Biology subjects

Ji, X.

Publications and source records attributed to Ji, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Characterization of N-glycosylation and its Functional Role in SIDT1-Mediated RNA Uptake

The mammalian SID-1 transmembrane family members, SIDT1 and SIDT2, are multi-pass transmembrane proteins that mediate the cellular uptake and intracellular trafficking of nucleic acids, playing important roles in the immune response and tumorigenesis. Previous work has suggested that human SIDT1 and SIDT2 are N-glycosylated, but the precise site-specific N-glycosylation information and its functional contribution remain unclear. In this study, we employ high-resolution liquid chromatography tandem mass spectrometry to comprehensively map the N-glycosites and quantify the N-glycosylation profiles of SIDT1 and SIDT2. Further molecular mechanistic probing elucidates the essential role of N-linked glycans in regulating cell surface expression, RNA binding, protein stability, and RNA uptake of SIDT1. Our results provide crucial information about the potential functional impact of N-glycosylation in the regulation of SIDT1-mediated RNA uptake and provide insights into the molecular mechanisms of this promising nucleic acid delivery system, with potential implications for therapeutic applications.

biochemistry↗

bioRxiv2023

UNI-RNA: UNIVERSAL PRE-TRAINED MODELS REVOLUTIONIZE RNA RESEARCH

AO_SCPLOWBSTRACTC_SCPLOWRNA molecules play a crucial role as intermediaries in diverse biological processes. Attaining a profound understanding of their function can substantially enhance our comprehension of lifes activities and facilitate drug development for numerous diseases. The advent of high-throughput sequencing technologies makes vast amounts of RNA sequence data accessible, which contains invaluable information and knowledge. However, deriving insights for further application from such an immense volume of data poses a significant challenge. Fortunately, recent advancements in pre-trained models have surfaced as a revolutionary solution for addressing such challenges owing to their exceptional ability to automatically mine and extract hidden knowledge from massive datasets. Inspired by the past successes, we developed a novel context-aware deep learning model named Uni-RNA that performs pre-training on the largest dataset of RNA sequences at the unprecedented scale to date. During this process, our model autonomously unraveled the obscured evolutionary and structural information embedded within the RNA sequences. As a result, through fine-tuning, our model achieved the state-of-the-art (SOTA) performances in a spectrum of downstream tasks, including both structural and functional predictions. Overall, Uni-RNA established a new research paradigm empowered by the large pre-trained model in the field of RNA, enabling the community to unlock the power of AI at a whole new level to significantly expedite the pace of research and foster groundbreaking discoveries.

bioinformatics↗

bioRxiv2023

Defining the single base importance of human mRNAs and lncRNAs

As the fundamental unit of a gene and its transcripts, nucleotides have enormous impacts on molecular function and evolution, and thus on phenotypes and diseases. Given that different nucleotides on one gene often exhibit diverse levels of effects, it is quite crucial to comprehensively and quantitatively measure the importance of each base on a gene transcript, however, tools are still not available. Here we proposed Base Importance Calculator (BIC), an algorithm to calculate the importance score of single bases based on sequence information of human mRNAs and long noncoding RNAs (lncRNAs). We then confirmed its power by applying BIC to three different tasks. Firstly, we revealed that BIC can effectively evaluate the pathogenicity of both genes and single bases by analyzing the BIC scores and the pathogenicity of single nucleotide variations (SNVs). Moreover, the BIC score in the Cancer Genome Atlas (TCGA) somatic mutations is able to predict the prognosis of some cancers. Finally, we show that BIC can also precisely predict the transmissibility of SARS-CoV-2. The above results indicate that BIC is a useful tool for evaluating the single base important of human mRNAs and lncRNAs. Key PointsO_LIBIC could measure the single base importance of human mRNAs and lncRNAs. C_LIO_LIBIC could be applied to many aspects including measuring the pathogenicity of SNVs and enhancing the ability of predicting cancer survival. C_LIO_LIBIC could predict the transmissibility of SARS-CoV-2 C_LI

