Biology subjects

Shan, X.

Publications and source records attributed to Shan, X..

33 records · Page 2Linked to original sources

bioRxiv2024

1 Microbiome determinants of productivity in whiteleg shrimp aquaculture

Aquaculture holds immense promise for addressing the food needs of our growing global population. Yet, a quantitative understanding of the factors that control its efficiency and productivity has remained elusive. In this study, we address this knowledge gap by focusing on the microbiome determinants of productivity, more specifically animal survival and growth, for one of the most predominant animal species in global aquaculture, whiteleg shrimp (Penaeus vannamei). Through analysis of the shrimp-associated microbiome from 610 aquaculture samples across Asia and Latin America, we established the presence of core phylogenetic groups, widely prevalent across aquaculture conditions in disparate geographic locations and including both pathogenic and beneficial microbes. Focusing on early stages of growth (larval hatcheries), we showed that the composition of the microbiome alone can predict approximately 50% of the variation in shrimp larvae survival rates. Taxa associated with high survival rates share recently acquired genes that appear to be specific to aquaculture conditions. These genes are involved in the biosynthesis of growth factors and in protein degradation, underscoring the potential role of beneficial microorganisms in nutrient assimilation. In contrast, the predictability of the microbiome on the adult shrimp weight in grow-out farms is weaker (10-20%), akin to observations in the context of livestock. In conclusion, our study unveils a novel avenue for predicting productivity in shrimp aquaculture based on microbiome analysis. This paves the way for targeted manipulation of the microbiome as a strategic approach to enhancing aquaculture efficiency from the earliest developmental stages.

microbiology↗

bioRxiv2024

The protective roles of Eugenol on type 1 diabetes mellitus through NRF2 mediated oxidative stress pathway

Type 1 diabetes mellitus (T1DM), known as insulin-dependent diabetes mellitus, is characterized by persistent hyperglycemia resulting from damage to the pancreatic {beta} cells and an absolute deficiency of insulin, leading to multi-organ involvement and a poor prognosis. The progression of T1DM is significantly influenced by oxidative stress and apoptosis. The natural compound eugenol (EUG) possesses anti-inflammatory, anti-oxidant, and anti-apoptotic properties. However, the potential effects of EUG on T1DM had not been investigated. In this study, we established the streptozotocin (STZ)-induced T1DM mouse model in vivo and STZ-induced pancreatic {beta} cell MIN6 cell model in vitro to investigate the protective effects of EUG on T1DM, and tried to elucidate its potential mechanism. Our findings demonstrated that the intervention of EUG could effectively induce the activation of nuclear factor E2-related factor 2 (NRF2), leading to an up-regulation in the expressions of downstream proteins NQO-1 and HO-1, which are regulated by NRF2. Moreover, this intervention exhibited a significant amelioration in pancreatic {beta} cell damage associated with T1DM, accompanied by an elevation in insulin secretion and a reduction in the expression levels of apoptosis and oxidative stress related markers. Furthermore, ML385, an NRF2 inhibitor, reversed these effects of EUG. The present study suggested that EUG exerted protective effects on pancreatic {beta} cells in T1DM by attenuating apoptosis and oxidative stress through the activation of the NRF2 signaling pathway. Consequently, EUG holds great promise as a potential therapeutic candidate for T1DM.

pharmacology and toxicology↗

bioRxiv2024

Nephrectomy and high-salt diet inducing pulmonary hypertension and kidney damage by increasing Ang II concentration in rats

BackgroundPulmonary hypertension (PH) is a common complication in patients with chronic kidney disease (CKD), affecting prognosis. However, the pathogenesis is not clear, and the lack of a stable animal model is a significant factor. MethodsIn this study, a rat model of chronic kidney disease with pulmonary hypertension (CKD-PH) was developed through 5/6 nephrectomy combined with a high-salt diet. The models hemodynamics and pathological changes in multiple organs were dynamically assessed. Lung tissues and serum were collected from the model rats to measure the expression of ACE2, the expression levels of vascular active components related to the renin-angiotensin-aldosterone system (RAAS), and changes in the serum metabolic profile of the model. ResultsAfter 14 weeks post-surgery, the CKD-PH rat model exhibited significant changes in hemodynamic parameters indicative of pulmonary arterial hypertension, along with alterations such as right ventricular hypertrophy. However, no evidence of pulmonary vascular remodeling was observed. An imbalance in the renin-angiotensin-aldosterone system was identified in the CKD-PH rat models. Downregulation of ACE2 expression was observed in pulmonary tissues. The serum metabolic profile of the CKD-PH rat models showed distinct differences compared to the sham surgery group. ConclusionsThe development of pulmonary arterial hypertension in CKD-PH rats may be primarily attributed to the disruption of the renin-angiotensin-aldosterone system (RAAS), coupled with a decrease in ACE2 expression in pulmonary vascular endothelial tissues and metabolic disturbances.

