Biology subjects

Liao, B.

Publications and source records attributed to Liao, B..

18 recordsLinked to original sources

bioRxiv2026

Non-canonical IL-2 signaling facilitates peripheral regulatory T cell differentiation

Non-canonical IL-2 signaling, termed Monoclonal antibody or Matrix-directed Alternative Cytokine Signaling (MACS), is mediated by a CD25-chemokine receptor complex and operates in concert with the canonical JAK-STAT5 pathway; however, its role in T cell homeostasis remains poorly defined. Here, we uncover a role for MACS in regulatory T cell (Treg) differentiation and functional specification. We generated Il2E66K/E66K mice in which CD25-CCR7 assembly is disrupted and IL-2-induced STAT5 phosphorylation is preserved. Immunophenotyping analysis by flow cytometry revealed that MACS deficiency reduces the accumulation of Nrp1- Foxp3+ Tregs in gut-associated lymphoid tissues from 24-weeks-old Il2E66K/E66K mutant mice. Single-cell transcriptomics, functional suppression assays, and in vitro differentiation revealed that MACS engagement drives Treg differentiation and sustains effector Treg programs - marked by robust IL-10 expression - in part via an AP-1-dependent transcriptional network. These findings establish IL-2 MACS as a distinct signal directing peripheral immune tolerance and highlight a potential node for targeted immunomodulation.

immunology↗

bioRxiv2026

Synergistic Inhibition of Notch Signaling and Forced Cell Cycle Re-entry Drive Müller Glia Reprogramming in Uninjured Mouse Retina

In regenerative species, such as teleost fish, Muller glia (MG) autonomously re-enter the cell cycle after injury and give rise to functional retinal neurons. In contrast, the loss of retinal neurons in mammals is irreversible due to the limited proliferative and regenerative ability of MG. Various strategies have been developed to induce proliferation of mature mouse MG with or without injury, yet most MG daughter cells retain glial cell fate. Here, we found that MG progenies maintain high Notch signaling, which may constrain their neurogenic potential. Conditional deletion of Rbpj, the central transcriptional effector of Notch, induced limited MG-to-neuron conversion in mature MG without proliferation. However, Rbpj deletion, combined with forced MG proliferation by overexpressing cyclin D1 and suppressing p27Kip1, significantly promoted MG dedifferentiation and ectopic expression of the neuronal marker Otx2 in MG daughter cells in uninjured mouse retina. Combining Notch inhibition with MG cell cycle re-activation not only increased the numbers of bipolar- and amacrine-like cells generated from MG but also promoted the further differentiation toward ON-cone, OFF-cone, and rod-bipolar subtypes. Single-nucleus RNA and ATAC sequencing data revealed that Notch inhibition facilitated the formation of MG-derived progenitor-like cells while MG proliferation increased chromatin accessibility of neurogenic genes. Notably, most MG-derived cells survived long term despite incomplete maturation. Together, our findings delineate how Notch inhibition and MG proliferation, alone or in combination, influence the regenerative potential of MG in the mammalian retina.

cell biology↗

bioRxiv2025

BCKDK, a novel hypoxia-responsive kinase that exacerbates cerebral ischemia injury

Alterations of circulating amino acid profile have been observed in patients with ischemic stroke. However, whether ischemia disrupts amino acid metabolism in the brain tissue and subsequently potentiates cellular stress and cerebral injury have never been explored. Employing a metabolomics approach combined with metabolic flux analysis, impaired catabolism and significant enrichment of branched-chain amino acids (BCAAs) were identified in mouse primary neuron cells upon oxygen-glucose deprivation. Consistently, BCAA catabolism was also damaged in the brain of mouse with acute ischemic stroke, accompanied with suppressed activity of branched-chain alpha-keto acid dehydrogenase (BCKDH) and upregulation of BCKDH kinase (BCKDK). Furthermore, restoration of BCAA catabolism by suppressing BCKDK via pharmacological inhibitor or silencing RNA dramatically alleviated cerebral ischemia injury in mice. Mechanistically, ischemia induces the expression of BCKDK via hypoxia-inducible factor 1-mediated transcriptional activation and inhibits BCAA conversion into substrates for tricarboxylic acid cycle, contributing to potentiated energy deficiency, glutamate excitotoxicity, and neuronal injury. Collectively, this study identified BCKDK as a novel hypoxia-responsive factor and a promising therapeutic target for cerebral ischemia injury.

