Biology subjects

Xia, Y.

Publications and source records attributed to Xia, Y..

At least 145 records · Page 8Linked to original sources

bioRxiv2022

The critical role of BTRC in hepatic steatosis as an ATGL E3 ligase

ObjectiveNon-alcoholic fatty liver disease (NAFLD), characterized by hepatic steatosis, is one of the most common causes of liver dysfunction. ATGL is closely related to hepatic steatosis as the speed-limited triacylglycerol lipase. Nevertheless, the expression and regulation of ATGL in NAFLD remain unclear. MethodsUsing immunohistochemistry and qRT-PCR to detect the expression of ATGL and BTRC in different models with hepatic steatosis. Co-IP evaluated the binding of ATGL and BTRC. Knockdown of BTRC employed by adenoviruses and then analyzed the ATGL expression, triglyceride levels, and lipid droplets accumulation. ResultsOur results revealed that ATGL protein level was decreased in animal and cellular models of hepatic steatosis and the liver tissues of cholangioma/hepatic carcinoma patients with hepatic steatosis, while the ATGL mRNA level had hardly changed; which means the decreased ATGL mainly degraded through the proteasome pathway. BTRC was identified as the E3 ligase for ATGL, up-regulated, and negatively correlated with ATGL level. Moreover, adenovirus-mediated knockdown of BTRC ameliorated hepatic steatosis via up-regulating ATGL level. ConclusionsOur study demonstrates a crucial role of elevated BTRC in hepatic steatosis through promoting ATGL proteasomal degradation as a new ATGL E3 ligase and suggests BTRC may serve as a potential therapeutic target for NAFLD. FundingThis study was supported by The National Natural Science Foundation of China (Grants 82070888, 82070882, 82100917, 81872165, 82273116, 82203661, 81901557 and 81902693); Key Project of Nature Science Foundation of Guangdong Province, China (Grant 2019B1515120077); National Key R&D Program of China (Grant 2018YFA0800403); Guangdong Special Support Program for Young Top Scientist (Grant 201629046); Guangdong Natural Science Fund (Grant 2019A1515011810, 2021A1515010434, 2022A1515012423 and 2022A1515012513); Key Sci-Tech Research Project of Guangzhou Municipality (Grants 202201010820) Fundamental Research Funds for the Central Universities (Grant 50000-31620106); China Postdoctoral Science Foundation (Grant 2021M703679, 2020M683110).

cell biology↗

bioRxiv2022

Incorporating Pre-training Paradigm for Antibody Sequence-Structure Co-design

Antibodies are versatile proteins that can bind to pathogens and provide effective protection for human body. Recently, deep learning-based computational antibody design has attracted popular attention since it automatically mines the antibody patterns from data that could be complementary to human experiences. However, the computational methods heavily rely on the high-quality antibody structure data, which is quite limited. Besides, the complementarity-determining region (CDR), which is the key component of an antibody that determines the specificity and binding affinity, is highly variable and hard to predict. Therefore, data limitation issue further raises the difficulty of CDR generation for antibodies. Fortunately, there exists a large amount of sequence data of antibodies that can help model the CDR and alleviate the reliance on structured data. By witnessing the success of pre-training models for protein modeling, in this paper, we develop an antibody pre-trained language model and incorporate it into the (antigen-specific) antibody design model in a systemic way. Specifically, we first pre-train an antibody language model based on the sequence data, then propose a one-shot way for sequence and structure generation of CDR to avoid the heavy cost and error propagation from an autoregressive manner, and finally leverage the pre-trained antibody model for the antigen-specific antibody generation model with some carefully designed modules. Through various experiments, we show that our method achieves superior performance over previous baselines on different tasks, such as sequence and structure generation, antigen-binding CDR-H3 design.

molecular biology↗

bioRxiv2022

Activation of an injury-associated transient progenitor state in the epicardium is required for zebrafish heart regeneration

