Biology subjects

Zhang, G.

Publications and source records attributed to Zhang, G..

At least 163 records · Page 9Linked to original sources

bioRxiv2024

Genetic modulation of yield and phenotypic plasticity of yield in winter wheat

For winter wheat in the US Central Great Plains, phenotypic plasticity of yield is agronomically adaptive, i.e., genotypes with higher plasticity have higher yield in high yielding environments with no tradeoff in stressful, low yielding environments. Using data from variety trials conducted between 2000 and 2022 and cultivars released between 1967 and 2022, we explored time trends in phenotypic plasticity and heritability of yield. We hypothesize that i) if yield plasticity is agronomically adaptive, then newer cultivars will have higher yield plasticity; ii) heritability of yield is declining in the time series; and iii) genomic regions associated with yield depend on the environment and do not fully overlap with those associated with phenotypic plasticity of yield. Breeding for yield and agronomic adaptation increased phenotypic plasticity of yield at 0.5% year -1; broad sense heritability of yield decreased from 0.23 in 1993 to 0.15 in 2017. Genome-wide-association analysis shows genomic regions associated with yield varied between high yielding and stressful environments and were partially independent of those associated with yield plasticity. Newer cultivars have a higher frequency of alleles associated with yield and its plasticity. We discuss implications for breeding and agronomy aimed to improve wheat phenotypes.

genetics↗

bioRxiv2024

A Multi-Modal Deep Learning Framework with Both Sequence and Structure for Tumor Antigens Prediction

Tumor antigens are key targets in cancer immunotherapies that can be recognized by T cell receptor and induce immune responses. However, precision screening of immunogenic tumor antigens remains a great challenge due to human leukocyte antigen (HLA) restriction and tumor antigen escape. Here, we introduce MultiTAP (Multi-modal Tumor Antigen Predictor), a pioneering multi-modal framework with TCR-peptide-HLA sequence and structure features incorporating an attention mechanism designed to accurately identify tumor antigens with immunogenic properties. By constructing the multi-modal TCR-peptide-HLA Dataset (TPHD) and integrating its sequence and structure, we perform antigen feature enhancement using peptide-HLA (pHLA) structural features at the residue level, achieving interpretable prediction of immunogenicity for tumor antigens. Relative to existing baseline models, the MultiTAP framework has exhibited superior efficacy in predicting the immunogenicity of tumor antigens. Through comprehensive out-of-distribution (OOD) assessments, MultiTAP has maintained predictive robustness across diverse HLA phenotypes and the continuously evolving landscape of epitope distributions. Overall, MultiTAP presents a brand-new and promising approach for cancer immunotherapies that target tumor antigens.

biophysics↗

bioRxiv2024

PreDigs: a Database of Context-specific Cell-type Markers and Precise cell subtypes for Digestive Cell Annotation

Research on cell type markers aids investigators in exploring the diverse cellular compositions within gastrointestinal tumors, enhancing our understanding of tumor heterogeneity and its implications for disease progression and treatment response. However, issues such as the integration of large-scale datasets and the lack of standardized cell type identification hinder comprehensive characterization. Here, we developed a user-friendly web interface called PreDigs (Predicted Signatures in Digestive System), which offers 124 tailored scRNA-seq datasets available for download, encompassing over 3.4 million cells. After unsupervised clustering, we unified the identification and naming of subtype labels, ultimately constructing a cell ontology tree that includes 142 cell types, with up to eight hierarchical levels. Meanwhile, we calculated three different context-specific cell-type markers--Cell Markers, Subtype Markers, and TPN Markers--based on various application requirements within or across tissues. Through the integrated analysis of PreDigs gastrointestinal data, we identified distinct cell subpopulations exclusive to tumors, one of which corresponds to tumor-specific endothelial cells (TEC). Furthermore, PreDigs offers online cell annotation tools that empower users to perform single-cell classification with greater flexibility, accessible at https://www.biosino.org/predigs/.

bioinformatics↗

bioRxiv2024

Physical-aware model accuracy estimation for protein complex using deep learning method

