Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 955 records · Page 53Linked to original sources

bioRxiv2021

Metabolic breakdown of non-small cell lung cancers by mitochondrial HSPD1 targeting

The identification of novel targets is of paramount importance to develop more effective drugs and improve the treatment of non-small cell lung cancer (NSCLC), the leading cause of cancer-related deaths worldwide. Since cells alter their metabolic rewiring during tumorigenesis and along cancer progression, targeting key metabolic players and metabolism-associated proteins represents a valuable approach with a high therapeutic potential. Metabolic fitness relies on the functionality of heat shock proteins (HSPs), molecular chaperones that facilitate the correct folding of metabolism enzymes and their assembly in macromolecular structures. Here, we show HSPD1 (HSP60) as a survival gene ubiquitously expressed in NSCLC and associated with poor patients prognosis. HSPD1 knockdown or its chemical disruption by the small molecule KHS101 induces a drastic breakdown of oxidative phosphorylation, and suppresses cell proliferation both in vitro and in vivo. By combining drug profiling with transcriptomics and through a whole-genome CRISPR/Cas9 screen, we demonstrate that HSPD1-targeted anti-cancer effects are dependent on OXPHOS and validated molecular determinants of KHS101 sensitivity, in particular, the creatine-transporter SLC6A8 and the subunit of the cytochrome c oxidase complex COX5B. These results highlight mitochondrial metabolism as an attractive target and HSPD1 as a potential theranostic marker for developing therapies to combat NCSLC. SignificanceHSPD1 elimination or disruption interferes with NSCLC metabolic activity causing a strong OXPHOS-dependent energetic breakdown, which the cancer cells fail to overcome, highlighting HSPD1 as a potential theranostic marker for improving lung cancer therapy.

cancer biology↗

bioRxiv2021

Network diffusion for scalable embedding of massive single-cell ATAC-seq data

With the rapid development of single-cell ATAC-seq technology, it has become possible to profile the chromatin accessibility of massive individual cells. However, it remains challenging to characterize their regulatory heterogeneity due to the high-dimensional, sparse and near-binary nature of data. Most existing data representation methods were designed based on correlation, which may be ill-defined for sparse data. Moreover, these methods do not well address the issue of excessive zeros. Thus, a simple, fast and scalable approach is needed to analyze single-cell ATAC-seq data with massive cells, address the "missingness" and accurately categorize cell types. To this end, we developed a network diffusion method for scalable embedding of massive single-cell ATAC-seq data (named as scAND). Specifically, we considered the near-binary single-cell ATAC-seq data as a bipartite network that reflects the accessible relationship between cells and accessible regions, and further adopted a simple and scalable network diffusion method to embed it. scAND can take information from similar cells to alleviate the sparsity and improve cell type identification. Extensive tests and comparison with existing methods using synthetic and real data as benchmarks demonstrated its distinct superiorities in terms of clustering accuracy, robustness, scalability and data integration. AvailabilityThe Python-based scAND tool is freely available at http://page.amss.ac.cn/shihua.zhang/software.html.

bioinformatics↗

bioRxiv2021

In vivo co-registered hybrid-contrast imaging by successive photoacoustic tomography and magnetic resonance imaging