molecular biology↗

bioRxiv2025

Identification of senescence-related hub genes and potential therapeutic agents for chronic heart failure

BackgroundChronic heart failure (CHF), the terminal phase of cardiovascular disease progression, has emerged as an increasingly severe global public health concern. Despite current therapeutic approaches aimed at symptom relief, their long-term effectiveness remains limited, urgently necessitating the exploration of novel treatment strategies. This study endeavored to explore the role of cellular senescence in CHF, identify the characteristic genes linked to cellular senescence, and predict potential therapeutic agents. MethodsWe acquired CHF-related datasets from the Gene Expression Omnibus database and cell senescence-related genes from the CellAge database to identify differentially expressed cell senescence-related genes. We then conducted Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to elucidate the functions of these differentially expressed genes, constructed a protein-protein interaction network, and screened hub genes. Using receiver operating curve (ROC) analysis, we developed a diagnostic model based on these hub genes. Furthermore, we constructed networks for the hub genes involving miRNAs, lncRNAs, transcription factors, and drugs. Subsequently, we explored the potential mechanism of action of metformin in the treatment of CHF through molecular docking studies. Lastly, we verified the expression of the hub genes in a doxorubicin-induced CHF model in rats. Results We ultimately identified nine hub genes associated with cellular senescence: STAT1, MMP9, MAP2K1, SOCS1, SDC1, MET, EIF4EBP1, ATF3, and NAMPT. These genes exhibited significant differential expression between CHF and normal tissues. The constructed diagnostic model demonstrated robust diagnostic performance in ROC curve analysis, with an area under the curve exceeding 0.7, thereby providing biomarker support for early CHF diagnosis. Furthermore, we identified a regulatory network comprising 94 lncRNAs, 63 miRNAs, and 11 transcription factors and screened 42 potential therapeutic drugs. Subsequent molecular docking simulations revealed that metformin could effectively bind to the hub genes. Finally, we validated the expression of some hub genes in a rodent CHF model, in which gene expression regulation varied across diverse experimental settings. ConclusionsOur research identified nine genes cellular senescence-related genes with potential roles in CHF pathogenesis, offering fresh perspectives concerning the diagnosis and treatment of CHF.

bioinformatics↗

bioRxiv2025

Genomic analysis reveals the interplay between ABA-GA in determining dormancy duration in groundnut

Groundnut is an important leguminous crop however; its productivity and seed quality are frequently reduced due to lack of fresh seed dormancy (FSD). To address this challenge, a mini-core collection of 184 accessions was phenotyped to identify donors in each agronomic type, in addition to analysing data on whole genome re-sequencing and multi-season phenotypic evaluations to identify stable marker-trait associations (MTAs) associated with FSD. Phenotypic analysis revealed substantial variability in dormancy durations, with days to 50% germination (DFG) ranging from 1 to 30 days. Multi-locus genome-wide association studies (ML-GWAS) identified 27 MTAs in individual seasons and 12 MTAs in pooled seasons data, respectively. Key candidate genes identified included Cytochrome P450 superfamily proteins, protein kinase superfamily proteins, and MYB transcription factors involved in the Abscisic acid (ABA) pathway, as well as F-box interaction domain proteins, ATP-binding ABC transporters, associated with the Gibberellic acid (GA) pathway. SNP-based KASP (Kompetitive Allele-Specific Polymerase chain reaction) markers for 12 SNPs were developed and validated, of these 6 markers (snpAH00577, snpAH00580, snpAH00582, snpAH00585, snpAH00586 and snpAH00588) showed polymorphism between dormant and non-dormant lines. Incorporating favourable dormant alleles into breeding strategies could enable the development of high-yielding cultivars with a dormancy period of 2-3 weeks.