With the breakthrough of AlphaFold2 on monomers, the research focus of structure prediction has shifted to protein complexes, driving the continued development of new methods for multimer structure prediction. Therefore, it is crucial to accurately estimate quality scores for the multimer model independent of the used prediction methods. In this work, we propose a physical-aware deep learning method, DeepUMQA-PA, to evaluate the residue-wise quality of protein complex models. For the input complex model, the residue-based contact area and orientation features were first constructed using Voronoi tessellation, representing the potential physical interactions and hydrophobic properties. Then, the relationship between local residues and the overall complex topology as well as the inter-residue evolutionary information are characterized by geometry-based features, protein language model embedding representation, and knowledge-based statistical potential features. Finally, these features are fed into a fused network architecture employing equivalent graph neural network and ResNet network to estimate residue-wise model accuracy. Experimental results on the CASP15 test set demonstrate that our method outperforms the state-of-the-art method DeepUMQA3 by 3.69% and 3.49% on Pearson and Spearman, respectively. Notably, our method achieved 16.8% and 15.5% improvement in Pearson and Spearman, respectively, for the evaluation of nanobody-antigens. In addition, DeepUMQA-PA achieved better MAE scores than AlphaFold-Multimer and AlphaFold3 self-assessment methods on 43% and 50% of the targets, respectively. All these results suggest that physical-aware information based on the area and orientation of atom-atom and atom-solvent contacts has the potential to capture sequence-structure-quality relationships of proteins, especially in the case of flexible proteins. The DeepUMQA-PA server is freely available at http://zhanglab-bioinf.com/DeepUMQA-PA/.

bioinformatics↗

bioRxiv2024

Comparative spatiotemporal single cell transcriptomes reveal rewiring of pre-existing regulations during emergence of Kranz anatomy in C4 grasses

Many of the worlds most productive food and bioenergy crops use C4 photosynthesis, which have high photosynthetic efficiency due to a Kranz anatomy-based CO2 concentrating mechanism. Here, we took a comparative transcriptomics approach using single cell spatial transcriptomes of leaf primordia for maize (Zea mays) and single cell RNA-seq (scRNA-seq) atlases of corresponding leaf tissues for three C4 species (Zea mays, Sorghum bicolor, Setaria viridis) and one C3 rice (Oryza sativa) to study regulatory networks involved in the development and evolution of Kranz anatomy. We show that the formation of Kranz anatomy involves extensive recruitment and modification of pre-existing regulatory modules, especially the SHR-SCR module and the auxin signaling pathway. Members of the INDETERMINATE DOMAIN (IDD) family transcription factors, including IDD7 and IDDP1, contribute to the modification of the involved modules. These extensive recruitment and modification of existing genetic regulatory programs underlie the repeated emergence of C4 photosynthesis during evolution.

plant biology↗

bioRxiv2024

Transcranial Brain-Wide Functional Ultrasound and Ultrasound Localization Microscopy in Mice using Multilinear Probes

Functional ultrasound imaging (fUS) and ultrasound localization microscopy (ULM) are advanced ultrasound imaging modalities for assessing both functional and anatomical characteristics of the brain. However, the application of these techniques at a whole-brain scale has been limited by technological challenges. While conventional linear acoustic probes provide a narrow 2D field of view and matrix probes lack sufficient sensitivity for 3D transcranial fUS, multilinear probes have been developed to combine high sensitivity to blood flow with fast 3D acquisitions. In this study, we present a novel approach the combined implementation of transcranial whole-brain fUS and ULM in mice using a motorized multilinear probe. This technique provides high-resolution, non-invasive imaging of neurovascular dynamics across the entire brain. Our findings reveal a significant correlation between absolute cerebral blood volume ({Delta}CBV) increases and microbubble velocity, indicating vessel-level dependency of the evoked response. However, the lack of correlation with relative CBV (rCBV) suggests that fUS cannot distinguish functional responses alterations across different arterial vascular compartments. This methodology holds promise for advancing our understanding of neurovascular coupling and could be applied in brain disease diagnostics and therapeutic monitoring.

neuroscience↗

bioRxiv2024

Nonlinear Singular Value Decomposition Beamforming for Ultrasound Imaging of Gas Vesicles