bioinformatics↗

bioRxiv2023

Electrocatalytic on-site oxygenation for transplanted cell-based-therapies

Implantable cell therapies and tissue transplants require sufficient oxygen supply to function and are limited by a delay or lack of vascularization from the transplant host1, 2. Exogenous oxygen production can support cells and tissues, such as pancreatic islets and engineered therapeutic cells. Previous oxygenation strategies have targeted gas circulation or decomposition of solid peroxides. These strategies however require bulky implants, transcutaneous supply lines, and are limited in their total oxygen production or regulation3, 4. Readily integrated and controlled production of oxygen has eluded cell therapy devices. Here, we show an electrocatalytic approach that enables bioelectronic control of oxygen generation in complex cellular environments to sustain engineered cell viability and therapy production under hypoxic stress and at high cell densities. Nanostructured sputtered iridium oxide serves as an ideal catalyst for oxygen evolution reaction (OER) at neutral pH. It enables a lower OER onset and shows selective oxygen production without evolution of toxic side products over a 300 mV window of operation. This electrocatalytic on site oxygenator (ecO2) can sustain high cell loadings (>60k cells/mm3) in hypoxic conditions in vitro and in vivo. Our results demonstrate that exogenous oxygen production devices can be readily integrated into bioelectronic platforms and enable high cell loadings in smaller device footprints with broad applicability.

bioengineering↗

bioRxiv2023

Expanding the toolbox of probiotic Escherichia coli Nissle 1917 for synthetic biology

Escherichia coli Nissle 1917 (EcN) is a probiotic microbe that has the potential to be developed as a promising chassis for synthetic biology applications. However, the molecular tools and techniques for utilizing EcN have not been fully explored. To address this opportunity, we systematically expanded the EcN-based toolbox, enabling EcN as a powerful platform for more applications. First, two EcN cryptic plasmids and other compatible plasmids were genetically engineered to enrich the manipulable plasmid toolbox for multiple gene coexpression. Next, we developed two EcN-based enabling technologies, including the conjugation strategy for DNA transfer, and quantification of protein expression capability. Finally, we expanded the EcN-based applications by developing EcN native integrase-mediated genetic engineering capabilities and establishing an in vitro cell-free protein synthesis (CFPS) system. Overall, this study expanded the toolbox for manipulating EcN as a commonly used probiotic chassis, providing several simplified, dependable, and predictable strategies for researchers working in synthetic biology fields. For Table of Contents Use Only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/543671v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1f8e91forg.highwire.dtl.DTLVardef@90fb70org.highwire.dtl.DTLVardef@6badbforg.highwire.dtl.DTLVardef@15be840_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2023

Gut microbiota-derived gamma-aminobutyric acid from metformin treatment reduces hepatic ischemia/reperfusion injury through inhibiting ferroptosis.

Hepatic ischemia/reperfusion injury (HIRI) is a common and inevitable factor leading to poor prognosis in various liver diseases, making the outcomes of current treatments in clinic unsatisfactory. Metformin has been demonstrated to be beneficial to alleviate HIRI in recent studies, however, the underpinning mechanism remains unclear. In this study, we found metformin mitigates HIRI-induced ferroptosis through reshaped gut microbiota in mice, which was confirmed by the results of fecal microbiota transplantation (FMT) treatment but showed the elimination of the beneficial effects when gut bacteria were depleted using antibiotics. Detailedly, through 16S rRNA and metagenomic sequencing, we identified that the metformin-reshaped microbiota was characterized by the increase of gamma-aminobutyric acid (GABA) producing bacteria. This increase was further confirmed by the elevation of GABA synthesis key enzymes, glutamic acid decarboxylase (GAD) and putrescine aminotransferase (PAT), in gut microbes of metformin-treated mice and healthy volunteers. Furthermore, the benefit of GABA against HIRI-induced ferroptosis was demonstrated in GABA-treated mice. Collectively, our data indicate that metformin can mitigate HIRI-induced ferroptosis by reshaped gut microbiota, with GABA identified as a key metabolite.

microbiology↗

bioRxiv2023

Disease Tolerance Acquired Through Repeated Plasmodium Infection Involves Epigenetic Reprogramming of Innate Immune Cells

