Biology subjects

Chen, S.

Publications and source records attributed to Chen, S..

At least 613 records · Page 34Linked to original sources

bioRxiv2022

DeepsmirUD: Precise prediction of regulatory effects on miRNA expression mediated by small molecular compounds using competing deep learning frameworks

Aberrant miRNA expression has pervasively been found to relate to a growing number of human diseases. Therefore, targeting miRNAs to regulate their expression levels has become an important therapy against diseases that stem from the dysfunction of oncogenic pathways regulated by the miRNAs. In recent years, small molecule compounds have demonstrated enormous potential as drugs to regulate miRNA expression (i.e., SM-miR). A clear understanding of the mechanism of action of small molecules on down- and up-regulating miRNA expression allows precise diagnosis and treatment of oncogenic pathways. However, outside of a slow and costly process of experimental determination, computational strategies to assist this in an ad hoc manner have still not been enabled. In this work, we develop, to the best of our knowledge, the first prediction tool, DeepsmirUD, to infer small molecule-mediated regulatory effects on miRNA expression. This method is powered by an ensemble of 12 cutting-edged deep learning frameworks and achieves state-of-the-art performance with AUC values of 0.840/0.969 and AUCPR values of 0.866/0.983 on two independent test datasets. With a complementarily constructed network inference approach based on similarity, we report a significantly improved accuracy of 0.813 in determining regulatory effects of nearly 650 SM-miR relations formed with either novel small molecules or novel miRNAs. By further integrating miRNA-cancer relations, we established a database of potentially pharmaceutical drugs to aid in understanding the drug mechanisms of action in diseases and to offer novel insight into drug repositioning. Taken together, our method shows great promise to assist and accelerate the therapeutic development of potential miRNA targets and small molecule drugs. Furthermore, we have employed DeepsmirUD to predict regulatory effects of a large number of high-confidence SM-miR relations curated from Psmir, which are publicly available through https://github.com/2003100127/deepsmirud and https://rujinlong.github.io/deepsmirud/ alongside the DeepsmirUD standalone package.

bioinformatics↗

bioRxiv2022

Serotyping Salmonella Enteritidis and Typhimurium Using Whole Cell Matrix Assisted Laser Desorption Ionization - Time of Flight Mass Spectrometry (MALDI-TOF MS) through Multivariate Analysis and Artificial Intelligence

Salmonella is one of the most frequent food-borne zoonoses, while Salmonella Typhimurium and Enteritidis are the major serovars of concern in public health. 113 Salmonella strains including 38 S. Enteritidis (SE), 38 S. Typhimurium (ST) and 37 strains of 32 other Salmonella serovars (SG) were tested in quadruplicate by whole-cell MALDI-TOF MS. Ions were studied and aligned from the raw data of mzXML files using Mass-Up (http://www.sing-group.org/mass-up), resulting in 1,741 aligned peaks. Datasets of ions (presence/absence) selected using a home-developed criteria on their specificity and detectability were subjected to multivariate analyses and artificial intelligence tools. Principle Component Analysis based on 88 selected ions separated SE, ST and SG without overlap on the first three principle components. The network and forest based deep learning tools were more sophisticated than the decision tree-based models. Neural Network carried out consistently well in training model, but no advantage was gained over the other models in validation results. HP (high performance) Neural, Support Vector Machine, HP Forest and Gradient Boasting were able to identify SE, ST and SG up to 100% correctly in both training and validation when 88 selected ions were used in analysis. Among them, HP Neural seemed to perform slightly better and relatively stable. Selection of serovar specific ions helps develop serotyping by increasing signal to noise. MALDI-TOF MS used with appropriate data processing strategies and classification tools could be applied to quickly alert when Salmonella serotypes of concern are suspected among routinely processed samples.