The epicardium, a mesothelial cell tissue that encompasses vertebrate hearts, supports heart regeneration after injury through paracrine effects and as a source of multipotent progenitors. However, the progenitor state in the adult epicardium has yet to be defined. Through single-cell RNA-sequencing of isolated epicardial cells from uninjured and regenerating adult zebrafish hearts, we defined the epithelial and mesenchymal subsets of the epicardium. We further identified a transiently activated epicardial progenitor cell (aEPC) subpopulation marked by ptx3a and col12a1b expression. Upon cardiac injury, aEPCs emerge from the epithelial epicardium, migrate to enclose the wound, undergo epithelial-mesenchymal transition (EMT), and differentiate into mural cells and pdgfra+hapln1a+ mesenchymal epicardial cells. These EMT and differentiation processes are regulated by the Tgf{beta} pathway. Conditional ablation of aEPCs blocked heart regeneration through reduced Nrg1 expression and mesenchymal cell number. Our findings identify a transient progenitor population of the adult epicardium that is indispensable for heart regeneration and highlight it as a potential target for enhancing cardiac repair.

developmental biology↗

bioRxiv2022

Research on protein structure prediction and folding based on novel remote homologs recognition

Recognition of remote homologous structures is a necessary module in AlphaFold2 and is also essential for the exploration of protein folding pathways. Here, we developed a new method, PAthreader, which identifies remote homologous structures based on the three-track alignment of distance profiles and structure profiles originated from PDB and AlphaFold DB by deep learning. Based on the identified templates, we further enhanced state-of-the-art modelling method and explored protein folding pathways based on the residue frequency distribution of homologs and the secondary structure. The results show that the average accuracy of templates identified by PAthreader is 11.6% higher than those of HHsearch on 551 nonredundant proteins. In terms of structure modelling, PAthreader improves the performance of AlphaFold2 and ranks first in CAMEO blind test for the last three months. Furthermore, we explored protein folding pathways for 37 proteins. The results are almost consistent with biological experiments for 7 proteins, and the remaining 30 human proteins have yet to be verified by biological experiments, revealing that folding information can be exploited from remote homologous structures.

bioinformatics↗

bioRxiv2022

PF-D-Trimer, a broadly protective SARS-CoV-2 subunit vaccine: immunogenicity and application

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has had and still has a considerable impact on global public health. One of the characteristics of SARS-CoV-2 is a surface homotrimeric spike protein, the primary responsible for the host immune response upon infection. Here we show the preclinical studies of a broad protective SARS-CoV-2 subunit vaccine developed from our Trimer Domain platform using the Delta spike protein, from antigen design to purification, vaccine evaluation and manufacturability. The prefusion trimerized Delta spike protein, PF-D-Trimer, was highly expressed in Chinese hamster ovary (CHO) cells, purified by a rapid one-step anti-Trimer Domain monoclonal antibody immunoaffinity process and prepared as a vaccine formulation with an adjuvant. The immunogenicity studies demonstrated that this vaccine candidate induces robust immune responses in mouse, rat and Syrian hamster models. It also protects K18-hACE2 transgenic mice in a homologous virus challenge. The neutralizing antibodies induced by this vaccine display a cross-reactive capacity against the ancestral WA1 and Delta variants as well as different Omicron, including BA.5.2. The Trimer Domain platform was proven to be a key technology in the rapid production of the PF-D-Trimer vaccine and may be crucial to accelerate the development of updated versions of SARS-CoV-2 vaccines.

immunology↗

bioRxiv2022

Leveraging Scaffold Information to Predict Protein-ligand Binding Affinity with an Empirical Graph Neural Network

MotivationProtein-ligand binding affinity prediction is an important task in structural bioinformatics for drug discovery and design. Although various scoring functions have been proposed, it remains challenging to accurately evaluate the binding affinity of a protein-ligand complex with known bound structure due to the potential preference of scoring system. In recent years, deep learning techniques have been applied to scoring functions without sophisticated feature engineering. Nevertheless, existing methods cannot model the differential contribution of atoms in various regions of proteins, and the relationship between atom properties and intermolecular distance is also not fully explored. ResultsWe propose a novel empirical graph neural network for accurate protein-ligand binding affinity prediction (EGNA). Graphs of protein, ligand and their interactions are constructed based on different regions of each bound complex. Proteins and ligands are effectively represented by graph convolutional layers, enabling the EGNA to capture interaction patterns precisely by simulating empirical scoring functions. The contributions of different factors on binding affinity can thus be transparently investigated. EGNA is compared with the state-of-the-art machine learning-based scoring functions on two widely used benchmark datasets. The results demonstrate the superiority of EGNA and its good generalization capability. Availability and implementationThe web server and source code of EGNA is available at www.csbio.sjtu.edu.cn/bioinf/EGNA and https://github.com/chunqiux/EGNA. Contacthbshen@sjtu.edu.cn or 2008xypan@sjtu.edu.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

