Biology subjects

Fan, X.

Publications and source records attributed to Fan, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Decoding yeast transcriptional regulation via a data- and mechanism-driven distributed large-scale network model

The complex transcriptional regulatory relationships among genes influence gene expression levels and play crucial roles in determining cellular phenotypes. Here, we present a novel distributed large-scale transcriptional regulatory neural network model (DLTRNM) by integrating prior knowledge into the reconstruction of pre-trained machine learning models followed with fine-tuning. Taken S. cerevisiae as the example, the transcriptional regulatory relationships, carefully compiled and documented, are utilized to define interactions between TFs and their TGs within DLTRNM. Subsequently, DLTRNM is pre-trained on pan-transcriptomic data and fine-tuned with time-series data, enabling it to accurately predict dynamic regulatory correlations between TFs and TGs, such as simulating TG responses by tuning the expression of TFs. In addition, DLTRNM can assist in identifying potential key TFs for a subset of genes, thus simplifying the complex and interrelated transcriptional regulatory networks (TRN). Based on the key TFs, it can also refine previously reported transcriptional regulatory subnetworks and highlight the core regulatory networks. DLTRNM offers a powerful tool for studying transcriptional regulation with reduced computational demands and enhanced interpretability. Thus, this study represents a significant step forward in systems biology for understanding the complicated transcriptional regulation within cells.

bioinformatics↗

bioRxiv2025

Effective in vivo RNA base editing via engineered cytidine deaminase APOBECs fused with PUF proteins

Base editing stands at the forefront of genetic engineering, heralding precise genetic modifications with broad implications. While CRISPR-based DNA and RNA base editing systems capitalize on sgRNA-guided specificity and diverse deaminase functionalities, the pursuit of efficient C-to-U RNA editing has been hampered by the inherent constraints of cytidine deaminases. Here, we report an RNA base editing platform by refining cytidine deaminases, termed professional APOBECs (ProAPOBECs), through systematic enhancements and AI-driven protein engineering. ProAPOBECs demonstrate unprecedented catalytic versatility, particularly fused with RNA-recognizing Pumilio and FBF (PUF) proteins. We present the first effective use of RNA base editing in the brain with ProAPOBECs in Mef2c mutant mice, a model for autism. The AAV-mediated RNA base editing via ProAPOBEC not only corrects genetic mutation in mRNAs but significantly alleviates autistic-like behaviors in the mice. This work introduces a pioneering collection of RNA base editing instruments, emphasizing their therapeutic potential in combatting genetic disorders.

molecular biology↗

bioRxiv2025

A pathological phosphorylation pattern enhances taucooperativity on microtubules and facilitates tau filamentassembly

Phosphorylation plays a crucial role in both normal and disease processes involving the microtubule-associated protein tau. Physiologically, phosphorylation regulates taus subcellular localization within neurons and is involved in fetal development and animal hibernation. However, abnormal phosphorylation of tau is linked to the formation of neurofibrillary tangles (NFTs) in various human tauopathies. Interestingly, the patterns of tau phosphorylation are similar in both normal and abnormal processes, leaving unclear whether phosphorylated tau retains its functional role in normal processes. The relationship between tau phosphorylation and NFT assembly in tauopathies is also still debated. To address these questions, we investigated the effects of tau phosphorylation on microtubule binding, cooperative protein envelope formation, and NFT filament assembly relevant to tauopathies. Consistent with previous results, our findings show that tau phosphorylation decreases taus overall affinity for microtubules, but we reveal that phosphorylation more dramatically impacts the cooperativity between tau molecules during tau envelope formation along microtubules. Additionally, we observed that the specific pattern of phosphorylation, rather than overall phosphorylation level, strongly impacts the assembly of tau filaments in vitro. Our results reveal new insights into how tau phosphorylation impacts taus physiological roles on microtubules and its pathoconversion into NFTs.

biochemistry↗

bioRxiv2025

Nucleoporins shape germ granule architecture and balance small RNA silencing pathways

