Biology subjects

Bai, B.

Publications and source records attributed to Bai, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Alpha Spatial: Language-guided prediction of single-cell spatial gene expression from histology

Routine histology preserves tissue architecture but leaves its molecular organization largely unmeasured. Recovering this information requires learning across heterogeneous gene panels and constraining a biologically ill-posed morphology-to-expression mapping. Here we present Alpha Spatial (AS), a language-conditioned framework that predicts cell-level gene expression from histology while jointly learning from different tissues and panels. Matched biological context improved prediction over omitted context, whereas incompatible context reduced accuracy. Multi-tissue learning further improved breast-tissue prediction, and AS outperformed the evaluated methods while preserving molecular-state organization. In breast cancer, AS recovered POSTN-associated stromal programmes and HER2-associated molecular and spatial differences. Exploratory patient-level analyses identified a CXCL14-associated spatial state whose abundance was associated with non-response to trastuzumab-containing treatment and larger residual invasive tumours. These findings establish a framework for reusing heterogeneous molecular observations to investigate tissue organization and treatment-associated microenvironments in archived histology.

bioinformatics↗

bioRxiv2026

Deep learning-based prediction of wall shear stress throughout the cardiac cycle in middle cerebral artery bifurcation aneurysms

Background and Objective: Cardiac-cycle wall shear stress (WSS) is relevant to intracranial aneurysm hemodynamic assessment, but transient computational fluid dynamics (CFD) is costly. Existing surrogates use steady-flow priors or joint steady/transient training; here we evaluate the transfer of separately pretrained spatial parameters. This study develops the Steady-to-Transient Estimation of Pulsatile Wall Shear Stress (STEP) framework, a two-stage geometric learning approach for full-cycle WSS prediction. Methods: Using the synthetic AneuG-Flow dataset, Stage 0 pretrained a geometric tokenizer, LaB-GATr backbone, and WSS decoder on 11,656 steady CFD cases. Stage 1 initialized these components from the pretrained model and fine-tuned them end to end using 449 transient training cases, with 72 validation and 57 primary test cases. Waveform embeddings multiplicatively conditioned geometric features across blocks at 80 cardiac-cycle time points. Gaussian curvature was included as an auxiliary geometry feature. Ablations evaluated steady initialization, temporal conditioning, and curvature, with rank-biserial effect sizes and Holm-adjusted p values. A fixed model was also evaluated on 231 additional cases, with registered-geometry overlap audited across stages. Results: On the primary test set, STEP achieved a whole-cycle WSS vector mean absolute error (MAE) of 1.688 Pa and root-mean-square error (RMSE) of 2.877 Pa. Time-averaged WSS, oscillatory shear index, and relative residence time MAEs were 1.040 Pa, 0.00625, and 0.06734 Pa-1, respectively. Steady initialization reduced vector MAE by 27.93% relative to training the same transient architecture from scratch; the complete blockwise conditioning configuration reduced MAE by 8.04% relative to input-only additive conditioning (rank-biserial correlations 0.995 and 0.982, respectively; Holm-adjusted p < 0.001). Curvature yielded a 3.46% reduction without a significant paired effect (adjusted p = 0.0521). The 80-time-point WSS prediction required a mean of 4.169 s (SD 0.063 s). Additional-cohort MAE was 1.712 Pa, but 185/231 geometries matched Stage 0 training, versus 1/57 in the primary test set. Conclusions: STEP demonstrated effective reuse of steady-pretrained spatial parameters for cardiac-cycle WSS prediction under the evaluated synthetic CFD protocol. The strongest controlled gains were associated with steady initialization and the complete temporal-conditioning configuration. The common inlet waveform and cross-stage geometry overlap limit generalization claims.

bioengineering↗

bioRxiv2026

COPAL: An ensemble of protein-ligand co-folding models enriches preferred ligand predictions for the LuxR-family of quorum sensing receptors