Ultrasound imaging holds significant promise for the observation of molecular and cellular phenomena through the utilization of acoustic contrast agents and acoustic reporter genes. Optimizing imaging methodologies for enhanced detection represents an imperative advancement in this field. Most advanced techniques relying on amplitude modulation scheme such as cross amplitude modulation (xAM) and ultrafast amplitude modulation (uAM) combined with Hadamard encoded multiplane wave transmissions have shown efficacy in capturing acoustic signals of gas vesicles (GVs). Nonetheless, uAM sequence requires odd- or even-element transmissions leading to imprecise amplitude modulation emitting scheme, and the complex multiplane wave transmission scheme inherently yields overlong pulse durations. xAM sequence is limited in terms of field of view and imaging depth. To overcome these limitations, we introduce an innovative ultrafast imaging sequence called nonlinear singular value decomposition (SVD) beamforming. Our method demonstrated a contrast imaging sensitivity comparable to the current gold-standard xAM and uAM, while requiring 4.8 times less pulse transmissions. With similar number of transmit pulses, nonlinear SVD beamforming outperforms xAM and uAM in terms of an improvement in signal-to-background ratio of + 4.78 {+/-} 0.35 dB and + 8.29 {+/-} 3.52 dB respectively. Additionally, our method provides a higher flexibility in terms of the selection of acoustic pressure amplitude compared to the other methods. Furthermore, it shows a significant potential for application in the realm of ultrasound localization microscopy (ULM), where it stands poised to facilitate the more precise extraction of nonlinear signatures originating from contrast agents.

biophysics↗

bioRxiv2024

Deciphering RNA regulation with a foundation language model

RNA metabolism is tightly regulated by cis-elements and trans-acting factors. Most information guiding such regulation is encoded in RNA sequences. Considering the similarities in semantic and syntactic features between RNAs and human language, we developed LAMAR, a transformer-based foundation language model for RNA regulation, to decipher general rules underlying RNA processing. The model was pretrained on approximately 15 million sequences from both genome and transcriptome of 225 mammals and 1569 viruses, and further fine-tuned with labeled datasets for various tasks. The resulting fine-tuned models outperformed the state-of-the-art methods in predicting mRNA translation efficiency and mRNA half-life, while achieving comparable accuracy to specifically designed methods in predicting splice sites of pre-mRNAs and internal ribosome entry sites. Our results indicated that a single foundation language model is applicable in the comprehensive analysis of different aspects of RNA regulation, providing new insight into the design and optimization of RNA drugs.

bioinformatics↗

bioRxiv2024

Cholecystokinin-expressing GABA neurons elicit long-term potentiation in the cortical inhibitory synapses and attenuate sound-shock associative memory

Neuronal interactions between inhibitory and excitatory neurons play a pivotal role in regulating the balance of excitation and inhibition in the central nervous system (CNS). Consequently, the efficacy of inhibitory/excitatory synapses profoundly affects neural network processing and overall neuronal functions. Here, we describe a novel form of long-term potentiation (LTP) induced at cortical inhibitory synapses and its behavioral consequences. We show that high-frequency laser stimulation (HFLS) of GABAergic neurons elicit inhibitory LTP (i-LTP) in pyramidal neurons of the auditory cortex (AC). The selective activation of cholecystokinin-expressing GABA (GABACCK) neurons is essential for the formation of HFLS-induced i-LTP, rather than the classical parvalbumin (PV) neurons and somatostatin (SST) neurons. Intriguingly, i-LTP can be evoked in the AC by adding the exogenous neuropeptide CCK when PV neurons and SST neurons are selectively activated in PV-Cre and SST-Cre mice, respectively. Additionally, we discovered that low-frequency laser stimulation (LFLS) of PV neurons paired with HFLS of GABACCK neurons potentiates the inhibitory effect of PV interneurons on pyramidal neurons, thereby generating heterosynaptic i-LTP in the AC. Notably, light activation of GABACCK neurons in CCK-Cre mice significantly attenuates sound-shock associative memory, while stimulation of PV neurons does not affect this memory in PV-Cre mice. In conclusion, these results demonstrate a critical mechanism regulating the excitation-inhibition balance and modulating learning and memory in cortical circuits. This mechanism might serve as a potential target for the treatment of neurological disorders, including epilepsy and Alzheimers disease.

neuroscience↗

bioRxiv2024

Integration of metabolomic and transcriptomic analyses reveals novel regulatory functions of the ChREBP transcription factor in energy metabolism