microbiology↗

bioRxiv2022

VPS13A and VPS13C influence lipid droplet abundance

Lipid transfer proteins mediate the exchange of lipids between closely apposed membranes at organelle contact sites and play key roles in lipid metabolism, membrane homeostasis, and cellular signaling. A recently discovered novel family of lipid transfer proteins, which includes the VPS13 proteins (VPS13A-D), adopt a rod-like bridge conformation with an extended hydrophobic groove that enables the bulk transfer of membrane lipids for membrane growth. Loss of function mutations in VPS13A and VPS13C cause chorea acanthocytosis and Parkinsons disease, respectively. VPS13A and VPS13C localize to multiple organelle contact sites, including endoplasmic reticulum (ER) - lipid droplet (LD) contact sites, but the functional roles of these proteins in LD regulation remains mostly unexplored. Here, we employ CRISPR-Cas9 genome editing to generate VPS13A and VPS13C knockout cell lines in U-2 OS cells via deletion of exon 2 and introduction of an early frameshift. Analysis of LD content in these cell lines revealed that loss of either VPS13A or VPS13C results in reduced LD abundance under oleate-stimulated conditions. These data implicate VPS13A and VPS13C in LD regulation and raise the intriguing possibility that VPS13A and VPS13C-mediated lipid transfer facilitates LD biogenesis.

cell biology↗

bioRxiv2022

Dermal nerve growth factor is increased in prurigo nodularis compared to atopic dermatitis

BackgroundPrurigo nodularis (PN) is a chronic, pruritic, inflammatory skin disease characterized by hyperkeratotic nodules on the trunk and extremities. While there is growing research on the immunological basis of PN, the neuropathic and structural components of PN lesions are unknown. ObjectiveTo determine the inflammatory, neuropathic, and structural pathways in PN compared to atopic dermatitis (AD). MethodsLesional and non-lesional skin biopsies were collected from 13 PN and 6 AD patients. mRNA and protein expression in biopsies was determined using RNA-Sequencing and immunohistochemistry (IHC), respectively. Differentially expressed genes (DEGs) were identified using the DESeq2 R package and pathway level enrichment was determined using Gene Set Enrichment Analysis. IHC expression was quantified with QuPath followed by statistical comparison with the Students t-test and Mann-Whitney U. ResultsCompared to lesional AD, lesional PN had greater mRNA expression of MMPs, OSM, NGF, IL1{beta}, CXCL2, CXCL5, CXCL8, and insulin-like growth factors, and lower expression of CCL13, CCL26, EPHB1, and collagens. Compared to non-lesional AD, non-lesional PN showed upregulation of keratin-family genes. GSEA revealed that lesional PN had greater keratinization, cornified envelope, myelin sheath, TGF-beta signaling, extracellular matrix disassembly, metalloendopeptidase activity, and neutrotrophin-TRK receptor signaling, while non-lesional PN had higher keratin filament, extracellular structure organization, extracellular matrix disassembly, and angiogenesis. IHC showed increased dermal nerve growth factor (NGF) expression in lesional PN compared to lesional AD (p=0.038), and greater epidermal NGF compared to dermal NGF in non-lesional PN (p=0.014). LimitationsSingle, tertiary care center. ConclusionsPN demonstrated increased neurotrophic and extracellular matrix (ECM) remodeling signatures compared to AD, possibly explaining the morphological differences in their lesions. These signatures may therefore be important components of the PN pathogenesis and may serve as therapeutic targets.

pathology↗

bioRxiv2022

High-Coverage Four-Dimensional Data-Independent Acquisition Proteomics and Phosphoproteomics Enabled by Deep Learning-Driven Multi-Dimensional Prediction

