Biology subjects

Cao, D.

Publications and source records attributed to Cao, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Identification of Novel Mutations Causing Clofazimine Resistance in Mycobacterium intracellulare

Clofazimine (CFZ) is a promising repurposed drug for treating Mycobacterium avium-intracellulare complex pulmonary disease (MAC-PD), but its resistance mechanisms in M. intracellulare remain poorly understood. In this study, we generated 36 CFZ-resistant M. intracellulare mutants in vitro and identified various mutations in the marR gene (WP_009952290.1) in 61% of resistant mutants through whole-genome sequencing. Mutations were identified in additional genes encoding flavin-dependent oxidoreductase (ssuD, C67A), membrane lipoprotein (lppI, C207 deletion), glucose-methanol-choline oxidoreductase (G157 deletion), MASE1 domain-containing protein (C62G), and PPE family protein (222C deletion). Gene complementation experiments demonstrated that introducing the wild-type marR in CFZ-resistant strains (L72 and L74) with marR mutations reduced CFZ minimum inhibitory concentrations (MICs) from 1 g/mL to the susceptible baseline (0.25 g/mL), confirming its critical role in CFZ resistance. Notably, the M. intracellulare MarR lacks homology to M. tuberculosis MarR family protein Rv0678 (MmpR) whose mutations are involved in CFZ and bedaquiline (BDQ) resistance and is flanked by non-efflux pump genes (dhmA and doxX), and unlike M. tuberculosis, its mutation does not cause bedaquiline cross-resistance, indicating a different MarR and distinct regulatory mechanism for CFZ resistance in M. intracellulare. This work highlights marR as a key determinant of CFZ resistance in M. intracellulare and underscores the need for further mechanistic studies with implications for clinical diagnostics and therapeutic strategies.

microbiology↗

bioRxiv2025

China Autism Brain Imaging Consortium: Charting Brain Growth in Chinese Children with Autism

Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental condition characterized by atypical brain growth. While advances in neuroimaging and openly sharing large-sample datasets such as the Autism Brain Imaging Data Exchange (ABIDE) have improved understanding of ASD, most studies focus on adolescents and adults, with early brain development-critical for diagnosis and intervention-remaining underexplored. Existing research predominantly involves Western samples, offering limited insight and generalizability into non-Caucasian populations. We introduce the China Autism Brain Imaging Consortium (CABIC) (https://php.bdnilab.com/resources/), a grassroots effort by researchers across the country to aggregate previously collected multi-site structural MRI datasets and phenotypic information from 1,451 autistic children and 1,119 typically developing children, covering an age range from early childhood to school age (1.0 - 12.92 years). Here, we present this resource and depict brain growth charts to push forward a more comprehensive understanding of the brain development in Chinese autism children. We constructed brain growth charts that reveal a developmental shift in autistic children, transitioning from early overgrowth to delayed maturation. Regional analyses identified distinct atypical trajectories across specific brain regions. Individual deviation scores quantified inter-subject variability, characterizing the heterogeneity of brain development in ASD. Comparative analyses between CABIC and ABIDE highlighted differences potentially attributable to ethnicity and culture, advancing our understanding of cross-population neurodevelopmental diversity. CABIC MRI datasets will be shared publicly to foster investigation of the potential neural mechanisms underlying ASD in non-Western populations and support efforts toward precision medicine for autistic individuals across diverse backgrounds.

neuroscience↗

bioRxiv2025

Feedback and feedforward control are differentially delayed in cerebellar ataxia

1Damage to the cerebellum can cause ataxia, a condition associated with impaired movement coordination. Typically, coordinated movement relies on a combination of anticipatory mechanisms (specifically, feedforward control) and corrective mechanisms (embodied by feedback control). Here, we show that in 3D reaching in VR, ataxia preserves the visuomotor feedforward and feedback control structure compared to the control group. However, the ataxia group exhibits a small increase in feedback delay (~ 20 ms) and a substantial increase in feedforward delay (~ 70 ms) together with a reduced feedback gain (~25 % lower). Our results suggest that the feedforward and feedback pathways remain largely intact in ataxia, but that time delay deficits and temoral discoordination amongst these control pathways may contribute to the disorder. We also find that providing a preview--analogous to driving on a clear night and seeing the road ahead vs. driving in the fog-- improves tracking performance in the ataxia group, although the control group was significantly better able to exploit this preview information. Overall, our results indicate that the feedforward control and preview utilization are relatively well-preserved in individuals with cerebellar ataxia, and that preview could potentially be leveraged to enhance the feedforward performance of those with ataxia.