Bone marrow AdipoQ-lineage progenitors are a major cellular source of M-CSF that dominates bone marrow macrophage development, osteoclastogenesis and bone mass

M-CSF is a critical growth factor for myeloid lineage cells, including monocytes, macrophages and osteoclasts. Tissue resident macrophages in most organs rely on local M-CSF. However, it is unclear what specific cells in bone marrow produce M-CSF to maintain myeloid homeostasis. Here, we identify bone marrow AdipoQ-lineage progenitors, but not bone marrow mature adipocytes or peripheral adipose tissue, as a major cellular source of M-CSF, with these AdipoQ-lineage progenitors producing M-CSF at levels much higher than those produced by osteoblast lineage cells. Deficiency of M-CSF in bone marrow AdipoQ-lineage progenitors drastically reduces the generation of bone marrow macrophages and osteoclasts, leading to severe osteopetrosis in mice. Furthermore, the postmenopausal osteoporosis in a mouse model can be significantly alleviated by the lack of M-CSF in bone marrow AdipoQ-lineage progenitors. Our findings identify bone marrow AdipoQ-lineage progenitors as a major cellular source of M-CSF in bone marrow and reveal their crucial contribution to bone marrow macrophage development, osteoclastogenesis, bone homeostasis and pathological bone loss.

cell biology↗

bioRxiv2022

Evolving copy number gains promote tumor expansion and bolster mutational diversification

Charting the evolutionary history of rampant somatic copy number alterations (SCNA) is an indispensable step toward a deeper understanding of their roles in tumor development. However, the existing SCNA timing analysis is limited to low copy number states and initiating gains, which are not necessarily close to the onset of the malignant proliferation. Moreover, it remains a critical question if the timing of an SCNA reveals the corresponding variants fitness effect. Here we propose a framework to estimate the arrival time of a clonal SCNA, i.e., the time delay from its last alteration to the start of population expansion, in addition to its initiation time when the first alteration occurs. Our method leverages the bias that a genomic segment, when resting on a copy number (CN) state, accumulates somatic single nucleotide variants (SSNV) at a rate proportional to its CN. From the whole genome sequencing data of 184 samples from 75 patients across five tumor types, we commonly observed late clonal CN gains following early initiating events, which appear right before the expansion leading to the observed tumor sample(s). Genome doubling (GD) can be late, but post-GD CN evolution is prevalent in the genealogy of the most recent common ancestor of patient tumors. Notably, mathematical modeling suggests that late evolving events could contain rate-limiting drivers. The advantage of evolving gains could arise from the dosage increase of cancer genes in proliferative signaling and amplification of early functional variants. In addition, evolving SCNAs bolster the diversification of SSNVs between sub-populations, exacerbating the vicious circle between malignant growth and accumulation of genomic heterogeneity. Our findings have broad implications for resolving the trajectory of SCNAs, discerning the CN markers of malignant growth in vivo, and properly quantifying tumor heterogeneity in aneuploid tumors.

genomics↗

bioRxiv2022

HybAVPnet: a novel hybrid network architecture for antiviral peptides identification

MotivationThe virus poses a great threat to human production and life, thus the research and development of antiviral drugs is urgently needed. Antiviral peptides play an important role in drug design and development. Compared with the time-consuming and laborious wet chemical experiment methods, accurate and rapid identification of antiviral peptides using computational methods is critical. However, it is still challenging to extract effective feature representations from the sequences for the accurate identification of antiviral peptides. ResultsThis study introduces a novel two-step approach, named HybAVPnet, with a hybrid network architecture to identify antiviral peptides based on neural networks and traditional machine learning methods. Firstly, eighteen kinds of features are extracted to predict labels and probabilities by the neural network classifier and LightGBM classifier, respectively. Secondly, the support vector machine classifier is carried out using the predicted probability of the first step to make the final prediction. The experimental result shows HybAVPnet can achieve better and more robust performance compared with the state-of-the-art methods, especially on independent datasets, which makes it useful for the research and development of antiviral drugs. Meanwhile, it can also be extended to other peptide recognition problems because of its generalization ability. Availability and implementationThe predicted model could be downloaded from: https://github.com/greyspring/HybAVPnet Contactgespring@hdu.edu.cn; yp.cai@siat.ac.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