Four-dimensional (4D) data-independent acquisition (DIA)-based proteomics is an emerging technology that has been proven to have high precursor ion sampling efficiency and higher precursor identification specificity. However, the current 4D DIA proteomics is still dependent on the building of project-specific experimental library which is time-consuming and limits the coverage for identification/quantification. Herein, a workflow of 4D DIA proteomics by using the predicted multi-dimensional in silico library was established. A deep learning model Deep4D that could high-accurately predict the CCS and RT of both the unmodified and phosphorylated peptides was developed. By using an integrated 4D in silico library containing millions of peptides, we have identified 25% more protein than using experimental libraries in the DIA proteomics analysis of HeLa cells. We further demonstrate that the introduction of in silico prediction library can greatly complement the experimental library of directly obtained phosphorylated peptides, resulting in a greater increase in the identification of phosphorylated peptides and phosphorylated proteins.

bioinformatics↗

bioRxiv2022

Regulation of protein translation by TRIM21

AbstractRegulation of translation initiation is essential for maintenance of protein homeostasis and typically involves the phosphorylation of translation initiation factor eIF2 in eukaryotes. In response to stressors, cells employ eIF2-dependent signaling to control translation initiation, which regulates multiple biological and physiological processes. However, the precise regulatory mechanism remains unclear. In this study, we focus on the role of TRIM21 in the regulation of protein translation mediated by protein kinase R (PKR), one of the classic kinases that phosphorylates eIF2. TRIM21 deficiency enhances the activation of PKR under different types of stress. TRIM21 interacts with PKR, and the E3 ligase activity of TRIM21 is crucial for stress-triggered PKR inactivation. TRIM21 interacts with the PKR phosphatase PP1 and promotes K6-linked polyubiquitination of PP1 under stresses. Ubiquitination of PP1 augments its interaction with PKR, causing PKR inactivation and subsequent dephosphorylation of eIF2, initiating protein synthesis. Moreover, TRIM21 constitutively restricts viral infection by reversing PKR-mediated inhibition of the protein synthesis of intrinsic antiviral genes. The TRIM21-PP1 axis acts as a newly discovered program that regulates PKR-associated protein synthesis and broadens our knowledge of antiviral genes. Moreover, TRIM21-mediated regulation of PKR activation provides evidence that TRIM21 may anticipate the interferon-dependent immunotherapy. Our study highlights the essential role of TRIM21 in regulating protein translation and may provide a novel target for the treatment of translation-associated diseases.

immunology↗

bioRxiv2022

A novel cuproptosis-related long non-coding RNAs model that effectively predicts prognosis in hepatocellular carcinoma

BackgroundCuproptosis has recently been considered a novel form of programmed cell death. To date, factors crucial to the regulation of this process remain unelucidated. Here, we aimed to identify long-chain non-coding RNAs (lncRNAs) associated with cuproptosis in order to predict the prognosis of patients with hepatocellular carcinoma (HCC). MethodsUsing RNA sequence data from The Cancer Genome Atlas Live Hepatocellular Carcinoma (TCGA-LIHC), a co-expression network of cuproptosis-related mRNAs and lncRNAs was constructed. For HCC prognosis, we developed a cuproptosis-related lncRNA signature (CupRLSig) using univariate Cox, lasso, and multivariate Cox regression analyses. Kaplan-Meier analysis was used to compare overall survival among high- and low-risk groups stratified by median CupRLSig score. Furthermore, comparisons of functional annotation, immune infiltration, somatic mutation, TMB (tumor mutation burden), and pharmacologic options were made between high- and low-risk groups. ResultsOur prognostic risk model was constructed using the cuproptosis-related PICSAR, FOXD2-AS1, and AP001065.1 lncRNAs. The CupRLSig high-risk group was associated with poor overall survival (hazard ratio = 1.162, 95% CI = 1.063- 1.270; p < 0.001). Model accuracy was further supported by receiver operating characteristic and principal component analysis as well as internal validation cohorts. A prognostic nomogram developed considering CupRLSig data and a number of clinical characteristics were found to exhibit adequate performance in survival risk stratification. Mutation analysis revealed that high-risk combinations with high TMB carried worse prognoses. Finally, differences in immune checkpoint expression and responses to chemotherapy as well as in targeted therapy among CupRLSig stratified high- and low-risk groups were explored. ConclusionsThe lncRNA signature constructed in this study is valuable in prognostic estimation in the setting of HCC.