Carbohydrate Response Element-Binding Protein (ChREBP) is a transcription factor that activates key genes involved in glucose, fructose, and lipid metabolism in response to carbohydrate feeding, but its other potential roles in metabolic homeostasis have not been as well studied. We used liver-selective GalNAc-siRNA technology to suppress expression of ChREBP in rats fed a high fat/high sucrose diet and characterized hepatic and systemic responses by integrating transcriptomic and metabolomic analyses. GalNAc-siChREBP-treated rats had lower levels of multiple short-chain acyl CoA metabolites compared to rats treated with GalNAc-siCtrl containing a non-targeting siRNA sequence. These changes were related to a sharp decrease in free CoA levels in GalNAc-siChREBP treated-rats, accompanied by lower expression of transcripts encoding enzymes and transporters involved in CoA biosynthesis. These activities of ChREBP likely contribute to its complex effects on hepatic lipid and energy metabolism. While core enzymes of fatty acid (FA) oxidation are induced by ChREBP knockdown, accumulation of liver acylcarnitines and circulating ketones indicate diversion of acetyl CoA to ketone production rather than complete oxidation in the TCA cycle. Despite strong suppression of pyruvate kinase and activation of pyruvate dehydrogenase, pyruvate levels were maintained, likely via increased expression of pyruvate transporters, and decreased expression of lactate dehydrogenase and alanine transaminase. GalNAc-siChREBP treatment increased hepatic citrate and isocitrate levels while decreasing levels of distal TCA cycle intermediates. The drop in free CoA levels, needed for the 2-ketoglutarate dehydrogenase reaction, as well as a decrease in transcripts encoding the anaplerotic enzymes pyruvate carboxylase, glutamate dehydrogenase, and aspartate transaminase likely contributed to these effects. GalNAc-siChREBP treatment caused striking increases in PRPP and ZMP/AICAR levels, and decreases in GMP, IMP, AMP, NaNM, NAD(P), and NAD(P)H levels, accompanied by reduced expression of enzymes that catalyze late steps in purine and NAD synthesis. ChREBP suppression also increased expression of a set of plasma membrane amino acid transporters, possibly as an attempt to replenish TCA cycle intermediates. In sum, combining transcriptomic and metabolomic analyses has revealed regulatory functions of ChREBP that go well beyond its canonical roles in control of carbohydrate and lipid metabolism to now include mitochondrial metabolism and cellular energy balance.

physiology↗

bioRxiv2024

Biological volume EM with focused Ga ion beam depends on formation of radiation-resistant Ga-rich layer at block face

Volume electron microscopy (vEM) enables biologists to visualize nanoscale 3D ultrastructure of entire eukaryotic cells and tissues processed by heavy atom staining and plastic embedding. The vEM technique with the highest resolution is focused ion-beam scanning electron microscopy (FIB-SEM), which provides nearly isotropic ([~]5-10 nm) spatial resolution at fluences up to 10,000 e-/nm2. However, it is still not understood how such resolution is achievable, because serial block-face (SBF) SEM, which incorporates an in-situ ultramicrotome instead of a Ga+ FIB beam, results in radiation-induced collapse of similar specimen blocks at fluences of only [~]20 e-/nm2. Here, we show that FIB-SEM implants a thin concentrated layer of Ga+ ions, which greatly reduces electron beam-damage, reduces the depth from which backscattered electrons are detected, and prevents specimen charging and collapse. Furthermore, we show that the z-resolution (perpendicular to block-face) in FIB-SEM is substantially higher than predicted by Monte Carlo modeling of the backscattered signal when Ga implantation is not included.

biophysics↗

bioRxiv2024

Proteogenomic Characterization of Primary Oral Squamous Cell Carcinomas Unveils the Extracellular Matrix Remodeling and Immunosuppressive Microenvironment Linked with Lymph Node Metastasis

