precise characterization of the spatial distribution and organization of tumor- infiltrating DCs in a large cohort of advanced melanoma patients, and in correlation with response to immunotherapy. While DCs are organized in dense areas with high homotypic connections, cDC1 exhibit a more scattered distribution and form heterotypic aggregates with other DC subsets. More importantly, a close connection between cDC1 and CD8 T cell is uniquely correlated with the patients response to immunotherapy. How this study might affect research, practice or policyThis study improves our understanding of CD8-DC spatial organization within the tumor microenvironment and will have a broad spectrum of implications in the design of anti-tumor immune-activating compounds and the design of biomarkers of response to immunotherapy for melanoma patients.

cancer biology↗

bioRxiv2024

Transcranial Photobiomodulation on the Left Prefrontal Cortex Enhances Mandarin Chinese L1 and L2 Complex Sentence Processing Performances

This study investigated the causal effect of transcranial photobiomodulation (tPBM) over the left prefrontal cortex (LPFC) on syntactically complex Mandarin Chinese first language (L1) and second language (L2) sentence processing performances. Two (L1 and L2) groups of participants (thirty per group) were recruited to receive the double-blind, sham-controlled tPBM intervention, followed by the sentence processing, the verbal working memory (WM), and the visual WM tasks. Results revealed a consistent pattern for both groups: (a) tPBM enhanced sentence processing performance but not verbal WM and visual WM performance; (b) Participants with lower sentence processing performances under sham tPBM benefited more from active tPBM. Taken together, the current study substantiated that tPBM enhanced L1 and L2 sentence processing ability directly without verbal WM interference, and would serve as a promising and cost-effective noninvasive brain stimulation (NIBS) tool for future applications on upregulating the human language faculty. HighlightsO_LIThe first study that applies tPBM to (complex) sentence processing. C_LIO_LItPBM enhances sentence processing performances in both Mandarin L1 & L2 speakers. C_LIO_LItPBM directly enhances sentence processing without the interference of verbal WM. C_LIO_LIA causal role of LPFC for sentence processing through active tPBM. C_LIO_LIOpening up the promising application prospect for tPBM on sentence processing. C_LI

neuroscience↗

bioRxiv2024

Spatiotemporal recruitment of the ubiquitin-specific protease USP8 directs endosome maturation

The spatiotemporal transition of small GTPase Rab5 to Rab7 is crucial for early-to-late endosome maturation, yet the precise mechanism governing Rab5-to-Rab7 switching remains elusive. USP8, a ubiquitin-specific protease, plays a prominent role in the endosomal sorting of a wide range of transmembrane receptors and is a promising target in cancer therapy. Here, we identified that USP8 is recruited to Rab5-positive carriers by Rabex5, a guanine nucleotide exchange factor (GEF) for Rab5. The recruitment of USP8 dissociates Rabex5 from early endosomes (EEs) and meanwhile promotes the recruitment of the Rab7 GEF SAND-1/Mon1. In USP8-deficient cells, the level of active Rab5 is increased, while the Rab7 signal is decreased. As a result, enlarged EEs with abundant intraluminal vesicles accumulate and digestive lysosomes are rudimentary. Together, our results reveal an important and unexpected role of a deubiquitinating enzyme in endosome maturation.

cell biology↗

bioRxiv2024

Recognition and localization of maize leaves in RGB images based on Point-Line Net

Plant phenotype detection plays a crucial role in understanding and studying plant biology, agriculture, and ecology. It involves the quantification and analysis of various physical traits and characteristics of plants, such as plant height, leaf shape, angle, number, and growth trajectory. By accurately detecting and measuring these phenotypic traits, researchers can gain insights into plant growth, development, stress tolerance, and the influence of environmental factors. Among these phenotypic information, the number of leaves and growth trajectory of the plant are more accessible. Nonetheless, obtaining these information is labor-intensive and financially demanding. With the rapid development of computer vision technology and artificial intelligence, using maize field images to fully analyze plant-related information such as growth trajectory and number of leaves can greatly eliminate repetitive labor work and enhance the efficiency of plant breeding. However, the application of deep learning methods still faces challenges due to the serious occlusion problem and complex background of field plant images. In this study, we developed a deep learning method called Point-Line Net, which is based on the Mask R-CNN frame-work, to automatically recognize maize field images and determine the number and growth trajectory of leaves and roots. The experimental results demonstrate that the object detection accuracy (mAP) of our Point-Line Net can reach 81.5%. Moreover, to describe the position and growth of leaves and roots, we introduced a new lightweight "keypoint" detection branch that achieved 33.5 using our custom distance verification index. Overall, these findings provide valuable insights for future field plant phenotype detection, particularly for the datasets with dot and line annotations.

