Biology subjects

Jing, X.

Publications and source records attributed to Jing, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Effect of Ascosphaera apis infestation on the activities of four antioxidant enzymes in Asian honey bee larval guts

Ascosphaera apis exclusively infects bee larvae and causes chalkbrood, a lethal fungal disease that results in the sharp reduction in adult bees and colony productivity. However, little is known about the effect of A. apis infestation on the activities of antioxidant enzymes in bee larvae. Here, A. apis spores were purified and used to inoculate Asian honey bee (Apis cerana) larvae, followed by detection of the host survival rate and evaluation of the activities of four major antioxidant enzymes. At 6 days post inoculation (dpi) with A. apis spores, white mycelia penetrated the posterior end of the larva, extended to the anterior end, and eventually covered the entire larval body surface, presenting an obvious symptom of chalkbrood disease similar to that occurs in Apis mellifera larvae. Additionally, PCR identification showed that the expected fragment was amplified from the A. apis-inoculated larval guts and the A. apis spores, verifying the A. apis infection of A. cerana larvae. The survival rate of larvae inoculated with A. apis was high at 1-2 dpi, sharply decreased to 4.16% at 4 dpi, and reached 0% at 5 dpi; whereas that of un-inoculated larvae was always high at 1~8 dpi, with an average survival rate of 95.37%, indicating the negative impact of A. apis infection on larval survival. Furthermore, in comparison with those in the corresponding un-inoculated groups, the superoxide dismutase (SOD) and catalase (CAT) activities in the 4-day-old larval gut in the A. apis-inoculated groups were reduced (p > 0.05), while those in the 5- and 6-day-old larval guts were significantly decreased (p < 0.05); the glutathione S-transferase (GST) activity in the 4- and 5-day-old larval guts was significantly increased (p < 0.05), while that in the 6-day-old larval gut was reduced (p > 0.05); the polyphenol oxidase (PPO) activity in 4-day-old larval gut was increased (p > 0.05) and that in the 5-day-old larval gut was significantly increased (p < 0.05), whereas that in the 6-day-old larval gut was significantly reduced (p < 0.01). These results together suggested that the activities of SOD and CAT in the larval guts were suppressed during the process of A. apis infestation, while the GST activity was induced to activation, and the PPO activity was first enhanced and then inhibited. Our findings not only unravel the response of A. cerana larvae to A. apis infestation from a biochemical perspective, but also offer a valuable insight into the interaction between Asian honey bee larvae and A. apis.

molecular biology↗

bioRxiv2022

DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data

With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq) technologies, it is of high importance to identify Cell-cell interactions (CCIs) from the ever-increasing scRNA-seq data. However, limited by the algorithmic constraints, current computational methods based on statistical strategies ignore some key latent information contained in scRNA-seq data with high sparsity and heterogeneity. To address the issue, here, we developed a deep learning framework named DeepCCI to identify meaningful CCIs from scRNA-seq data. Applications of DeepCCI to a wide range of publicly available datasets from diverse technologies and platforms demonstrate its ability to predict significant CCIs accurately and effectively.

bioinformatics↗

bioRxiv2022

ame-miR-34 modulates the larval body weight and immune response of Apis mellifera workers to Ascosphara apis invasion