Oral squamous cell carcinoma (OSCC) is an increasingly prevalent malignancy worldwide. This study aims to understand molecular alterations associated with lymph node metastasis of OSCC in order to improve treatment strategies. We analyzed a cohort of 46 patients with primary OSCC, including 10 with lymph node metastasis and 36 without. Using a comprehensive multi-omics approach--encompassing genomic, transcriptomic, proteomic, epigenetic, single-cell, and spatial analyses--we integrated data to delineate the molecular landscape of OSCC in the context of lymph node metastasis. Our genomic analysis identified significant mutations in key genes within the MAPK, TGF-{beta}, and WNT signaling pathways, which are essential for tumor development. The proteogenomic analysis highlighted pathways critical for lymph node dissemination and factors contributing to an immunosuppressive tumor microenvironment. Elevated levels of POSTN were found to reorganize the extracellular matrix (ECM), interact with TGF-{beta}, disrupt cell cycle regulation, and suppress the immune response by reducing VCAM1 activity. Integrated analyses of single-cell and spatial transcriptome data revealed that cancer-associated fibroblasts (CAFs) secrete TGF-{beta}1/2, promoting cancer cell metastasis through epithelial-mesenchymal transition (EMT). Our integrated multi-omics analysis provides a detailed understanding of molecular mechanisms driving lymph node metastasis of OSCC. These insights could lead to more precise diagnostics and targeted treatments.

cancer biology↗

bioRxiv2024

A Comprehensive Proteogenomic and Spatial Analysis of Innate and Acquired Resistance of Metastatic Melanoma to Immune Checkpoint Blockade Therapies

While a subset of patients with metastatic melanoma achieves durable responses to immune checkpoint blockade (ICB) therapies, the majority ultimately exhibit either innate or acquired resistance to these treatments. However, the molecular mechanisms underlying resistance to ICB therapies remain elusive and are warranted to elucidate. Here, we comprehensively investigated the tumor and tumor immune microenvironment (TIME) of paired pre- and post-treatment tumor specimens from metastatic melanoma patients who were primary or secondary resistance to anti-CTLA-4 and/or anti-PD-1/PD-L1 therapies. Differentially expressed gene (DEG) analysis and single-sample gene set enrichment analysis (ssGSEA) with transcriptomic data identified cell cycle and c-MYC signaling as pathway-based resistance signatures. And weighted gene co-expression network analysis (WGCNA) revealed the activation of a cross-resistance meta-program involving key signaling pathways related to tumor progression in ICB resistant melanoma. Moreover, spatially-resolved, image-based immune monitoring analysis by using NanoStrings digital spatial profiling (DSP) and Cyclic Immunofluorescence (CyCIF) showed infiltration of suppressive immune cells in the tumor microenvironment of melanoma with resistance to ICB therapies. Our study reveals the molecular mechanisms underlying resistance to ICB therapies in patients with metastatic melanoma by conducting such integrated analyses of multi-dimensional data, and provides rationale for salvage therapies that will potentially overcome resistance to ICB therapies. Statement of translational relevanceThis study paves the way for the creation of innovative therapeutic strategies, aimed at subverting resistance to immune checkpoint blockade (ICB) therapies in metastatic melanoma patients. By unraveling the specific molecular mechanisms underlying resistance, scientists can design effective alternative treatments that target pathways such as pathways associated with cell cycle dysregulation and c-MYC signaling. Furthermore, through the application of advanced immune monitoring techniques such as NanoString Digital Spatial Profiling (DSP) and Cyclic Immunofluorescence (CyCIF), this study has significantly enriched our understanding of the tumor microenvironment. This enhanced characterization facilitates the discovery of potential biomarkers that may forecast a patients response to ICB treatment. Ultimately, these advancements could potentially refine patient outcomes and foster the development of more personalized cancer treatments in the future.

genetics↗

bioRxiv2024

Discovery of novel 1,4-dicarbonylthiosemicarbazides as DNA gyrase inhibitors for the treatment of MRSA infection