Magnetic resonance imaging (MRI) and photoacoustic tomography (PAT) are two advanced imaging modalities that offer two distinct image contrasts: MRI has a multi-parameter contrast mechanism that provides excellent anatomical soft tissue contrast, whereas PAT is capable of mapping tissue physiological metabolism and exogenous contrast agents with optical specificity. Attempts have been made to integrate these two modalities, but rigid and reliable registration of the images for in vivo imaging is still challenging. In this paper, we present a complete hardware-software solution for the successive acquisition and co-registration of PAT and MRI images in in vivo animal studies. Based on commercial PAT and MRI scanners, our solution includes a 3D-printed dual-modality animal imaging bed, a 3-D spatial image co-registration algorithm with bi-model markers, and a robust modality switching protocol for in vivo imaging studies. Using the proposed solution, we successfully demonstrated co-registered hybrid-contrast PAT-MRI imaging that simultaneously display multi-scale anatomical, functional and molecular characteristics on healthy and cancerous living mice. Week-long longitudinal dual-modality imaging of tumor development reveals information on size, border, vascular pattern, blood oxygenation, and molecular probe metabolism of the tumor micro-environment at the same time. Additionally, by incorporating soft-tissue information in the co-registered MRI image, we further show that PAT image quality could be enhanced by MRI-guided light fluence correction. The proposed methodology holds the promise for a wide range of pre-clinical research applications that benefit from the PAT-MRI dual-modality image contrast.

bioengineering↗

bioRxiv2021

Aberrant Temporal-spatial Patterns to Sad expressions in Major Depressive Disorders via Hidden Markov Model

BackgroundThe pathological mechanisms of Major depressive disorders (MDD) is associated with over-expressing of negative emotions, and the overall temporal-spatial patterns underlying over-representation in depression still remained to be revealed to date. We hypothesized that the aberrant spatio-temporal attributes of the process of sad expressions relate to MDD and help to detect depression severity. MethodsWe enrolled a total of 96 subjects including 47 MDDs and 49 healthy controls (HCs), and recorded their Magnetoencephalography data under a sad expressions recognition task. A hidden Markov model (HMM) was applied to separate the whole neural activity into several brain states, then to characterize the dynamics. To find the disrupted spatial-temporal features, power estimations and fractional occupancy of each state were contrasted between MDDs and HCs. ResultsThree states were found over the period of emotional stimuli processing procedure. The visual state was mainly distributed in early stage (0 - 270ms) and the limbic state in middle and later stage (270ms - 600ms) of the task, while the fronto-parietal state remained a steady proportion across the whole period. MDDs activated statistically more in limbic system during limbic state (p = 0.0045) and less in frontoparietal control network during fronto-parietal state (p = 5.38*10-5) relative to HCs. Hamilton-Depression-Rating Scale scores was significantly correlated with the predicted severity value using the state descriptors (p = 0.0062, r = 0.3933). DiscussionAs human brain exhibited varied activation patterns under the negative stimuli, MDDs expressed disrupted temporal-spatial activated patterns across varied stages involving the primary visual perception and emotional contents processing compared to HCs, indicting disordered regulation of brain functions. Furthermore, descriptors built by HMM could be potential biomarkers for identifying the severity of depression disorders.

neuroscience↗

bioRxiv2021

A genetically encoded fluorescent biosensor for extracellular L-lactate

To enable investigations of the emerging roles of cell-to-cell shuttling of L-lactate, we have developed an intensiometric green fluorescent genetically encoded biosensor for extracellular L-lactate. We demonstrate that this biosensor, designated eLACCO1.1, enables minimally invasive cellular resolution imaging of extracellular L-lactate in cultured mammalian cells and brain tissue.

molecular biology↗

bioRxiv2021

Optimal transport analysis reveals trajectories in steady-state systems

Understanding how cells change their identity and behaviour in living systems is an important question in many fields of biology. The problem of inferring cell trajectories from single-cell measurements has been a major topic in the single-cell analysis community, with different methods developed for equilibrium and non-equilibrium systems (e.g. haematopoeisis vs. embryonic development). We show that optimal transport analysis, a technique originally designed for analysing time-courses, may also be applied to infer cellular trajectories from a single snapshot of a population in equilibrium. Therefore optimal transport provides a unified approach to inferring trajectories, applicable to both stationary and non-stationary systems. Our method, StationaryOT, is mathematically motivated in a natural way from the hypothesis of a Waddingtons epigenetic landscape. We implemented StationaryOT as a software package and demonstrate its efficacy when applied to simulated data as well as single-cell data from Arabidopsis thaliana root development.