Acyl-homoserine lactone (AHL) quorum sensing enables many species of proteobacteria to coordinate collective behaviors. In such systems, a synthase produces an AHL signal, which is sensed by a LuxR-family receptor. Despite extensive genomic annotation of LuxR homologs, preferred AHLs for most receptors remain unknown, limiting functional understanding of quorum sensing across diverse bacteria. Here, we present the COPAL (combining ordered predictions of audited ligands) pipeline, which integrates multiple protein-ligand co-folding models to identify preferred AHLs for a specific LuxR. Benchmarking on a leakage-controlled subset of 96 experimentally characterized LuxR-AHL pairs shows that COPAL places the preferred AHL within the top-6 candidates (out of 58) for 68% of receptors, outperforming every individual co-folding model. Further, inter-model agreement correlates with ranking accuracy, offering an indication of confidence. We show that COPAL resolves the specificity shift induced by three-point mutations in LasR and correctly nominates C8-HSL as the preferred ligand for the previously uncharacterized Mesorhizobium sp. NJ3 receptor, which we verified experimentally. Finally, we release the Ranked AHL-LuxR Prediction Hub (RALPH), comprising precomputed rankings for about 10,000 unique LuxR homologs. More broadly, COPAL shows that unweighted rank aggregation of complementary co-folding models offers a general strategy for predicting receptor-ligand specificity in data-scarce biological systems.

biochemistry↗

bioRxiv2026

HistoSB-Net: Semantic Bridging for Data-Limited Cross-Modal Histopathological Diagnosis

Vision-language models (VLMs) provide a unified framework for multimodal reasoning, yet their representations are primarily learned from natural image-text corpora and often exhibit semantic misalignment when transferred to histopathology, particularly under data-limited diagnostic settings. To address this limitation, we propose HistoSB-Net, a semantic bridging network designed to adapt pre-trained VLMs to multimodal histopathological diagnosis while preserving their original semantic structure. HistoSB-Net introduces a constrained semantic bridging (CSB) module that operates within the self-attention projection space of both vision and text encoders. Instead of employing explicit cross-attention or full fine-tuning, CSB adaptively modulates pre-trained attention projections through a lightweight nonlinear semantic bottleneck, enabling structured cross-modal regulation with limited additional parameters. The framework supports both patch-level and whole-slide image (WSI)-level diagnosis within a unified architecture. Experiments on six pathology benchmarks, comprising two WSI-level and four patch-level datasets, demonstrate consistent improvements over zero-shot inference across 36 backbone-dataset combinations under limited supervision. Further analysis of prototype-based margin distributions and confusion matrices shows that these improvements are accompanied by enhanced intra-class compactness and increased inter-class separation in the embedding space. These results indicate that CSB provides an effective and computationally manageable strategy for adapting pre-trained VLMs to data-limited digital pathology tasks.

pathology↗

bioRxiv2025

Identification of SASP-associated biomarkers and regulatory mechanisms in diabetic foot ulcers based on transcriptomics and experimental validation