neuroscience↗

bioRxiv2025

Clinical and Taxonomic Characterization of a Novel Urinary Tract Pathogen Providencia lanzhouensis

BackgroundThe genus Providencia includes species of ecological and clinical significance, with some acting as opportunistic pathogens in hospital-acquired infections such as urinary tract infection (UTI). However, overlapping phenotypic traits and genetic similarities pose challenges for accurate species characterization. This study exemplifies this challenge by identifying a novel Providencia isolate through genomic analysis. ResultsIn this study, strain PAZ2 was isolated from the urine sample of a hospitalized patient in Lanzhou, Gansu Province, China. Initial mass spectrometry analysis identified the strain as Providencia alcalifaciens. It exhibits a resistance profile against antibiotics including ampicillin, tetracycline, tigecycline, polymyxin B, colistin, trimethoprim-sulfamethoxazole, and ciprofloxacin. However, whole-genome sequence analysis indicated that this strain is a novel species with an average nucleotide identity (ANI) values ranging from 79.92% to 94.73% and digital DNA-DNA hybridization (dDDH) values between 21.2% and 57.6% when compared with all known Providencia species. Furthermore, strain PAZ2 exhibited unique biochemical properties that differentiated it from all previously described species within the genus. ConclusionsGenomic and biochemical evidence supports PAZ2 as a novel Providencia species, which we named Providencia lanzhouensis sp. nov. This finding enhances the taxonomy of Providencia and underscores its clinical relevance, notably in UTIs and other nosocomial infections. Accurate identification is crucial for guiding effective treatment and preventing misdiagnosis. Further studies should investigate its pathogenicity, antimicrobial resistance, and epidemiology to inform infection control measures.

microbiology↗

bioRxiv2025

TOC1 phosphorylation disproportionally enhances chromatin binding at rhythmic gene promoters

Protein phosphorylation is a key regulatory mechanism in circadian systems. TIMING OF CAB EXPRESSION 1(TOC1) is a core transcriptional repressor in the plant circadian system that is phosphorylated near its N-terminus. Phenotype testing of single and multi-phosphosite mutants shows incomplete rescue of the short period toc1 mutant. We establish that TOC1 phosphorylation (particularly at S175) is necessary for optimal interaction with FAR-RED ELONGATED HYPOCOTYL3 (FHY3) and PHYTOCHROME INTERACTING FACTOR 5 (PIF5) at the CIRCADIAN CLOCK-ASSOCIATED 1 (CCA1) promoter to downregulate CCA1 expression. At the same time, expression of the closely related LATE ELONGATED HYPOCOTYL (LHY) also requires TOC1, but is independent of the TOC1 phosphorylation state, suggesting different TOC1-dependent mechanisms in the repression of these two genes. We additionally show how phosphorylation-dependent interactions of TOC1 at specific clock gene promoters selectively regulate these circadian system components more acutely than non-rhythmic genes. Our genome-wide analysis shows that the phosphostate of TOC1 is important for optimal chromatin presence and robust rhythmic gene expression.

plant biology↗

bioRxiv2025

1,3- and 1,4-linked Polysaccharides Uptake in Intestinal Cells Relies on Clathrin/Dynamin 1/Rab5-dependent Endocytosis