Animals have evolved distinct small RNA pathways, including piRNA and siRNA, to silence invasive and selfish nucleic acids. piRNA pathway factors are concentrated in perinuclear germ granules that frequently associate with nuclear pore complexes (NPCs). However, the factors mediating germ granule-NPC association and the functional relevance of such association remain unknown. Here we show that the conserved nucleoporins NPP-14 (NUP-214) and NPP-24 (NUP-88), components of the cytoplasmic filaments of NPC, play critical roles in anchoring germ granule to NPC and in attenuating piRNA silencing In C. elegans. Proximity labeling experiments further identified EPS-1 (enhanced piRNA silencing) as a key germ granule factor contributing to germ granule-NPC interaction. In npp-14, npp-24, or eps-1 mutant animals, we observed fewer but enlarged, unorganized germ granules, accompanied by the over-amplification of secondary small RNAs at piRNA targeting sites. Nonetheless, we found this enhancement of piRNA silencing comes at the cost of dampened RNAi efficiency and RNAi inheritance. Together, our studies uncovered factors contributing to germ granule-NPC association and underscored the importance of spatial organization of germ granules in balancing small RNA silencing pathways.

genetics↗

bioRxiv2025

Bioinformatic analysis reveals the molecular mechanisms of Trefoil factor 3 involved in asthma pathogenesis

ObjectiveInvestigate the expression, regulatory network and function of TFF3 in asthma from a multi-omics perspective through bioinformatics and cellular experiments to provide clues for understanding its molecular mechanisms in asthma. MethodsDownloaded two asthma-related datasets (GSE67472 and GSE147878) from GEO. Conducted differential expression analysis and WGCNA to find common genes related to asthma phenotype and TFF3 expression. Constructed a PPI network to identify key genes interacting with TFF3. Performed GO and pathway enrichment analysis using DAVID. Analyzed the relationship between TFF3 and immune cell infiltration with CIBERSORTx. Used molecular docking to validate interactions. In vitro, induced 16HBE cells with HDM to establish asthma model and detected inflammatory indicators and TFF3 by RT-qPCR and western blotting. ResultsTFF3 expression was significantly increased in asthma patients in both datasets. ROC analysis showed good diagnostic specificity and sensitivity. 57 co-expressed genes related to asthma and TFF3 were screened, with 11 genes directly interacting with TFF3 and upregulated. Functional enrichment analysis indicated involvement in asthma-related processes. Immune infiltration analysis showed increased M2 macrophages and mast cells, decreased M1 macrophages, and positive correlation with TFF3. Molecular docking confirmed stable binding. In vitro experiments showed increased inflammation index and TFF3 expression after HDM intervention. ConclusionThe study used bioinformatics and cellular experiments to show TFF3s key roles in asthma pathogenesis in aspects like gene expression, protein interaction, and immune microenvironment. TFF3 may regulate genes like AGR2 and AKT1, affect immune cells, and be involved in processes like cell migration and immune response. It provides clues for exploring molecular mechanisms and may offer new directions for asthma diagnosis and treatment.

genomics↗

bioRxiv2025

Molecular basis for shifted receptor recognition by an encephalitic arbovirus

After decades of inactivity throughout the Americas, western equine encephalitis virus (WEEV) recently re-emerged in South America, causing a large-scale outbreak in humans and horses. WEEV binds protocadherin 10 (PCDH10) as a receptor; however, nonpathogenic strains no longer bind human or equine PCDH10 but retain the ability to bind avian receptors. Highly virulent WEEV strains can also bind the very low-density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2) as alternative receptors. Here, by determining cryo-electron microscopy structures of WEEV strains isolated from 1941-2005 bound to mammalian receptors, we identify polymorphisms in the WEEV spike protein that explain shifts in receptor dependencies and that can allow nonpathogenic strains to infect primary cortical neurons. We predict the receptor dependencies of additional strains and of a related North American alphavirus. Our findings have implications for outbreak preparedness and enhance understanding of arbovirus neurovirulence through virus receptor binding patterns.

microbiology↗

bioRxiv2024

Single-Cell Profiling Reveals Global Immune Responses during the Progression of Murine Epidermal Neoplasms