The regulation of inflammation is a critical aspect of disease tolerance and naturally acquired immunity to malaria. Here, we demonstrate using RNA sequencing and epigenetic landscape profiling by cytometry by Time-Of-Flight (EpiTOF), that the regulation of inflammatory pathways during asymptomatic parasitemia occurs downstream of pathogen sensing--at the epigenetic level. The abundance of certain epigenetic markers (methylation of H3K27 and dimethylation of arginine residues) and decreased prevalence of histone variant H3.3 correlated with suppressed cytokine responses among monocytes of Ugandan children. Such an epigenetic signature was observed across diverse immune cell populations and not only characterized active asymptomatic parasitemia but also predicted long-term future disease tolerance when observed in uninfected children. This broad methylated signature likely develops gradually and was associated with age and recent parasite exposure. Our data support a model whereby exposure to Plasmodium falciparum induces epigenetic changes that regulate excessive inflammation and contribute to naturally acquired immunity to malaria.

immunology↗

bioRxiv2023

Osteoblast-intrinsic defect in glucose metabolism impairs bone formation in type II diabetic mice

Skeletal fragility is associated with type 2 diabetes mellitus (T2D), but the underlying mechanism is not well understood. Here, in a mouse model for youth-onset T2D, we show that both trabecular and cortical bone mass are reduced due to diminished osteoblast activity. Stable isotope tracing in vivo with 13C-glucose demonstrates that both glycolysis and glucose fueling of the TCA cycle are impaired in diabetic bones. Similarly, Seahorse assays show suppression of both glycolysis and oxidative phosphorylation by diabetes in bone marrow mesenchymal cells as a whole, whereas single-cell RNA sequencing reveals distinct modes of metabolic dysregulation among the subpopulations. Metformin not only promotes glycolysis and osteoblast differentiation in vitro, but also improves bone mass in diabetic mice. Finally, targeted overexpression of Hif1a or Pfkfb3 in osteoblasts of T2D mice averts bone loss. The study identifies osteoblast-intrinsic defects in glucose metabolism as an underlying cause of diabetic osteopenia, which may be targeted therapeutically.

physiology↗

bioRxiv2023

Construction of Model Animals to Explore Intestinal Microbiome for Detection of Breast Cancer

Breast cancer ranks first among female cancers and has become a major public health problem in the current society. More studies indicated that these cancers are related to the change in the gut microbiome that can cause metabolic and immune system disorders in the body. However, there are few studies on the changes in gut microbiome caused by the onset of breast cancer, and the relationship between breast cancer and gut microbiome needs to be further clarified. In this study, we inoculated 4T1 breast cancer cells to induce breast cancer tumorigenesis in mice and collected their feces samples at different stages during this process. These intestinal florae were analyzed using 16S rRNA gene amplicon sequencing, and the results showed that at the phylum level, the ratio of Firmicutes/Bacteroidetes decreased with the development of the tumor; at the family level, the intestinal microbiome had obvious variations of Lachnospiraceae, Bacteroidaceae, Erysipelotrichaceae, etc. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and COG annotation demonstrated that decreased abundance of cancer related signaling pathways. This study elucidated the relationship between breast cancer and intestinal microbiome, and the research results can be used as an important biomarker for the diagnosis of breast cancer.

cancer biology↗

bioRxiv2023

Epigenetically silenced DACT3 promotes tumor growth via affecting Wnt/beta-catenin signaling and supports chidamide plus azacitidine therapy in acute myeloid leukemia