Natural polysaccharides are considered to be a promising feedstock for manufacturing sustainable materials. However, polysaccharides are believed by most biologists that they could not be absorbed by intestinal mucosa to enter circulation system owing to their high hydrophilicity and large molecule size. Herein, {beta}-1,3-linked glucan (GFPBW1) and -1,4-linked glucan (WGE) is used as the model polysaccharide and the transport experiments show that different linked and charged polysaccharides can permeate Caco-2 cell monolayers. The in vivo experiments demonstrate that GFPBW1 and WGE are detectable in rodent plasma and liver after oral administration the isotope (99mTc, 3H) and fluorescein labeled polysaccharides. Further study show that polysaccharide uptake requires clathrin heavy chain (CLTC) and its associated factors Rab5 and dynamin1 in intestinal cells using gene-knockdown strategies and inhibitors. Strikingly, polysaccharide absorption is attenuated in both CLTC intestine deficient mice and Rab5, dynamin1 conventional-knockout mice. Importantly, membrane receptors bone morphogenetic protein receptor type IA (BMPRIA), Dectin-1 and epidermal growth factor receptor (EGFR) are also critical for specific structural polysaccharide internalization. These findings provide novel insight to understand polysaccharide absorption mechanism and lay foundation for oral polysaccharide- based new drugs development.

pharmacology and toxicology↗

bioRxiv2024

Mouse Forebrain Region-specific Molecular Characteristics and Cholinergic Neurons Subtyping: An Integrated Analysis Based on Spatial Multi-omics

The forebrain regions displays distinct yet under-characterized gene expression patterns. This study analyzed region-specific feature genes in forebrain regions and Isocortex sub-regions at both transcriptomic and proteomic levels. The key finding is the observation of low correlation but high functional similarity between mRNA and protein expression, which offers insights into the connection between gene expression forms in neuronal pathways and the neuronal activity state. Cholinergic neurons (CNs), play a vital role for the forebrains sensory and motor regulation. With Spatial-transcriptome and immunofluorescence joint analysis (STIF), which overcomes the limited resolution of the 10X Visium system, CNs- and CN-subtypes specific feature genes in the striatum and basal forebrain were identified, which providing crucial insights into the heterogeneity and functional diversity of these neuronal populations. The spatial distribution and expression pattern of the feature genes in this study were validated with either external datasets or rolling circle amplification-FISH, coincident results were revealed.

bioinformatics↗

bioRxiv2024

Tensions in tillage: Reduction in tillage intensity associates with lower wheat growth and nutritional grain quality despite enhanced soil biological indicators

Dryland ecosystems are particularly susceptible to the adverse effects of intensive agriculture, with intensive tillage exerting a major impact on soil health and its biotic components. The implementation of less disturbing soil management practices can be essential for preserving the soil environment and maintaining the diverse communities of microorganisms, micro- and mesofauna, which are essential contributors to soil fertility. In this study, we assessed soil chemical properties, soil biodiversity and functionality, and wheat crop growth across a tillage gradient encompassing no-tillage (NT), minimum tillage (MT), and standard tillage (ST). Results showed that NT resulted in increased soil macronutrient levels compared to MT and ST. In general, reduced tillage increased the abundance of soil biota, with significantly higher levels of bacterial and fungal marker genes observed in MT and NT compared to ST. Nematode abundance increased by 25% in MT and 50% in NT, compared to ST and predatory acari were significantly more abundant in NT, while numbers of total acari were higher in both NT and ST compared to MT. Community structure analysis revealed that tillage strongly influenced bacterial, fungal and acari community composition, reflecting a gradient of soil disturbance intensity. Corresponding to the increased abundance of soil biota, reduced tillage increased microbial activity and soil functionality along the disturbance gradient. This was evident in the potential activity of carbon, nitrogen and phosphorus cycling enzymes, as well as the microbial capacity for carbon utilisation. In addition, evidence of the formation of biocrust as a possible source of carbon input was found. Furthermore, we observed important wheat pathogens to decrease and fungal antagonists to increase in NT compared to ST. Despite enhanced soil biological indicators under reduced tillage, wheat growth, nitrogen uptake and grain B vitamin contents were higher in ST compared to NT. In addition, we observed a shift in technological grain properties across tillage practices. The higher root:shoot ratio (an indicator of nitrogen deficiency) and median root diameter (hormone-driven lateral expansion) in NT suggest that soil compaction could be a potential cause of reduced wheat performance. These results suggest that despite improved soil biological indicators, other factors such as a low rates of N mineralization potential and prevalence of soil compaction may be limiting wheat performance in NT systems. HighlightsO_LIEnhanced microbial activity and functionality under reduced tillage C_LIO_LITillage intensity shaped community structure of microbes, nematodes and acari C_LIO_LISoil biocrust development under NT may increase soil organic carbon C_LIO_LIRoot traits revealed soil compaction and nutrient limitation in NT systems C_LIO_LIReduced tillage impaired wheat quality and changed technological grain properties C_LI