PPIX-binding Proteins Reveal Porphyrin Synthesis and Ferroptosis Link

All aerobic organisms require the cofactor heme to survive, but its synthesis requires formation of a potentially toxic intermediate protoporphyrin IX (PPIX). Little is known about the extent of PPIXs cellular interactions. Here, we report the development of PPB, a biotin-conjugated, PPIX-probe that captures proteins capable of interacting with PPIX. Quantitative proteomics with PPB identified common proteins among a diverse panel of mammalian cell lineages. Pathway and quantitative difference analysis revealed PPB-bound proteins related to iron and heme metabolism and suggested that these processes might be altered by heme/porphyrin synthesis. We show that increased heme/porphyrin synthesis in cells promotes ferroptosis that is pharmacologically distinct from canonical ferroptosis driven by erastin, an inhibitor of the cystine/glutamate antiporter. Proteomic data derived from PPB revealed an interactor, PRDX3, a mitochondrial peroxidase, that modulated heme/porphyrin biosynthesis driven ferroptosis. Consistent with a role in porphyrin-induced ferroptotic death targeted gene knockdown of PRDX3, but not peroxidases, PRDX1 or 2, enhanced porphyrin-induced ferroptotic death. The relationship between increased heme/porphyrin synthesis and ferroptosis was also found in a ferrochelatase-deficient T-lymphoblastoid leukemia cell line, suggesting potential strategy for treating certain cancers. We demonstrate that when the PPB probe is coupled with unbiased proteomics a previously unreported relationship between heme/porphyrin synthesis, and ferroptosis was discovered.

biochemistry↗

bioRxiv2022

Extraintestinal roles of intestinal vitamin D receptor in protecting against dysbiosis and tumorigenesis in breast cancer

The microbiota play critical roles in regulating the function and health of intestine and extraintestinal organs. A fundamental question is whether there is an intestinal-microbiome-breast axis during the development of breast cancer. If yes, what are the roles of host factors? Vitamin D receptor (VDR) involves host factors and the human microbiome. Vdr gene variation shapes the human microbiome and VDR deficiency leads to dysbiosis. We hypothesized that intestinal VDR protects hosts against tumorigenesis in breast. Reduced VDR mRNA expression was observed in patients with breast cancer. We used a 7,12-dimethylbenzanthracene (DMBA)-induced breast cancer model in intestinal epithelial VDR knockout (VDR{Delta}IEC) mice. We reported that VDR{Delta}IEC mice with dysbiosis are more susceptible to breast cancer induced by DMBA. Intestinal and breast microbiota analysis showed that lacking VDR leads to bacterial profile shift from normal to susceptible carcinogenesis. We found enhanced bacterial staining within breast tumors. At the molecular and cellular levels, we identified the mechanisms by which intestinal epithelial VDR deficiency led to increased gut permeability, disrupted tight junctions, microbial translocation, and enhanced inflammation, thus increasing the tumor size and number in breast. Furthermore, treatment with beneficial bacterial metabolite butyrate or probiotic Lactobacillus plantarum reduced the breast tumors, enhanced the tight junctions, and inhibited inflammation in the VDR{Delta}IEC mice. Gut microbiome contribute to the pathogenesis of diseases, not only in the intestine, but also in the breast. Our study provides new insights into the mechanism by which intestinal VDR dysfunction and gut dysbiosis led to high risk of extraintestinal tumorigenesis. Gut-tumor-microbiome interactions indicate a new target in the prevention and treatment of breast cancer. O_FIG O_LINKSMALLFIG WIDTH=165 HEIGHT=200 SRC="FIGDIR/small/492300v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@7e354eorg.highwire.dtl.DTLVardef@1dd9b50org.highwire.dtl.DTLVardef@1ffe2c5org.highwire.dtl.DTLVardef@810b1a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Dysfunction of transfer RNA modifications in inflammatory bowel disease

