Biology subjects

Shao, Y.

Publications and source records attributed to Shao, Y..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

From sequence to ecology: siderophore-receptor coevolution algorithm predicts bacterial interactions in complex communities

Predicting bacterial social interactions from genome sequences is notoriously difficult. Here, we developed bioinformatic tools to predict whether secreted iron-scavenging siderophores stimulate or inhibit the growth of community members. Siderophores are chemically diverse and can be stimulatory or inhibitory depending on whether bacteria possess or lack corresponding uptake receptors. We focused on 1928 representative Pseudomonas genomes and developed a co-evolution algorithm to match all encoded siderophore synthetases to corresponding receptor gene groups with >90% accuracy based on experimental validation. We derived community-level iron interaction networks to show that selection for siderophore-mediated interactions differs across habitats and lifestyles. Specifically, dense networks of siderophore sharing and competition were observed among environmental (soil/water/plant) strains and non-pathogenic species, while only fragmented networks occurred among human-derived strains and pathogenic species. Altogether, our sequence-to-ecology approach empowers the analyses of social interactions among thousands of bacterial strains and uncovers ways for targeted intervention to microbial communities. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/565711v3_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@60d907org.highwire.dtl.DTLVardef@48756eorg.highwire.dtl.DTLVardef@115aac1org.highwire.dtl.DTLVardef@17d76e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2023

Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewiseconstant rates varying at different epochs in time, to which we refer as episodic birthdeath-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.

evolutionary biology↗

bioRxiv2023

From sequence to molecules: Feature sequence-based genome mining uncovers the hidden diversity of bacterial siderophore pathways

Microbial secondary metabolites are a rich source for pharmaceutical discoveries and play crucial ecological functions. While tools exist to identify secondary metabolite clusters in genomes, precise sequence-to-function mapping remains challenging because neither function nor substrate specificity of biosynthesis enzymes can accurately be predicted. Here we developed a knowledge-guided bioinformatic pipeline to solve these issues. We analyzed 1928 genomes of Pseudomonas bacteria and focused on iron-scavenging pyoverdines as model metabolites. Our pipeline predicted 188 chemically different pyoverdines with nearly 100% structural accuracy and the presence of 94 distinct receptor groups required for the uptake of iron-loaded pyoverdines. Our pipeline unveils an enormous yet overlooked diversity of siderophores (151 new structures) and receptors (91 new groups). Our approach, combining feature sequence with phylogenetic approaches, is extendable to other metabolites and microbial genera, and thus emerges as powerful tool to reconstruct bacterial secondary metabolism pathways based on sequence data. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/564663v5_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1dedad4org.highwire.dtl.DTLVardef@1f0a39eorg.highwire.dtl.DTLVardef@185e345org.highwire.dtl.DTLVardef@10beec6_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2023

Cardiac glycosides restore autophagy flux in an iPSC-derived neuronal model of WDR45 deficiency

Beta-Propeller Protein-Associated Neurodegeneration (BPAN) is one of the commonest forms of Neurodegeneration with Brain Iron Accumulation, caused by mutations in the gene encoding the autophagy-related protein, WDR45. The mechanisms linking autophagy, iron overload and neurodegeneration in BPAN are poorly understood and, as a result, there are currently no disease-modifying treatments for this progressive disorder. We have developed a patient-derived, induced pluripotent stem cell (iPSC)-based midbrain dopaminergic neuronal cell model of BPAN (3 patient, 2 age-matched controls and 2 isogenic control lines) which shows defective autophagy and aberrant gene expression in key neurodegenerative, neurodevelopmental and collagen pathways. A high content imaging-based medium-throughput blinded drug screen using the FDA-approved Prestwick library identified 5 cardiac glycosides that both corrected disease-related defective autophagosome formation and restored BPAN-specific gene expression profiles. Our findings have clear translational potential and emphasise the utility of iPSC-based modelling in elucidating disease pathophysiology and identifying targeted therapeutics for early-onset monogenic disorders.

cell biology↗

bioRxiv2023

Elimination of subtelomeric repeat sequences exerts little effect on telomere functions in Saccharomyces cerevisiae