genomics↗

bioRxiv2025

AarMIXTAs: key factors of T-shaped non-glandular trichome development in Artemisia argyi

Trichomes are necessary for stress resistance and metabolite synthesis in plant. T-shaped non-glandular trichomes (TSTs) as the main component of moxa floss, which are the specific characteristics of A. argyi. Here, we observed that TSTs were at an extremely high density on the lower surfaces in A. argyi leaves. The key transcription factors (TFs) involved in regulation of TSTs development of A. argyi were identified through RNA sequencing of TSTs and non-TSTs. The core regulatory genes, AarMIXTAs showed allelic amplification and functional differentiation compared with A. annua, might contribute development of TSTs. The overexpression of AarMIXTA1.2 significantly increased the density of TSTs in transgenic Arabidopsis and may regulate trichome development by regulating the downstream genes, which played an important positively regulatory role in the development of TSTs. This study provides a good reference for the molecular mechanisms related to the development of TSTs and a theoretical basis for the high-yield moxa floss cultivation of A. argyi.

plant biology↗

bioRxiv2024

Deletion of Zyxin Reduces Endothelial Inflammation and Mitigates Atherosclerosis

BACKGROUNDOscillatory shear stress (OSS)-induced endothelial inflammation plays a critical role in the pathogenesis of atherosclerosis. However, the involvement of endothelial zyxin, a mechanosensor, in OSS-associated atherosclerosis and its underlying mechanisms remains unclear. METHODSTo investigate the role of zyxin in vivo, ZyxiniECKOApoE-/- mice were utilized in atherosclerosis model induced by carotid artery ligation; in vitro, endothelial cells were subjected to disturbed flow in Ibidi systerm. RESULTSZyxin was significantly upregulated in the OSS regions of both human and mouse arteries. The specific deletion of zyxin in endothelial cells (ECs) in ApoE-/- (ZyxiniECKOApoE-/-) mice reversed the ECs activation and atherosclerosis induced by OSS. In vitro studies indicated that the absence of zyxin reduced the induction of adhesion molecules and pro-inflammatory cytokines stimulated by OSS. Mechanistic investigations demonstrated that 14-3-3{beta} facilitated yes-associated protein (YAP) phosphorylation at Serine 127, which played a critical role in retaining YAP within the cytoplasm. Under OSS stimulation, zyxin inhibited the phosphorylation of YAP at Serine 127 through its interaction with 14-3-3{beta}, rather than direct regulation of YAP. This inhibition enhanced YAPs nuclear translocation and promoted endothelial inflammation. Furthermore, it was shown that rosuvastatin inhibited zyxin expression in human umbilical vein endothelial cells and the vascular endothelium of ApoE-/- mice. This inhibition led to decreased levels of inflammatory markers and adhesion molecules associated with atherosclerotic lesions observed in the partially ligated left common carotid arteries of ApoE-/- mice. CONCLUSIONSThis study further confirms that zyxin is a mechanoreceptor in endothelial cells and elucidates the indispensable role of the zyxin-14-3-3{beta}-YAP axis in endothelial inflammation and atherogenesis. This indicates that Zyxin plays a crucial role in protecting against atherosclerosis.

cell biology↗

bioRxiv2024

Muller glia cell cycle re-activation by simultaneous cyclin D1 overexpression and p27kip1 knockdown promotes retinal regeneration in mice