Immune cells determine the role of the tumor microenvironment during tumor progression, either suppressing tumor formation or promoting tumorigenesis. We analyzed the profile of immune cells in the tumor microenvironment of control mouse skins and skin tumors at the single-cell level. We identified 15 CD45+ immune cell clusters, which broadly represent the most functionally characterized immune cell types including macrophages, Langerhans cells (LC), conventional type 1 dendritic cells (cDC1), conventional type 2 dendritic cells (cDC2), migratory/mature dendritic cells (mDC), dendritic epidermal T cells (DETC), dermal {gamma}{delta} T cells ({gamma}{delta}T), T cells, regulatory T cells (Tregs), natural killer cells (NK), type 2 innate lymphoid cells (ILC2), neutrophils (Neu), mast cells (Mast), and two proliferating populations (Prolif.1 and Prolif.2). Skin tumor progression reprogramed immune cells and led to a marked increase in the relative percentages of macrophages, cDC2, mDC, Tregs, and Neu. Macrophages, the largest cell cluster of immune cells in skin tumors. In addition, macrophages emerged as the predominant communication hub in skin tumors, highlighting the importance of macrophages during skin tumor progression. In contrast, other immune cell clusters decreased during skin tumor progression, including DETC, {gamma}{delta}T, ILC2, and LC. In addition, skin tumor progression dramatically upregulated Jak2/Stat3 expression and the interferon response across various immune cell clusters. Further, skin tumor progression activated T cells and NK cells indicated by elevated expression of IFN-{gamma} and Granzyme B in skin tumors. Meanwhile, a pronounced infiltration of M2-macrophages and Tregs in skin tumors created an immunosuppressive microenvironment, consistent with the elevated expression of the Stat3 pathway in skin tumors. In summary, our study elucidates the immune cell landscape of epidermal neoplasms, offering a comprehensive understanding of the immune response during skin tumor progression and providing new insights into cancer immune evasion mechanisms.

cancer biology↗

bioRxiv2024

A Systematic Comparison of Single-Cell Perturbation Response Prediction Models

Predicting single-cell transcriptional responses to perturbations is central to dissecting gene regulation and accelerating therapeutic design, yet the field lacks a rigorous, task-spanning assessment of model behavior. We present a large-scale benchmark of 13 representative methods and baselines across 25 datasets spanning diverse perturbation modalities and species, including two primary immune-cell drug-response resources. We evaluated three core tasks--generalization to unseen single-gene perturbations, prediction of combinatorial interactions, and transfer across cell types--using 24 metrics covering expression-level accuracy, relative changes, differential expression recovery, and distributional similarity. Across tasks, performance depended strongly on perturbation effect size and evaluation perspective: expression-level agreement was highest for small-effect perturbations resembling controls, whereas delta- and DE-based metrics improved with larger effects, providing clearer signals. Models shared a conservative bias, with fine-tuned foundation models compressing variance and underestimating synergistic effects in combinations. PerturbNet showed superior recovery of DE signatures in Tasks 1 and 2, while no method consistently generalized across cell types in Task 3, where biological consistency dominated outcomes. This benchmark establishes current methodological limits, clarifies that different metrics probe distinct biological signals rather than redundant summaries of the same prediction problem, and provides a foundation for developing virtual-cell models that more faithfully capture heterogeneous perturbation responses. Teaser: A large-scale benchmark reveals strengths and limits of models predicting single-cell perturbation responses.

bioinformatics↗

bioRxiv2024

Multiomic foundation model predicts epigenetic regulation by zero-shot

Deciphering cell type-specific perturbation effects on genes and cellular states demands considerable experimental resources. To overcome this challenge, we propose Perturbation Transformer (PertFormer), a foundation model to uncover functional and regulatory mechanisms through interpretable in silico perturbation process. PertFormer comprises 3 billion parameters pretrained on both bulk and single-cell datasets covering 9 types of multiomics (55 billion bp bulk multiomics and the largest-to-date 1.5 billion paired multiomic samples from 1 million single cells), capturing regulation of 300 kb around every genic region. PertFormer enables zero-shot prediction of functional perturbations and cell fate dynamics, outperforming existing methods by 20.9%-480.2%. PertFormer identifies novel tumor treatment targets, validated experimentally. The generalization capabilities of PertFormer have the potential to accelerate the discovery of biological and clinical targets.