MiRNAs are critical regulators of numerous physiological and pathological processes. Ascosphaera apis exclusively infects bee larvae and causes chalkbrood disease. However, the function and mechanism of miRNAs in the bee larval response to A. apis infection is poorly understood. Here, ame-miR-34, a previously predicted miRNA involved in the response of Apis mellifera ligustica larvae to A. apis invasion, was subjected to molecular validation, and overexpression and knockdown were then conducted to explore the regulatory functions of ame-miR-34 in larval body weight and immune response. Stem-loop RT-PCR and Sanger sequencing confirmed the authenticity of ame-miR-34 in the larval gut of A. m. ligustica. RT-qPCR results demonstrated that compared with that in the uninfected larval guts, the expression level of ame-miR-34 was significantly downregulated (P < 0.001) in the guts of A. apis-infected 4-, 5-, and 6-day-old larvae, indicative of the remarkable suppression of host ame-miR-34 due to A. apis infection. In comparison with the corresponding negative control (NC) groups, the expression level of ame-miR-34 in the larval guts in the mimic-miR-34 group was significantly upregulated (P < 0.001), while that in the inhibi- tor-miR-34 group was significantly downregulated (P < 0.01). Similarly, effective overexpression and knockdown of ame-miR-34 were achieved. In addition, the body weights of 5- and 6-day-old larvae were significantly increased compared with those in the mimic-NC group; the weights of 5-day-old larvae in the inhibitor-miR-34 group were significantly decreased in comparison with those in the inhibitor-NC group, while the weights of 4- and 6-day-old larvae in the inhibi- tor-miR-34 group were significantly increased, indicating the involvement of ame-miR-34 in modulating larval body weight. Furthermore, the expression levels of both hsp and abct in the guts of A. apis-infected 4-, 5- and 6-day-old larvae were significantly upregulated after ame-miR-34 overexpression. In contrast, after ame-miR-34 knockdown, the expression levels of the aforementioned two key genes in the A. apis-infected 4-, 5- and 6-day-old larval guts were significantly downregu- lated. Together, the results demonstrated that effective overexpression and knockdown of ame-miR-34 in both noninfected and A. apis-infected A. m. ligustica larval guts could be achieved by the feeding method, and ame-miR-34 exerted a regulatory function in the host immune response to A. apis invasion through positive regulation of the expression of hsp and abct. Our findings not only provide a valuable reference for the functional investigation of bee larval miRNAs but also reveal the regulatory role of ame-miR-34 in A. mellifera larval weight and immune response. Additionally, the results of this study may provide a promising molecular target for the treatment of chalkbrood disease.

molecular biology↗

bioRxiv2022

The overlooked dimension: soil depth drives microbial community structure and function along a salinity gradient

AimA fundamental challenge in soil macroecology is to understand how microbial community structure shapes ecosystem functions along environmental gradients of land surface (i.e., horizontal dimension). However, little is known of microbial community structure-function relationships along environmental gradients of soil depth (i.e., vertical dimension) in extreme environments. A full understanding of the consequences of environmental change for microbial communities structure and subsequent changes in microbial functions could enable more accurate predictions of extreme environmental change effects. Here, we leveraged a 200-km desert soil salinity gradient that is created by a 12-year saline-water irrigation to evaluate how soil microbial community structure-function relationships change with soil salinity in the horizontal and vertical dimensions. LocationThe Tarim basin of Taklamakan desert. TaxaSoil bacteria and fungi. MethodsWe assessed the prime ecological processes controlling the assembly of microbial communities and the activity of enzymes relevant to carbon, nitrogen, and phosphorus cycling along soil salinity gradients across study sites (horizontal dimension) and soil depths (vertical dimension) by using the general linear model, hierarchical variance partitioning, and path model. ResultsDifferences in soil depth (on the scale of meters) was as important as geographic distance (on the scale of kilometers) in shaping the structure of bacterial and fungal communities, while both the vertical and horizontal variability in enzymatic activity were largely attributed to the increase in the heterogeneity of soil properties, such as soil texture, water content, and pH. Main conclusionsOur results suggest that dispersal limitation and environmental heterogeneity, not soil salinization, along soil depth governs microbial community assembly and enzymatic activity, respectively. This work highlights that conservation efforts of soil macroecology should consider soil depth as a key attribute in the face of ongoing salinization in arid ecosystems.

ecology↗

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

Single-Cell RNA Sequencing Reveals the Effects of Chemotherapy on Human Pancreatic Adenocarcinoma and its Tumor Microenvironment