Harnessing the regenerative potential of endogenous stem cells to restore lost neurons is a promising strategy for treating neurodegenerative disorders. Muller glia (MG), the primary glial cell type in the retina, exhibit extraordinary regenerative abilities in zebrafish, proliferating and differentiating into neurons post-injury. However, the regenerative potential of mouse MG is limited by their inherent inability to re-enter the cell cycle, constrained by high levels of the cell cycle inhibitor p27Kip1 and low levels of cyclin D1. Here, we report a method to drive robust MG proliferation by adeno-associated virus (AAV)-mediated cyclin D1 overexpression and p27Kip1 knockdown. MG proliferation induced by this dual targeting vector was self-limiting, as MG did not undergo uncontrolled proliferation. As shown by single-cell RNA-sequencing, cell cycle reactivation led to suppression of interferon signaling, activation of reactive gliosis, and downregulation of glial genes in MG. Over time, the majority of the MG daughter cells retained the glial fate, resulting in an expanded MG pool. Interestingly, about 1% MG daughter cells expressed markers for retinal interneurons, suggesting latent neurogenic potential in a small MG subset. By establishing a safe, controlled method to promote MG proliferation in vivo while preserving retinal integrity, this work provides a valuable tool for combinatorial therapies integrating neurogenic stimuli to promote neuron regeneration.

neuroscience↗

bioRxiv2023

Characterization of the Complete Chloroplast Genome Sequences and Phylogenetic Relationships of Four Oil-Seed Camellia spp. and related taxa

Some species in the Sect. Oleifera of the genus Camellia L. known as oil-seed camellia because of their high oil content and economic value. Additional studies aimed at clarifying the phylogenetic relationships and chloroplast genomes of Camellia species are needed to hybridization, as well as improve the breeding, selection and interspecific hybridization of Camellia species. The complete chloroplast genomes (cpDNA) of the four oil-seed camellia species C. semiserrata, C. meiocarpa, C. suaveolens, and C. osmantha were resequenced to clarify their interspecific relationships. These cpDNA had typical tetrad structures, and they were highly conserved in various structural features. The total lengths of the cpDNA ranged from 156,965 to 157,018 bp, and 134 genes were annotated, including 88 protein-coding genes, 37 transfer RNA genes, and 8 messenger RNA genes. The average GC content of these genomes was 37.3%. The codons with the highest and lowest codon usage bias were UUA (which codes for leucine) and AGC (which codes for serine), respectively. The number of simple sequences repeats of the four Camelia species ranged from 38 to 40. Mononucleotide repeats were the most common repeat type, followed by tetranucleotide, trinucleotide, and hexanucleotide repeats. Our phylogenetic analysis of cpDNA, coupled with the results of previous ploidy analyses and artificial interspecific hybridization, revealed that C. semiserrata was most closely related to C. azalea, C. suaveolens was most closely related to C. gauchowensis, C. osmantha was most closely related to C. vietnamensis, and C. meiocarpa was most closely related to C. oleifera. The phylogenetic relationships between oil-seed camellia species with high oil content and economic value were characterized. Our analysis of the cpDNA provided new insights that will aid the use of artificial distant hybridization in camellia breeding programs.

genomics↗

bioRxiv2023

MMD-DTA: A multi-modal deep learning framework for drug-target binding affinity and binding region prediction

AbstractThe prediction of drug-target affinity (DTA) plays an important role in the development of drugs and the discovery of potential drug targets. In recent years, computer-assisted DTA prediction has become an important method in this field. In this work, we propose a multi-modal deep learning framework for drug-target binding affinity and binding region prediction, namely MMD-DTA. The model can predict DTA while unsupervised learning of drug-target binding regions. The experimental results show that MMD-DTA performs better than the existing models on the main evaluation metrics. In addition, external validation results show that MMD-DTA improves the generalization ability of the model by integrating sequence information and structural information of drugs and targets, and the model trained on the benchmark dataset can be well generalized to independent virtual screening tasks. Visualization of drug-target binding region prediction shows the powerful interpretability of MMD-DTA, which has important implications for exploring the functional regions of drug molecules acting on proteins.

bioinformatics↗

bioRxiv2023

Cellular protein painting for structural and binding sites analysis via lysine reactivity profiling with o-phthalaldehyde