ecology↗

bioRxiv2024

Sensitivity of Cerebellar Reaching Ataxia to Kinematic and Dynamic Demands

Individuals with cerebellar ataxia face significant challenges in controlling reaching, especially when multi-joint movements are involved. This study investigated the effects of kinematic and dynamic demands on reaching using a home-based virtual reality task. Participants with and without cerebellar ataxia reached to target locations designed to elicit a range of coordination strategies between shoulder and elbow joint movements. Compared with control subjects, cerebellar subjects presented greater initial reaching direction errors, larger hand trajectory curvatures, and more variability. Kinematic simulations indicated that early hand movement errors were sensitive to the required onset times and rates of joint movements and were most impaired when opposite direction joint movements were required (e.g., elbow extension with shoulder flexion). Dynamic analysis revealed that cerebellar participants movements were more impaired in reaching directions where interaction torques would normally assist the desired elbow and shoulder movements. These reach directions were also those that required joint movements in opposite directions. Overall, our data suggest that reaching deficits in cerebellar ataxia result from 1) the early-phase motion planning deficits that are exacerbated by stringent timing coordination requirements and 2) the inability to compensate for interaction torques, particularly when they assist the intended movement.

neuroscience↗

bioRxiv2024

Multi-modal profiling identifies CD4+CXCR5+PD-1- Tfh cells as prognostic and predictive biomarkers for response to R-CHOP therapy in human DLBCL

Despite the improvements in clinical outcomes for patients with Diffuse Large B-Cell Lymphoma (DLBCL), a significant proportion of those patients still face challenges with refractory/relapsed (R/R) disease after receiving first-line R-CHOP treatment. Characterizing the heterogeneity of the tumor microenvironment (TME) in diffuse large B cell lymphoma (DLBCL) is crucial for understanding relapsed/refractory disease. However, the complex and diverse nature of the TME has impeded progress. Here, using single-cell RNA sequencing(scRNA-seq), we explored the DLBCL landscape at single-cell resolution, profiling 77,344 cells from both primary and relapsed DLBCL patients. We further investigated the shared and distinct molecular and cellular features of tumor microenvironment in both primary and relapsed DLBCL tumors by integrating next-generation DNA sequencing data and multiple scRNA-seq datasets from total 72,351 cells. Our results demonstrated that there was a significant decrease of CD4+CXCR5+PD-1- Tfh cells, along with excessive activation of the TNF-NF{kappa}B signaling pathways in malignant B cells in R/R disease. Furthermore, by using multiplex IHC, we confirmed that CD4+CXCR5+PD-1- Tfh cells are prognostic and predictive biomarkers for response to R-CHOP treatment. As a proof of concept, we successfully generated mutilplexed images of CD4+CXCR5+PD-1- Tfh cells from a single DAPI staining in human DLBCL tissues through using generative artificial intelligence. Our study offers critical insights into the heterogeneity and molecular features of DLBCL, shedding light on the crucial role of CD4+CXCR5+PD-1- Tfh cells in the recurrent process. HighlightsO_LIShared and distinct molecular and cellular features of tumor microenvironment in both primary and relapsed DLBCL tumors; C_LIO_LIThe characteristic of relapsed DLBCL TME is a dysfunctional immune microenvironment with a significant decrease of CD4+CXCR5+PD-1- Tfh cells. C_LIO_LICD4+CXCR5+PD-1- Tfh cells are prognostic and predictive biomarkers for response to R-CHOP treatment C_LIO_LIDetermination of CD4+CXCR5+PD-1- Tfh cells in human DLBCL tissues through using generative artificial intelligence. C_LI

immunology↗

bioRxiv2024

Identification and Targeting of Regulators of SARS-CoV-2-Host Interactions in the Airway Epithelium.

