Biology subjects

Jiang, T.

Publications and source records attributed to Jiang, T..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

A type II secreted subtilase from commensal rhizobacteria disarms the immune elicitor peptide flg22

Plant roots grow in association with a community of microorganisms collectively known as the rhizosphere microbiome. Immune activation in response to elicitors like the flagellin-derived epitope flg22 restricts bacteria on plant roots but also inhibits plant growth. Some commensal root-associated bacteria are capable of suppressing the plant immune response to elicitors. In this study, we investigated the ability of 165 root-associated bacteria to suppress flg22-induced immune activation and growth restriction. We demonstrate that a type II secreted subtilase, which we term Immunosuppressive Subtilase A (IssA), from Dyella japonica strain MF79 cleaves the immune eliciting peptide flg22 and contributes to immune suppression. IssA homologs are found in other plant-associated commensals, with particularly high conservation in the order Xanthomonadales. This represents a novel mechanism by which commensal microbes modulate flg22-induced immunity in the rhizosphere microbiome.

microbiology↗

bioRxiv2024

Targeting oncogenic K-Ras mutants with a small-molecule degrader through Nedd4-1

K-Ras mutations represent a most prevalent oncogenic alteration in human cancers. Despite of tremendous efforts, it remains a big challenge to develop inhibitors that can target the oncogenic K-Ras mutants, especially mutants without specific active or charged side chains such as K-RasG12V. Here, taking advantage of our previous finding that Nedd4-1 is a bona fide E3 ubiquitin ligase for wild-type Ras proteins, we developed a compound XMU-MP-9 that can promote ubiquitination and degradation of various K-Ras mutants including K-RasG12V, and significantly inhibit proliferation and tumor development of K-Ras mutant harboring cells. Mechanistically, XMU-MP-9 acts as a bifunctional compound to bind the C2 domain of Nedd4-1 and an allosteric site of K-Ras to enhance Nedd4-1 and K-Ras interaction, and to induce a conformational change of Nedd4-1/K-Ras complex to allow Nedd4-1 targeting K128 of K-Ras for ubiquitination. Hence, our study presents a robust strategy to develop small-molecule degrader of K-Ras mutants, and also sheds light on the development of small-molecule degraders for H-Ras and N-Ras mutants.

cancer biology↗

bioRxiv2024

Deep convolutional neural network with face identity recognition experience exhibits brain-like neural representations of personality traits

Faces contain both identity and personality trait information. Previous studies have found that convolutional neural networks trained for face identity recognition spontaneously generate personality trait information. However, the successful classification of different personality traits does not necessarily mean that convolutional neural networks adopt brain-like representation mechanisms to achieve the same computational goals. Our study found that convolutional neural network with visual experience in face identity recognition (VGG-face) exhibited brain-like neural representations of personality traits, including coupling effects and confusion effects, while convolutional neural networks with the same network architecture but lacked visual experience for face identity recognition (VGG-16 and VGG-untrained) did not exhibit brain-like effects. In addition, compared to the VGG-16 and the VGG-untrained, the VGG-face exhibited higher similarity in neural representations with the human brain across all individual personality traits. In summary, these findings revealed the necessity of visual experience in face identity recognition for developing face personality traits judgment.

neuroscience↗

bioRxiv2024

Reference-informed prediction of alternative splicing and splicing-altering mutations from sequences

Alternative splicing plays a crucial role in protein diversity and gene expression regulation in higher eukaryotes and mutations causing dysregulated splicing underlie a range of genetic diseases. Computational prediction of alternative splicing from genomic sequences not only provides insight into gene-regulatory mechanisms but also helps identify disease-causing mutations and drug targets. However, the current methods for the quantitative prediction of splice site usage still have limited accuracy. Here, we present DeltaSplice, a deep neural network model optimized to learn the impact of mutations on quantitative changes in alternative splicing from the comparative analysis of homologous genes. The model architecture enables DeltaSplice to perform "reference-informed prediction" by incorporating the known splice site usage of a reference gene sequence to improve its prediction on splicing-altering mutations. We benchmarked DeltaSplice and several other state-of-the-art methods on various prediction tasks, including evolutionary sequence divergence on lineage-specific splicing and splicing-altering mutations in human populations and neurodevelopmental disorders, and demonstrated that DeltaSplice outperformed consistently. DeltaSplice predicted [~]15% of splicing quantitative trait loci (sQTLs) in the human brain as causal splicing-altering variants. It also predicted splicing-altering de novo mutations outside the splice sites in a subset of patients affected by autism and other neurodevelopmental disorders, including 19 genes with recurrent splicing-altering mutations. Among the new candidate disease risk genes, MFN1 is involved in mitochondria fusion, which is frequently disrupted in autism patients. Our work expanded the capacity of in silico splicing models with potential applications in genetic diagnosis and the development of splicing-based precision medicine.

