Biology subjects

Lin, W.

Publications and source records attributed to Lin, W..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Structural insights into transcription regulation of the global virulence factor PhoP from Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb), remaining as the leading cause of the worldwide threat Tuberculosis, relies heavily on its transcriptional reprogramming of diverse stress genes to swiftly adapt to adverse environments and ensure infections. The global virulence factor PhoP plays a pivotal role in coordinating transcription activation or repression of the essential phosphate-nitrogen metabolic remodeling genes. However, what defines PhoP to deferentially act as an activator or a repressor remains largely unexplored. Here, we determine one cryo-EM structure of Mtb RNAP-promoter open complex, three cryo-EM structures of PhoP-dependent transcription activation complexes (PhoP-TACs) consisting of Mtb RNA polymerase (RNAP), different number of PhoP molecules binding to different types of well-characterized consensus promoters, and one cryo-EM structure of Mtb PhoP-dependent transcription repression complex (PhoP-TRC) comprising of Mtb RNAP, PhoP, the nitrogen metabolism regulator GlnR and their co-regulated promoter. Structural comparisons reveal phosphorylation of PhoP is required for stabilization of PhoP-TACs, PhoP specifically recognizes promoters as novel tandem dimers and recruits RNAP through extensively interacting with its conserved {beta} flap and {sigma}AR4 domains. Strikingly, the distinct promoter spacer length and PhoP-GlnR interactions in PhoP-TRC constrain the upstream DNA into a distinct topology and retain PhoP in a novel dragging repression mode. Collectively, these data highlight the dual regulatory mechanisms of PhoP-dependent transcription regulation in governing stress adaptation. These findings provide structural basis for developing potential anti-tuberculosis drugs and/or interventions.

microbiology↗

bioRxiv2024

Riluzole reverses blood-testis barrier loss to rescue chemotherapy induced male infertility by binding to TRPC

Cancer treatments, including cytotoxic therapy, often result in male infertility, necessitating the development of safe and effective strategies to preserve male reproductive potential during chemotherapy. Notably, our study uncovers the potential of repurposing riluzole, an FDA-approved drug for amyotrophic lateral sclerosis (ALS), in enhancing spermatogenesis. Hence, this research aims to explore the feasibility of utilizing riluzole to alleviate male infertility induced by busulfan (BSF), a commonly used chemotherapy drug. We established a BSF-induced oligospermia model in 4-week-old male mice and found that riluzole could effectively countered the detrimental effects of BSF on sperm production in mice with oligospermia. By restoring blood-testis barrier (BTB) functionality, riluzole improves sperm quality and reduces testicular atrophy. Through transcriptomic and molecular docking analyses, we identify transient receptor potential canonical subfamily member 5 (TRPC5) as a potential target for riluzole-mediated regulation of blood-testis barrier function. These findings propose riluzole as a promising therapeutic option for chemotherapy-induced male infertility, thereby addressing the fertility challenges associated with cancer treatments. Moreover, repurposing riluzole could streamline the drug development process, providing a cost-effective approach with reduced risk compared to developing entirely new drugs.

pharmacology and toxicology↗

bioRxiv2024

The under-recognized dominance of magnetosome gene cluster-containing bacteria in oxygen-stratified freshwater ecosystems

Magnetotactic bacteria (MTB) capable of magnetosome organelle biomineralization and magnetotaxis are widespread in chemically stratified aquatic environments. Conventionally, it has long been considered that the overall abundance of MTB in microbiota is not very high and that Magnetococcia is the most frequently identified and predominant MTB members. However, the diversity and distribution of MTB in chemically stratified environments remain elusive due to the lack of large-scale systematic analyses. Here we conduct a comprehensive survey of genomes containing magnetosome gene clusters (MGCs), a group of genes responsible for magnetosome biomineralization and magnetotaxis, in 267 metagenomes from 38 oxygen-stratified freshwater environments. A total of 63 MGC-containing genomes belonging to eight bacterial phyla are reconstructed, including the newly identified Myxococcota. We discover an unexpectedly high relative abundance of putative MTB (up to 15.4% of metagenomic reads) in hypoxic and anoxic water columns, in which Deltaproteobacteria, rather than traditionally considered Magnetococcia, are the most ubiquitous and predominant MGC-containing bacteria. Our analysis reveals a depth-specific taxonomy and function of MGC-containing bacteria in stratified water columns shaped by physicochemical conditions. These findings underscore the unrecognized ecophysiological importance of MTB in freshwater ecosystems.