bioinformatics↗

bioRxiv2021

DeepMotifSyn: a deep learning approach to synthesize heterodimeric DNA motifs

MotivationThe cooperativity of transcription factors (TFs) is a widespread phenomenon in the gene regulation system. However, the interaction patterns between TF binding motifs remain elusive. The recent high-throughput assays, CAP-SELEX, have identified over 600 composite DNA sites (i.e. heterodimeric motifs) bound by cooperative TF pairs. However, there are over 25,000 inferentially effective heterodimeric TFs in human cell. It is not practically feasible to validate all heterodimeric motifs due to cost and labour. Therefore, it is highly demanding to develop a fast and accurate computational tool for heterodimeric motif synthesis. ResultsWe introduce DeepMotifSyn, a deep-learning-based tool for synthesizing heterodimeric motifs from monomeric motif pairs. Specifically, DeepMotifSyn is composed of heterodimeric motif generator and evaluator. The generator is a U-Net-based neural network that can synthesize heterodimeric motifs from aligned motif pairs. The evaluator is a machine-learning-based model that can score the generated heterodimeric motif candidates based on the motif sequence features. Systematic evaluations on CAP-SELEX data illustrates that DeepMotif-Syn significantly outperforms the current state-of-the-art predictors. In addition, DeepMotifSyn can synthesize multiple heterodimeric motifs with different orientation and spacing settings. Such a feature can address the shortcomings of previous models. We believe Deep-MotifSyn is a more practical and reliable model than current predictors on heterodimeric motif synthesis. Availability and implementationThe software is freely available at https://github.com/JasonLinjc/deepMotifSyn.

bioinformatics↗

bioRxiv2021

Young and Undamaged rMSA Improves the Longevity of Mice

Improvement of longevity is an eternal dream of human beings. Here we report that a single protein recombinant mouse serum albumin (rMSA) improved the lifespan and healthspan of C57BL/6N mice. The median lifespan extensions were 17.6% for female and 20.3% for male, respectively. The grip strength of rMSA-treated female and male mice increased by 29.6% and 17.4%, respectively. Meanwhile, the percentage of successful escape increased 23.0% in rMSA-treated male mice using the Barnes Maze test. The rMSA used in this study is young and almost undamaged. We define the concept "young and undamaged" to any protein without any unnecessary modifications by four parameters: intact free thiol (if any), no advanced glycation end-product, no carbonylation, and no homocysteinylation. Here "young and undamaged" rMSA is much younger and less damaged than the endogenous serum albumin from young mice at 1.5 months of age. We predict that young and undamaged proteins altogether can further improve the longevity.

biochemistry↗

bioRxiv2021

EZH2 Engages TGFβ Signaling to Promote Breast Cancer Bone Metastasis via Integrin β1-FAK Activation

Bone metastasis is a frequent complication of breast cancer, occurring in about 50-70% of breast cancer patients with late-stage disease. The lack of effective therapy suggests that the precise molecular mechanisms underlying bone metastasis are still unclear. Enhancer of zeste homolog 2 (EZH2) is considered a breast cancer oncogene and its expression is correlated with metastasis of breast cancer, but its function in bone metastasis has not been well explored. Herein we report that EZH2 promotes osteolytic metastasis of breast cancer through regulating transforming growth factor beta (TGF{beta}) signaling, a key pathway in bone metastasis. Knocking down EZH2 decreases bone metastasis incidence and outgrowth in vivo. EZH2 induces cancer cell proliferation and osteoclast maturation, when breast cancer cells are co-cultured with osteoblasts and osteoclasts together in vitro. Mechanistically, EZH2 increases transcription of ITGB1, which encodes for integrin {beta}1. Integrin {beta}1 activates focal adhesion kinase (FAK), which phosphorylates TGF{beta} receptor type I (TGF{beta}RI) at tyrosine 182, thus enhances the binding of TGF{beta}RI to TGF{beta} receptor type II (TGF{beta}RII), therefore activates Smad2 and increases parathyroid hormone-like hormone (PTHLH) expression. Clinically applicable FAK inhibitors but not EZH2 methyltransferase inhibitor effectively inhibits breast cancer bone metastasis in vivo. Overall, our data signify integrin {beta}1-FAK as a new downstream effector of EZH2 in breast cancer cells, and EZH2-integrin {beta}1-FAK axis cooperates with TGF{beta} signaling pathway to promote bone metastasis of breast cancer.