bioinformatics↗

bioRxiv2024

Cancer Stemness Online: A resource for investigating cancer stemness and associations with immune response

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features, which are potential culprit in immunotherapy resistance. Although the state-of-art predictive computational methods have facilitated predicting the cancer stemness, currently there is no efficient resource that can meet various requirements of usage. Here, we presented the Cancer Stemness Online, an integrated resource for efficiently scoring cancer stemness potential at bulk and single-cell level. The resource integrates 8 robust predictive algorithms as well as 27 signature gene sets associated with cancer stemness for predicting the stemness scores. Downstream analyses were performed from five different aspects, including identifying the signature genes of cancer stemness, exploring the association with cancer hallmarks, cellular states, immune response and communication with immune cells, investigating the contributions for patient survival and the robustness analysis of cancer stemness among different methods. Moreover, the pre-calculated cancer stemness atlas for more than 40 cancer types can be accessed by users. Both the tables and diverse visualization for the analytical results are available for download. Together, Cancer Stemness Online is a powerful resource for scoring cancer stemness and going deeper and wider in the downstream functional interpretation, including immune response as well as cancer hallmark. Cancer Stemness Online is freely accessible at http://bio-bigdata.hrbmu.edu.cn/CancerStemnessOnline.

bioinformatics↗

bioRxiv2024

DeepPrep: An accelerated, scalable, and robust pipeline for neuroimaging preprocessing empowered by deep learning

Neuroimaging has entered the era of big data. However, the advancement of preprocessing pipelines falls behind the rapid expansion of data volume, causing significant computational challenges. Here, we present DeepPrep, a pipeline empowered by deep learning and workflow manager. Evaluated on over 55,000 scans, DeepPrep demonstrates a 11-fold acceleration, exceptional scalability, and robustness compared to the current state-of-the-art pipeline, providing a promising solution to meet the scalability requirements of neuroimaging.

neuroscience↗

bioRxiv2024

Stimulation Effects Mapping for Standardizing Coil Placement in Transcranial Magnetic Stimulation

BackgroundThe position and orientation of transcranial magnetic stimulation (TMS) coil, which we collectively refer to as coil placement, significantly affect both the assessment and modulation of cortical excitability. TMS electric field (E-field) simulation can be used to identify optimal coil placement. However, the present E-field simulation required a laborious segmentation and meshing procedure to determine optimal coil placement. ObjectiveWe intended to create a framework that would enable us to offer optimal coil placement without requiring the segmentation and meshing procedure. MethodsWe constructed the stimulation effects map (SEM) framework using the CASIA dataset for optimal coil placement. We used leave-one-subject-out cross-validation to evaluate the consistency of the optimal coil placement and the target regions determined by SEM for the 74 target ROIs in MRI data from the CASIA, HCP15 and HCP100 datasets. Additionally, we contrasted the E-norms determined by optimal coil placements using SEM and auxiliary dipole method (ADM) based on the DP and CASIA II datasets. ResultsWe provided optimal coil placement in head-anatomy-based (HAC) polar coordinates and MNI coordinates for the target region. The results also demonstrated the consistency of the SEM framework for the 74 target ROIs. The normal E-field determined by SEM was more significant than the value received by ADM. ConclusionWe created the SEM framework using the CASIA database to determine optimal coil placement without segmentation or meshing. We provided optimal coil placement in HAC and MNI coordinates for the target region. The validation of several target ROIs from various datasets demonstrated the consistency of the SEM approach. By streamlining the process of finding optimal coil placement, we intended to make TMS assessment and therapy more convenient.

bioengineering↗

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

FFCM-MRF: An accurate and generalizable cerebrovascular segmentation pipeline for humans and rhesus monkeys based on TOF-MRA