BackgroundDiabetic foot ulcers (DFU) constitute a major complication arising from diabetes mellitus. Emerging research findings have underscored the pivotal contribution of cellular senescence to the pathophysiological development of wounds exhibiting delayed healing; nevertheless, the molecular regulatory networks governing this process in DFU pathogenesis remain incompletely elucidated MethodsDFU-related transcriptomic datasets were acquired from public databases. Biomarkers were identified through machine learning algorithms combined with expression validation. To evaluate the diagnostic predictive capacity of identified biomarkers for DFU, a nomogram prediction model was developed and validated. Further analyses included Gene Set Enrichment Analysis (GSEA), molecular network regulation, immune infiltration profiling, and drug prediction. Subsequently, the expression profiles of these biomarkers were quantitatively assessed through reverse transcription quantitative PCR (RT-qPCR) methodology. ResultsFour feature genes were identified using machine learning. Among them, CXCR2 and SIGLEC7 passed expression validation and were significantly up-regulated in DFU groups across two datasets (p < 0.05), confirming their potential as biomarkers. A nomogram constructed based on these two biomarkers demonstrated high discriminative accuracy and good calibration (decision curve net benefit > 0, AUC = 0.99). GSEA indicated that CXCR2 and SIGLEC7 were both enriched in the cytokine-cytokine receptor interaction pathway as well as other functionally associated pathways. Molecular regulatory network analysis indicated that both CXCR2 and SIGLEC7 were predicted to be regulated by transcription factors (TFs) such as SOX2. Immune infiltration analysis showed a significant strong positive correlation between CXCR2 and activated mast cells (correlation coefficient (cor) = 0.72, p < 0.001), and between SIGLEC7 and macrophages M0 (cor = 0.71, p < 0.001). Drug prediction identified 12 drugs targeting CXCR2 (e.g., Indoprofen) and one drug targeting SIGLEC7 (N-acetyl-alpha-D-glucosamine). Validation through Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) revealed that CXCR2 and SIGLEC7 expression levels were markedly increased in the DFU group, showing statistically significant differences (p<0.05), which aligned with the bioinformatics analysis outcomes ConclusionThis study identified CXCR2 and SIGLEC7 as SASPRG-related biomarkers in DFU through bioinformatic analysis, providing new theoretical support and a basis for early diagnosis and treatment of DFU.

genomics↗

bioRxiv2025

N6-Methyladenosine Safeguards Mouse and Human Germline Competence

N6-Methyladenosine (m6A) regulation of germline entry in post-implantation-like-pluripotent states remains poorly defined. We characterized m6A depletion by Mettl3 or Mettl14 knock-down or METTL3 inhibition in in vitro models enabling primordial germ-cell-like-cell and somatic differentiation. Upon m6A depletion, mouse epiblast-like cells upregulated embryonic Ras (Eras) and PI3K-pAKT, facilitating EZH2 repression and depletion of H3K27me3. Consequently, enhancer activation promoted global gene deregulation and impaired germline entry. In mouse formative stem cells, ERAS-PI3K-pAKT upregulation resulted in unscheduled Blimp1 and Otx2 co-expression, germline entry deficiency and enhanced mesodermal differentiation. Conversely, upon m6A depletion, germline competent human pluripotent stem cells upregulated OTX2 through FGF-pERK activation, resulting in germline entry deficiency and enhanced neuroectodermal differentiation. meRIP-seq revealed preferential m6A deposition on mouse mesodermal and human neuroectodermal transcripts, suggesting a basis for differentiation bias following m6A depletion. We illustrate how decreasing m6A abundances impact signaling, chromatin epigenetics and transcript stabilities, constituting a powerful cell intrinsic barrier for germline entry.

developmental biology↗

bioRxiv2025

Translational landscape during Seed Germination at Sub-Codon resolution

Seed germination is crucial for agricultural reproduction. A deep understanding of this process can secure healthy growth at the early phases of plant development and therefore the yield. Recent research indicates that germination is a complex process involving translational regulation. A large group of seed stored mRNAs together with newly synthesized transcripts are regulated by post-transcriptional mechanisms and selectively translated at different stages to support the germination process. To investigate the mechanism of translational control, we performed ribosome profiling on mRNAs of distinct physiological stages during Arabidopsis thaliana seed germination. The 3-nucleotide periodicity of the ribosome association on mRNAs identified indicates their translational potential. Dry seeds, in which translation is on hold are characterized by a unique ribosome association landscape with high association at the 5 and 3 UTR, compared to physiological stages that show active translation. Start codon specific stalling of ribosomes in dry seeds is associated with an adenine enriched sequence motif. Throughout germination codons encoding glycine, aspartate, tyrosine and proline are the most frequent ribosome pausing sites. Moreover, the non-coding RNAs which we identified as associated to ribosomes are indeed translated as was revealed by investigating total seed proteome data. Seed specific upstream Open Reading Frames (uORFs) are identified which may be associated to translational control of adaptative response during early seed germination. Altogether, we present a first ribosome profiling analysis across seed germination that illuminates various regulatory mechanisms that potentially contribute to the seeds survival strategy.