Backgrounds and aimsTransfer RNA (tRNA) is the most extensively modified RNA in cells. Queuosine (Q)-modification is a fundamental process for fidelity and efficiency of translation from RNA to proteins. In eukaryotes, tRNA-Q-modification relies on the intestinal microbial product queuine. However, the roles and potential mechanisms of Q-tRNA modifications in IBD are unknown. MethodsWe explored the Q-tRNA modifications and expression of Q tRNA ribosyltransferase catalytic subunit 1 (QTRT1) in patients with IBD by investigating human biopsies and reanalyzing datasets. We used colitis models, organoids, and cultured cells for loss- and gain-of-function studies to investigate the molecular mechanisms of Q-tRNA modifications in intestinal inflammation. ResultsQTRT1 expression was significantly downregulated in ulcerative colitis and Crohns disease patients. The four Q-tRNA-related tRNA synthetases (asparaginyl-aspartyl-, histidyl-, and tyrosyl-tRNA synthetase) were decreased in IBD patients. This reduction was further confirmed in DSS-induced colitis and IL10-deficient mice. Reduced QTRT1 was significantly correlated with cell proliferation and intestinal junctions, including downregulated {beta}-catenin and Claudin-5 and upregulated Claudin-2. These alterations were confirmed in vitro by deleting QTRT1 from cells. Queuine treatment significantly enhanced cell proliferation and junction functions in cell lines and human colonoids. Queuine treatment also reduced inflammation in epithelial cells. Moreover, altered QTRT1-related metabolites were found in human IBD. ConclusiontRNA modifications play an unexplored novel role in the pathogenesis of intestinal inflammation by altering epithelial proliferation and junctions. Investigations on tRNA modification will uncover novel molecular mechanisms for potential prevention and therapy for IBD.

cell biology↗

bioRxiv2022

An attempt to find the correlations between body weight and the composition of gut microbiota in Zhejiang and Shanghai

Previous studies showed that the human gut microbiota was associated with metabolic diseases, but the interaction and mechanism between the gut microbiota and metabolic disease are still unclear. In this study, the gut microbiota of 58 persons living in Zhejiang and Shanghai area will be analyzed. Then, the potential contribution of the human gut microbiota to obesity/high Body Mass Index (BMI) will be explored. The gut microbiota was studied by high throughput sequencing analysis of bacterial 16S rRNA gene fragments, and the gut microbiota samples with different BMI were compared. Meanwhile, some gut microorganisms from faeces of a healthy individual were cultivated and isolated, and the classification was identified by 16S rRNA sequencing. The main microbes in human gut microbiota were assigned to the phyla of Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. Moreover, four strains were isolated from an individual fecal sample, of which one species was assigned to Escherichia fergusonii and the other three strains were assigned to Weissella cibaria. These four species belong to both abundant and low-abundant species revealed by high throughput sequencing. It was found that individuals with different BMI have different gut microbiota; while the differences are not significant. Also, the Firmicutes/Bacteroidetes ratio increases with the decrease of BMI, which is corresponding to previous results. In the future, more cohort gut microbiota in Zhejiang and Shanghai area will be collected and recovered, and the gut microbiota database of Zhejiang and Shanghai area will be built up in order to provide the basis for future gut microbiota modulation in this area.

microbiology↗

bioRxiv2022

Maps of high density microsatellites accumulation in human genome

BackgroundMicrosatellites are increasingly realized to have biological significance in human genome and health in past decades, the assembled complete reference sequence of human genome T2T-CHM13 brought great help for a comprehensive study of short tandem repeats in the human genome. ResultsMicrosatellites density landscapes of all 24 chromosomes were built here for the first complete reference sequence of human genome T2T-CHM13. These landscapes showed that short tandem repeats (STRs) are prone to aggregate characteristically to form a large number of STRs density peaks. We classified 8,823 High Microsatellites Density Peaks (HMDPs), 35,257 Middle Microsatellites Density Peaks (MMDPs) and 199, 649 Low Microsatellites Density Peaks (LMDPs) on the 24 chromosomes; and also classified the motif types of every microsatellites density peak. These STRs density aggregation peaks are mainly composing of a single motif, and AT is the most dominant motif, followed by AATGG and CCATT motifs. And 514 genomic regions were characterized by microsatellite density feature in the full T2T-CHM13 genome. ConclusionsThese landscape maps exhibited that microsatellites aggregate in many genomic positions to form a large number of microsatellite density peaks with composing of mainly single motif type in the complete reference genome, indicating that the local microsatellites density varies enormously along the every chromosome of T2T-CHM13.