The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) is a complex ecosystem that drives tumor progression; however, in-depth single cell characterization of the PDAC TME and its role in response to therapy is lacking. We performed single-cell RNA sequencing on freshly collected human PDAC samples either before or after chemotherapy. Overall, we found a heterogeneous mixture of basal and classical cancer cell subtypes, along with distinct cancer-associated fibroblast and macrophage subpopulations. Strikingly, classical and basal-like cancer cells exhibited similar transcriptional responses to chemotherapy, and did not demonstrate a shift towards a basal-like transcriptional program among treated samples. We observed decreased ligand-receptor interactions in treated samples, particularly TIGIT on CD8+ T cells and its receptor on cancer cells, and identified TIGIT as the major inhibitory checkpoint molecule of CD8+ T cells. Our results suggest that chemotherapy profoundly impacts the PDAC TME and may promote resistance to immunotherapy.

cancer biology↗

bioRxiv2022

Genome-wide signatures of geographic expansion and breeding process in soybean

The clarification of genomic signatures left during evolutionary histories of crops is crucial for breeding varieties adapting to changing climate. Soybean, a leguminous crop, provides both plant oil and protein. Here, we analyzed genome sequences of 2,214 soybeans and proposed its evolutionary route, which includes four geographic paths, expansion of annual wild soybean (Glycine soja Sieb. & Zucc.) from Southern China, domestication in Central China, expansion of landrace (G. max (L.) Merr.), and local breeding. We observed that local adaptation of the wild and cultivated soybeans was largely independent, and that genetic introgression was mostly derived from sympatric rather than allopatric wild populations during the range expansion of soybean landraces. Range expansion and breeding processes were accompanied with positive selection of flowering-time genes including GmSPA3c as validated by knock-out mutants. Our study shed lights on the evolutionary history of soybean and provides valuable genetic resources for future breeding. TeaserThe expansion and selection history of soybean

genomics↗

bioRxiv2021

In vivo adenine base editing corrects newborn murine model of Hurler syndrome

Mucopolysaccharidosis type I (MPS I) is a severe disease caused by loss-of-function mutations variants in the -L-iduronidase (IDUA) gene. In vivo genome editing represents a promising strategy to correct IDUA mutations, and has the potential to permanently restore IDUA function over the lifespan of the patients. Here, we used adenine base editing to directly convert A>G (TAG>TGG) in newborn murine model harboring Idua-W392X mutation, which recapitulates the human condition and is analogous to the highly prevalent human W402X mutation. We engineered a split-intein dual-adeno-associated virus (AAV) 9 in vivo adenine base editor to circumvent the package size limit of AAV vectors. Intravenous injection of AAV9-base editor system into MPS I newborn mice led to sustained enzyme expression sufficient for correction of metabolic disease (GAGs substrate accumulation) and prevention of neurobehavioral deficits. We observed a reversion of the W392X mutation in 22.46{+/-}6.74% of hepatocytes, 11.18{+/-}5.25% of heart and 0.34{+/-}0.12% of brain, along with decreased GAGs storage in peripheral organs (liver, spleen, lung and kidney). Collectively, these data showed the promise of a base editing approach to precisely correct a common genetic cause of MPS I in vivo and could be broadly applicable to the treatment of a wide array of monogenic diseases.

genetics↗

bioRxiv2021

A bacterial genome and culture collection of gut microbial in weanling piglet

The microbiota hosted in the pig gastrointestinal tract are important for productivity of livestock. However, the individual species and functional repertoires that make up the pig gut microbiome remain largely undefined. Here we comprehensively investigated the genomes and functions of the piglet gut microbiome using culture-based and metagenomics approaches. A collection included 266 cultured genomes and 482 metagenome-assembled genomes (MAGs) that were clustered to 428 species across 10 phyla was established. Among these clustered species, 333 genomes represent potential new species. Less matches between cultured genomes and MAGs revealed a substantial bias for the acquisition of reference genomes by the two strategies. Glycoside hydrolases was the dominant category of carbohydrate-active enzymes. 445 secondary metabolite biosynthetic genes were predicted from 292 genomes with bacteriocin being the most. Pan genome analysis of Limosilactobacillus reuteri uncover the biosynthesis of reuterin was strain-specific and the production was experimentally determined. These genomic resources will enable a comprehensive characterization of the microbiome composition and function of pig gut.