plant biology↗

bioRxiv2025

Neural organoids protect engineered heart tissues from glucolipotoxicity by transferring versican in a co-culture system

Metabolic disorders could cause dysregulated glucose and lipid at the systemic level, but how inter-tissue/organ communications contribute to glucolipotoxicity is difficult to dissect in animal models. To solve this problem, myocardium and nerve tissues were modeled by 3D engineered heart tissues (EHTs) and neural organoids (NOs), which were co-cultured in a generalized medium with normal or elevated glucose/fatty acid contents. Morphology, gene expression, cell death and functional assessments detected no apparent alterations of EHTs and NOs in co-culture under normal conditions. By contrast, NOs significantly ameliorated glucolipotoxicity in EHTs. Transcriptomic and protein secretion assays identified the extracellular matrix protein versican as a key molecule that was transferred from NOs into EHTs in the high-glucose/fatty acid condition. Recombinant versican protein treatment was sufficient to reduce glucolipotoxicity in EHTs. Adeno-associated virus-delivered versican overexpression was sufficient to ameliorate cardiac dysfunction in a murine model of diabetic cardiomyopathy. These data provide the proof-of-concept evidence that inter-tissue/organ communications exist in the co-culture of engineered tissues and organoids, which could be systemically studied to explore potential pathological mechanisms and therapeutic strategies for multi-organ diseases in vitro.

cell biology↗

bioRxiv2024

NOLC1 Suppresses Immuno-chemotherapy by Inhibiting p53-mediated Ferroptosis in Gastric Cancer

Gastric cancer (GC) is one of the most malignant cancers, and cisplatin (Cis)-based chemotherapy remains the main clinical treatment for GC. However, Cis resistance often occurs, largely limiting its therapeutic efficacy in tumors. Therefore, a better understanding of the drug resistance mechanism could reveal new approaches for improving GC treatment efficacy. Here, we define the integrative role of nucleolar and coiled-body phosphoprotein 1 (NOLC1), a molecular chaperone that is significantly upregulated in GC tissues and Cis-resistant GC cells. Knocking down NOLC1 increased GC sensitivity to Cis by regulating ferroptosis. Mechanistically, NOLC1 binds to the p53 DNA binding domain (DBD), decreasing p53 nuclear accumulation stimulated by Cis and suppressing p53 transcriptional functions. Then, the p53-mediated ferroptosis is suppressed. Furthermore, the silence of NOLC1 promoted ferroptosis-induced immunogenic cell death (ICD) and reprogrammed the immunosuppressive tumor microenvironment, thereby increasing sensitivity to anti-programmed cell death-1 (PD-1) therapy plus Cis. The combination of anti-PD-1 plus Cis effectively inhibited GC growth without significant side effects. In summary, our findings reveal that targeting NOLC1 may be a novel therapeutic strategy for GC and may increase the efficacy of chemotherapy combined with immune checkpoint inhibitor (ICI) therapy.

cancer biology↗

bioRxiv2024

Chromosome-scale genome assembly of Apocynum pictum, a drought-tolerant medicinal plant from the Tarim Basin

Apocynum pictum Schrenk is a semi-shrub of the Apocynaceae family with a wide distribution throughout the Tarim Basin that holds significant ecological, medicinal, and economic values. Here, we report the assembly of its chromosome-level reference genome using Nanopore long-read, Illumina HiSeq paired-end, and high-throughput chromosome conformation capture sequencing. The final assembly is 225.32 Mb in length with a scaffold N50 of 19.64 Mb. It contains 23,147 protein-coding genes across 11 chromosomes, 21,148 of which (91.36%) have protein functional annotations. Comparative genomics analysis revealed that A. pictum diverged from the closely related species Apocynum venetum approximately 2.2 million years ago and has not undergone additional polyploidizations after the core eudicot WGT-{gamma} event. Karyotype evolution analysis was used to characterize interchromosomal rearrangements in representative Apocynaceae species and revealed that several A. pictum chromosomes were derived entirely from single chromosomes of the ancestral eudicot karyotype. Finally, we identified 50 members of the well-known stress-responsive WRKY transcription factor family and used transcriptomic data to document changes in their expression at two stages of drought stress, identifying a number of promising candidate genes. Overall, this study provides high-quality genomic resources for evolutionary and comparative genomics of the Apocynaceae, as well as initial molecular insights into the drought adaptation of this valuable desert plant.