Telomeres, which are chromosomal end structures, play a crucial role in maintaining genome stability and integrity in eukaryotes. In the bakers yeast Saccharomyces cerevisiae, the X-and Y-elements are subtelomeric repetitive sequences found in all thirty-two and seventeen telomeres, respectively. While the Y-elements serve as a backup for telomere functions in cells lacking telomerase, the function of the X-elements remains unclear. This study utilized the S. cerevisiae strain SY12, which has three chromosomes and six telomeres, to investigate the role of X-elements (as well as Y-elements) in telomere maintenance. Deletion of Y-elements (SY12Y{Delta}), X-elements (SY12XY{Delta}+Y), or both X- and Y-elements (SY12XY{Delta}) did not impact the length of the terminal TG1-3 tracks or telomere silencing. However, inactivation of telomerase in SY12Y{Delta}, SY12XY{Delta}+Y, and SY12XY{Delta} cells resulted in cellular senescence and the generation of survivors. These survivors either maintained their telomeres through homologous recombination-dependent TG1-3 track elongation or underwent microhomology-mediated intra-chromosomal end-to-end joining. Our findings indicate the non-essential role of subtelomeric X-and Y-elements in telomere regulation in both telomerase-proficient and telomerase-null cells and suggest that these elements may represent remnants of S. cerevisiae genome evolution. Furthermore, strains with fewer or no subtelomeric elements exhibit more concise telomere structures and offer potential models for future studies in telomere biology.

genetics↗

bioRxiv2023

Predicting Gene Spatial Expression and Cancer Prognosis: An Integrated Graph and Image Deep Learning Approach Based on HE Slides

Interpreting the tumor microenvironment (TME) heterogeneity within solid tumors presents a cornerstone for precise disease diagnosis and prognosis. However, while spatial transcriptomics offers a wealth of data, ranging from gene expression and spatial location to corresponding Hematoxylin and Eosin (HE) images, to explore the TME of various cancers, its high cost and demanding infrastructural needs significantly limit its clinical application, highlighting the need for more accessible alternatives. To bridge this gap, we introduce the Integrated Graph and Image Deep Learning (IGI-DL) model. This innovation, a fusion of Convolutional Neural Networks and Graph Neural Networks, is designed to predict gene spatial expression using HE images. The IGI-DL model outperforms its predecessors in analyzing colorectal cancer (CRC), breast cancer, and cutaneous squamous cell carcinoma (cSCC) by leveraging both pixel intensity and structural features in images. Significantly, across all cancer types, the IGI-DL model enhances the mean correlation of the top five genes by an average of 0.125 in internal and external test sets, rising from 0.306 to 0.431, surpassing existing state-of-the-art (SOTA) models. We further present a novel risk score derived from a super-patch graph, where gene expression predicted by IGI-DL serves as node features. Demonstrating superior prognostic accuracy, this risk score, with a C-index of 0.713 and 0.741 for CRC and breast cancer, supersedes traditional HE-based risk scores. In summary, the approach augments our understanding of the TME from the aspect of histological images, portending a transformation in cancer prognostics and treatment planning and ushering in a new era of personalized and precision oncology.

bioinformatics↗

bioRxiv2023

In Vivo Three-dimensional Brain Imaging with Chemiluminescence Probes in Alzheimers Disease Models

Optical three-dimensional (3D) molecular imaging is highly desirable for providing precise distribution of the target-of-interest in disease models. However, such 3D imaging is still far from wide applications in biomedical research; 3D brain optical molecular imaging, in particular, has rarely been reported. In this report, we designed chemiluminescence probes with high quantum yields (QY), relatively long emission wavelengths, and high signal-to-noise ratios (SNRs) to fulfill the requirements for 3D brain imaging in vivo. With assistance from density-function theory (DFT) computation, we designed ADLumin-Xs by locking up the rotation of the double-bond via fusing the furan ring to the phenyl ring. Our results showed that ADLumin-5 had a high quantum yield of chemiluminescence and could bind to amyloid beta (A{beta}). Remarkably, ADLumin-5s radiance intensity in brain areas could reach 4x107 photon/s/cm2/sr, which is probably 100-fold higher than most chemiluminescence probes for in vivo imaging. Because of its strong emission, we demonstrated that ADLumin-5 could be used for in vivo 3D brain imaging in transgenic mouse models of Alzheimers disease (AD). Significance StatementAlthough MRI, PET, CT, and SPECT have been routinely used for 3D imaging, including 3D brain imaging, they are considerably expensive. Optical imaging is largely low-cost and high throughput. However, the 3D capacity of optical imaging is always limited. Obviously, optical 3D molecular imaging is highly challenging, particularly for 3D brain imaging. In this report, we provided the first example of 3D brain imaging with chemiluminescence probes ADLumin-Xs, which have advantages in quantum yields (QY), emission wavelengths, and signal-to-noise ratios (SNRs) to fulfill the requirements for 3D brain imaging. And we believe that such 3D capacity is potentially a game-changer for brain molecular imaging in preclinical studies.