Although the impact of SARS-CoV-2 in the lung has been extensively studied, the molecular regulators and targets of the host-cell programs hijacked by the virus in distinct human airway epithelial cell populations remain poorly understood. This is in part ascribed to the use of nonprimary cell systems, overreliance on single-cell gene expression profiling that does not ultimately reflect protein activity, and bias toward the downstream effects rather than their mechanistic determinants. Here we address these issues by network-based analysis of single cell transcriptomic profiles of pathophysiologically relevant human adult basal, ciliated and secretory cells to identify master regulator (MR) protein modules controlling their SARS-CoV-2-mediated reprogramming. This uncovered chromatin remodeling, endosomal sorting, ubiquitin pathways, as well as proviral factors identified by CRISPR analyses as components of the host response collectively or selectively activated in these cells. Large-scale perturbation assays, using a clinically relevant drug library, identified 11 drugs able to invert the entire MR signature activated by SARS-CoV-2 in these cell types. Leveraging MR analysis and perturbational profiles of human primary cells represents a novel mechanism-based approach and resource that can be directly generalized to interrogate signatures of other airway conditions for drug prioritization.

cell biology↗

bioRxiv2024

Pipeline for Assessing Tumor Immune Status Using Superplex Immunostaining and Spatial Immune Interaction Analysis

The characteristics of the tumor microenvironment (TME) are closely linked to tumor progression and treatment response. The TME comprises various cell types, their spatial distribution, cell-cell interactions, and their organization into cellular niches or neighborhoods. To capture this complexity, several spatial profiling technologies have been developed. However, challenges such as low throughput, high costs, and complicated data analysis have limited their widespread use in immune research. In this study, we introduce the Cyclic-multiplex TSA (CmTSA) staining platform, a high-throughput superplex staining technology based on tyramide signal amplification (TSA) immunostaining combined with an efficient fluorophore recycling method. The CmTSA platform allows for the labeling of 30-60 antigens across multiple parallel formalin-fixed paraffin-embedded (FFPE) slides. Furthermore, the automated CmTSA workflow requires only standard histological equipment and conventional immunohistochemistry (IHC) primary antibodies (Abs), significantly reducing costs. While the superplex images produced contain extensive multidimensional information, extracting the spatial features of the TME from raw pixel data can be challenging. To address this, we present a computer vision-based analysis pipeline, which begins with deep learning-based algorithms to segment individual cells and identify cell types based on defined annotation rules. It then evaluates the spatial distribution tendencies of each cell type, the interaction intensity between paired cells, and the multicellular functional niches. This comprehensive approach enables researchers to visualize and quantify the types, states, and levels of immune activities within the TME effectively, advancing tumor immunology research and precision immune medicine.

cancer biology↗

bioRxiv2024

mosGraphFlow: a novel integrative graph AI model mining disease targets from multi-omic data

Multi-omic data can better characterize complex cellular signaling pathways from multiple views compared to individual omic data. However, integrative multi-omic data analysis to rank key disease biomarkers and infer core signaling pathways remains an open problem. In this study, our novel contributions are that we developed a novel graph AI model, mosGraphFlow, for analyzing multi-omic signaling graphs (mosGraphs), 2) analyzed multi-omic mosGraph datasets of AD, and 3) identified, visualized and evaluated a set of AD associated signaling biomarkers and network. The comparison results show that the proposed model not only achieves the best classification accuracy but also identifies important AD disease biomarkers and signaling interactions. Moreover, the signaling sources are highlighted at specific omic levels to facilitate the understanding of the pathogenesis of AD. The proposed model can also be applied and expanded for other studies using multi-omic data. Model code is accessible via GitHub: https://github.com/FuhaiLiAiLab/mosGraphFlow

bioinformatics↗

bioRxiv2024

mosGraphGPT: a foundation model for multi-omic signaling graphs using generative AI