The three-dimensional structure and the molecular interaction of proteins determine their roles in many cellular processes. Chemical protein painting with protein mass spectrometry can identify changes in structural conformations and molecular interactions of proteins including their binding sites. Nevertheless, most current protein painting techniques identified protein targets and binding sites of drugs in vitro using cell lysate or purified protein. Here, we screened 11 membrane-permeable lysine-reactive chemical probes for intracellular covalent labeling of endogenous proteins, which reveals ortho-phthalaldehyde (OPA) as the most reactive probe in intracellular environment. An MS workflow was developed and coupled with a new data analysis strategy termed RAPID (Reactive Amino acid Profiling by Inverse Detection) to enhance detection sensitivity. RAPID-OPA successfully identified structural change induced by allosteric drug TEPP-46 on its target protein PKM2, and was applied to profile conformation change of the proteome occurring in cells during thermal denaturation. Application of RAPID-OPA on cells treated with geldanamycin, selumetinib, and staurosporine successfully revealed their binding sites on target proteins. Thus, RAPID-OPA for cellular protein painting permits the identification of ligand-binding sites and detection of protein structural changes occurring in cells. Significance StatementProtein painting can be used to identify changes in the three-dimensional structure and molecular interaction of proteins that govern many cellular processes but are mostly applied to cell lysate or purified protein. We identified lysine reactive probes for the intracellular labeling of endogenous proteins, and developed an MS procedure with new data analysis strategy termed RAPID-OPA to characterize the intracellular conformation change of the proteome during thermal denaturation, and identified structural change mediated by allosteric regulator TEPP-46 on target protein PKM2. Furthermore, the approach could identify ligand binding sites exemplified by labeling of target proteins in cells treated with geldanamycin, selumetinib and staurosporine. Overall, RAPID-OPA for cellular protein painting enables the detection of protein structural changes happening in cells as well as the identification of ligand-binding sites.

cell biology↗

bioRxiv2023

Fully automated and integrated proteomics sample preparation platform for high-throughput drug target identification

With the increased demand of large-cohort proteomic analysis, fast and reproducible sample preparation has become the critical issue that needs to be solved. Herein, we developed a fully automated and integrated proteomics sample preparation workflow (autoSISPROT), enabling the simultaneous processing of 96 samples in less than 2.5 hours. Benefiting from its 96-channel all-in-tip operation, protein digestion, peptide desalting, and TMT labeling could be achieved in a fully automated manner. The autoSISPROT demonstrated good sample preparation performances, including >94% of digestion efficiency, nearly 100% of alkylation efficiency, >98% of TMT labeling efficiency, and >0.9 of intra- and inter-batch Pearson correlation coefficients. Furthermore, by combining with cellular thermal shift assay-coupled to mass spectrometry (CETSA-MS), the autoSISPROT was able to process and TMT-label 40 samples automatically and accurately identify the known target of methotrexate. Importantly, taking advantage of the data independent acquisition and isothermal CETSA-MS, the autoSISPROT was well applied for identifying known targets and potential off-targets of 20 kinase inhibitors by automatedly processing 87 samples, affording over a 10-fold improvement in throughput when compared to classical CETSA-MS. Collectively, we developed a fully automated and integrated workflow for high-throughput proteomics sample preparation and drug target identification.

systems biology↗

bioRxiv2022

Ratiometric NAD+ sensors reveal subcellular NAD+ modulators

Mapping NAD+ dynamics in live cells and human are essential for translating NAD+ interventions into effective therapies. Yet genetically encoded NAD+ sensors with better specificity and pH-resistance are still needed for cost-effective monitoring of subcellular and clinical NAD+. We introduce multicolor, resonance energy transfer-based NAD+ sensors that cover nano- to milli-molar concentration ranges for clinical NAD+ measurement and subcellular NAD+ visualization. The sensors captured the blood NAD+ increase induced by NMN supplementation and revealed the distinct subcellular effects of NAD+ supplements and modulators. Then, the sensors enabled high-throughput screenings for mitochondrial and nucleic NAD+ modulators and identified -GPC, a cognition-related metabolite, induces NAD+ redistribution from mitochondria to nucleus relative to the total adenine nucleotides, which was confirmed by NAD+ FRET microscopy.