bioinformatics↗

bioRxiv2022

Distinct Single-cell Immune Ecosystems Distinguish True and De Novo HBV-related Hepatocellular Carcinoma Recurrences

Revealing differential tumor immune microenvironment (TIME) characteristics between true versus de novo hepatocellular carcinoma (HCC) recurrence could help optimal development and use of immunotherapies. Here, we studied the TIME of recurrent HBV-related HCCs by 5and VDJ single-cell and bulk RNA-sequencing, flow cytometry, and multiplexed immunofluorescence. Analyses of mutational profiles, evolutionary trajectories, and clonal architecture using whole-exome sequencing identified de novo versus true recurrences, some of which occurred before clinical diagnosis. The TIME of truly recurrent HCCs was characterized by an increased abundance in KLRB1+CD8+ T cells with memory phenotype and low cytotoxicity. In contrast, we found an enrichment in cytotoxic and exhausted CD8+ T cells in the TIME of de novo recurrent HCCs. Transcriptomic and interaction analyses showed an upregulated GDF15 expression level on HCC cells in proximity to dendritic cells, which may have dampened antigen presentation and inhibited anti-tumor immunity in the TIME of truly recurrent lesions. In contrast, we found that myeloid cells crosstalk with T cells mediated T cell exhaustion and immunosuppression in the TIME of de novo recurrent HCC. In conclusion, our results support genomic diagnosis and immune profiling for guiding immunotherapy implementation based on the type of HCC recurrence and TIME. HighlightsO_LITruly recurrent lesions are seeded before primary tumor diagnosis, and that de novo cancer can occur earlier than the clinically used 2-year limit. C_LIO_LIScRNA-seq unravels distinct immune ecosystems in true versus de novo HCC recurrences, highlighting the need for different immunotherapy strategies for two types of HCC recurrence. C_LIO_LICD8+ T cells in de novo recurrence displayed cytotoxic and exhausted phenotypes while those in truly recurrent lesions showed a memory phenotype with weak cytotoxicity. C_LIO_LIHCC cells expressing the inhibitory molecule GDF15 were in the proximity of DCs only in truly recurrent lesions. C_LIO_LIHigh GDF15 expression level was associated with truly recurrent HCC and worse prognosis. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=186 SRC="FIGDIR/small/494526v1_ufig1.gif" ALT="Figure 1"> View larger version (71K): org.highwire.dtl.DTLVardef@1b76bf0org.highwire.dtl.DTLVardef@10f889aorg.highwire.dtl.DTLVardef@d16b52org.highwire.dtl.DTLVardef@dceb7a_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

Combined small molecule treatment accelerates timing of maturation in human pluripotent stem cell-derived neurons

The maturation of human pluripotent stem cell (hPSC)-derived neurons mimics the protracted timing of human brain development, extending over months and years to reach adult-like function. Prolonged in vitro maturation presents a major challenge to stem cell-based applications in modeling and treating neurological disease. We designed a high-content imaging assay based on morphological and functional readouts in hPSC-derived cortical neurons to reveal underlying pathways and to identify chemicals capable of accelerating neuronal maturation. Probing a library of 2688 bioactive drugs, we identified multiple compounds that drive neuronal maturation including inhibitors of LSD1 and DOT1L and activators of calcium-dependent transcription. A cocktail of 4 factors GSK-2879552, EPZ-5676, NMDA and Bay K 8644, which we collectively termed GENtoniK, triggered maturation across all assays tested including measures of synaptic density, electrophysiology and transcriptomics. Remarkably, GENtoniK was similarly effective in enhancing neuronal maturation in 3D cortical organoids and in spinal motoneurons, and improved aspects of cell maturation in non-neural lineages such as melanocytes and pancreatic beta cells. These results demonstrate that the maturation of multiple hPSC-derived cell types can be enhanced by simple pharmacological intervention and suggests that some of the mechanisms controlling the timing of human maturation are shared across lineages.