genomics↗

bioRxiv2024

The IQGAP1-Claudin Cell Junction Axis in Cisplatin-induced Kidney Damage

Kidney damage resulting from nephrotoxicity is a major side effect of chemotherapy. Cisplatin is an effective antineoplastic agent broadly used in oncology where it interferes with DNA replication in dividing cells, however, its mechanism in kidney damage remains unclear. We tested the hypothesis that cisplatin displaces cell-contact proteins such as IQGAP1-claudin complex in the kidney tubules, causing epithelial cell dissociation and kidney damage. Employing a multifaceted approach, using mutant analyses and optimal cisplatin dose, this hypothesis was tested in cell culture and iqgap1-/- mouse models. Cisplatin inhibited cell proliferation and migration in an IQGAP1-dependent manner, displaced IQGAP1 from cell junctions and altered the expression level of key junctional markers, including claudins 2/4/8 and nephrin. Similar effects were observed in animal models where cisplatin treatment and loss of IQGAP1 had additive effects. These functional outcomes are accounted for by suppression of Akt1/PKB survival and ERK1/2 proliferation signals and activation of JNK-GSK3{beta} stress and inflammatory signal, widely implicated in kidney injury. These findings present IQGAP1-claudin axis as biomarkers and therapeutic targets in kidney damage and pave the way for formulating new analogs that eliminate cisplatin adverse side effects while preserving its antineoplastic efficacy.

cell biology↗

bioRxiv2024

Assessing Forearm Exertion in Manual Tasks with Surface EMG: A Comparative Analysis of Through-Forearm vs. Muscle Specific EMG Placements

BackgroundHand-intensive work is associated with musculoskeletal disorders (MSDs) such as carpal tunnel syndrome, tendinitis, and nerve entrapment. Estimating internal load on tissues like tendons and muscles in the hand and forearm is essential but challenging. Consequently, external force or self-reported exertion are often used as proxies for internal load assessment. Surface electromyography (sEMG) provides a promising method for continuous and objective monitoring of force. Through-forearm sEMG - placing one electrode on the flexors and one on the extensors - has been suggested as a pragmatic approach for capturing physical load under different wrist and forearm postures. However, further validation is needed to determine its accuracy in predicting exertion and force across diverse tasks, as well as to understand what specific aspects of muscle activity it captures. This study aimed to compare through-forearm sEMG with two common muscle-specific placements, i.e., the forearm extensor and flexor, in estimating force and perceived exertion during hand-intensive tasks and to explore the correlations of sEMG signals between these three sEMG placements. MethodsSixteen participants performed four simulated tasks, i.e. gripping, thumb-pressing, screwing, and key-pinching, at five exertion levels following a modified OMNI-Resistance Exercise Scale (OMNI-RES). The sEMG signals from the through-forearm, extensor, and flexor placements were recorded alongside exerted force. Polynomial mixed-effects models were used to estimate self-rated exertion and exerted force from muscle activity. Pearson correlation and linear mixed-effects models were used to explore correlations of sEMG signals between these three sEMG placements. ResultsAll sEMG placements predicted self-rated exertion and exerted force with strong model fit (R2 > 0.95 in most tasks) and high precision (residual SD < 1 for self-rated exertion, and < 5% for force in most tasks). However, moderate inter-subject and inter-task variability was observed. Through-forearm sEMG consistently outperformed both extensor and flexor placements across tasks by a small margin. The sEMG signals obtained from the three sEMG placements were highly correlated, and through-forearm sEMG could be expressed as a linear combination of extensor and flexor signals. DiscussionThe findings suggest that exertion estimation with a single-channel sEMG is feasible, although individual calibrations and additional task-specific information may be necessary for real-world applications. Through-forearm sEMG placement marginally outperformed extensor and flexor placements, which could be due to its integration of muscle activities from both muscle groups. ConclusionThe through-forearm sEMG placement provides slightly better performance estimating exertion than muscle-specific placements in the assessed manual tasks, possibly due to its integration of information from multiple muscles. Further research is needed to explore methods for individual calibration and ways to obtain task-specific information to enhance applicability in broader real-world settings.

bioengineering↗

bioRxiv2024

Single-Cell full-length Isoform Sequencing Unveils Transcriptional Dysregulation in Autism Spectrum Disorder During Cerebral Cortex Development