bioengineering↗

bioRxiv2023

SRSF1-mediated alternative splicing of Tial1/Tiar is essential for homing and self-renewal in mouse spermatogonial stem cells

AbstractSpermatogonial stem cells (SSCs) are essential for continuous spermatogenesis and male fertility. The underlying mechanisms of alternative splicing (AS) in mouse SSCs are still largely unclear. We demonstrated that SRSF1 is essential for gene expression and splicing in mouse SSCs. Crosslinking immunoprecipitation and sequencing (CLIP-seq) data revealed that spermatogonia-related genes (e.g., Plzf, Id4, Setdb1, Stra8, Tial1/Tiar, Bcas2, Ddx5, Srsf10, Uhrf1, and Bud31) were bound by SRSF1 in the mouse testes. Specific deletion of Srsf1 in mouse germ cells impairs homing of precursor SSCs leading to male infertility. Whole-mount staining data showed the absence of germ cells in the testes of adult conditional knockout (cKO) mice, which indicates Sertoli cell-only syndrome (SCOS) in cKO mice. The expression of spermatogonia-related genes (Gfra1, Pou5f1, Plzf, Dnd1, Stra8, and Taf4b) was significantly reduced in the testes of cKO mice. Moreover, multiomics analysis suggests that SRSF1 may affect survival of spermatogonia by directly binding and regulating Tial1/Tiar expression through AS. In addition, immunoprecipitation mass spectrometry (IP-MS) and co-immunoprecipitation (Co-IP) data showed that SRSF1 interacts with RNA splicing-related proteins (SART1, RBM15, and SRSF10). Collectively, our data reveal the critical role of SRSF1 in spermatogonia survival, which may provide a framework to elucidate the molecular mechanisms of the posttranscriptional network underlying homing of precursor SSCs.

developmental biology↗

bioRxiv2023

Mechanically stimulated osteocytes maintain tumor dormancy in bone metastasis of non-small cell lung cancer by releasing small extracellular vesicles

Although preclinical and clinical studies have shown that exercise can inhibit bone metastasis progression, the mechanism remains poorly understood. Here, we found that non-small cell lung cancer (NSCLC) cells adjacent to bone tissue had a much lower proliferative capacity than the surrounding tumor cells. Subsequently, it was demonstrated that osteocytes, sensing mechanical stimulation generated by exercise, inhibit NSCLC cell proliferation and sustain the dormancy thereof by releasing small extracellular vesicles with tumor suppressor microRNAs, such as miR-99b-3p. Furthermore, mechanical loading of the tibia inhibited the bone metastasis progression of NSCLC. Notably, bone metastasis progression of NSCLC was inhibited by moderate exercise, and combinations with zoledronic acid had additive effects. Moreover, exercise preconditioning effectively suppressed bone metastasis progression. This study significantly advances the understanding of the mechanism underlying exercise-afforded protection against bone metastasis progression.

cancer biology↗

bioRxiv2022

Effect of depth on crowding investigated with a multi-depth plane display

Crowding occurs when the presence of nearby features causes highly visible objects to become unrecognizable. Although crowding has implications for many everyday tasks and the tremendous amounts of research reflect its importance, surprisingly little is known about how depth affects crowding. Most available studies show that stereoscopic disparity reduces crowding, indicating that crowding may be relatively unimportant in three-dimensional environments. However, most previous studies tested only small stereoscopic differences in depth in which disparity, defocus blur, and accommodation are inconsistent with the real world. Using a novel multi-depth plane display, this study investigated how large (0.54 - 2.25 diopters), real differences in target-flanker depth, representative of those experienced between many objects in the real world, affect crowding. Our findings show that large differences in target-flanker depth increased crowding in the majority of observers, contrary to previous work showing reduced crowding in the presence of small depth differences. Furthermore, when the target was at fixation depth, crowding was generally more pronounced when the flankers were behind the target as opposed to in front of it. However, when the flankers were at fixation depth, crowding was generally more pronounced when the target was behind the flankers. These findings suggest that crowding from clutter outside the limits of binocular fusion can still have a significant impact on object recognition and visual perception in the peripheral field.