pathology↗

bioRxiv2023

DNA origami assembled spheroid for evaluating cytotoxicity and infiltration of chimeric antigen receptor macrophage (CAR-M)

Chimeric antigen receptor (CAR) T-cell therapies have shown remarkable results in patients with hematological malignancies. However, their success in treating solid tumors has been limited. As an alternative candidate for the CAR approach, CAR-macrophages (CAR-M) have demonstrated activation and phagocytosis directed by tumor antigens, showing promise in the treatment of solid tumors. Nevertheless, the mechanisms by which CARs direct tumor chemotaxis and invasion of CAR-M remain poorly understood. In this study, we aim to investigate the role of CARs in CAR-M attachment and infiltration using 3D tumor micro-spheroids, which were created by utilizing a novel nucleic acid nanostructures decorated living cells (NACs) based origami assembly technique. First, the effectiveness of phagocytosis and killing conducted by CAR-M was validated in the conventional 2D well/plate-surface culture models. Then,peripheral blood mononuclear cell (PBMC) invasion assay confirmed that the 3D tumor micro-spheroids were feasible for cell invasion. Finally, our results demonstrated that CAR-M exhibited higher invasion and killing capacity in 3D tumor micro-spheroids. In summary, the 3D NACs-origami assembled tumor spheroid model provides a suitable platform for target screening and pharmacodynamic evaluation of CAR-M.

bioengineering↗

bioRxiv2022

Cell-type-specific co-expression inference from single cell RNA-sequencing data

The inference of gene co-expressions from microarray and RNA-sequencing data has led to rich insights on biological processes and disease mechanisms. However, the bulk samples analyzed in most studies are a mixture of different cell types. As a result, the inferred co-expressions are confounded by varying cell type compositions across samples and only offer an aggregated view of gene regulations that may be distinct across different cell types. The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. However, the high sequencing depth variations and measurement errors in scRNA-seq data present significant challenges in inferring cell-type-specific gene co-expressions, and these issues have not been adequately addressed in the existing methods. We propose a statistical approach, CS-CORE, for estimating and testing cell-type-specific co-expressions, built on a general expression-measurement model that explicitly accounts for sequencing depth variations and measurement errors in the observed single cell data. Systematic evaluations show that most existing methods suffer from inflated false positives and biased co-expression estimates and clustering analysis, whereas CS-CORE has appropriate false positive control, unbiased co-expression estimates, good statistical power and satisfactory performance in downstream co-expression analysis. When applied to analyze scRNA-seq data from postmortem brain samples from Alzheimers disease patients and controls and blood samples from COVID-19 patients and controls, CS-CORE identified cell-type-specific co-expressions and differential co-expressions that were more reproducible and/or more enriched for relevant biological pathways than those inferred from other methods.