Antibiotic resistance has become a serious threat to public health, thus novel antibiotics are urgently needed to combat drug-resistant bacteria including MRSA (methicillin-resistant S. aureus). The 1,4-dicarbonylthiosemicarbazide is an interesting chemotype that could exhibit antibacterial activity. However, the currently available compounds are not as potent as clinical antibiotics. Herein, we adopted the computer-aided drug design strategy, substructure search, to retrieve antibacterial 1,4-dicarbonylthiosemicarbazide derivatives, and identified compound B5 (Specs ID: AG-690/15432331) from the Specs chemical library that exhibited moderate activity (minimum inhibitory concentration (MIC): 6.25 {micro}g/mL) against S. aureus (ATCC 29213). Based on that compound, we further designed and synthesized 45 derivatives, and evaluated their antibacterial activity. Eight derivatives were more potent than or equivalent to vancomycin (MIC: 1.56 {micro}g/mL). We compared the three most potent ones for their cytotoxicity to HepG2 and HUVEC cells and selected compound 1b as our lead compound for comprehensive biological evaluation. As a result, compound 1b exhibited a bacteriostatic mode, and was active against a panel of gram-positive bacteria strains, metabolically stable, and effective to protect the mice from MRSA infection. More importantly, we applied 2D similarity calculation and reverse docking to predict potential targets of compound 1b. Through experimental validation and molecular dynamics simulation, we were able to confirm that compound 1b inhibited S. aureus DNA gyrase (IC50: 1.81 {micro}M) and DNA supercoiling, potentially by binding to the ATPase domain, where ASP81, GLU58 and GLN91 formed key hydrogen bonds. Taken together, we have discovered a new class of DNA gyrase inhibitors represented by compound 1b for the treatment of MRSA infection, through the design, synthesis, and biological evaluation of novel 1,4-dicarbonylthiosemicarbazides. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/611349v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@549dadorg.highwire.dtl.DTLVardef@13bff64org.highwire.dtl.DTLVardef@1fc2c00org.highwire.dtl.DTLVardef@acee76_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIAn interesting 1,4-dicarbonylthiosemicarbazide derivative B5 with moderate antibacterial activity for S. aureus was discovered by substructure search. C_LIO_LIBased on B5, 45 new 1,4-dicarbonylthiosemicarbazides were designed, synthesized and biologically evaluated, which led to the discovery of a promising lead compound 1b. C_LIO_LICompound 1b exhibited good antibacterial activity for a panel of gram-positive bacteria strains, and was effective to protect mice from MRSA infection. C_LIO_LIThe 1,4-dicarbonylthiosemicarbazides represented by compound 1b were discovered as a new class of DNA gyrase inhibitors, by target prediction and experimental validation. C_LI

pharmacology and toxicology↗

bioRxiv2024

Discovery of novel quinoline papain-like protease inhibitors for COVID-19 through topology constrained molecular generative model

The rapid emergence of drug-resistant SARS-CoV-2 variants poses a persistent challenge to current antiviral strategies. Mutations in key viral targets, including RNA-dependent RNA polymerase (RdRp), main protease (3CLpro), and papain-like protease (PLpro), have been shown to markedly reduce the efficacy of approved therapeutics, highlighting the urgent need for next-generation antivirals capable of overcoming resistance. Here, we report the discovery of a novel class of PLpro inhibitors through an AIDD strategy based on a topology-constrained molecular generative model (Tree-Invent) integrated with structure-guided optimization. Scaffold hopping from a previously reported lead enabled the identification of a quinoline-based chemical series with substantially improved metabolic stability and antiviral potency. Structure-guided optimization yielded compound GZNL-2016, which exhibited potent enzymatic inhibition of PLpro (IC50 = 10.5 nM), robust antiviral activity against multiple SARS-CoV-2 variants, including Omicron BA.5 and XBB.1, and favorable pharmacokinetic properties following oral administration. Notably, GZNL-2016 retained substantial inhibitory activity against the clinically relevant drug-resistant mutant PLpro E167K (IC50 = 480.2 nM; Ki = 439.3 nM), in contrast to previously reported inhibitors that exhibit markedly reduced potency. In a SARS-CoV-2 infection mouse model, oral administration of GZNL-2016 significantly reduced pulmonary viral titers, demonstrating in vivo antiviral efficacy. Collectively, this study establishes an AI-enabled strategy for rapid antiviral discovery and identifies GZNL-2016 as a promising lead compound to address the threat of coronavirus infections caused by drug-resistant mutant SARS-CoV-2 variants. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/611841v3_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@ecbd3eorg.highwire.dtl.DTLVardef@7c663corg.highwire.dtl.DTLVardef@11c0e37org.highwire.dtl.DTLVardef@e950f0_HPS_FORMAT_FIGEXP M_FIG C_FIG We leveraged an AI generative model to discover a novel PLpro inhibitor with excellent liver stability, low CYP, hERG inhibition and reasonable oral PK properties. At the same time, the compound 16 exhibits high efficacy for the resistance mutation E167K, which resulted in severe resistance to the previously reported inhibitor Jun12682 and PF-07957472.