neuroscience↗

bioRxiv2022

Development and Application of a Novel Simple Sequence Repeat Mining Algorithm Based on Regular Expression

Simple sequence repeats (SSRs) are molecular genetic markers that are powerful tools in genomics studies; SSR markers are routinely mined as a part of genetic workflows. Here, we developed a novel SSR mining algorithm based on regular expression that can reduce the complexity of commonly used SSR mining software. We used the following SSR mining regular expression: ({i, j}?) (\1) {k}, where i and j denote the minimum and maximum lengths of the motifs of the SSR sequence, respectively, and k is the minimum number of repeat motifs. From this SSR mining algorithm, we developed an SSR sequence analysis software (named "regexSSRw") that is capable of mining eligible SSR loci from FASTA format sequences; regexSSRw can be accessed at https://github.com/renm79/rgxSSRw. This SSR mining algorithm can aid a range of applications, from being used by programmers in the development of SSR mining software to being implemented by scholars into their SSR marker workflow.

bioinformatics↗

bioRxiv2022

The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit in humans

The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped in the last few decades. However, the pivotal brain nodes and directed casual regulation within this inhibitory circuit in humans remains controversial. Here, we capitalize on recent progress in robust and biologically plausible directed causal modelling (DCM-PEB) and a large fMRI response inhibition dataset (n=218) to determine key nodes, their causal regulation and modulation via biological variables (sex) and inhibitory performance in the inhibitory control circuit encompassing the right inferior frontal gyrus (rIFG), caudate nucleus (rCau), globus pallidum (rGP) and thalamus (rThal).The entire neural circuit exhibited high intrinsic connectivity and an increasing rIFG inflow and its causal regulation over the rCau and rThal during response inhibition. In addition, sex and behavioral performance influenced the architecture of the regulatory circuits such that women displayed increased rThal self-inhibition and decreased rThal to GP modulation, while better inhibitory performance was associated with stronger rThal to rIFG communication. Furthermore, control analyses did not reveal a similar key communication in a left lateralized model. Together these findings indicate a pivotal role of the rIFG as input and causal regulator of subcortical response inhibition nodes.

neuroscience↗

bioRxiv2022

Privacy-preserving integration of multiple institutional data for single-cell type identification with scPrivacy

The rapid accumulation of large-scale single-cell RNA-seq datasets from multiple institutions presents remarkable opportunities for automatically cell annotations through integrative analyses. However, the privacy issue has existed but being ignored, since we are limited to access and utilize all the reference datasets distributed in different institutions globally due to the prohibited data transmission across institutions by data regulation laws. To this end, we present scPrivacy, which is the first and generalized automatically single-cell type identification prototype to facilitate single cell annotations in a data privacy-preserving collaboration manner. We evaluated scPrivacy on a comprehensive set of publicly available benchmark datasets for single-cell type identification to stimulate the scenario that the reference datasets are rapidly generated and distributed in multiple institutions, while they are prohibited to be integrated directly or exposed to each other due to the data privacy regulations, demonstrating its effectiveness, time efficiency and robustness for privacy-preserving integration of multiple institutional datasets in single cell annotations.

bioinformatics↗

bioRxiv2022

Alignment-free metal ion-binding site prediction from protein sequence through pretrained language model and multi-task learning

More than one-third of the proteins contain metal ions in the Protein Data Bank. Correct identification of metal ion-binding residues is important for understanding protein functions and designing novel drugs. Due to the small size and high versatility of metal ions, it remains challenging to computationally predict their binding sites from protein sequence. Existing sequence-based methods are of low accuracy due to the lack of structural information, and time-consuming owing to the usage of multi-sequence alignment. Here, we propose LMetalSite, an alignment-free sequence-based predictor for binding sites of the four most frequently seen metal ions (Zn2+, Ca2+, Mg2+ and Mn2+). LMetalSite leverages the pretrained language model to rapidly generate informative sequence representations and employs transformer to capture long-range dependencies. Multi-task learning is adopted to compensate for the scarcity of training data and capture the intrinsic similarities between different metal ions. LMetalSite was shown to surpass state-of-the-art structure-based methods by more than 19.7%, 14.4%, 36.8%, and 12.6% in AUPR on the four independent tests, respectively. Further analyses indicated that the self-attention modules are effective to learn the structural contexts of residues from protein sequence.