Regulation of RNA splicing is pivotal in neural development, with established gene isoform expression patterns (1, 2). However, the specific roles of isoform diversity across cell types in both healthy and diseased brains warrant further investigation. Here, we employed a combination of metabolic RNA labeling using 4-thiouridine (4sU) and long-read sequencing based single-cell full-length transcriptome sequencing to capture newly synthesized transcripts within the developing mouse cortices. This approach allowed us to identify predetermined cell states supported by new RNAs and the driving isoforms of transcription factors that regulate the development of deep-and upper-layer neurons. Through detailed single-cell isoform expression analysis, we discovered novel cell type-specific isoforms and uncovered isoform switch events that modulate neuron differentiation. Additionally, we investigated isoform regulation associated with Autism Spectrum Disorder (ASD) during embryonic development of BTBR T+ Itpr3tf (BTBR) mice. Notably, our findings indicate a premature emergence of cortical projection neurons (CPNs) with an immature identity in ASD-affected cortices. These CPNs exhibit the highest degree of differential transcript usage (DTU), significantly overlapping with their cell type markers and being enriched in RNA splicing processes. Exon inclusion was significantly enriched in ASD and the related RNA binding proteins (RBPs) were extracted, nearly 60% of which have been reported as ASD risk genes. Lastly, we revealed a reduction in isoform diversity in ASD, potentially linked to H3K27ac dysregulation in the associated genes. Collectively, our study marks a substantial advancement in understanding the molecular basis of cortical development and function, paving the way for future studies on neurodevelopmental disorders.

developmental biology↗

bioRxiv2024

Quantifying information stored in synaptic connections rather than in firing patterns of neural networks

A cornerstone of our understanding of both biological and artificial neural networks is that they store information in the strengths of synaptic connections among the neurons. However, in contrast to the well-established theory for quantifying information encoded by the firing activity of neural networks, there does not exist a framework for quantifying information stored in the networks connection distribution itself. Here, we develop a theoretical framework for synaptic information by using densely connected Hebbian networks performing autoassociative memory tasks and by modeling data patterns to be stored as log-normal distributions. Specifically, we derive analytical approximations for Shannon mutual information between the data and single-tons, pairs, and arbitrary n-tuples of synaptic connections within the network. Our framework corroborates well-established insights regarding pattern storage capacity, supports the principle of distributed coding in neural firing activities, and formalizes the heterogeneity inherent in information encoding across synapses in a network. Notably, it discovers synergistic interactions among synapses, revealing that the information encoded jointly by all the synapses exceeds the sum of its parts. Taken together, this study introduces a powerful, interpretable framework for quantitatively understanding information storage in the synapses of neural networks, one that illustrates the duality of synaptic connectivity and neural population activity in learning and memory.

neuroscience↗

bioRxiv2024

RING1 dictates GSDMD-mediated inflammatory response and host susceptibility to pathogen infection

RING1 is an E3 ligase component of the polycomb repressive complex 1 (PRC1) with known roles in chromatin regulation and cellular processes such as apoptosis and autophagy. However, its involvement in inflammation and pyroptosis needs to be better characterized. Here, we found that human RING1, but not RING2, promoted K48-linked ubiquitination of Gasdermin D (GSDMD) and acted as a negative regulator of pyroptosis and bacterial infection. Ring1 knockout mice increased the bacterial loads and mortality rate by treatment of S. typhimurium. Upon infection by M. tuberculosis (Mtb) H37Rv strain, RING1 deletion initially reduced bacterial loads but later increased lung inflammation and impaired immune defense responses in mice. Also, Ring1 knockout exacerbated acute sepsis induced by lipopolysaccharide (LPS). Mechanistically, RING1 directly interacts with GSDMD and ubiquitinates the K51 and K168 sites of GSDMD for K48-linked proteasomal degradation, thereby inhibiting pyroptosis. Inhibition of RING1 E3 ligase activity by mutation or small molecular compound increased GSDMD level and cell death during pyroptosis. Our findings reveal that RING1 dictates GSDMD-mediated inflammatory response and host susceptibility to pathogen infection, highlighting RING1 as a potential therapeutic target for combating infectious diseases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/622030v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@e6d4a6org.highwire.dtl.DTLVardef@92f137org.highwire.dtl.DTLVardef@11a69c4org.highwire.dtl.DTLVardef@115dc0b_HPS_FORMAT_FIGEXP M_FIG Graphic Abstract C_FIG HighlightsO_LIE3 ubiquitin ligase RING1 targets GSDMD for proteasomal degradation. C_LIO_LIMice lacking RING1 are more vulnerable to S. typhimurium infection and LPS- induced sepsis. C_LIO_LIIn the early stages of M. tuberculosis (Mtb) infection, Ring1-/- mice exhibit efficient bacterial clearance. C_LIO_LIChronic inflammation in Ring1-/- mice impairs the ability to control Mtb in the late stages of infection. C_LI