Generative pretrained models represent a significant advancement in natural language processing and computer vision, which can generate coherent and contextually relevant content based on the pre-training on large general datasets and fine-tune for specific tasks. Building foundation models using large scale omic data is promising to decode and understand the complex signaling language patterns within cells. Different from existing foundation models of omic data, we build a foundation model, mosGraphGPT, for multi-omic signaling (mos) graphs, in which the multi-omic data was integrated and interpreted using a multi-level signaling graph. The model was pretrained using multi-omic data of cancers in The Cancer Genome Atlas (TCGA), and fine-turned for multi-omic data of Alzheimers Disease (AD). The experimental evaluation results showed that the model can not only improve the disease classification accuracy, but also is interpretable by uncovering disease targets and signaling interactions. And the model code are uploaded via GitHub with link: https://github.com/mosGraph/mosGraphGPT

bioinformatics↗

bioRxiv2024

Nuclear FAK aggravates CD8+ T cell exhaustion via the SP1-IL-6 axis in colorectal cancer

Nuclear abnormalities such as nuclear deformation are hallmarks of many diseases, including cancer. Accumulating evidence suggests that the dense and mechanically stiff tumor microenvironment promotes nuclear deformation in cancer cells. However, little is known about how nuclear deformation in neoplastic cells regulates immune exhaustion in the tumor microenvironment. Here, we found that lamin A/C-mediated nuclear stiffening in neoplastic cells promotes the nuclear translocation of phosphorylated focal adhesion kinase (pFAK), which is strongly correlated with the heterogeneity and exhaustion of CD8+ T cells within the spatial context of the tumor microenvironment in human colorectal cancer. Mechanistically, we revealed that increased nuclear tension within tumor cells promotes pFAK nuclear translocation, where nuclear pFAK was found to regulate SP1/IL-6-mediated T-cell exhaustion and the transcription of proinflammatory cytokines/chemokines. Pharmacological inhibition or disruption of pFAK nuclear translocation enhanced antitumor immune responses and synergistically potentiated PD-1 and TIM-3 immunotherapy by increasing CD8+ T-cell cytotoxicity and restoring exhaustion in preclinical models of colorectal cancer. These findings highlight the pivotal role of nuclear tension-mediated pFAK translocation into the tumor cell nucleus in regulating CD8+ T-cell exhaustion, suggesting that pFAK is a promising target for advancing cancer immunotherapy.

immunology↗

bioRxiv2024

The cGAS-STING Pathway Is Essential in Acute Ischemia-Induced Neutropoiesis and Neutrophil Priming in the Bone Marrow