genomics↗

bioRxiv2023

SARS-CoV-2 Mpro protease variants of concern display altered viral and host target processing but retain potency towards antivirals

Main protease of SARS-CoV-2 (Mpro) is the most promising drug target against coronaviruses due to its essential role in virus replication. With newly emerging variants there is a concern that mutations in Mpro may alter structural and functional properties of protease and subsequently the potency of existing and potential antivirals. We explored the effect of 31 mutations belonging to 5 variants of concern (VOC) on catalytic parameters and substrate specificity, which revealed changes in substrate binding and rate of cleavage of a viral peptide. Crystal structures of 11 Mpro mutants provided structural insight into their altered functionality. Additionally, we show Mpro mutations influence proteolysis of an immunomodulatory host protein Galectin-8 (Gal-8) and subsequent significant decrease in cytokine secretion, providing evidence for alterations in escape of host-antiviral mechanisms. Accordingly, mutations associated with the highly virulent Delta VOC resulted in significant increase in Gal-8 cleavage. Importantly, IC50s of nirmatrelvir (Pfizer) and our irreversible inhibitor AVI-8053 demonstrated no changes in potency for both drugs for all mutants, suggesting Mpro will remain a high-priority antiviral drug candidate as SARS-CoV-2 evolves.

biochemistry↗

bioRxiv2022

Chromosome-level Reference Genome Provides Insights into Divergence and Stress Adaptation of the African Oil Palm

The palm family (Arecaceae), consisting of [~] 2600 species, is the third most economically important family of plants. The African oil palm (Elaeis guineensis) is one of the most important palms. However, the genome sequences of palms available are still limited and fragmented. Here, we report a high-quality chromosome-level reference genome of an oil palm Dura. The genome of 1.7 Gb was assembled by integrating long reads with [~] 150 x genome coverage. The assembled genome covered 94.5% of the estimated genome size, within which 91.6% were assigned into 16 pseudochromosomes and 73.7% were repetitive sequences. Relying on the conserved synteny with oil palm, the existing draft genome sequences of both date palm and coconut were further assembled into chromosomal level. Transposon burst, particularly long terminal repeat retrotransposons (LTRs) retrotransposons, following the last whole-genome duplication (WGD), likely explains genome size variation across palms. Convergent evolution of fruit colors tends to eliminate the roles of the virescens gene in controlling accumulation of anthocyanins in exocarp of ripe fruit of palms. Recent duplications of high tandemly repeated pathogenesis-related proteins (PRs) from the same tandem arrays played an important role in defense responses to Ganoderma. Whole genome re-sequencing of both ancestral African and introduced oil palms in Southeast Asia revealed that genes under putative selection were notably associated with stress responses, suggesting adaptation to stresses in the new habitat. The genomic resources and insights gained in this study could be exploited for accelerating genetic improvement and understanding the evolution of palms.

genomics↗

bioRxiv2022

Selection and validation of reference genes for quantitative real-time polymerase chain reaction in Serratia ureilytica DW2

Serratia ureilytica DW2 is a highly efficient phosphate-solubilizing bacterium isolated from Codonopsis pilosula rhizosphere soil that can promote the growth of C. pilosula. However, no validated reference genes from the genus Serratia for use in quantitative real-time polymerase chain reaction (RT-qPCR) normalization have been reported. To screen stable reference genes in S. ureilytica DW2, the expression of eight candidate reference genes (16S rRNA, ftsZ, ftsA, mreB, recA, slyD, thiC, and zipA) under different treatment conditions (pH, temperature, culture time, and salt content) was assayed by RT-qPCR. The expression stability of these genes was analyzed with different algorithms (geNorm, NormFinder, and BestKeeper). To verify the reliability of the data, the most stably expressed reference gene was used to quantify expression of the glucose dehydrogenase (gdh) gene under different soluble phosphate levels. The results showed that the zipA and 16S rRNA genes were the most stable reference genes, and the least stable were thiC and recA. The expression of gdh was consistent with the phosphate solubilization ability on plates containing National Botanical Research Institute phosphate (NBRIP) growth medium. Therefore, this study provides a stable and reliable reference gene for Serratia, which is vital for the accurate quantification of functional gene expression in future studies.