plant biology↗

bioRxiv2024

Genomic and transcriptomic characteristics of type VI secretion system in Klebsiella pneumoniae

The Type VI secretion system (T6SS) serves as a crucial molecular weapon in interbacterial competition and significantly influences cell-cell interactions. Various bacterial species utilize their T6SSs to execute a multitude of functions, dictated by their ecological niche. However, the characteristics of T6SS in clinical Klebsiella pneumoniae, a common opportunistic nosocomial pathogen, have not been fully elucidated. Here, we conducted a genomic analysis of 65 clinical K. pneumoniae isolates obtained from patients with varying infections. Genes encoding a T6SS cluster were present in all analyzed strains of K. pneumoniae. Strains of identical sequence type (ST) carried structurally and numerically identical T6SS. Our study also highlights the importance of selecting conserved regions in key T6SS genes for effective primer design in PCR identification. We then utilized the predominant ST11 K. pneumoniae HS11286 to investigate the effect of knocking out T6SS marker genes hcp or vgrG. Transcriptome analysis identified a total of 1,298 co-upregulated and 1,752 co-downregulated differentially expressed genes. Additionally, the absence of hcp or vgrG gene suppressed the expression of other T6SS-related genes within the locus I cluster. Pathway analysis showed that the {Delta}hcp mutant exhibited alterations in transport, establishment of localization, localization and cell processes. Furthermore, interbacterial competition experiments showed that hcp and vgrG are essential for competitive ability of ST11 K. pneumoniae HS11286. This study furthers our understanding of the genomic characteristics of T6SS in K. pneumoniae and suggested that the involvement of multiple genes in T6SS of strain HS11286. ImportanceGram-negative bacteria use T6SS to deliver effectors that interact with neighboring cells for niche advantage. K. pneumoniae is an opportunistic nosocomial pathogen that often carriers multiple T6SS loci, the function of which has not yet been elucidated. We performed a genomic analysis of 65 clinical K. pneumoniae strains isolated from various sources, confirming that all strains contained T6SS. We then used transcriptomics to further study changes in gene expression and effect upon interbacterial competition following knockout of key T6SS genes in ST11 K. pneumoniae HS11286. Our findings revealed the distribution and genomic characteristics of T6SS in clinical K. pneumoniae. This study also described the overall transcriptional changes in the predominant Chinese ST11 strain HS11286 upon deletion of crucial T6SS genes. Additionally, this work provides a reference for future research on the identification of T6SS in bacteria.

microbiology↗

bioRxiv2024

Tumor relapse-free survival prognosis related consistency between cancer tissue and adjacent normal tissue in drug repurposing for solid tumor via connectivity map

Traditional drug discovery encounters challenges, including high costs, time-intensive processes, and inherent risks. Drug repurposing emerges as a compelling alternative strategy to identify new indications for investigational or approved drugs, circumventing these obstacles. Among the various drug repurposing methods, the Disease-specific Signature-based Connectivity Map (Cmap) approach is widely utilized. However, the commonly employed method for constructing disease-specific signatures, known as Differentially Expressed Genes (DEG), faces issues related to inconsistencies between dysregulated genes and the prognosis of genes in tumor tissue, as well as discrepancies in prognosis genes between tumor and normal tissues. In this study, we propose a novel approach, Prognosis Consistency Scoring (PCS), aimed at addressing these inconsistencies. PCS measures the consistency of gene prognosis between tumor and normal tissues by combining the Recurrence-Free Survival (RFS) prognosis power of genes in both contexts. Disease-specific signatures are then constructed based on PCS, and drug repurposing is performed using the Cmap and Lincs Unified Environment (CLUE). Validation of predicted drugs is conducted using data from DrugBank and ClinicalTrials databases. Our findings reveal that the aforementioned inconsistencies are pervasive. Compared to signatures based on DEGs, PCS-based signatures exhibit superior performance, identifying more drugs with higher prediction accuracy, as confirmed by DrugBank annotations. Notably, a significant proportion of predicted drugs without corresponding indications were subsequently validated in the ClinicalTrials database. Additionally, PCS-based signatures demonstrate elevated disease specificity and association with Drug Related Gene (DRG).