neuroscience↗

bioRxiv2022

Down-regulated GAS6 impairs synovial macrophage efferocytosis and promotes obesity-associated osteoarthritis

Obesity has always been considered a significant risk factor in OA progression, but the underlying mechanism of obesity-related inflammation in OA synovitis remains unclear. The present study found that synovial macrophages infiltrated and polarized in the obesity microenvironment and identified the essential role of M1 macrophages in impaired macrophage efferocytosis using pathology analysis of obesity-associated OA. The present study revealed that obese OA patients and ApoE-/- mice showed a more pronounced synovitis and enhanced macrophage infiltration in synovial tissue, accompanied by dominant M1 macrophage polarization. Obese OA mice had a more severe cartilage destruction and increased levels of synovial apoptotic cells than OA mice in the control group. Enhanced M1-polarized macrophages in obese synovium decreased growth arrest-specific 6 (GAS6) secretion, resulting in impaired macrophage efferocytosis in synovial apoptotic cells. Intracellular contents released by accumulated apoptotic cells further triggered an immune response and lead to a release of inflammatory factors, such as TNF-, IL-1{beta}, and IL-6, which induce chondrocyte homeostasis dysfunction in obese OA patients. Intra-articular injection of GAS6 restored the phagocytic capacity of macrophages, reduced the accumulation of local apoptotic cells, and decreased the levels of TUNEL- and caspase-3-positive cells, preserving cartilage thickness and preventing the progression of obesity-associated OA. Therefore, blocking M1 macrophage polarization or intra-articular injection of GAS6 is a potential therapeutic strategy for obesity-associated OA.

immunology↗

bioRxiv2022

Cuproptosis is correlated with clinical status, tumor immune microenvironment and immunotherapy in colorectal cancer: a multi-omic analysis

Copper, like double-edged sword, either too little or too much can lead to cell death. Cuproptosis, a novel identified cell death form induced by copper, is characterized by aggregation of lipoylated mitochondrial enzymes and the destabilization of Fe-S cluster proteins. However, the function and potential clinical value of cuproptosis in colorectal cancer remains largely unknown. In this study, 16 cuproptosis-related molecules (CPRMs) were identified and analyzed by transcriptomics, genomics, and single-cell transcriptome profiling from multiple databases. We established two cuproptosis-related molecular phenotypes (CMP1 and 2) to distinguish CRC individuals, in which there were significantly differences in prognosis, biological function, somatic mutation frequency, immune cell infiltration in CRC individuals. A novel cuproptosis-related scoring system (CuproScore) was also constructed to predict the prognosis of CRC individuals, TME and the response to immunotherapy. Of notion, the value of CuproScore was also confirmed in our transcriptome cohort, demonstrating that CRC individuals in the high CuproScore group tended to have higher immune cell infiltrations and higher immune checkpoint expression. We also checked and analyzed the expression and clinical significance of 16 CPRMs in CRC cell lines and CRC tissues. This study indicated that cuproptosis and CPRMs played significant role in CRC progression and in modeling the TME. Inducing cuproptosis may be a useful tool for tumor therapy in the future.

cancer biology↗

bioRxiv2022

A Subtle Balance between Host Selection and Microbial Size Effect Mediates Plant Microbiome Assembly in Mulberry