bioinformatics↗

bioRxiv2022

Polo-like kinase-1 Inhibitors and the Antiandrogen Abiraterone Synergistically Disrupt Mitosis and Kill Cancer Cells of Disparate Origin Independently of Androgen Receptor Signaling

Abiraterone, a standard treatment for metastatic castrate-resistant prostate cancer (mCRPC), slows disease progression by abrogating androgen synthesis and antagonizing the androgen receptor (AR). We report that inhibitors of the mitotic kinase Plk1, including the clinically active third-generation Plk1 inhibitor onvansertib, when co-administered with abiraterone, synergistically kill cancer cells from a wide variety of tumor types in an androgen-independent manner, both in vitro and in vivo. Abiraterone treatment alone results in defects in mitotic spindle orientation, failure of complete chromosome condensation, and upregulation of mitosis and mitotic-spindle related gene sets independently of its effects on AR signaling. These effects, while mild following abiraterone monotherapy, result in profound sensitization to the anti-mitotic effects of Plk1 inhibition, leading to spindle assembly checkpoint-dependent mitotic cell death and entosis. In a murine PDX model of mCRPC, combined onvansertib and abiraterone resulted in enhanced mitotic arrest and dramatic inhibition of tumor cell growth compared to either agent alone. STATEMENT OF SIGNIFICANCEA phase 2 clinical trial is underway (NCT03414034) testing combined Plk1 inhibitor onvansertib and abiraterone in mCRPC patients with nascent abiraterone resistance. Our work establishes a mechanistic basis for that trial and indicates that combined abiraterone and onvansertib co-treatment may have broad utility for cancer treatment beyond mCRPC.

cancer biology↗

bioRxiv2022

Long-term ecological and evolutionary dynamics in the gut microbiomes of carbapenemase-producing Enterobacteriaceae colonized subjects

Long-term colonization of the gut microbiome by carbapenemase-producing Enterobacteriaceae (CPE) is a growing area of public health concern as it can lead to community transmission and rapid increase in cases of life-threatening CPE infections. Leveraging the observation that many subjects are decolonized without interventions within a year, we used longitudinal shotgun metagenomics (up to 12 timepoints) for detailed characterization of ecological and evolutionary dynamics in the gut microbiome of a cohort of CPE-colonized subjects and family members (n=46; 361 samples). Subjects who underwent decolonization exhibited a distinct ecological shift marked by recovery of microbial diversity, key commensals and anti-inflammatory pathways. In addition, colonization was marked by elevated but unstable Enterobacteriaceae abundances, which exhibited distinct strain-level dynamics for different species (Escherichia coli and Klebsiella pneumoniae). Finally, comparative analysis with whole genome sequencing data from CPE isolates (n=159) helped identify sub-strain variation in key functional genes and the presence of highly similar E. coli and K. pneumoniae strains with variable resistance profiles and plasmid sharing. These results provide an enhanced view into how colonization by multi-drug resistant bacteria associates with altered gut ecology and can enable transfer of resistance genes, even in the absence of overt infection and antibiotic usage.