PurposeCerebrovascular segmentation and quantification of vascular morphological features on humans and rhesus monkeys are essential for prevention, diagnosis, and treatment of brain diseases. However, current automated whole-brain vessel segmentation methods are often not generalizable to independent datasets, limiting their usefulness in real-world environments with their heterogeneity in participants, scanners, and species. Materials and MethodsIn this study, we proposed an automated, accurate and generalizable segmentation method for magnetic resonance angiography images called FFCM-MRF. This method integrates fast fuzzy c-means clustering and Markov random field optimization using blood vessel shape priors and spatial constraints. We used a total of 123 human and 44 macaque MRA images scanned at 1.5 T, 3 T, and 7 T MRI from 9 datasets to develop and validate the method. ResultsThe average Dice score coefficients for multiple independent datasets were 69.16-89.63%, with the improvements in FFCM-MRF ranged from 0.16-16.14% compared with state-of-the-art machine learning methods. Quantitative analysis showed that FFCM-MRF can accurately segment major arteries in the Circle of Willis at the base of the brain and smaller distal pial arteries while effectively suppressing noise. Test-retest analysis showed that the model yielded high vascular volume and diameter reliability. ConclusionsOur results demonstrate that the proposed method is highly accurate and reliable and largely independent of variations in field strength, scanner platforms, acquisition parameters, and species. The macaque MRA data and user-friendly open-source toolbox are freely available at OpenNeuro and GitHub to facilitate studies of imaging biomarkers for cerebrovascular and neurodegenerative diseases.

neuroscience↗

bioRxiv2023

Deep Learning-based Optical Aberration Estimation Enables Offline Digital Adaptive Optics and Super-resolution Imaging

Optical aberrations degrade the performance of fluorescence microscopy. Conventional adaptive optics (AO) leverages specific devices, such as the Shack-Hartmann wavefront sensor and deformable mirror, to measure and correct optical aberrations. However, conventional AO requires either additional hardware or a more complicated imaging procedure, resulting in higher cost or a lower acquisition speed. In this study, we proposed a novel space-frequency encoding network (SFE-Net) that can directly estimate the aberrated point spread functions (PSFs) from biological images, enabling fast optical aberration estimation with high accuracy without engaging extra optics and image acquisition. We showed that with the estimated PSFs, the optical aberration can be computationally removed by deconvolution algorithm. Furthermore, to fully exploit the benefits of SFE-Net, we incorporated the estimated PSF with neural network architecture design to devise an aberration-aware deep-learning super-resolution (DLSR) model, dubbed SFT-DFCAN. We demonstrated that the combination of SFE-Net and SFT-DFCAN enables instant digital AO and optical aberration-aware super-resolution reconstruction for live-cell imaging.

bioengineering↗

bioRxiv2023

Dual Ethanolamine Head Groups in Ionizable Lipids Facilitate Phospholipid-free Stable Nanoparticle Formulation for Augmented and Safer mRNA Delivery

The accelerated advent of mRNA-based therapeutics and vaccines, highlighted by the battle against SARS-CoV-2, underscores the urgency to refine lipid nanoparticles (LNPs) for efficient mRNA delivery. In this work, we introduce a novel series of ionizable lipids characterized by double ethanolamine head groups, significantly amplifying mRNA binding affinity. A succinct three-component formulation is subsequently delineated, obviating the conventional dependency on phospholipids inherent in traditional four-component LNPs. Intriguingly, this formulation enables particle formation under neutral pH conditions, a notable departure from the acidic milieu traditionally required, attributable to the enhanced nonionic interactions predominating in mRNA encapsulation. The resultant particles exhibit exceptional stability, superior mRNA encapsulation efficiency, and maintain robust delivery efficacy. When deployed as a vaccine platform, the formulation elicited pronounced humoral and T-cell immune responses, concurrently exhibiting a favorable toxicity profile with a reduced induction of pro-inflammatory cytokines such as IL-6. Our exploration suggests that by fine-tuning the non-electrostatic interactions between the ionizable lipid and mRNA, the dynamics of particle formation can be considerably divergent from the prevailing paradigms of mRNA-LNP formation, hinting at a broader horizon for lipid optimization within the realm of mRNA delivery systems.

bioengineering↗

bioRxiv2023

A telomere-to-telomere genome assembly of Zhonghuang 13, a widely-grown soybean variety from the original center of Glycine max