Breeding toward improved ecological plant-microbiome interactions requires improved knowledge of ecological processes/principles underlying microecological patterns, but these remain elusive. Here, we systematically investigated in-planta biogeographic patterns of plant-associated bacteriome and mycobiome along soil- plant and episphere-endosphere continuum in Morus alba. Microecological patterns in diversity, structure, co-occurrence network, species turnover, and assembly process were revealed and varying between bacteriome and mycobiome, possibly driven by multiple factors including host selection, community cohesion, and particularly size-dependent dispersal limitation. Based on these findings, we hypothesized that host selection historically recruits microbiotas, whereas microbial size affects the subsequent turnovers due to the limited dispersal of larger-size microbes. This hypothesis was supported by datasets from other plant species and confirmed by stochastic dispersal experiments showing that smaller-size microbes are more likely to escape/disperse from endosphere niches, contributing to fleeting niches occupied by larger-size microbes. These findings may open new avenues toward an improved understanding of the dynamics of plant microbiome assembly.

microbiology↗

bioRxiv2022

Relating local connectivity and global dynamics in recurrent excitatory-inhibitory networks

How the connectivity of cortical networks determines the neural dynamics and the resulting computations is one of the key questions in neuroscience. Previous works have pursued two complementary strategies to quantify the structure in connectivity, by specifying either the local statistics of connectivity motifs between small groups of neurons, or by defining network-wide low-rank patterns of connectivity that determine the resulting low-dimensional dynamics. A direct relationship between these two approaches is however currently missing, and in particular it remains to be clarified how local connectivity statistics are related to the global connectivity structure and shape the low-dimensional activity. To bridge this gap, here we develop a method for mapping local connectivity statistics onto an approximate global low-rank structure. Our method rests on approximating the global connectivity matrix using dominant eigenvectors, which we compute using perturbation theory for random matrices. This approach demonstrates that multi-population networks defined from local connectivity properties can in general be approximated by low-rank connectivity with Gaussian-mixture statistics. We specifically apply this method to excitatory-inhibitory networks, and show that it leads to accurate predictions for both the low-dimensional dynamics, and for the activity of individual neurons. Altogether, our approach allows us to disentangle the effects of mean connectivity and reciprocal motifs on the global recurrent feedback, and provides an intuitive picture of how local connectivity shapes global network dynamics. Author summaryThe structure of connections between neurons is believed to determine how cortical networks control behaviour. Current experimental methods typically measure connections between small numbers of simultaneously recorded neurons, and thereby provide information on statistics of local connectivity motifs. Collective network dynamics are however determined by network-wide patterns of connections. How these global patterns are related to local connectivity statistics and shape the dynamics is an open question that we address in this study. Starting from networks defined in terms of local statistics, we develop a method for approximating the resulting connectivity by global low-rank patterns. We apply this method to classical excitatory-inhibitory networks and show that it allows us to predict both collective and single-neuron activity. More generally, our approach provides a link between local connectivity statistics and global network dynamics.

neuroscience↗

bioRxiv2022

CRISPR/Cas9 screens implicate RARA and SPNS1 in doxorubicin cardiotoxicity

Doxorubicin (DOX) is an efficacious chemotherapy compound used to treat various cancers which elicits severe side effects, including heart failure. Uptake of DOX by cardiomyocytes causes metabolic dysfunction and cell death but causal mechanisms remain largely undefined. We applied genome-wide CRISPR/Cas9 knockout screens to discover genetic modifiers of DOX-induced cardiomyocyte cell death, and independently, DOX uptake and clearance. Both screens discovered known and novel factors. In cell death screens and validation studies, loss of retinoic acid receptor- (RARA) predisposed cardiomyocytes to DOX-mediated cell death. Conversely, RARA activation reduced DOX cytotoxicity in wild type cardiomyocytes. RNA-Seq analysis revealed that whilst DOX caused large-scale suppression of metabolic and mitochondrial gene expression, RARA activation mitigated this effect. In DOX accumulation screens, an essential role for lysosomes in DOX clearance was observed. Loss of Sphingolipid Transporter 1 (SPNS1) led to DOX hyperaccumulation, suppression of autophagy, increased DNA damage, and increased cell death. Hence, SPNS1 plays a key role in buffering against DOX accumulation and toxicity. Collectively, our study nominated hundreds of drug-gene interactions, providing a springboard for exploration of causal mechanisms, and a technical framework for future screening campaigns.