microbiology↗

bioRxiv2020

Development of next-generation sequencing-based sterility test

The sterility testing methods described in pharmacopoeias require an incubation period of 14 days to obtain analysis results. An alternative method that can significantly shorten the detection time and improve the accuracy is in urgent need to meet the sterility testing requirements of regenerative medicine products with a short shelf life. In this study, we developed the next-generation sequencing-based sterility test (NGSST) based on sequencing and multiple displacement amplification. The NGSST can be finished within 48 hours with five steps including whole genome amplification, sequencing, alignment, sterility testing report, and microorganism identification. We use RPKM ratio to minorize the influence of environmental bacteria and determine its cutoff based AUC curve. The NGSST showed high sensitivity in reporting contaminates at 0.1 CFU in supernatant of biological product or 1 CFU in cell suspension. Furthermore, we identified microorganisms in 5 primary umbilical cord mesenchymal stem cell samples that were tested positive by BacT/ALERTR 3D. Overall, the NGSST can serve as a promising alternative for sterility testing of biological products.

microbiology↗

bioRxiv2020

Pulmonary stromal expansion and intra-alveolar coagulation are primary causes of Covid-19 death

Most Covid-19 victims are old and die from unrelated causes. Here we present twelve complete autopsies, including two rapid autopsies of young patients where the cause of death was Covid-19 ARDS. The main virus induced pathology was in the lung parenchyma and not in the airways. Most coagulation events occurred in the intra-alveolar and not in the intra-vascular space and the few thrombi were mainly composed of aggregated thrombocytes. The dominant inflammatory response was the massive accumulation of CD163+ macrophages and the disappearance of T killer, NK and B-cells. The virus was replicating in the pneumocytes and macrophages but not in bronchial epithelium, endothel, pericytes or stromal cells. The lung consolidations were produced by a massive regenerative response, stromal and epithelial proliferation and neovascularization. We suggest that thrombocyte aggregation inhibition, angiogenesis inhibition and general proliferation inhibition may have a roll in the treatment of advanced Covid-19 ARDS.

pathology↗

bioRxiv2020

Fast and effective protein model refinement by deep graph neural networks

Protein structure prediction has been greatly improved, but there are still a good portion of predicted models that do not have very high quality. Protein model refinement is one of the methods that may further improve model quality. Nevertheless, it is very challenging to refine a protein model towards better quality. Currently the most successful refinement methods rely on extensive conformation sampling and thus, take hours or days to refine even a single protein model. Here we propose a fast and effective method that may refine protein models with very limited conformation sampling. Our method applies GNN (graph neural networks) to predict refined inter-atom distance probability distribution from an initial model and then rebuilds the model using the predicted distance as restraints. On the CASP13 refinement targets our method may refine models with comparable quality as the two leading human groups (Feig and Baker) and greatly outperforms the others. On the CASP14 refinement targets our method is only second to Feigs method, comparable to Bakers method and much better than the others (who worsened instead of improved model quality). Our method achieves this result by generating only 5 refined models for an initial model, which can be done in [~]15 minutes. Our study also shows that GNN performs much better than convolutional residual neural networks for protein model refinement when conformation sampling is limited. AvailabilityThe code will be released once the manuscript is published and available at http://raptorx.uchicago.edu Contactjinboxu@gmail.com

bioinformatics↗

bioRxiv2020

Improved protein model quality assessment by integrating sequential and pairwise features using deep learning