bioinformatics↗

bioRxiv2022

Mutation-induced infections of phage-plasmids

Phage-plasmids are extra-chromosomal elements that act both as plasmids and as phages, whose eco-evolutionary dynamics remain poorly constrained. Here, we show segregational drift and loss- of-function mutations play key roles in the infection dynamics of a cosmopolitan phage-plasmid, allowing it to create continuous productive infections in a population of marine Roseobacter. Recurrent loss-of-function mutations in the phage repressor that controls prophage induction led to constitutively lytic phage-plasmids that spread rapidly throughout the population. The entire phage-plasmid genome was packaged into virions, which were horizontally transferred by re-infecting lysogenized cells, leading to an increase in phage-plasmid copy number and to a heterozygous phage repressor locus within re-infected cells. While wild-type repressor variants prevented induction of phage-plasmids in a cell, the uneven apportionment of phage-plasmids after cell division (i.e., segregational drift) led to the production of offspring carrying only the constitutively lytic phage-plasmid, thus restarting the lysis-reinfection-segregation life-cycle. Mathematical models and experiments showed that these dynamics lead to a continuous productive infection of the bacterial population in which lytic and lysogenic phage-plasmids coexist. An analysis of marine bacterial genomes shows that the same plasmid backbone here described carries different phages in the environment and disseminates trans-continentally, suggesting that the phage-plasmid strategy is relevant and widespread in nature. Together, our study describes how the interplay between phage infection and plasmid genetics provide a unique eco-evolutionary strategy for phage-plasmids.

microbiology↗

bioRxiv2022

Annotation-free discovery of functional groups in microbial communities

Recent studies have shown that microbial communities are composed of groups of functionally cohesive taxa, whose abundance is more stable and better associated with metabolic fluxes than that of any individual taxon. However, identifying these functional groups in a manner that is independent from error-prone functional gene annotations remains a major open problem. Here, we develop a novel approach that identifies functional groups of taxa in an unsupervised manner, solely based on the patterns of statistical variation in species abundance and environmental parameters. We demonstrate the power of this approach on three distinct data sets. On data of replicate microcosm with heterotrophic soil bacteria, our unsupervised algorithm recovered experimentally validated functional groups that divide metabolic labor and remain stable despite large variation in species composition. When leveraged against the ocean microbiome data, our approach discovered a functional group that combines aerobic and anaerobic ammonia oxidizers, whose summed abundance tracks closely with nitrate concentrations in the water column. Finally, we show that our framework can enable the detection of species groups that are likely responsible for the production or consumption of metabolites abundant in animal gut microbiomes, serving as a hypothesis generating tool for mechanistic studies. Overall, this work advances our understanding of structure-function relationships in complex microbiomes and provides a powerful approach to discover functional groups in an objective and systematic manner.

ecology↗

bioRxiv2022

TME induced TRAIL secretion from engineered macrophages for anti-tumor therapy

Capacity of tumor niche chemotaxis and long-term persistency making macrophage as great vehicles for anti-tumor factor delivery. Macrophages-based delivery of chemokines or cytokines have been tested for tissue homeostasis and cancer repression. TRAIL as a promising anti-tumor cytokine, made little clinical progress due to limited stability and off-target toxicity. Here we engineered macrophages with tumor micro-environment (TME)-induced trimerized CP1-TRAIL secretion under the TME specific promoter Arg1 (Tri-TRAIL-iM). The Tri-TRAIL-iM cells displayed high specific inducible activity in both cell-based co-culture assay and in tumor baring mice models. Compared to normal TRAIL over-expressed macrophages under none-inducible promoter, Tri-TRAIL-iM infiltrated to tumor sites and showed superior apoptosis induction of cancer cells and tumor growth repression as well as less systemic side effect. This inducible delivery TRAIL strategy can be effectively further applied in clinical studies and can be coupled with other engineered methods to maximize the therapeutic outcomes for solid tumors.

cancer biology↗

bioRxiv2021

All-optical electrophysiology in hiPSC-derived neurons with synthetic voltage sensors

Voltage imaging and "all-optical electrophysiology" in human induced pluripotent stem cell (hiPSC)-derived neurons have opened unprecedented opportunities for high-throughput phenotyping of activity in neurons possessing unique genetic backgrounds of individual patients. While prior all-optical electrophysiology studies relied on genetically encoded voltage indicators, viral transduction of human neurons with large or multiple expression vectors can impact cell function and often lead to massive cell death. Here, we demonstrate an alternative protocol using a synthetic voltage sensor and genetically encoded optogenetic actuator that generate robust and reproducible results. We demonstrate the functionality of this method by measuring spontaneous and evoked activity in three independent hiPSC-derived neuronal cell lines with distinct genetic backgrounds.

neuroscience↗

bioRxiv2020

Investigation of white spot syndrome virus (WSSV) infection in wild crustaceans in the Bohai Sea