cell biology↗

bioRxiv2024

Striatal cell-type-specific molecular signatures reveal therapeutic targets in a model of dystonia

Striatal dysfunction is implicated in many forms of dystonia, including idiopathic, inherited and iatrogenic dystonias. The striatum is comprised largely of GABAergic spiny projection neurons (SPNs) that are defined by their long-range efferents. Direct SPNs (dSPNs) project to the internal globus pallidus/substantia nigra reticulata whereas indirect pathway SPNs (iSPNs) project to the external pallidum; the concerted activity of both SPN subtypes modulates movement. Convergent results from genetic, imaging and physiological studies in patients suggest that abnormalities of both dSPNs and iSPNs contribute to the expression of dystonia, but the molecular adaptations underlying these abnormalities are not known. Here we provide a comprehensive analysis of SPN cell-type-specific molecular signatures in a model of DOPA-responsive dystonia (DRD mice), which is caused by gene defects that reduce dopamine neurotransmission, resulting in dystonia that is specifically associated with striatal dysfunction. Individually profiling the translatome of dSPNs and iSPNs using translating ribosome affinity purification with RNA-seq revealed hundreds of differentially translating mRNAs in each SPN subtype in DRD mice, yet there was little overlap between the dysregulated genes in dSPNs and iSPNs. Despite the paucity of shared adaptations, a disruption in glutamatergic signaling was predicted for both dSPNs and iSPNs. Indeed, we found that both AMPA and NMDA receptor-mediated currents were enhanced in dSPNs but diminished in iSPNs in DRD mice. The pattern of mRNA dysregulation was specific to dystonia as the adaptations in DRD mice were distinct from those in parkinsonian mice where the dopamine deficit occurs in adults, suggesting that the phenotypic outcome is dependent on both the timing of the dopaminergic deficit and the SPN-specific adaptions. We leveraged the unique molecular signatures of dSPNs and iSPNs in DRD mice to identify biochemical mechanisms that may be targets for therapeutics, including LRRK2 inhibition. Administration of the LRRK2 inhibitor MLi-2 ameliorated the dystonia in DRD mice suggesting a novel target for therapeutics and demonstrating that the delineation of cell-type-specific molecular signatures provides a powerful approach to revealing both CNS dysfunction and therapeutic targets in dystonia.

neuroscience↗

bioRxiv2024

The transcription factor ZmbZIP75 promotes both grain filling and kernel dehydration in maize