MotivationAccurately estimating protein model quality in the absence of experimental structure is not only important for model evaluation and selection, but also useful for model refinement. Progress has been steadily made by introducing new features and algorithms (especially deep neural networks), but accuracy of quality assessment (QA) is still not very satisfactory, especially local QA on hard protein targets. ResultsWe propose a new single-model-based QA method ResNetQA for both local and global quality assessment. Our method predicts model quality by integrating sequential and pairwise features using a deep neural network composed of both 1D and 2D convolutional residual neural networks (ResNet). The 2D ResNet module extracts useful information from pairwise features such as model-derived distance maps, co-evolution information and predicted distance potential. The 1D ResNet is used to predict local (global) model quality from sequential features and pooled pairwise information generated by 2D ResNet. Tested on the CASP12 and CASP13 datasets, our experimental results show that our method greatly outperforms existing state-of-the-art methods. Our ablation studies indicate that the 2D ResNet module and pairwise features play an important role in improving model quality assessment. Availability and Implementationhttps://github.com/AndersJing/ResNetQA Contactjinboxu@gmail.com

bioinformatics↗

bioRxiv2020

Enhanced specificity of high sensitivity somatic variant profiling in cell-free DNA via paired normal sequencing: design, validation, and clinical experience of the MSK-ACCESS liquid biopsy assay

Circulating cell-free DNA (cfDNA) from blood plasma of cancer patients can be used to interrogate somatic tumor alterations non-invasively or when adequate tissue is unavailable. We have developed and clinically implemented MSK-ACCESS (Analysis of Circulating cfDNA to Evaluate Somatic Status), an NGS assay for detection of very low frequency somatic alterations in select exons and introns of 129 genes. Analytical validation demonstrated 92% sensitivity in de-novo mutation calling down to 0.5% allele frequency and 98% for a priori mutation profiling. To evaluate the performance and utility of MSK-ACCESS, we report results from the first 681 prospective blood samples (617 patients) that underwent clinical analysis to guide patient management. Somatic mutations, copy number, and/or structural variants were detected in 73% of the samples, and 56% of these circulating-tumor DNA (ctDNA) positive samples had clinically actionable alterations. The utilization of matched white blood cell sequencing allowed retention of somatic alterations while filtering out over 10,000 germline and clonal hematopoiesis variants, thereby greatly enhancing the specificity of the assay. Taken together, our experience illustrates the importance of analyzing a matched normal sample when interpreting cfDNA results and highlights the potential of cfDNA profiling to guide treatment selection, monitor treatment response, and identify mechanisms of treatment resistance.

genomics↗

bioRxiv2019

Perturbation biology links temporal protein changes to drug responses in a melanoma cell line

Data-driven mathematical modeling of biological systems has enormous potential to understand and predict the interplay between molecular and phenotypic response to perturbation, and provides a rational approach to the nomination of therapies in complex diseases such as cancer. Melanoma is a particularly debilitating disease for which most therapies eventually fail as resistance to chemotherapy and targeted drugs develop. We have previously applied an iterative experimental-computational modeling approach, termed perturbation biology, to predict and test effective drug combinations in melanoma cell lines [1].\n\nIn this work, we extend our analysis framework to derive models of temporally-acquired perturbation data that do not require prior knowledge and explicit specification of the targets of individual drugs. Specifically, we characterize the response of the melanoma cell line A2058 to 54 cancer drug combinations at 8 logarithmically spaced time points from 10 minutes to 67 hours. At each time point, 124 antibodies of proteins and phospho-proteins with broad coverage of cancer-related pathways and two phenotypes (cell number and apoptosis) were measured. These data are used to infer interactions in ordinary differential equation-based models that capture temporal aspects of the drug perturbation data. This network representation of drug-protein, protein-protein, and protein-phenotype interactions can be used to identify new logical (not necessarily direct biochemical) interactions. The agreement between the predicted phenotypic response and corresponding data for unseen drug perturbations has a Pearsons correlation coefficient of 0.79. We further use model predictions to nominate effective combination therapies and perform experimental validation of the highest ranked combinations.\n\nThis new data-driven modeling framework is a step forward in perturbation biology as it incorporates the temporal aspect of data. This work therefore opens the door to a new understanding of dynamic drug responses at a molecular level.

systems biology↗

bioRxiv2018

Regulation of DNA methylation on key parasitism genes of Cysticercus cellulosae revealed by integrative epigenomic-transcriptomic analyses