microbiology↗

bioRxiv2024

Tissue-specific and functional loci analysis of CASP14 gene in the sheep horn

Under the current context of intensive farming, small-horned animals are more suitable for large-scale breeding. The CASP14 gene, closely associated with skin and keratin formation, may influence horn size due to its link with skin development. This study comprehensively analyzed the tissue-specific expression of CASP14 using RNA-Seq data, identified functional sites through whole-genome sequencing (WGS), and investigated allele-specific expression (ASE) validated by KASP assays. Results showed significantly higher CASP14 expression in the scurred group com-pared to the SHE group, with pronounced expression in the skin. Interbreed comparisons also revealed elevated CASP14 levels in the scurred group. Analysis of potential functional sites indicated structural similarities in the CASP14 protein among horned mammals. Five ASE events were discovered, and intersecting these with SNPs and high fixation index loci (Fst > 0.05) identified three potential functional sites: 7941628, 7941817, and 7941830. The SNP site 7944295 was selected for T-test analysis and further validated through KASP assays, corroborating the role of CASP14 in sheep horn phenotypes. Our findings suggest that CASP14 plays a significant role in horn development, offering insights into breeding strategies for small-horned animals.

zoology↗

bioRxiv2024

A wheat tandem kinase and NLR pair confers resistance to multiple fungal pathogens

Recently discovered tandem kinase proteins (TKPs) are pivotal to the innate immune systems of cereal plants, yet how they initiate plant immune responses remains unclear. This report identifies the wheat protein WTN1, a non-canonical NLR receptor featuring tandem NB-ARC domains, as crucial for WTK3-mediated disease resistance. Both WTK3 and its allelic variant Rwt4, known for conferring resistance to wheat powdery mildew and blast respectively, are capable of recognizing the blast effector PWT4, and activate WTN1 to form calcium-permeable channels, akin to ZAR1 and Sr35. This study unveils a unique plant defense mechanism wherein TKPs and associated NLRs operate as "sensor-executor" pairs against fungal pathogens. Additionally, evolutionary analyses reveal a co-evolutionary trajectory of the TKP-NLR module, highlighting their synergistic role in triggering plant immunity. One Sentence SummaryAn ancient synergistic TKP-NLR pair triggers innate immunity for multiple disease resistance in wheat.

plant biology↗

bioRxiv2024

Conservation of gene expression patterns between the amniotic epithelium at birth and a newborn's nasal epithelium

BackgroundAmniotic epithelial cells are foetal-derived stem cells, capable of differentiating into all three germ layers, including mature epithelial cell populations. However, the conservation between amniotic epithelium and other epithelial tissues has not been sufficiently explored. We hypothesised that the amniotic epithelium might serve as a surrogate tissue source for investigating transcriptional profiles in the respiratory epithelium of the newborn. We compared gene expression profiles and weighted gene co-expression network structure in paired amniotic and newborn nasal epithelial samples from 85 participants in the Airway Epithelium Respiratory Illnesses and Allergy (AERIAL) birth cohort. ResultsIn total, 11,867 genes (79.7%) were commonly expressed in both amniotic and nasal epithelium, with uniquely expressed genes (2,563 and 458, respectively) enriched for biological functions related to each tissues specialist functions (e.g. developmental programs and ciliated cells, respectively). We observed a strong overlap in weighted gene co-expression network structure between both tissues, with ten co-expression modules identified in consensus network analysis. Genes commonly expressed in both tissues and/or found in the consensus network modules were enriched for biologically relevant gene signatures and pathway terms related to airway function. We also observed significant overlap in gene expression and network structure between the amniotic epithelium and published datasets of epithelial samples from the lower airway and other epithelial tissues including skin and oesophagus, suggesting a global epithelial signature. ConclusionsOverall, we observed significant overlap in gene expression and network structure between paired amniotic and nasal epithelial samples, supporting the potential of the amnion as a non-invasive and abundant tissue surrogate. Observed differences between tissues were related to each tissues specialist functions, which remains an important consideration when assessing their overlap. Future studies aimed at investigating amnion-based biomarkers for respiratory exposures in utero and disease outcomes in childhood are needed to extend these results towards clinical translation.

molecular biology↗