Selecting both high-yield and low-kernel-moisture varieties is essential for modern maize production, but relevant breeding efforts are hindered by a lack of valuable regulatory genes. Here, we demonstrate that the transcription factor (TF) basic leucine zipper 75 (ZmbZIP75) promotes grain yield and reduces kernel moisture in maize. Knockout of ZmbZIP75 results in defective grain filling and kernel dehydration, whereas ZmbZIP75 overexpression confers increased grain yield per plant and decreased kernel moisture without altering plant architecture. Mechanistically, during the grain filling stage, ZmbZIP75 is transcriptionally induced by maternal-derived basal abscisic acid (ABA) and directly activates multiple core starch synthesis-related genes and key TFs, thereby promoting grain filling and final yield. In the late stage of kernel development, high concentrations of zygotic ABA enhance ZmbZIP75 phosphorylation through SnRK2.10. The phosphorylated ZmbZIP75 subsequently transactivates and interacts with TF VP1 to synergistically promote kernel dehydration. This study thus highlights the potential of ZmbZIP75 for engineering both high-yield and low-kernel-moisture varieties to meet the demands of high-efficient maize production. IN A NUTSHELLO_ST_ABSBackgroundC_ST_ABSHigh grain yield in maize is generally associated with elevated kernel moisture at harvest, which is the main limiting factor for modern maize production. Therefore, it is of importance to select varieties with both high-yield and low-kernel-moisture. These traits are largely controlled by grain filling and kernel dehydration, two tightly connected processes during maize kernel development. Abscisic acid (ABA) is well-documented for its vital role in grain filling and dehydration maturation. However, the molecular mechanisms by which ABA coordinates these two processes remain unclear. QuestionWhat are the regulatory factors involved, and how do they mediate ABA signaling to coordinate grain filling and dehydration maturation in maize? FindingsZmbZIP75 is transcriptionally induced by ABA and directly activates multiple core starch synthesis-related genes and key TFs in developing maize endosperm, thereby promoting grain filling. In developing embryo, ABA enhances ZmbZIP75 phosphorylation via SnRK2.10. The phosphorylated ZmbZIP75 then transactivates and interacts with VP1 to synergistically promote kernel dehydration. Moreover, ZmbZIP75 overexpression confers increased grain yield and reduced kernel moisture in maize. Next stepsWhile ZmbZIP75 is directly phosphorylated to mediate ABA signaling during dehydration maturation, ZmbZIP75 is transcriptionally induced by ABA during grain filling. We plan to identify upstream factors that mediate ABA signaling to regulate ZmbZIP75 expression, thereby enhancing our understanding of ABA-promoted grain filling in maize.

plant biology↗

bioRxiv2024

Regulative synthesis of capsular polysaccharides in the pathogenesis of Streptococcus suis

Streptococcus suis (S. suis) is an important zoonotic pathogen causing substantial economic losses in the swine industry. S. suis serotype 2 (SS2) is often isolated from the diseased. S. suis expresses capsular polysaccharide (CPS), a virulence factor crucial for their survival in the blood. However, the role of CPS in the pathogenesis of S. suis is incomplete. Here, we showed a dynamic regulation of CPS in S. suis pathogenesis. In a mouse infection model, an SS2 strain (05ZYH33) was detected in the nasal-associated lymphoid tissue (NALT) and cerebrospinal fluid (CSF) as early as 30 min after intranasal inoculation without bacteremia. Histological analysis revealed that 05ZYH33 in the nasal cavity invaded the olfactory epithelium, resulting in early brain inflammation. Transmission electron microscopy showed that 05ZYH33 isolated from NALT and CSF at early infection time had a thin layer of CPS, and those detected in the blood 5 h post- inoculation showed a much thicker CPS. In addition, adoptive transfer of anti-CPS restricted 05ZYH33 in the blood but not in NALT or CSF. However, an antiserum directed to multiple non-CPS virulence factors (anti-V5) efficiently inhibited 05ZYH33 in NALT, CSF, and blood. Thus, 05ZYH33 colonizes NALT more efficiently without CPS and subsequently invades the meninges through the olfactory nerve system. These findings provide valuable information for the treatment of S. suis infection and the development of vaccines across serotypes of S. suis by targeting CPS-independent immunity.

microbiology↗

bioRxiv2024

Stratifying variant deleteriousness and trait-modulating effect under human recent adaptation

Despite advances in annotating and interpreting human genetic variants, existing methods to distinguish deleterious/pathogenic from neutral variants still inadequately capture the nuanced impact of genetic variants on fitness and disease susceptibility. In this study, we introduced a new deep learning framework, the FIND model, by stratifying genetic variants into refined categories based on selection pressures and derived allele frequency. FIND demonstrated superior performance over existing genome-wide methods, delivering enhanced resolution in differentiating trait-modulating alleles from those that are pathogenic or neutral. Access to base-wise informative annotations has unveiled novel features that significantly enhance the model interpretability, and FIND has adeptly delineated evolutionary trends in human accelerated regions. Furthermore, applying FIND to the interpretation of clinical variants demonstrates its substantial potential in reclassifying variants of unknown significance. This work advances our understanding of the genetic underpinnings of human adaptation and disease, providing a new tool to explore the complexities of genetic contributions to health.

genetics↗