microbiology↗

bioRxiv2024

Sensitive Fluorescent Biosensor Reveals Differential Subcellular Regulation of PKC

The protein kinase C (PKC) family of serine/threonine kinases, which consist of three distinctly regulated subfamilies, have long been established as critical for a variety of cellular functions. However, how PKC enzymes are regulated at different subcellular locations, particularly at emerging signaling hubs such as the ER, lysosome, and Par signaling complexes, is unclear. Here, we present a sensitive Excitation Ratiometric (ExRai) C Kinase Activity Reporter (ExRai-CKAR2) that enables the detection of minute changes in subcellular PKC activity. Using ExRai-CKAR2 in conjunction with an enhanced diacylglycerol (DAG) biosensor capable of detecting intracellular DAG dynamics, we uncover the differential regulation of PKC isoforms at distinct subcellular locations. We find that G-protein coupled receptor (GPCR) stimulation triggers sustained PKC activity at the ER and lysosomes, primarily mediated by Ca2+ sensitive conventional PKC (cPKC) and novel PKC (nPKC), respectively, with nPKC showing high basal activity due to elevated basal DAG levels on lysosome membranes. The high sensitivity of ExRai-CKAR2, targeted to either the cytosol or Par-complexes, further enabled us to detect previously inaccessible endogenous atypical PKC (aPKC) activity in 3D organoids. Taken together, ExRai-CKAR2 is a powerful tool for interrogating PKC regulation in response to physiological stimuli.

bioengineering↗

bioRxiv2024

Aeromonas hydrophila CobQ is a new type of NAD+- and Zn2+-independent protein lysine deacetylase in prokaryotes

Protein N--lysine acetylation (Kac) modifications play crucial roles in diverse physiological and pathological functions in cells. In prokaryotic cells, there are only two types of lysine deacetylases (KDACs) that are Zn2+- or NAD+-dependent. In this study, we reported a protein, AhCobQ, in Aeromonas hydrophila ATCC 7966 that presents NAD+- and Zn2+-independent KDAC activity. Furthermore, its KDAC activity is located in an unidentified domain (from 195-245 aa). Interestingly, AhCobQ has no homology with current known KDACs, and no homologous protein was found in eukaryotic cells. A protein substrate analysis showed that AhCobQ has specific protein substrates in common with other known KDACs, indicating that these KDACs can dynamically co-regulate the states of Kac proteins. Microbiological methods employed in this study affirmed AhCobQs positive regulation of isocitrate dehydrogenase (ICD) enzymatic activity at the K388 site, implicating AhCobQ in the modulation of bacterial enzymatic activities. In summary, our findings present compelling evidence that AhCobQ represents a distinctive type of KDAC with significant roles in bacterial biological functions. SummaryThe lack of exploration of new lysine acetylases and deacetylases (KDACs) and their protein substrates in prokaryotic cells has become a bottleneck in the functional study of lysine acetylation modifications. In this study, we reported a novel Zn2+- and NAD+-independent KDAC protein, AhCobQ, in Aeromonas hydrophila. Interestingly, this protein does not share homology with current known KDACs, and its KDAC activity is located in an unknown domain for which a homologous protein cannot be found in eukaryotic cells. The following analysis showed that AhCobQ affected the enzymatic activity and protein-protein interaction ability of its protein substrates. In summary, these results extended our understanding of the regulatory mechanism of bacterial lysine acetylation modifications. HighlightsAhCobQ is an NAD+- and Zn2+-independent protein lysine deacetylase. There are no proteins homologous to AhCobQ in eukaryotes. The deacetylase activity of AhCobQ is located in an unknown domain. AhCobQ has specific protein substrates and substrates in common with other lysine deacetylases. AhCobQ positively regulates the enzymatic activity of isocitrate dehydrogenase at its K388 site.