bioinformatics↗

bioRxiv2024

Hunting for peptide binders of specific targets with data-centric generative language models

Bioactive peptides have become strong candidates for a variety of clinical therapies due to their diverse advantages, which promotes the development of deep generative models for peptide design. Considering that existing methods cannot effectively deal with the conformational flexibility of peptides and are difficult to capture accurate residue-to-residue interaction dependencies, we propose a unified weakly order-dependent autoregressive language modeling architecture (PepGenWOA) for bioactive peptide generative design with tolerating out-of-order input as inductive bias. The superiority of PepGenWOA is demonstrated by generating three classes of therapeutic peptides, including antimicrobial peptides, anticancer peptides, and peptide binders. For antimicrobial and anticancer peptide generation, PepGenWOA not only comprehensively outperforms state-of-the-art baseline models, but also exhibits a significant propensity to incorporate specific types of residues that are beneficial for antimicrobial or anticancer bioactivity. For characteristic-guided peptide binder generation, the pretrained PepGenWOA is fine-tuned with Mixture-of-Experts-style plugins with lifelong learning paradigm, thereby achieving the best trade-off between memory stability for world knowledge and learning plasticity for new downstream tasks. The subsequent structure-based virtual screening anchors the 7 most promising candidates from the mega-scale synthetic sequence space, reducing the number of candidates for in vitro experimental validation by 5 orders of magnitude. A target binding rate of 28.6% with binding specificity further confirms the effectiveness of the fine-tuning strategy. Overall, PepGenWOA is a unified architecture for peptide generative design that can be flexibly customized for different task requirements, thereby harnessing generative language models to reach the "dark space" of biological language.

bioinformatics↗

bioRxiv2023

Broadly neutralizing antibody induction by non-stabilized SARS-CoV-2 Spike mRNA vaccination in nonhuman primates

Immunization with mRNA or viral vectors encoding spike with diproline substitutions (S-2P) has provided protective immunity against severe COVID-19 disease. How immunization with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spike elicits neutralizing antibodies (nAbs) against difficult-to-neutralize variants of concern (VOCs) remains an area of great interest. Here, we compare immunization of macaques with mRNA vaccines expressing ancestral spike either including or lacking diproline substitutions, and show the diproline substitutions were not required for protection against SARS-CoV-2 challenge or induction of broadly neutralizing B cell lineages. One group of nAbs elicited by the ancestral spike lacking diproline substitutions targeted the outer face of the receptor binding domain (RBD), neutralized all tested SARS-CoV-2 VOCs including Omicron XBB.1.5, but lacked cross-Sarbecovirus neutralization. Structural analysis showed that the macaque broad SARS-CoV-2 VOC nAbs bound to the same epitope as a human broad SARS-CoV-2 VOC nAb, DH1193. Vaccine-induced antibodies that targeted the RBD inner face neutralized multiple Sarbecoviruses, protected mice from bat CoV RsSHC014 challenge, but lacked Omicron variant neutralization. Thus, ancestral SARS-CoV-2 spike lacking proline substitutions encoded by nucleoside-modified mRNA can induce B cell lineages binding to distinct RBD sites that either broadly neutralize animal and human Sarbecoviruses or recent Omicron VOCs. One Sentence SummaryNon-stabilized SARS-CoV-2 Spike mRNA vaccination activated B cells that target either conserved epitopes on SARS-CoV-2 Omicron variants of concern, or cross-neutralizing epitopes on pre-emergent Sarbecoviruses.

immunology↗

bioRxiv2023

Long-term abstinence reduces optimal energy required for transitions from the exogenous networks to the frontoparietal network in methamphetamine addicts