cancer biology↗

bioRxiv2021

Immune deposit and vasculopathy in metabolic-active lung tissues of patients with pulmonary tuberculosis

Metabolic activity in pulmonary lesion is associated with disease severity and relapse risk in tuberculosis. However, the nature of the metabolic activity associated with tuberculosis in humans remains unclear. Previous works indicate that tuberculosis bears resemblance transcriptionally with systemic lupus erythematosus in peripheral blood, except that the plasma cell component was absent in tuberculosis. Here we reported that the missing transcriptional component was present within the metabolic active tissues in the lung of patients with sputum culture-negative tuberculosis, within which increased levels of circulating immune complexes and anti-dsDNA antibodies were found relative to nearby non-metabolic active tissues. Histological examination revealed specific vascular deposition of immune complexes, neutrophil extracellular traps, and vascular necrosis in the metabolic-active tissue. Thus, tuberculosis-initiated metabolic activity was associated with hyperactive antibody responses and vascular pathology, and shared features with systemic lupus erythematosus and other autoimmune diseases. We discussed these observations in the context of earlier literatures demonstrating that similar effects could be induced in humans and animal models by complete freunds adjuvant, the most potent antibody response inducer ever reported. Our small case series, if verified in a larger size study, might help inform host-directed therapies to alleviate disease progression and augment treatment efficacy. IMPORTANCEIn patients with pulmonary tuberculosis, lung tissues were destroyed by a hyperactive inflammatory response towards M. tuberculosis. The mechanisms underlying the inflammatory response are still poorly understood. Using 18F-FDG avidity as a surrogate marker of inflammation, we have identified that hyper-inflamed tissues possessed features associated with systemic lupus erythematosus: gene expression signatures of plasma cell and immunoglobulins and increased levels of anti-dsDNA antibodies, immune deposits, and vasculopathy. This observation might suggest an explanation to why patients with tuberculosis share more gene expression signatures with autoimmune diseases than infectious diseases and why they are more likely to develop autoimmune diseases. Defining the inflammatory responses at the lesion could help inform host-directed therapies to intervene disease progression or even accelerate cure.

immunology↗

bioRxiv2021

Targeting CTP Synthetase 1 to Restore Interferon Induction and Impede Nucleotide Synthesis in SARS-CoV-2 Infection

The newly emerged SARS-CoV-2 caused a global pandemic with astonishing mortality and morbidity. The mechanisms underpinning its highly infectious nature remain poorly understood. We report here that SARS-CoV-2 exploits cellular CTP synthetase 1 (CTPS1) to promote CTP synthesis and suppress interferon (IFN) induction. Screening a SARS-CoV-2 expression library identified ORF7b and ORF8 that suppressed IFN induction via inducing the deamidation of interferon regulatory factor 3 (IRF3). Deamidated IRF3 fails to bind the promoters of classic IRF3-responsible genes, thus muting IFN induction. Conversely, a shRNA-mediated screen focused on cellular glutamine amidotransferases corroborated that CTPS1 deamidates IRF3 to inhibit IFN induction. Functionally, ORF7b and ORF8 activate CTPS1 to promote de novo CTP synthesis while shutting down IFN induction. De novo synthesis of small-molecule inhibitors of CTPS1 enabled CTP depletion and IFN induction in SARS-CoV-2 infection, thus impeding SARS-CoV-2 replication. Our work uncovers a strategy that a viral pathogen couples immune evasion to metabolic activation to fuel viral replication. Inhibition of the cellular CTPS1 offers an attractive means for developing antiviral therapy that would be resistant to SARS-CoV-2 mutation.