The ecological risks of white spot syndrome virus (WSSV), an important aquatic pathogen, has been causing increasing concern recently. A continuous survey on the prevalence of WSSV in the wild crustaceans of the Bohai Sea was conducted in present study. The result of loop-mediated isothermal amplification detection showed that WSSV positivity rates of sampling sites were determined to be 76.73%, 55.0% and 43.75% in 2016, 2017 and 2018, respectively. And the WSSV positivity rates of samples were 17.43%, 12.24% and 7.875% in 2016, 2017 and 2018, respectively. Meanwhile, the investigation revealed that 11 wild species from the sea were identified to be WSSV positive. The WSSV infection in wild crustacean species was confirmed by transmission electron microscopy analysis. The results of this study suggest that WSSV had been colonized in wild species offshore and the impact caused by WSSV to the wild marine ecosystem cannot be ignored.

microbiology↗

bioRxiv2020

Predicting drug-target interactions using multi-label learning with community detection method (DTI-MLCD)

Identifying drug-target interactions (DTIs) is an important step for drug discovery and drug repositioning. To reduce heavily experiment cost, booming machine learning has been applied to this field and developed many computational methods, especially binary classification methods. However, there is still much room for improvement in the performance of current methods. Multi-label learning can reduce difficulties faced by binary classification learning with high predictive performance, and has not been explored extensively. The key challenge it faces is the exponential-sized output space, and considering label correlations can help it. Thus, we facilitate the multi-label classification by introducing community detection methods for DTIs prediction, named DTI-MLCD. On the other hand, we updated the gold standard data set proposed in 2008 and still in use today. The proposed DTI-MLCD is performed on the gold standard data set before and after the update, and shows the superiority than other classical machine learning methods and other benchmark proposed methods, which confirms the efficiency of it. The data and code for this study can be found at https://github.com/a96123155/DTI-MLCD.

bioinformatics↗

bioRxiv2020

A fundamental structure-function mapping in the ocean microbiome

Recent work on microbial communities from various environments has shown that coexisting microorganisms with similar metabolic functions can be combined into high level "functional groups", which explain a larger proportion of variance in abiotic parameters than any individual taxon. However, the general rules by which taxa should be aggregated into functional groups remain elusive. Here, we show that two conditions are required for species-assemblages to explain a higher percentage of variance in abiotic factors than single taxa. 1) consistent taxa-environment correlations, and 2) weak or negative correlations (i.e. complementarity) between taxa. Applying this recipe to the ocean microbiome, we found that the best grouping of taxa is one that partitions it into only two groups, a core and a flexible assemblage. The core assemblage is enriched in Cyanobacteria and oligotrophic heterotrophs, and was strongly correlated to the first principal component of the taxa-sample matrix. The flexible assemblage instead was enriched in metabolically versatile copiotrophs, abundant at higher depths. This simple core / flexible bipartition explained the most variance in abiotic parameters and outperformed annotation-based functional groups as well as individual taxa. It therefore represents the simplest and best grouping of taxa that can be extracted from current ocean microbiome surveys.

ecology↗

bioRxiv2019

Biased Signaling: Distinct Ligand-directed Plasma Membrane Signalsomes Using a Common RGS/G Protein Core

Biased signaling occurs when different ligands that are directed at the same receptor launch different cellular outcomes. Because of their pharmacological importance, we know the most about biased ligands and little is known about other mechanisms to achieve signaling bias. In the canonical animal G protein system, endocytosis of a 7-transmembrane GPCR is mediated by arrestins to propagate or arrest cytoplasmic signaling depending on the bias. In Arabidopsis, GPCRs are not required for G protein coupled signaling because the heterotrimeric G protein complex spontaneously exchanges nucleotide. Instead, the prototype 7-transmembrane Regulator of G Signaling 1 protein AtRGS1 modulates G signaling and through ligand-dependent endocytosis, de-repression of signaling is initiated but canonical arrestins are not involved. Endocytosis initiates from two separate pools of plasma membrane: sterol-dependent domains, possibly lipid rafts, and a clathrin-accessible neighborhood, each with a select set of discriminators, activators, and newly-discovered arrestin-like adaptors. Different trafficking origins and trajectories lead to different cellular outcomes. Thus, compartmentation with its attendant signalosome architecture is a previously unknown mechanism to drive biased signaling.