Methamphetamine (MA) use disorder is a chronic neurotoxic brain disease characterized by a high risk of relapse driven by intense cravings. However, the neurobiological signatures of cravings remain unclear, limiting the effectiveness of various treatment methods. Diffusion MRI (dMRI) scans from 62 MA users and 57 healthy controls (HC) were used in this study. The MA users were longitudinally followed up during their period of long-term abstinence (duration of long-term abstinence: 347.52{+/-}99.25 days). We systematically quantified the control ability of each brain region for craving-associated state transitions using network control theory from a causal perspective. Craving-associated structural alterations (CSA) were investigated through multivariate group comparisons and biological relevance analysis. The neural mechanisms underlying CSA were elucidated using transcriptomic and neurochemical analyses. We observed that long-term abstinence-induced structural alterations significantly influenced the state transition energy involved in the cognitive control response to external information, which correlated with changes in craving scores (r [~] 0.35, P <0.01). Our causal network analysis further supported the crucial role of the prefrontal cortex (PFC) in craving mechanisms. Notably, while the PFC is central to the craving, the CSAs were distributed widely across multiple brain regions (PFDR<0.05), with strong alterations in somatomotor regions (PFDR<0.05) and moderate alterations in high-level association networks (PFDR<0.05). Additionally, transcriptomic, chemical compounds, cell-type analyses, and molecular imaging collectively highlight the influence of neuro-immune communication on human craving modulation. Our results offer an integrative, multi-scale perspective on unraveling the neural underpinnings of craving and suggest that neuro-immune signaling may be a promising target for future human addiction therapeutics.

neuroscience↗

bioRxiv2023

iTraNet: A Web-Based Platform for integrated Trans-Omics Network Visualization and Analysis

ABSTRACTA major goal in biology is to comprehensively understand molecular interactions within living systems. Visualization and analysis of biological networks play crucial roles in understanding these biochemical processes. Biological networks include diverse types, from gene regulatory networks and protein-protein interactions (PPIs) to metabolic networks. Metabolic networks include substrates, products, and enzymes, which are regulated by allosteric mechanisms and gene expression. Given this complexity, there is a pressing need to investigate trans-omics networks that include these various regulations to understand living systems. However, analyzing various omics layers is laborious due to the diversity of databases and the intricate nature of network analysis. We developed iTraNet, a user-friendly interactive web application that visualizes and analyzes trans-omics networks involving four major types of networks: gene regulatory networks (including transcription factor, microRNA, and mRNA); PPIs; metabolic networks (including enzyme, mRNA, and metabolite); and metabolite exchange networks (including transporter, mRNA, and metabolite). Using iTraNet, we found that in wild-type mice, hub molecules within the network tended to respond to glucose administration, whereas in ob/ob mice, this tendency disappeared. With its ability to facilitate network visualization and analysis, we anticipate that iTraNet will help researchers gain insights into biological systems. iTraNet is available at (https://transomics.streamlit.app/). GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/569499v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@12bb1c1org.highwire.dtl.DTLVardef@1a326b7org.highwire.dtl.DTLVardef@42cfc9org.highwire.dtl.DTLVardef@57aee6_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2023

High-fidelity, high-resolution light-field reconstruction with physics-informed neural representation learning

Light-field microscopy (LFM) captures 3D biological dynamics by single 2D snapshots but suffers from limited resolution and artifacts during 2D-to-3D inversion. Here, we introduce light-field meta neural representation (LFMNR), a novel self-supervised paradigm that utilizes physics-informed light-field implicit neural representation (LFINR) and meta learning for high-quality 3D reconstruction in Fourier-LFM. By developing a physics-based hybrid-rendering model, LFINR achieves artifact-free light-field reconstruction with enhanced spatial resolution (>1.4-fold improvement). Additionally, the integration of meta-learning and progressive sampling strategies mitigates INRs intrinsic limitations in low reconstruction speed caused by scene-specific optimization, enabling a [~]100-fold acceleration in the representation of consecutive volumes and facilitating the visualization of sustained 3D dynamics. These advancements enable LFMNR to deliver superior imaging with high spatiotemporal resolution and low phototoxicity, as demonstrated by capturing instantaneous voltage signals in C. elegans at 100 volumes per second and recording 6000 time points of organelle dynamics over 25 hours.

cell biology↗