microbiology↗

bioRxiv2021

The glycosphingolipid inhibitor eliglustat inhibits autophagy in osteoclasts to increase bone mass and reduce myeloma bone disease

Multiple myeloma (MM) is a fatal hematological malignancy, where the majority of patients are diagnosed with, or develop, destructive and debilitating osteolytic bone lesions. Current treatments for MM bone disease such as the bisphosphonate zoledronic acid can result in deleterious side effects at high doses. In this study, eliglustat, an FDA approved glycosphingolipid inhibitor, was shown to reduce MM bone disease in preclinical models of MM. Mechanistically, eliglustat alters the lipid composition and plasma membrane fluidity and acts as an autophagy flux inhibitor in bone-resorbing osteoclasts (OC). Autophagic degradation of the signaling molecule TRAF3 is key step in OC differentiation; this was prevented by eliglustat in OC precursors. In addition, eliglustat works depend on TRAF3 in vivo. Furthermore, the combination of eliglustat and zoledronic acid was found to have an additive effect to reduce MM bone disease, suggesting the potential for combination therapies that would allow for drug dose reductions. Taken together, this project identifies a novel mechanism in which glycosphingolipid inhibition reduces osteoclastogenesis via autophagy and highlights the translational potential of eliglustat for the treatment of bone loss disorders such as MM. One Sentence SummaryTranslational use of eliglustat as an autophagy inhibitor to limit bone lesions in multiple myeloma.

cell biology↗

bioRxiv2021

Stimulated oxygen transport in tissue by magnetic needles - Physiology of acupuncture

AimTo understand physiology of magnetic needle acupuncture by investigating O2 transport in tissue during needle intervention. MethodsO2 transport in tissue is modeled by utilizing COMSOL with magnetic needle inserted into muscle tissue in a 2D porous media. The damaged tissue has been mimicked by an extracted tissue block with 1st order O2 consumption rate. The convection-diffusion O2 transport in the damaged tissue has been further evaluated by varying magnetic flux density B0 of the needle (0-1 T), myoglobin concentration (0-1 mM), O2 tension (5-100 Torr), O2 consumption rates, tissue permeability (10-12-10-6 m2) and porosity (0.1-0.9). Results1) Active O2 transport carried by interstitial flow is enhanced with the intervention of a magnetic needle by generating a high gradient magnetic field around the tip, which exerts a strong force (104 N/m3) on the diamagnetic interstitial fluid to accelerate the flow. 2) This interstitial flow can reach 30 m/s at B0 = 1T and strongly correlates to the needle B0 and tissue permeability. 3) The needle stirs the interstitial flow can pump O2 flux by 1-2 orders of magnitude compared to that without magnetic field. 4) The enhancement of active O2 transport by magnetic needle is site-specific to the tissue in the vicinity of the tip. This enhancement is more effective in edema condition with a high tissue permeability (>10-9 m2). ConclusionsThe dramatic enhancement of O2 transport to restore the O2 mitochondria metabolism for dysfunctional muscle tissues is the fundamental physiological mechanism of magnetic needle acupuncture.

physiology↗

bioRxiv2021

Molecular mechanism behind the involvement of apple flavonoid glycosyltransferase gene MdGT1 in the color of apple leaves