genomics↗

bioRxiv2022

Simultaneous and sequential multi-species coronavirus vaccination

Although successful COVID-19 vaccines have been developed, multiple pathogenic coronavirus species exist, urging for development of multi-species coronavirus vaccines. Here we developed prototype LNP-mRNA vaccine candidates against SARS-CoV-2 (Delta variant), SARS-CoV and MERS-CoV, and test how multiplexing of these LNP-mRNAs can induce effective immune responses in animal models. A triplex scheme of LNP-mRNA vaccination induced antigen-specific antibody responses against SARS-CoV-2, SARS-CoV and MERS-CoV, with a relatively weaker MERS-CoV response in this setting. Single cell RNA-seq profiled the global systemic immune repertoires and the respective transcriptome signatures of multiplexed vaccinated animals, which revealed a systemic increase in activated B cells, as well as differential gene expression signatures across major adaptive immune cells. Sequential vaccination showed potent antibody responses against all three species, significantly stronger than simultaneous vaccination in mixture. These data demonstrated the feasibility, antibody responses and single cell immune profiles of multi-species coronavirus vaccination. The direct comparison between simultaneous and sequential vaccination offers insights on optimization of vaccination schedules to provide broad and potent antibody immunity against three major pathogenic coronavirus species. One sentence summaryMultiplexed mRNA vaccination in simultaneous and sequential modes provide broad and potent immunity against pathogenic coronavirus species.

immunology↗

bioRxiv2022

m6A epitranscriptomic modification regulates neural progenitor-to-glial cell transition in the retina

N6-methyladenosine (m6A) is the most prevalent mRNA internal modification and has been shown to regulate the development, physiology and pathology of various tissues. However, the functions of the m6A epitranscriptome in the visual system remain unclear. In this study, using a retina-specific conditional knockout mouse model, we show that retinas deficient in Mettl3, the core component of the m6A methyltransferase complex, exhibit structural and functional abnormalities beginning at the end of retinogenesis. Immunohistological and scRNA-seq analyses of retinogenesis processes reveal that retinal progenitor cells (RPCs) and Muller glial cells are the two cell types primarily affected by Mettl3 deficiency. Integrative analyses of scRNA-seq and MeRIP-seq data suggest that m6A fine-tunes the transcriptomic transition from RPCs to Muller cells by promoting the degradation of RPC transcripts, the disruption of which leads to abnormalities in late retinogenesis and compromises the glial functions of Muller cells. Finally, overexpression of m6A-regulated RPC-enriched transcripts in late RPCs partially recapitulates the Mettl3-deficient retinal phenotype. Collectively, our study reveals an epitranscriptomic mechanism governing progenitor-to-glial cell transition during late retinogenesis, which is essential for the homeostasis of the mature retina. The mechanism revealed in this study might also apply to other nervous systems.

developmental biology↗

bioRxiv2022

A transcriptional complex of FtMYB102 and FtbHLH4 coordinately regulates the accumulation of rutin in Fagopyrum tataricum

Tartary buckwheat is rich in flavonoids, which not only play an important role in plant-environment interaction, but are also beneficial to human health. Rutin is a therapeutic flavonol which is massively accumulated in Tartary buckwheat. It has been demonstrated that transcription factors control rutin biosynthesis. However, the transcriptional regulatory network of rutin is not fully clear. In this study, through transcriptome and target metabolomics, we validated the role of FtMYB102 and FtbHLH4 TFs at the different developmental stages of Tartary buckwheat. The elevated accumulation of rutin in the sprout appears to be closely associated with the expression of FtMYB102 and FtHLH4. Yeast two-hybrid, transient luciferase activity and co-immunoprecipitation demonstrated that FtMYB102 and FtbHLH4 can interact and form a transcriptional complex. Moreover, yeast one-hybrid showed that both FtMYB102 and FtbHLH4 directly bind to the promoter of chalcone isomerase (CHI), and they can coordinately induce CHI expression as shown by transient luciferase activity assay. Finally, we transferred the FtMYB102 and FtbHLH4 into the hairy roots of Tartary buckwheat and found that they both can promote the accumulation of rutin. Our results indicate that FtMYB102 and FtbHLH4 can form a transcriptional complex by inducing CHI expression to coordinately promote the accumulation of rutin.

plant biology↗