BackgroundDACT gene is a potential Wnt antagonist and tumor suppressor gene. However, the expression of DACT gene in acute myeloid leukemia (AML) and its role are still unknown. MethodsIn this study, we first multidimensionally analyzed the expression of DACT gene in AML through RNA seq, qRT-PCR and Western blotting analysis as well as TCGA database analysis. Then DACT3 was identified as playing a critical role in AML, and its clinical significance was further explored. The molecular mechanism of DACT3 down-regulation in AML from aspects of DNA methylation and histone acetylation were inquired. Finally, the biological functions of DACT3 in AML were investigated by cell models in vitro and animal experiments in vivo. ResultsCompared with DACT1 and DACT2, DACT3 was the most differentially expressed DACT family member in AML, suggesting that DACT3 plays the major role. The mRNA and protein expression levels of DACT3 were significantly decreased and positively correlated in AML. Moreover, low expression of DACT3 is associated with no remission disease status and poor prognosis in AML patients. In addition, down-regulation of DACT3 in AML was not completely dependent on promoter methylation, but also affected by histone deacetylation. We found that loss of DACT3 in AML is related to activation of Wnt signaling pathway. Furthermore, DACT3 inhibits the growth of AML cells in vitro and in severe immunodeficiency (SCID) mice. Importantly, DACT3 improved the sensitivity of adriamycin in treating AML cells. Further research showed that co-treatment of chidamide and azacytidine up-regulates DACT3 expression and promotes cell apoptosis via inhibiting Wnt/{beta}-catenin signaling in AML, suggesting a promising therapeutic prospects in FLT3-mutant AML. ConclusionThis is the first study revealing the epigenetic regulatory molecular mechanism of the down regulated expression of DACT3 in AML. Our data also shows that DACT3 is a candidate gene for therapeutic target and targeting DACT3 has the potential to validate the combination therapy of DNMT inhibitors and HDAC inhibitors.

molecular biology↗

bioRxiv2023

ASTK: a software for comprehensive analysis of alternative splicing

Alternative splicing (AS) is a fundamental mechanism that regulates gene expression. Splicing dynamics is involved in both physiological and pathological processes. In this paper, we introduce ASTK, a software package covering upstream and downstream analysis of AS. Initially, ASTK offers a module to perform enrichment analysis at both the gene- and exon-level to incorporate various impacts by different spliced events on a single gene. We further cluster AS genes and alternative exons into three groups based on spliced exon sizes (micro-, mid-, and macro-), which are preferentially associated with distinct biological pathways. A major challenge in the field has been decoding the regulatory codes of splicing. ASTK adeptly extracts both sequence features and epigenetic marks associated with AS events. Through the application of machine learning algorithms, we identified pivotal features influencing the inclusion levels of most AS types. Notably, the splice site strength is a primary determinant for the inclusion levels in alternative 3/5 splice sites (A3/A5). For the alternative first exon (AF) and skipping exon (SE) classes, a combination of sequence and epigenetic features collaboratively dictate exon inclusion/exclusion. Our findings underscore ASTKs capability to enhance the functional understanding of AS events and shed light on the intricacies of splicing regulation.

bioinformatics↗

bioRxiv2022

Sequencing-free Tissue-wide Spatial Profiling of Post-transcriptional Regulations

The importance of genetic or epi-genetic heterogeneity has been increasingly recognized, but it has been challenging to profile intracellular post-transcriptional targets with sufficient throughput and resolution at across large-scale tissue samples. This study describes a technique, Spectrum-FISH, for high-throughput, sequencing-free, and tissue-wide spatial profiling of various post-transcriptional targets in acute tissue sections with subcellular resolution. The platform uses a biochip with an array of vertically aligned nanoprobes to effectively extract intracellular molecules for downstream analysis in the coordinates of the large-scale of cells within a tissue slice. As a proof-of-concept, the Spectrum-FISH is used to profile the spatial dynamics of 24 miRNAs and 9 m6A-modified messenger RNAs (m6A-mRNA) in acute olfactory bulb (OB) slices of millimeter scale. The results showed potentially multiomics spatial heterogeneity for the examined post-transcriptional regulations in rodent OB, especially in the outer plexiform layer and granule layer, where highly correlated miRNAs and m6A-mRNAs groups were identified, indicating a potential cooperative involvement of different post-transcriptional regulations at these OB regions.

genomics↗

bioRxiv2022

Modeling cell size control using differential scaling of cell-cycle regulators with cell size