bioinformatics↗

bioRxiv2022

Validation of the first PGT-whole genome sequencing approach including mitochondrial variants

Whole Genome Sequencing (WGS) is used in healthcare and in the clinic, with the notable exception of preimplantation genetic testing (PGT). In PGT, only a few cells are available for sequencing, requiring DNA amplification which reduces data quality, sequence fidelity and sharply limits subsequent clinical impact. Here we demonstrate the first clinical validation of WGS on embryo biopsies using our lab development protocol, opening the door to broad use of WGS in fertility. We find that amplified DNA with comparable sensitivity and specificity to genomic DNA when performing whole genome sequencing assays. DNA amplification on cell lines and donated human embryos had an amplification success rate of >99.9% and 98.2% respectively and accuracy on both was >99.9% on aneuploidy status. GIAB samples (Genome in the Bottle reference NA12878) showed that our amplified DNA was broadly comparable to genomic DNA (99.99% accuracy, 99.99% specificity, 98.0% sensitivity and 98.1% precision). Using our assay, we were able to call variants, detect mitochondrial heteroplasmy, perform high precision screening without access to parental genomes, detect compound heterozygous variants, and score microdups/dels and uniparental disomies (to reduce risk of diseases such as DiGeorge syndrome and Prader-Willi syndrome). Our clinical study suggests that the full spectrum of traditional clinical genome bioinformatics, so far reserved to large samples, can now be performed on embryos before implantation.

genomics↗

bioRxiv2022

Intestinal epithelial Axin1 deficiency protects against colitis via altered gut microbiota

Background and AimsIntestinal homeostasis is maintained by specialized host cells and the gut microbiota. Wnt/{beta}-catenin signaling is essential for gastrointestinal development and homeostasis, and its dysregulation has been implicated in inflammation and colorectal cancer. Axin1 negatively regulates activated Wnt/{beta}-catenin signaling, but little is known regarding its role in regulating host-microbial interactions in health and disease. Here, we aim to demonstrate that intestinal Axin1 determines gut homeostasis and host response to inflammation. MethodsThe expression of Axin1 was analyzed in human IBD datasets. To explore the effects and mechanism of intestinal Axin1 in regulating intestinal homeostasis and colitis, we generated mouse models with Axin1 conditional knockout in intestinal epithelial (Axin1{Delta}IEC) and Paneth cells (Axin1{Delta}PC) to compare with control (Axin1LoxP) mice. ResultsWe found increased Axin1 expression in the colonic epithelium of human IBD. Axin1{Delta}IEC mice exhibited altered goblet cell spatial distribution, Paneth cell morphology, reduced lysozyme expression, and enriched Akkermansia muciniphila. Absence of intestinal epithelial and Paneth cell Axin1 decreased susceptibility to DSS-induced colitis in vivo. Axin1{Delta}IEC and Axin1{Delta}PC became more susceptible to DSS-colitis after cohousing with control mice, suggesting the non-colitogenic effect is driven by the gut microbiota. ConclusionWe found loss of intestinal Axin1 protects against colitis, which is likely driven through Paneth cell Axin1 and the microbiota. Our study demonstrates a novel role of Axin1 in mediating intestinal homeostasis and the microbiota. Further mechanistic studies using specific Axin1 mutations elucidating how Axin1 modulates microbiome and host inflammatory response, will provide new therapeutic strategies for human IBD. What you Need to Know1. Background and ContextWnt/beta-catenin is a fundamental molecular pathway that affects intestinal proliferation and differentiation. Axin1 negatively regulates activated Wnt/{beta}-catenin signaling, but little is known regarding its role in the microbiome. Dysfunction of Wnt/beta-catenin was reported in human inflammatory bowel disease (IBD) and Axin1 serum level was elevated in patients with UC. 2. New FindingsWe found increased Axin1 expression at both the mRNA and protein level in human IBD. Specifically, we identified increased Axin1 expression positive correlated with pro-inflammatory cytokines IL-6 and TNF- in CD. Our study, for the first time, identifies links between the gut microbiota and intestinal Axin1 in intestinal inflammation through utilization of innovative deletion mouse models in intestinal epithelium and Paneth cells. Loss of intestinal Axin1 plays a novel role in intestinal inflammation by altering the Paneth cells and microbiome (e.g., enriched Akkermansia mucinlphila). Our study has provided insights into the molecular mechanism that might contribute to IBD, especially the novel role of Paneth cell Axin1 in colitis. 3. LimitationsThere are no human or mice studies assessing the role of intestinal epithelial and Paneth cell Axin1 in inflammation and the microbiome. 4. ImpactFurther explorations of the gut microbiota and Axin1 interaction as we report will provide novel mechanistic strategies for therapeutic approaches for human IBD by targeting intestinal Axin1 and Axin1-associated microbiome.