plant biology↗

bioRxiv2019

DTI-CDF: a CDF model towards the prediction of DTIs based on hybrid features

Drug-target interactions play a crucial role in target-based drug discovery and exploitation. Computational prediction of DTIs has become a popular alternative strategy to the experimental methods for identification of DTIs of which are both time and resource consuming. However, the performances of the current DTIs prediction approaches suffer from a problem of low precision and high false positive rate. In this study, we aimed to develop a novel DTIs prediction method, named DTI-CDF, for improving the prediction precision based on a cascade deep forest model which integrates hybrid features, including multiple similarity-based features extracted from the heterogeneous graph, fingerprints of drugs, and evolution information of target protein sequences. In the experiments, we built five replicates of 10 fold cross-validations under three different experimental settings of data sets, namely, corresponding DTIs values of certain drugs (SD), targets (ST), or drug-target pairs (SP) in the training set are missed, but existed in the test set. The experimental results show that our proposed approach DTI-CDF achieved significantly higher performance than the state-of-the-art methods.

bioinformatics↗

bioRxiv2018

Molecular characterization of the viral structural gene of the first dengue virus type 1 outbreak in Xishuangbanna, a border area of China, Burma and Laos

In the context of recent arbovirus epidemics, dengue fever is becoming a greater concern around the world. In August 2017, Xishuangbanna, which is a border city of China, Burma and Laos, had its first major dengue outbreak. A total of 156 serum samples from febrile patients were collected; 97 DENV positive serum samples were screened out, and viral RNAs were successfully and directly extracted, including 77 cases from China and 20 cases from Myanmar. Phylogenetic analysis revealed that all of the strains were classified as DENV-1. There are eight epidemic dengue strains from Myanmar and 74 from Jinghong, Xishuangbanna, that were classified as cluster 1, which are the most similar to the strain of China Guangzhou 2011. There are three epidemic strains from Xishuangbanna Mengla that were classified as cluster 2, which have the closest relationship to the strain of China Hubei 2014. However, there are 12 epidemic strains from Myanmar that were classified as cluster 3, which have the closest relationship to the strain of Laos from 2008, which shows that there is a recycling epidemic trend of DENV in China. There were 236 mutations in the base, which caused 31 nonsynonymous mutations in the DENV structural protein C/prM/E genes when the strain of Xishuangbanna and Myanmar were compared with the DENV-1SS. There is no clear homologous recombination signal among these stains. Homology modeling possibly predicted a three-dimensional structure of the structural protein of these strains and revealed that they had the same three-dimensional structure and all had five predicted protein binding sites, but there are differences in binding site 434 (DENV-1SS: Thr434, DV-Jinghong: Ser434, DV-Myanmar: Ser434, DV-Mengla: Ser434). The results of the molecular clock phylogenetic and demographic reconstruction analysis show that DENV-1 became highly diversified in 1972 followed by a slightly decreased period until 2017. In conclusion, our study lays the foundation for studying the global evolution and prevalence of DENV.\n\nAuthor SummaryDengue fever (DF) is a mosquito-borne illness caused by a flavivirus. Human infections with Dengue virus (DENV) could cause fever, cutaneous rash and malaise. Xishuangbanna, which is located in the southwestern Yunnan Province and is a border city with China, Burma and Laos, was reported to have outbreak of DENV in 2013 and 2015 with different types. However, there was a large outburst of dengue in May 2017. To understand the genetic characterization, potential source and evolution of the virus, 156 serum samples were analyzed. We focused on: (i) Phylogenetic analysis of the structural protein genes sequences; (ii) Mutation, recombination analysis and predicted protein binding sites of the structural protein genes; (iii) Molecular clock and demographic reconstruction of global dengue virus serotype 1(DENV-1). Our results indicated that this is the first outbreak of DENV-1 in Xishuangbanna, dengue epidemic strains on the Burma border of China show diversification, we found a virulence site changed from I to T(amino acid position: 440), which may lead to weakened virulence of the epidemic strains. We found that the evolution of DENV-1 is dominated by regional evolution. Whats more, DENV-1 became highly diversified in 1972 followed by a slightly decreased period until 2017.

epidemiology↗