Accurate timing of division and size homeostasis is crucial for cells. A potential mechanism for cells to decide the timing of division is the differential scaling of regulatory protein copy numbers with cell size. However, it remains unclear whether such a mechanism can lead to robust growth and division, and how the scaling behaviors of regulatory proteins influence the cell size distribution. Here we study a mathematical model combining gene expression and cell growth, in which the cell-cycle activators scale superlinearly with cell size while the inhibitors scale sublinearly. The cell divides once the ratio of their concentrations reaches a threshold value. We find that the cell can robustly grow and divide within a finite range of the threshold value with the cell size proportional to the ploidy. In a stochastic version of the model, the cell size at division is uncorrelated with that at birth. Also, the more differential the cell-size scaling of the cell-cycle regulators is, the narrower the cell-size distribution is. Intriguingly, our model with multiple regulators rationalizes the observation that after the deletion of a single regulator, the coefficient of variation of cell size remains roughly the same though the average cell size changes significantly. Our work reveals that the differential scaling of cell-cycle regulators provides a robust mechanism of cell size control. Author summaryHow cells determine the timing of cell division is a fundamental question of cell biology. It has been found that the concentration of cell-cycle activators tends to increase with cell size, while the concentration of inhibitors tends to decrease. Therefore, an attractive hypothesis is that the ratio of activators to inhibitors may trigger cell division. To investigate this hypothesis quantitatively, we study a model including gene expression and cell growth simultaneously. The cell divides once the activator-to-inhibitor ratio reaches a threshold. Combining theories and simulations, we analyze the conditions of robust cell cycle and the cell size distribution. Our model successfully rationalizes several experimental observations, including the relation between cell size and ploidy, the sizer behavior of cell size control, and the change of the mean and breadth of cell size distribution after regulator deletion.

cell biology↗

bioRxiv2022

ExposomeX: Integrative Exposomic Platform Expediates Discovery of "Exposure-Biology-Disease" Nexus

Exposome has become the hotspot of next-generation health studies. To date, there is no available effective platform to standardize the analysis of exposomic data. In this study, we aim to propose one new framework of exposomic analysis and build up one novel integrated platform "ExposomeX" to expediate the discovery of the "Exposure-Biology-Disease" nexus. We have developed 13 standardized modules to accomplish six major functions including statistical learning (E-STAT), exposome database search (E-DB), mass spectrometry data processing (E-MS), meta-analysis (E-META), biological link via pathway integration and protein-protein interaction (E-BIO) and data visualization (E-VIZ). Using ExposomeX, we can effectively analyze the multiple-dimensional exposomics data and investigate the "Exposure-Biology-Disease" nexus by exploring mediation and interaction effects, understanding statistical and biological mechanisms, strengthening prediction performance, and automatically conducting meta-analysis based on well-established literature databases. The performance of ExposomeX has been well validated by re-analyzing two previous multi-omics studies. Additionally, ExposomeX can efficiently help discover new associations, as well as relevant in-depth biological pathways via protein-protein interaction and gene ontology network analysis. In sum, we have proposed a novel framework for standardized exposomic analysis, which can be accessed using both R and online interactive platform (http://www.exposomex.cn/).

bioinformatics↗

bioRxiv2022

Junctophilin-2 promotes cardiomyocyte survival by blocking MURF1-mediated Junctin ubiquitination and proteasome-dependent degradation

AimsJunctophilin-2 is required for the development, maturation and integrity of the t-tubule system and the gating stability of RyR2 in cardiomyocytes. This study investigated whether and how junctophilin-2 maintained junctin, a scaffold protein stabilizing RyR2, to prevent cardiomyocyte death under stress. MethodsCardiomyocytes were exposed to conditions of stress including palmitate, doxorubicin, or hypoxia/re-oxygenation. Adenoviral vectors were employed to manipulate expression of junctophilin-2 and junctin in cardiomyocytes. Molecular/cellular/biochemical analyses were conducted. ResultsDifferent conditions of stress decreased junctophilin-2 expression through aberrant autophagy and concomitantly induced a reduction of junctin protein in cardiomyocytes. Over-expression of junctophilin-2 preserved the protein levels of junctin and attenuated cytosolic Ca2+ and apoptosis in cardiomyocytes under stress. Knockdown of junctophilin-2 reproduced the detrimental phenotypes of stress in cardiomyocytes. Notably, over-expression of junctin prevented cardiomyocyte death under stress whereas knockdown of junctin offset the protective effects conferred by junctophilin-2 over-expression. Mechanistically, junctophilin-2 blocked MURF1-junctin interaction thereby preventing junctin ubiquitination and proteasome-dependent degradation. Mass spectrometry analysis identified multiple ubiquitination sites on the junctin protein and the non-ubiquitinated junctin mutant (K8A/K102A/K107A/K140A) was resistant to degradation. ConclusionsThis study uncovers an unrecognized role of junctophilin-2 in preventing junctin ubiquitination and degradation in maintaining cytosolic Ca2+ homeostasis. Both junctophilin-2 and junctin represent two new survival factors of cardiomyocytes and thus, may be new therapeutic targets for cardiac protection.