BackgroundThe life cycle of Taenia solium is characterized by different stages of development, requiring various kinds of hosts that can appropriately harbor the eggs (proglottids), the oncospheres, the larvae and the adults. Similar to other metazoan pathogens, T. solium undergoes transcriptional and developmental regulation via epigenetics during its complex lifecycle and host interactions.\n\nResultIn the present study, we integrated whole-genome bisulfite sequencing and RNA-seq technologies to characterize the genome-wide DNA methylation and its effect on transcription of Cysticercus cellulosae of T. solium. We confirm that the T. solium genome in the cysticercus stage is epigenetically modified by DNA methylation in a pattern similar to that of other invertebrate genomes, i.e., sparsely or moderately methylated. We also observed an enrichment of non-CpG methylation in defined genetic elements of the T. solium genome. Furthermore, an integrative analysis of both the transcriptome and the DNA methylome indicated a strong correlation between these two datasets, suggesting that gene expression might be tightly regulated by DNA methylation. Importantly, our data suggested that DNA methylation might play an important role in repressing key parasitism-related genes, including genes encoding excretion-secretion proteins, thereby raising the possibility of targeting DNA methylation processes as a useful strategy in therapeutics of cysticercosis.\n\nConclusionOur study will provide a foundation for future studies to explore this key epigenetic modification in development of Cysticercus cellulosae and in human cysticercus disease.

genetics↗

bioRxiv2018

Implementation of CRISPR-Cas13a system in fission yeast and its repurposing for precise RNA editing

In contrast to genome editing that introduces genetic changes at DNA level, disrupting or editing genes transcripts provides a distinctive approach to perturb a genetic system, offering benefits complementary to classic genetic approaches. To develop a new toolset for manipulation of RNA, we first implemented a member of type VI CRISPR systems, Cas13a from Leptotrichia shahii (LshCas13a) in Schizosaccharomyces pombe, an important model organism employed by biologists to study key cellular mechanisms conserved from yeast to humans. While it was shown to knock down targeted endogenous genes transcripts, differently from previous studies in E. coli, no collateral cleavage of other non-specific RNA by activated Cas13a-crRNA complex was detected in fission yeast. Second, we engineered a RNA-editing system by tethering an inactive form of LshCas13a (dCas13) to the catalytic domain of human Adenosine Deaminase Act on RNA 2 (hADAR2d), which was shown to be programmable with crRNA to target messenger RNAs and precisely edit specific nucleotide residues. We optimized the system parameters using a dual-florescence reporter and demonstrated its utility in editing of randomly selected endogenous genes transcripts. Our engineered RNA-editing system enables a new toolset for transcriptomic manipulation that is widely applicable in basic genetic and biotechnological research.

synthetic biology↗

bioRxiv2017

Climate change will lead to pronounced shifts in the diversity of soil microbial communities

Soil bacteria are key to ecosystem function and maintenance of soil fertility. Leveraging associations of current geographic distributions of bacteria with historic climate, we predict that soil bacterial diversity will increase across the majority (~75%) of the Tibetan Plateau and northern North America if bacterial communities equilibrate with existing climatic conditions. This prediction is possible because the current distributions of soil bacteria have stronger correlations with climate from ~50 years ago than with current climate. This lag is likely associated with the time it takes for soil properties to adjust to changes in climate. The predicted changes are location specific and differ across bacterial taxa, including some bacteria that are predicted to have reductions in their distributions. These findings demonstrate the widespread influence that climate change will have on belowground diversity and highlight the importance of considering bacterial communities when assessing climate impacts on terrestrial ecosystems.\n\nIMPORTANCEThere have been many studies highlighting how plant and animal communities lag behind climate change, causing extinction and diversity debts that will slowly be paid as communities equilibrate. By virtue of their short generation times and dispersal abilities, soil bacteria might be expected to respond to climate change quickly and to be effectively in equilibrium with current climatic conditions. We found strong evidence to the contrary in Tibet and North America. These findings could significantly improve understanding of climate impacts on soil microbial communities.

ecology↗