Soybean (Glycine max) stands as a globally significant agricultural crop, and the comprehensive assembly of its genome is of paramount importance for unraveling its biological characteristics and evolutionary history. Nevertheless, previous soybean genome assemblies have harbored gaps and incompleteness, which have constrained in-depth investigations into soybean. Here, we present the first Telomere-to-Telomere (T2T) assembly of the Chinese soybean cultivar "Zhonghuang 13" (ZH13) genome, termed ZH13-T2T, utilizing PacBio Hifi and ONT ultralong reads. We employed a multi-assembler approach, integrating Hifiasm, NextDenovo, and Canu, to minimize biases and enhance assembly accuracy. The assembly spans 1,015,024,879 bp, effectively resolving all 393 gaps that previously plagued the reference genome. Our annotation efforts identified 50,564 high-confidence protein-coding genes, 707 of which are novel. ZH13-T2T revealed longer chromosomes, 421 not-aligned regions (NARs), 112 structure variations (SVs), and a substantial expansion of repetitive element compared to earlier assemblies. Specifically, we identified 25.67 Mb of tandem repeats, an enrichment of 5S and 48S rDNAs, and characterized their genotypic diversity. In summary, we deliver the first complete Chinese soybean cultivar T2T genome. The comprehensive annotation, along with precise centromere and telomere characterization, as well as insights into structural variations, further enhance our understanding of soybean genetics and evolution.

plant biology↗

bioRxiv2023

Shape-changing electrode array for minimally invasive large-scale intracranial brain activity mapping

Large-scale brain activity mapping is important for understanding the neural basis of behaviour. Electrocorticograms (ECoGs) have high spatiotemporal resolution, bandwidth, and signal quality. However, the invasiveness and surgical risks of electrode array implantation limit its application scope. We developed an ultrathin, flexible shape-changing electrode array (SCEA) for large-scale ECoG mapping with minimal invasiveness. SCEAs were inserted into cortical surfaces in compressed states through small openings in the skull or dura and fully expanded to cover large cortical areas. MRI and histological studies on rats proved the minimal invasiveness of the implantation process and the high chronic biocompatibility of the SCEAs. High-quality micro-ECoG activities mapped with SCEAs from rodent brains during seizures and canine brains during the emergence period revealed the spatiotemporal organization of different brain states with resolution and bandwidth that cannot be achieved using existing noninvasive techniques. The biocompatibility and ability to map large-scale physiological and pathological cortical activities with high spatiotemporal resolution, bandwidth, and signal quality in a minimally invasive manner offer SCEAs as a superior tool for applications ranging from fundamental brain research to brain-machine interfaces.

neuroscience↗

bioRxiv2023

Lysine vitcylation is a novel vitamin C-derived protein modification that enhances STAT1-mediated immune response

Vitamin C (vitC) is a vital nutrient for health and also used as a therapeutic agent in diseases such as cancer. However, the mechanisms underlying vitCs effects remain elusive. Here we report that vitC directly modifies lysine without enzymes to form vitcyl-lysine, termed "vitcylation", in a dose-, pH-, and sequence-dependent manner across diverse proteins in cells. We further discover that vitC vitcylates K298 site of STAT1, which impairs its interaction with the phosphatase PTPN2, preventing STAT1 Y701 dephosphorylation and leading to increased STAT1-mediated IFN pathway activation in tumor cells. As a result, these cells have increased MHC/HLA class-I expression and activate immune cells in co-cultures. Tumors collected from vitC-treated tumor-bearing mice have enhanced vitcylation, STAT1 phosphorylation and antigen presentation. The identification of vitcylation as a novel PTM and the characterization of its effect in tumor cells opens a new avenue for understanding vitC in cellular processes, disease mechanisms, and therapeutics.

biochemistry↗

bioRxiv2023

Diffusion model of delipidation in biological sample clearing

Biological sample clearing techniques are a potent tool for three-dimensional biological imaging, among which delipidation is an essential step in achieving high-quality biological sample transparency. Detergents and organic solvents can both be used for lipids removal. The former has been extensively investigated in biological sample clearing, while the delipidation process based on organic solvents remains to be further elucidated. Recently, organic solvents also served as a delipidation reagent in aqueous-based clearing methods and exhibited very fast clearing speed. To explain the high efficiency of organic solvents, we described the delipidation process of both detergents and organic solvents with a simple diffusion model, we proposed a possible mechanism of the delipidation process of water-miscible polar organic solvents based on the clearing results of brain samples. Both our results and model revealed that polar or non-polar organic solvents with a certain molecular structure could achieve a much faster clearing speed than detergents which could be a guide for establishing a rapid clearing protocol for biological samples with large volumes.

neuroscience↗

bioRxiv2023

Projectome-defined subtypes and modular intra-hypothalamic subnetworks of peptidergic neurons