Nowadays, the plant family 1 UDP-glycosyltransferases (UGTs) are more and more investigated owing to their contribution to the plant secondary metabolism and diverse biological roles. Apple (Malus domestica) is one of the most widely cultivated fruit trees with great economical importance. However, poor knowledge is known about the apple UGTs. In this study, we identified 229 members of family 1 through a genome-wide analysis of the apple UGTs, which were clustered into 18 groups, from A to R. We also performed detailed analysis to 34 apple UGTs with quantitavive RT-PCR, and discovered a number of stress-regulated UGTs. Among them, we characterized the role of MD09G1064900, also named as MdUGT83L3, which is significantly induced by salt and cold. In vivo analysis showed that it has high activity towards cyanidin, and moderate activity towards quercetin and keampferol. The transgenic callus and regenerated apple plants overexpressing MdUGT83L3 showed enhanced tolerance to salt and cold treatments. Overexpression of MdUGT83L3 also increased anthocyanin accumulation in the callus tissues and enhanced ROS clearing upon exposed to salt and cold stresses. Futhermore, via yeast-two-hybrid assay, EMSA and CHIP analysis, we also found that MdUGT83L3 could be directly regualted by MdMYB88. Our study indicated that MdUGT83L3, under the regulation of MdMYB88, plays important roles in salt and cold stress adaptation via modulating flavonoid metabolism in apple.

molecular biology↗

bioRxiv2021

LncRNA XIST knockdown suppresses cell proliferation and promotes apoptosis in diabetic cataract via miR-34a/SMAD2 axis

Emerging evidence has manifested that long non-coding RNAs (lncRNAs) played critical roles in diabetes. The present research aimed to investigate the role and mechanism of XIST on proliferation, migration and apoptosis in diabetic cataract (DC). In the present study, lens epithelial cells (SRA01/04) were treated by high glucose (HG). The levels of XIST, miR-34a and SMAD2 were examined by RT-qPCR. MTT, transwell, wound healing and TUNEL assays were employed to examine cell proliferation, invasion, migration and apoptosis. The interaction between miR-34a and XIST or SMAD2 was verified by luciferase reporter assay. It was found that XIST expression was increased and miR-34a level was decreased in DC tissues and HG-induced SRA01/04 cells. XIST knockdown or miR-34a addition attenuated cell proliferation and migration, and induced apoptosis in SRA01/04 cells under HG. XIST targeted miR-34a and regulated DC progression via miR-34a. SMAD2 was a target gene of miR-34a and was positively modulated by XIST. SMAD2 addition accelerated cell proliferation, migration and inhibited the apoptosis in HG-stimulated SRA01/04 cells, which were abrogated by XIST depletion. In conclusion, XIST facilitated the proliferation, migration and invasion, and inhibited the apoptosis via miR-34a/SMAD2 axis in DC.

microbiology↗

bioRxiv2021

LRH-1 NUTRIGENOMICS: The Provision of Lauric Acid Results in the Endogenous Production of the Liver Receptor Homolog-1 Ligand, Dilauroylphosphatidylcholine, and LRH-1 Transactivation

BackgroundThe unusual phosphatidylcholine species, dilauroylphosphatidylcholine (DLPC), has been reported to bind and activate the orphan nuclear receptor, liver receptor homolog-1 (LRH-1). To date, DLPC has not been reported endogenously in metabolomic databases. ObjectiveHerein, we test the hypothesis that the provision of the acyl constituent of DLPC, lauric acid (C12:0), a saturated fatty acid rich in tropical oils such as coconut oil, will 1) result in endogenous DLPC production and 2) enhance LRH-1 transcriptional activity. MethodsWe measured DLPC following provision of C12:0 to HepG2 cells, C57/BL6J mice, and to healthy human participants in an acute, randomized, controlled cross-over trial. LRH-1fl/fl and LRH-1fl/fl Albumin-Cre mice were used in ex vivo and in vivo approaches. to assess the impact of C12:0 on LRH-1 target gene expression. 1-13C-lauric acid and methyl-d9-choline were used to assess DLPC production dynamics. ResultsDLPC was not observed in any C12:0-free approach. Provision of C12:0 in the culture media or to C57/BL6J mice resulted in the rapid production of DLPC, including DLPCs presence in multiple LRH-1 expressing tissues. Coconut oil-fed human participants exhibited DLPC in postprandial serum samples. Ex vivo and in vivo C12:0 provision resulted in increased mRNA expression of LRH-1 target genes, an effect that was not observed in hepatic knockout mice. Methyl-d9-choline administration revealed a complex reliance on CDP-choline-derived DLPC. ConclusionC12:0 provision results in endogenous production of the LRH-1 ligand, DLPC, and LRH-1 transcriptional activation phenotypes. Our findings highlight pleiotropic effects of lauric acid, a common hypercholesterolemic dietary saturated fatty acid, secondary to LRH-1 agonism.