Acute myocardial ischemia triggers a rapid mobilization of neutrophils from the bone marrow to peripheral blood, facilitating their infiltration into the infarcted myocardium. These cells are critical for inducing inflammation and contributing to myocardial repair. While neutrophils in infarcted tissue are better characterized, our understanding of whether and how ischemia regulates neutrophil production, differentiation, and functionality in the bone marrow remains limited. This study investigates these processes and the influence of the cGAS-STING pathway in the context of myocardial infarction. The cGAS-STING pathway detects aberrant DNA within cells, activates STING, and initiates downstream signaling cascades involving NFKB and IRF3. We analyzed neutrophils from bone marrow, peripheral blood, and infarct tissues using MI models generated from wild-type, Cgas-/-, and Sting-/- mice. These models are essential for studying neutropoiesis (neutrophil production and differentiation), as it involves multiple cell types. RNA sequencing analysis revealed that ischemia not only increased neutrophil production but also promoted cytokine signaling, phagocytosis, chemotaxis, and degranulation in the bone marrow before their release into the peripheral blood. Inhibition of the cGAS-STING pathway decreased neutrophil production after MI and down-regulated the same pathways activated by ischemia. Neutrophils lacking cGAS or STING were less mature, exhibited reduced activation, and decreased degranulation. Deletion of cGAS and STING decreased the expression of a large group of IFN-stimulated genes and IFIT1+ neutrophils from peripheral blood and the infarct tissue, suggesting that cGAS-STING plays an essential role in neutrophils with the IFN-stimulated gene signature. Importantly, transcriptomic analysis of Cgas-/- and Sting-/- neutrophils from bone marrow and MI tissues showed downregulation of similar pathways, indicating that the functionality developed in the bone marrow was maintained despite infarct-induced stimulation. These findings highlight the importance of neutropoiesis in dictating neutrophil function in target tissues, underscoring the critical role of the cGAS-STING pathway in neutrophil-mediated myocardial repair post-ischemia.

immunology↗

bioRxiv2024

Design nonrepetitive and diverse activity single-guide RNA by deep learning

Multiplex and precise control of the gene expression based on CRISPR/Cas9 is important to metabolic regulation in synthetic biology. However, employing single guide RNAs (sgRNAs) that possess repetitive DNA sequences and exhibit uniform activity could detrimentally affect the editing process, undermining both its stability and regulatory potential. In this study, we developed a deep generative model based on a decoder-only Transformer architecture (sgRNAGen) for the de novo generation of a series of nonrepetitive and diverse sgRNAs with activity. To assess the quality of sgRNAs generated by sgRNAGen, we evaluated their activity by targeting essential genes, with the results indicating that 98% of the generated sgRNAs were active in Bacillus subtilis. The generated sgRNAs were further validated for applications in single-gene editing, large fragment knockouts, and multiplex editing. Notably, the efficiency of knocking out long fragments up to 169.5 kb reached 100%, and targeting multiple sites allowed for the creation of strains with various combinations of mutations in a single editing. Furthermore, we developed a CRISPRi system utilizing the designed sgRNAs to regulate gene expression with desired strength and high precision. SgRNAGen offers a method for devising nonrepetitive and diverse activity sgRNAs, enhancing metabolic control and advancing applications within synthetic biology. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/596019v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@f68faaorg.highwire.dtl.DTLVardef@151f5e2org.highwire.dtl.DTLVardef@1e5cb28org.highwire.dtl.DTLVardef@17cd3f8_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

mosGraphGen: a novel tool to generate multi-omic signaling graphs to facilitate integrative and interpretable graph AI model development

Multi-omics data, i.e., genomics, epigenomics, transcriptomics, proteomics, characterize cellular complex signaling systems from multi-level and multi-view and provide a holistic view of complex cellular signaling pathways. However, it remains challenging to integrate and interpret multi-omics data for mining key disease targets and signaling pathways. Graph AI models have been widely used to analyze graph-structure datasets, and are ideal for integrative multi-omics data analysis because they can naturally integrate and represent multi-omics data as a biologically meaningful multi-level signaling graph and interpret multi-omics data via graph node and edge ranking analysis. However, it is non-trivial for graph-AI model developers to pre-analyze multi-omics data and convert the data into biologically meaningful graphs, which can be directly fed into graph-AI models. To resolve this challenge, we developed mosGraphGen (multi-omics signaling graph generator), generating Multi-omics Signaling graphs (mos-graph) of individual samples by mapping multi-omics data onto a biologically meaningful multi-level background signaling network with data normalization by aggregating measurements and aligning to the reference genome. With mosGraphGen, AI model developers can directly apply and evaluate their models using these mos-graphs. In the results, mosGraphGen was used and illustrated using two widely used multi-omics datasets of TCGA and Alzheimers disease (AD) samples. The code of mosGraphGen is open-source and publicly available via GitHub: https://github.com/FuhaiLiAiLab/mosGraphGen

systems biology↗