molecular biology↗

bioRxiv2022

Crystal structure of monkeypox H1 phosphatase, an Antiviral Drug Target

The current monkeypox outbreak has caused over 64,000 global cases, but the effective treatments are very limited. The dual specific phosphatase (H1) from monkeypox antagonizes the immune response and is crucial for viral replication, making it an attractive antiviral target. Here we determined a 1.8-[A] crystal structure of H1, which forms a domain swapped dimer resembling a butterfly. Each active site, which consists of a Cys-Arg-Asp triad, captures a phosphate ion. The observed conformation mimics the final step of catalysis prior to product release. The crystal structure provides a strong foundation for the discovery of new antivirals against this emerging worldwide pathogen.

microbiology↗

bioRxiv2022

Engineering Escherichia coli to utilize erythritol as sole carbon source

Erythritol, one of the natural sugar alcohols, is widely used as a sugar substitute sweetener in food industries. Human themselves are not able to catabolize erythritol and their gut microbes lack related catabolic pathways either to metabolize erythritol. Here, we engineer Escherichia coli to utilize erythritol as sole carbon source aiming for defined applications. First, we isolate the erythritol metabolic gene cluster and experimentally characterize the erythritol-binding transcriptional repressor and its DNA-binding site. Transcriptome analysis suggests that carbohydrate metabolism-related genes in the engineered E. coli are overall upregulated, which then guides the selection of four genes for overexpression that notably enhances cell growth. Finally, engineered E. coli strains can be used as a living detector to distinguish erythritol-containing soda soft drinks and can grow in the simulated intestinal fluid supplemented with erythritol. We expect our work will inspire the engineering of more hosts to respond and utilize erythritol for broad applications in metabolic engineering, synthetic biology, and biomedical engineering.

synthetic biology↗

bioRxiv2022

Sensitivity of diffusion-tensor and correlated diffusion imaging to white-matter microstructural abnormalities: application in COVID-19

There has been growing attention on the effect of COVID-19 on white-matter microstructure, especially among those that self-isolated after being infected. There is also immense scientific interest and potential clinical utility to evaluate the sensitivity of single-shell diffusion MRI methods for detecting such effects. In this work, the sensitivities of three single-shell-compatible diffusion MRI modeling methods are compared for detecting the effect of COVID-19, including diffusion-tensor imaging, diffusion-tensor decomposition of orthogonal moments and correlated diffusion imaging. Imaging was performed on self-isolated patients at baseline and 3-month follow-up, along with age- and sex-matched controls. We demonstrate through simulations and experimental data that correlated diffusion imaging is associated with far greater sensitivity, being the only one of the three single-shell methods to demonstrate COVID-19-related brain effects. Results suggest less restricted diffusion in the frontal lobe in COVID-19 patients, but also more restricted diffusion in the cerebellar white matter, in agreement with several existing studies highlighting the vulnerability of the cerebellum to COVID-19 infection. These results, taken together with the simulation results, suggest that a significant proportion of COVID-19 related white-matter microstructural pathology manifests as a change in water diffusivity. Interestingly, different b-values also confer different sensitivities to the effects. No significant difference was observed in patients at the 3-month follow-up, likely due to the limited size of the follow-up cohort. To summarize, correlated diffusion imaging is shown to be a sensitive single-shell diffusion analysis approach that allows us to uncover opposing patterns of diffusion changes in the frontal and cerebellar regions of COVID-19 patients, suggesting the two regions react differently to viral infection.

biophysics↗