bioengineering↗

bioRxiv2022

Genomic legacies of ancient adaptation illuminate the GC-content evolution in bacterial genomes

In conventional views, the bacterial adaptation is characterized by strong purifying selection as well as rapid evolution in changing environments. However, the genomic GC content varies greatly but has some degree of phylogenetic stability. Using 11,083 representative genomes, we report a phylogenetically constrained bimodal distribution of the genomic GC. Results suggest that such divergence of the genomic GC can be well explained by the DNA replication and repair (DRR) system, in which multiple pathways are observed correlated to the genomic GC. The biased conservations of various stress-related genes especially the DRR-related ones imply distinct adaptive evolution of the ancestral lineages of high or low GC clades which may be induced by major environmental changes in early evolution. Furthermore, our findings support that the mutational biases resulted from these legacies of adaptation have changed the course of adaptive evolution in bacteria thus causing great variation in the genomic GC. This study demonstrates the importance of indirect effects from natural selection which may be easily misinterpreted as neutral processes.

evolutionary biology↗

bioRxiv2021

Deep-BGCpred: A unified deep learning genome-mining framework for biosynthetic gene cluster prediction

Natural products produced by microorganisms constitute an important source of essential pharmaceuticals, including antimicrobial and anti-tumor drugs. These bioactive molecules are microbial secondary metabolites synthesized by co-localized genes termed Biosynthetic Gene Clusters (BGCs). The rapid increase of microbial genomics resources, due to the availability of high-throughput sequencing technologies, has spurred the development of computational methods for microbial genome mining for BGC discovery. Current machine learning methods, however, have limited successes in uncovering novel BGCs due to an excessive number of false positives in their predictions. To this end, we propose Deep-BGCpred, a framework that effectively addresses the aforementioned issue by improving a deep learning model termed DeepBGC. The new model embeds multi-source protein family domains and employs a stacked Bidirectional Long Short-Term Memory model to boost accuracy for BGC identifications. In particular, it integrates two customized strategies, sliding window strategy and dual-model serial screening, to improve the models performance stability and reduce the number of false positive in BGC predictions. We compare the proposed model against other well-established methods on common benchmarks and achieve new state-of-the-art results with convincing evidences. We expect that researchers working on genome mining for natural products may be greatly benefited from our newly proposed method, Deep-BGCpred.

bioinformatics↗

bioRxiv2020

The dynamic landscape of parasitaemia dependent intestinal microbiota shifting at species level and the correlated gut transcriptome during Plasmodium yoelii infection

BackgroundMalaria, caused by Plasmodium, is a global life-threatening infection disease especially during the COVID-19 pandemic. However, it is still unclear about the dynamic change and the interactions between intestinal microbiota and host immunity. Here, we investigated the change of intestinal microbiome and transcriptome during the whole Plasmodium infection process in mice to analyze the dynamic landscape of parasitaemia dependent intestinal microbiota shifting and related to host immunity. ResultsThere were significant parasitaemia dependent changes of intestinal microbiota and transcriptome, and the microbiota was significantly correlated to the intestinal immunity. We found that (i) the diversity and composition of the intestinal microbiota represented a significant correlation along with the Plasmodium infection in family, genus and species level; (ii) the up-regulated genes from the intestinal transcriptome were mainly enriched in immune cell differentiation pathways along with the malaria development, particularly, naive CD4+ T cells differentiation; (iii) the abundance of the parasitaemia phase-specific microbiota represented a high correlation with the phase-specific immune cells development, particularly, Th1 cell with family Bacteroidales BS11 gut group, genera Prevotella 9, Ruminococcaceae UCG 008, Moryella and specie Sutterella*, Th2 cell with specie Sutterella*, Th17 cell with family Peptococcaceae, genus Lachnospiraceae FCS020 group and spices Ruminococcus 1*, Ruminococcus UGG 014* and Eubacterium plexicaudatum ASF492, Tfh and B cell with genera Moryella and species Erysipelotrichaceae bacterium canine oral taxon 255. ConclusionThere was a remarkable dynamic landscape of the parasitaemia dependent shifting of intestinal microbiota and immunity, and a notable correlation between the abundance of intestinal microbiota.