microbiology↗

bioRxiv2022

A novel fully-spliced accessory gene in equine lentivirus with distinct Rev-responsive element

All lentiviruses encode an accessory protein Rev, whose main biological function is to mediate the nuclear export of unspliced and incompletely spliced viral transcripts by binding to a viral cis-acting element (termed the Rev-responsive element, RRE) that is located within env-encoding region. Equine infectious anemia virus (EIAV) is a member of the Lentivirus genus in the Retroviridae family, and is considered an important model for the study of lentivirus pathogenesis. Here, we identified a novel transcript from the EIAV genome that encodes a viral protein, named Mat, with unknown function. The transcript mat is fully spliced and comprises parts of the coding regions of MA and TM. Interestingly, the expression of Mat depends on Rev and the CRM1 pathway. Rev could specifically bind to Mat mRNA to promote its nuclear export. We further identified that the first exon of Mat mRNA, which is located within the Gag-encoding region, acts as an unreported RRE. Altogether, we identified a novel fully spliced transcript mat with an unusual RRE, which interacts with Rev for nuclear export through the CRM1 pathway. Our findings may help to expend the understanding of gene transcription and expression of lentivirus. Author summaryIn lentiviruses, the nuclear export of viral transcripts is an important step in controlling viral gene expression. Generally, the unspliced and incompletely spliced (that is, intron-containing) transcripts are exported via the CRM1-dependent export pathway in a process mediated by the viral Rev protein by binding to the Rev-responsive element (RRE) located within the Env-coding region. However, the completely spliced (intronless) transcripts are exported via an endogenous cellular pathway which is Rev independent. Here we identified a novel intronless transcript from EIAV and demonstrated that it encodes a viral protein, termed Mat. Interestingly, we have determined that the expression of Mat depends on Rev, and identified that the first exon of Mat mRNA could specifically bind to Rev and be exported to the cytoplasm, which suggests that first exon of Mat mRNA is a second RRE of EIAV. These findings update the EIAV genome structure and highlight the diversification of post-transcriptional regulation patterns in EIAV, and provides important insights into the Rev-dependent nuclear export of completely spliced transcripts in lentiviruses.

molecular biology↗

bioRxiv2020

Maturation of human induced pluripotent stem cell-derived cardiomyocytes for modeling hypertrophic cardiomyopathy

RationaleHuman induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) are a powerful platform for biomedical research. However, they are immature, which is a barrier to modeling adult-onset cardiovascular disease. ObjectiveWe sought to develop a simple method which could drive cultured hiPSC-CMs towards maturity across a number of phenotypes. Methods and resultsCells were cultured in fatty acid-based media and plated on micropatterned surfaces to promote alignment and elongation. These cells display many characteristics of adult human cardiomyocytes, including elongated cell morphology, enhanced maturity of sarcomeric structures, metabolic behavior, and increased myofibril contractile force. Most notably, hiPSC-CMs cultured under optimal maturity-inducing conditions recapitulate the pathological hypertrophy caused by either a pro-hypertrophic agent or genetic mutations. ConclusionsThe more mature hiPSC-CMs produced by the methods described here will serve as a useful in vitro platform for characterizing cardiovascular disease.

cell biology↗

bioRxiv2019

Protein profiling reveals the characteristic changes of complement cascade pathway in the tissues of gastric signet ring cell carcinoma