pathology↗

bioRxiv2022

Studies of a siderophore-producing cyclization domain: A refined proposal of substrate binding

Nonribosomal peptide synthetase (NRPS) heterocyclization (Cy) domains generate biologically important ox-/thiazoline modifications in natural products, including in production of compounds targeting disease or siderophores that are important for bacterial pathogenicity. Cy domains share the NRPS condensation domain fold but catalyze consecutive condensation and cyclodehydration reactions via an unknown mechanism. To further understanding of Cy domain catalysis, we report the crystal structure of the second Cy domain (Cy2) of yersiniabactin synthetase from the causative agent of the plague, Yersinia pestis. We find the high-resolution structure of Cy2 adopts a conformation enabling exploration of binding the extended, thiazoline-containing cyclodehydration intermediate for catalysis and the acceptor carrier protein to which it is tethered. We also report complementary electrostatic interfaces between Cy2 and its donor carrier protein that mediate donor binding. Lastly, we explore domain flexibility through the normal mode approximation and identify small-molecule fragment binding sites to inform antibiotic design targeting Cy function. Our results suggest how carrier protein binding may influence global conformation, with consequences for active site catalytic states and inhibitor development.

biochemistry↗

bioRxiv2022

Structural analogue-based protein structure domain assembly assisted by deep learning

MotivationWith the breakthrough of AlphaFold2, the protein structure prediction problem has made a remarkable progress through end-to-end deep learning techniques, in which correct folds could be built for nearly all single-domain proteins. However, the full-chain modelling appears to be lower on average accuracy than that for the constituent domains and requires higher demand on computing hardware, indicating the performance of full-chain modelling still needs to be improved. In this study, we investigate whether the predicted accuracy of full-chain model can be further improved by domain assembly assisted by deep learning. ResultsIn this article, we developed a structural analogue-based protein structure domain assembly method assisted by deep learning, named SADA. In SADA, a multi-domain protein structure database (MPDB) was constructed for the full-chain analogue detection using individual domain models. Starting from the initial model constructed from the analogue, the domain assembly simulation was performed to generate the full-chain model through a two-stage differential evolution algorithm guided by the physics-based force field and an inter-residue distance potential predicted by deep learning. SADA was compared with the state-of-the-art domain assembly methods on 356 benchmark proteins, and the average TM-score of SADA models is 8.1% and 27.0% higher than that of DEMO and AIDA, respectively. We also assembled full-chain models of 20 human multi-domain proteins using individual domain models independently predicted by AlphaFold2, where the SADA full-chain models obtained a 4.8% higher average TM-score than full-chain models directly predicted by AlphaFold2 and fewer computing resources were required. In addition, we also find that the domains often interact in the similar way in the quaternary orientations if the domains have similar tertiary structures. Furthermore, homologous templates and structural analogues are complementary for multi-domain protein full-chain modelling. AvailabilityThe SADA web server are freely available at http://zhanglab-bioinf.com/SADA.

bioinformatics↗