immunology↗

bioRxiv2017

Driver Pattern Identification Over The Gene Co-Expression Of Drug Response In Ovarian Cancer By Integrating High Throughput Genomics Data

The multiple types of high throughput genomics data create a potential opportunity to identify driver pattern in ovarian cancer, which will acquire some novel and clinical biomarkers for appropriate diagnosis and treatment to cancer patients. However, it is a great challenging work to integrate omics data, including somatic mutations, Copy Number Variations (CNVs) and gene expression profiles, to distinguish interactions and regulations which are hidden in drug response dataset of ovarian cancer. To distinguish the candidate driver genes and the corresponding driving pattern for resistant and sensitive tumor from the heterogeneous data, we combined gene co-expression modules and mutation modulators and proposed the identification driver patterns method. Firstly, co-expression network analysis is applied to explore gene modules for gene expression profiles via weighted correlation network analysis (WGCNA). Secondly, mutation matrix is generated by integrating the CNVs and somatic mutations, and a mutation network is constructed from this mutation matrix. The candidate modulators are selected from the significant genes by clustering the vertex of the mutation network. At last, regression tree model is utilized for module networks learning in which the achieved gene modules and candidate modulators are trained for the driving pattern identification and modulator regulatory exploring. Many of the candidate modulators identified are known to be involved in biological meaningful processes associated with ovarian cancer, which can be regard as potential driver genes, such as CCL11, CCL16, CCL18, CCL23, CCL8, CCL5, APOB, BRCA1, SLC18A1, FGF22, GADD45B, GNA15, GNA11 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

bioinformatics↗

bioRxiv2017

Inoculation Of Biocontrol Bacteria Alleviated Panax ginseng Replanting Problem

Replanting problem is a common and serious issue hindering the continuous cultivation of Panax plants. Changes in soil microbial community driven by plant species of different ages and developmental stages are speculated to cause this problem. Inoculation of microbial antagonists is proposed to alleviate replanting issues efficiently.\n\nHigh-throughput sequencing revealed that bacterial diversity evidently decreased, and fungal diversity markedly increased in soils of adult ginseng plants in the root growth stage. Relatively few beneficial microbe agents, such as Luteolibacter, Cytophagaceae, Luteibacter, Sphingomonas, Sphingomonadaceae, and Zygomycota, were observed. On the contrary, the relative abundance of harmful microorganism agents, namely, Brevundimonas, Enterobacteriaceae, Pandoraea, Cantharellales, Dendryphion, Fusarium, and Chytridiomycota, increased with pant age. Furthermore, Bacillus subtilis 50-1 was isolated and served as microbial antagonists against pathogenic Fusarium oxysporum of ginseng root-rot, and its biocontrol efficacy was 67.8% using a dual culture assay. The ginseng death rate and relative abundance of Fusarium decreased by 63.3% and 46.1%, respectively, after inoculation with 50-1 in replanting soils. Data revealed that changes in the diversity and composition of rhizospheric microbial communities driven by ginseng of different ages and developmental stages could cause microecological degradation. Biocontrol using microbial antagonists was an effective method for alleviating the replanting problem.\n\nHighlightChanges in rhizospheric microbial communities driven by ginseng plants 13 of different ages and developmental stages could cause microecological degradation. 14 Biocontrol using microbial antagonists effectively alleviated the replanting problem.

microbiology↗