The hypothalamus plays a vital role in coordinating essential neuroendocrine, autonomic, and somatomotor responses for survival and reproduction. While previous studies have explored population-level projections of hypothalamic neurons, the specific innervation patterns of individual hypothalamic axons remain unclear. To understand the organization of hypothalamic axon projections, we conducted a comprehensive reconstruction of single-cell projectomes from 7,180 mouse hypothalamic neurons expressing specific neuropeptides. Our analysis identified 31 distinct subtypes based on projectome-defined characteristics, with many exhibiting long-range axon collateral projections to multiple brain regions. Notably, these subtypes selectively targeted specific subdomains within downstream areas, either unilaterally or bilaterally. Furthermore, we observed that individual peptidergic neuronal types encompassed multiple projectome-defined subtypes, explaining their diverse functional roles. Additionally, by examining intra-hypothalamic axon projections, we uncovered six modular subnetworks characterized by enriched intramodular connections and distinct preferences for downstream targets. This modular organization of the intra-hypothalamic network likely contributes to the coordinated organization of hypothalamic outputs. In summary, our comprehensive projectome analysis reveals the organizational principles governing hypothalamic axon projections, providing a framework for understanding the neural circuit mechanisms underlying the diverse and coordinated functions of the hypothalamus.

neuroscience↗

bioRxiv2023

Interleukin-16/STAT6 recruits CBP/p300 to upregulate TIMP-3 and promote atherosclerotic plaque stability

BackgroundAtherosclerotic plaque rupture increases the risk of ischemic heart disease and stroke and commonly causes sudden death. High levels of circulating or intraplaque interleukin 16 (IL-16) are clinically associated with a reduced incidence of cardiovascular events. Here, we investigated the effects of IL-16 on plaque phenotypic modification and identified the molecules involved in smooth muscle cells (SMCs). MethodsWe deleted IL-16 in ApoE-/- mice to generate IL16-/-ApoE-/- mice, and the double mutant was used for plaque phenotype analysis after a 24-week high-fat diet. RNA sequencing was performed to identify the changes in cellular processes and molecule expression in response to IL-16 defects. Affinity purification-mass spectrometry was used to identify the STAT6 binding protein. Bone marrow transplantation was used to investigate the effects of hematopoietic IL-16 deficiency or reconstitution on plaque stability. ResultsIL-16 deficiency reduced collagen deposition and increased the necrotic core area in the plaques of the brachiocephalic artery and aortic root lesions. Intraplaque TIMP-3 levels were found to be decreased in association with an increase in the proteolytic activity of MMPsinIL16-/-ApoE-/- mice. Next, we demonstrated that IL-16 activates the CD4/JAK2/STAT6 pathway and that STAT6 directly binds the TIMP-3 promoter in SMCs. Furthermore, IL-16 treatment increased the interaction of cAMP-response element binding protein (CBP)/p300 with STAT6, which promoted STAT6 acetylation and increased histone H3 acetylation in the TIMP-3 promoter. Inhibition of CBP/p300 resulted in decreased acetylation of STAT6 and TIMP-3 promoter histone H3 and TIMP-3 expression, suggesting a requirement for CBP/p300 as a coactivator. Finally, we found that hematopoietic-derived IL-16 from ApoE-/- mice or overexpression of TIMP-3 successfully attenuated plaque instability in IL16-/-ApoE-/- mice. ConclusionsIL-6 upregulates TIMP-3 expression and remodels the intraplaque extracellular matrix toward a stable phenotype, suggesting IL-16 as a potential target for intervening in atherosclerosis at later stages.

pathology↗

bioRxiv2023

Self-supervised denoising for structured illumination microscopy enables long-term super-resolution live-cell imaging

Detection noise significantly degrades the quality of structured illumination microscopy (SIM) images, especially under low-light conditions. Although supervised learning based denoising methods have shown prominent advances in eliminating the noise-induced artifacts, the requirement of a large amount of high-quality training data severely limits their applications. Here we developed a pixel-realignment-based self-supervised denoising framework for SIM (PRS-SIM) that trains an SIM image denoiser with only noisy data and substantially removes the reconstruction artifacts. We demonstrated that PRS-SIM generates artifact-free images with 10-fold less fluorescence than ordinary imaging conditions while achieving comparable super-resolution capability to the ground truth (GT). Moreover, the proposed method is compatible with multiple SIM modalities such as total internal reflective fluorescence SIM (TIRF-SIM), three-dimensional SIM (3D-SIM), lattice light-sheet SIM (LLS-SIM), and non-linear SIM (NL-SIM). With PRS-SIM, we achieved long-term super-resolution live-cell imaging of various bioprocesses, revealing the clustered distribution of clathrin coated pits and detailed interaction dynamics of multiple organelles and the cytoskeleton.

cell biology↗