Signet ring cell carcinoma (SRCC) is a histological subtype of gastric cancer that has distinct features in cellular morphology, epidemiology and clinicopathology compared with adenocarcinomas (ACs). Lacking of systematically molecular overview to this disease made a slow progress in diagnosis and therapy for SRCC. In the present proteomics study, the gastric tissues were collected from tumor and adjacent regions including 14 SRCC and 34 AC cases, and laser capture microdissection (LCM) was employed to eradicate cellular heterogeneity of the tissues. Over 6,000 proteins were quantified through data independent acquisition (DIA) mass spectrometry (MS). The quantitative profiles of proteomes in tumor tissues, either AC or SRCC, were dramatically different from that in the corresponding adjacencies, whereas the SRCC proteomes appeared not distinguishable to the AC proteomes via hierarchical clustering. However, focusing on univariate analysis and pathway enrichment unrevealed that some proteins and pathways bared the differences between SRCC and ACs. Importantly, the abundance changes for a bulk of proteins involved in complement cascade were highly associated with SRCC but not so sensitive to the AC status. A hypothesis, therefore, was proposed that the complement cascade was evoked in the SRCC microenvironment upon infiltration, while the SRCC cells survived from the complement cytotoxicity by secreting negative regulators. Moreover, an attempt was made to seek appropriate cell model for gastric SRCC, through proteomic comparison of the 15 gastric cell lines and the gastric tumors. The prediction upon supervised classifier suggested none of these gastric cell lines qualified in mimic to SRCC.

cell biology↗

bioRxiv2019

Transcriptome and translatome profiling and translational network analysis during seed maturation reveals conserved transcriptional and distinct translational regulatory patterns

Seed maturation is an important plant developmental process that follows embryo development. It is associated with a series of physiological changes such as the establishment of desiccation tolerance, seed longevity and seed dormancy. However, the translational dynamics associated with seed maturation, especially its connection with seed germination remains largely elusive. Here transcriptome and translatome profiling were performed during seed maturation. During seed maturation we observed a gradual disappearance of polysomes and a relative increase of monosomes, indicating a gradual reduction of global translation. Comparing the levels of polysomal associated mRNAs with total mRNA levels showed that thousands of genes are translationally regulated at early sates of maturation, as judged by dramatic changes in polysomal occupancy. By including previous published data from germination and seedling establishment, a translational regulatory network: SeedTransNet was constructed. Network analysis identified hundreds of gene modules with distinct functions and transcript sequence features indicating the existence of separate translational regulatory circuits possibly acting through specific regulatory elements. The regulatory potential of one such element was confirmed in vivo. The network identified several seed maturation associated genes as central nodes, and we could confirm the importance of many of these hub genes with a maturation associated seed phenotype by mutant analysis. One of the identified regulators an AWPM19 family protein PM19-Like1 (PM19L1) was shown to regulate seed dormancy and longevity. This putative RBP also affects the transitional regulation of one its, by the SeedTransNet identified, target mRNAs. Our data shows the usefulness of SeedTransNet in identifying regulatory pathways during seed phase transitions.

systems biology↗

bioRxiv2018

PTPN22 interacts with EB1 to regulate T cell receptor signaling

PTPN22 has been reported as an important negative regulator of T cell signaling. Here we identified EB1 as an associated protein of PTPN22 via 2-hybrid and mass spectrometry screening.\n\nRecently the phosphorylation of EB1 has been proved in the regulation of T cell receptor (TCR) mediated signaling pathway. Our results shown that PTPN22 interacted with EB1 through the P1 domain of PTPN22, and regulated the Y247 phosphorylation site of EB1. The subsequent results suggest that PTPN22 interacts with EB1 and regulate the phosphorylation of EB1, which results in the regulation of the expression of T cell activation markers of CD25 and CD69, and the phosphorylation levels of the T cell signaling molecules, such as ZAP-70, LAT and Erk, ultimately resulting in NFAT transcription factors entering the nucleus and regulating the secretion of cytokine IL-2. This newly identified interaction between PTPN22 and EB1 may play an important role in TCR signal pathways.

cell biology↗