cell biology↗

bioRxiv2022

Strong pathogen competition in neonatal gut colonisation

Bacterial pathogen species and their strains that colonise the human gut are generally understood to compete against both each other and the commensal species colonising this ecosystem. However, currently we are lacking a population-wide quantification of strain-level colonisation dynamics for many common bacterial pathogens and the relationship of colonisation potential to prevalence in disease is unknown. In addition, it is unclear how ecological factors might be modulating the dynamics. Here, using a combination of latest high-resolution metagenomics and strain-level genomic epidemiology methods leveraging large genomic reference libraries of key pathogens, we performed a characterisation of the competition (co-exclusion and co-presence) and colonisation dynamics for a longitudinal cohort of neonatal gut microbiomes. We found a strong inter- and intra-species competition dynamic in the gut colonisation process, but also a number of synergistic relationships among several species belonging to genus Klebsiella, which includes the prominent human pathogen Klebsiella pneumoniae. Additionally, we find no evidence of preferential colonisation by hospital-adapted pathogen lineages in either vaginal or caesarean section birth groups. Our analysis also enables the first unbiased assessment of the strain-level colonisation potential of extra-intestinal pathogenic Escherichia coli (ExPEC) in comparison with their potential to cause bloodstream infections. We determined that the established common ExPEC clones ST73 and ST95 are overall significantly more pathogenic than the more recent, globally circulating multi-drug resistant clone ST131, where only a single subclone (ST131-C2) exhibited excess pathogenic potential. Our study highlights the importance of systematic surveillance of bacterial gut pathogens, not only from disease but also from carriage state, to better inform therapies and preventive medicine in the future.

microbiology↗

bioRxiv2022

The mutational landscape of single neurons and oligodendrocytes reveals evidence of inflammation-associated DNA damage in multiple sclerosis

Neuroinflammation has been linked to DNA damage in multiple sclerosis (MS), but its impact on neural cell genomes at nucleotide resolution is unknown. To address this question, we performed single nucleus whole genome sequencing to determine the landscape of somatic mutation in 172 neurons and oligodendrocytes (OLs) extracted from post-mortem brain tissue from 5 MS cases and three controls. We identified two cases with a significant excess of somatic single nucleotide variants (sSNV) in neurons and OLs from MS inflammatory demyelinated lesions. For a case with primary progressive MS, this translated to a 68% increase in sSNV frequency and 32-year equivalent increase in biological age of lesion-resident cells. Mutational signature analysis conducted on all cells revealed that defective DNA repair and transcription-associated DNA damage are important mutagenic mechanism in both neurons and OLs in MS. Our findings provide the first evidence that inflammation in the brains of people with MS is associated with DNA damage, which may have implications for other neurodegenerative diseases and future drug development.

genomics↗

bioRxiv2022

The senescence regulator S40 family members from Caragana intermedia and Arabidopsis thaliana inhibit leaf senescence via promoting cytokinins synthesis

Leaf senescence is regulated by both endogenous hormones and environmental stimuli in a programmed and concerted way. The members of the S40 family have been reported to play roles in leaf senescence. Here we report that overexpression of an S40 family member from Caragana intermedia, CiS40-11, delayed the leaf senescence. Phylogenetic analysis revealed that the CiS40-11 protein had the highest identity with AtS40-5 and AtS40-6 of A. thaliana. CiS40-11 was highly expressed in leaves and was down-regulated after dark treatment. The subcellular localization analysis showed that CiS40-11 was a cytoplasm-nucleus dual-localized protein. Leaf senescence was delayed in CiS40-11 transgenic A. thaliana or by its transient expression in C. intermedia. Transcriptomic analysis and endogenous hormones assay revealed that CiS40-11 inhibited leaf senescence via promoting the biosynthesis of cytokinins, through blocking AtMYB2 expression in CiS40-11 overexpression lines. Furthermore, in the ats40-5a and ats40-6a mutants, AtMYB2 expression was increased and their leaves exhibited a premature senescence phenotype. Our results show that CiS40-11 (and its orthologs, AtS40-5 and AtS40-6) promoted cytokinin synthesis by inhibiting the expression of MYB2 and releasing its negative regulation on the expression of IPTs to inhabit leaf senescence. HighlightThe senescence regulator S40 family members CiS40-11, AtS40-5 and AtS40-6 are induced by light and inhibition leaf senescence by promoting cytokinin synthesis.

plant biology↗