physiology↗

bioRxiv2021

Predicting Epigenomic Functions of Genetic Variants in the Context of Neurodevelopment via Deep Transfer Learning

Decoding the regulatory effects of non-coding variants is a key challenge in understanding the mechanisms of gene regulation as well as the genetics of common diseases. Recently, deep learning models have been introduced to predict genome-wide epigenomic profiles and effects of DNA variants, in various cellular contexts, but they were often trained in cell lines or bulk tissues that may not be related to phenotypes of interest. This is particularly a challenge for neuropsychiatric disorders, since the most relevant cell and tissue types are often missing in the training data of such models. To address this issue, we introduce a deep transfer learning framework termed MetaChrom that takes advantage of both a reference dataset - an extensive compendium of publicly available epigenomic data, and epigenomic profiles of cell types related to specific phenotypes of interest. We trained and evaluated our model on a comprehensive set of epigenomic profiles from fetal and adult brain, and cellular models representing early neurodevelopment. MetaChrom predicts these epigenomic features with much higher accuracy than previous methods, and than models without the use of reference epigenomic data for transfer learning. Using experimentally determined regulatory variants from iPS cell-derived neurons, we show that MetaChrom predicts functional variants more accurately than existing non-coding variant scoring tools. By combining genome-wide association study (GWAS) data with MetaChrom predictions, we prioritized 31 SNPs for Schizophrenia (SCZ). These candidate SNPs suggest potential risk genes of SCZ and the biological contexts where they act. In summary, MetaChrom is a general transfer learning framework that can be applied to the study of regulatory functions of DNA sequences and variants in any disease-related cell or tissue types. The software tool is available at https://github.com/bl-2633/MetaChrom and a prediction web server is accessible at https://metachrom.ttic.edu/.

bioinformatics↗

bioRxiv2021

SiCEP3, a C-terminally encoded peptides from Setaria italica, promotes ABA import and signaling pathway

C-terminally encoded peptides (CEPs) are small peptides, typically post-translationally modified, and highly conserved in many species. CEPs are known to play roles in inhibition of plant growth and regulation of development, but the mechanisms are not well understood. In this study, we searched for CEP peptides in foxtail millet (Setaria italica). The 14 peptides we identified are divided into two subfamilies. The transcripts of most SiCEPs were more abundant in roots than in other tissues. SiCEP3, SiCEP4, and SiCEP5 were also expressed at high levels in panicles. Moreover, expression of all SiCEPs was induced by biotic stress and phytohormones. SiCEP3 overexpression and application of biosynthetic SiCEP3 both inhibited the growth of seedlings. In the presence of ABA, growth inhibition and ABA content of seedlings increased with the concentration of SiCEP3. Transcripts encoding two ABA transporters and one ABA receptor were induced by SiCEP3, ABA, and the two in combination. Further analysis revealed that SiCEP3 promoted ABA transport via NRT1.2 and ABCG40. In addition, SiCEP3, ABA, or the combination inhibited the kinase activities of CEP receptors CEPR1/2. Taken together, our results indicated that the CEP-CEPR module mediates ABA signaling by regulating ABCG40, NRT1.2, and PYL4 in planta. HighlightSiCEP3, a C-terminally encoded peptide, can promote ABA import and signaling pathway by inhibiting the kinase activity of its receptors under abiotic stress in Setaria italica.

cell biology↗