microbiology↗

bioRxiv2024

Light-gated Integrator for Highlighting Kinase Activity in Living Cells

Protein kinases are key signaling nodes that regulate fundamental biological and disease processes. Illuminating kinase signaling from multiple angles can provide deeper insights into disease mechanisms and improve therapeutic targeting. While fluorescent biosensors are powerful tools for visualizing live-cell kinase activity dynamics in real time, new molecular tools are needed that enable recording of transient signaling activities for post hoc analysis and targeted manipulation. Here, we develop a light-gated kinase activity coupled transcriptional integrator (KINACT) that converts dynamic kinase signals into "permanent" fluorescent marks. KINACT enables robust monitoring of kinase activity across scales, accurately recording subcellular PKA activity, highlighting PKA signaling heterogeneity in 3D cultures, and identifying PKA activators and inhibitors in high-throughput screens. We further leverage the ability of KINACT to drive signaling effector expression to allow feedback manipulation of the balance of GsR201C-induced PKA and ERK activation and dissect the mechanisms of oncogenic G protein signaling.

bioengineering↗

bioRxiv2024

Causal Brain Network Evaluates Surgical Outcomes in Patients with Drug-Resistant Epilepsy: A Retrospective Comparative Study

Network neuroscience has greatly facilitated epilepsy studies; meanwhile, drug-resistant epilepsy (DRE) is increasingly recognized as a brain network disorder. Unfortunately, surgical success rates in patients with DRE are still very limited, varying 30% [~] 70%. At present, there is almost no systematic exploration of intracranial electrophysiological brain network closely related to surgical outcomes, and it is not clear which brain network methodologies can effectively promote DRE precision medicine. In this retrospective comparative study, we included multicenter datasets, containing electrocorticogram (ECoG) data from 17 DRE patients with 55 seizures. Ictal ECoG within clinically-annotated epileptogenic zone (EZ) and non-epileptogenic zone (NEZ) were separately computed using six different algorithms to construct causal brain networks. All the brain network results were divided into two groups, successful and failed surgery. Statistical results based on the Mann-Whitney-U-test show that: causal connectivity of -frequency band (8 [~] 13 Hz) in EZ calculated by convergent cross mapping (CCM) gains the most significant differences between the surgical success and failure groups, with a P value of 7.85e-08 and Cohens d effect size of 0.77. CCM-defined EZ brain network can also distinguish the successful and failed surgeries considering clinical covariates (clinical centers, DRE types) with P < 0. 001. Based on the brain network features, machine learning models are established to predict the surgical outcomes. Among them, SVM classifier with Gaussian kernel function and Bayesian Optimization demonstrates the highest average accuracy of 84.48% through 5-fold cross validation, further indicating that the CCM-defined EZ brain network is a reliable biomarker for predicting DREs surgical outcomes.

neuroscience↗

bioRxiv2024

iSORT: An Integrative Method for Reconstructing Spatial Organization of Cells using Transfer Learning

Spatial tissues exhibit complex gene expression and multicellular patterns that are difficult to dissect. Single-cell RNA sequencing (scRNA-seq) provides full coverages of genes, but lacking spatial information, whereas spatial transcriptomics (ST) measures spatial locations of individual or group of cells, with more restrictions on gene information. To integrate scRNA-seq and ST data, we introduce a transfer learning method to decipher spatial organization of cells named iSORT. iSORT trains a neural network that maps gene expressions to spatial locations using scRNA-seq data along with ST slices as references. iSORT can find spatial patterns at single-cell scale, identify key genes that drive the patterning, and infer pseudo-growth trajectories using a concept of SpaRNA velocity. Benchmarking on simulation data and comparing with multiple existing tools show iSORTs robustness and accuracy in reconstructing spatial organization. Using our own new human artery datasets, iSORT shows its capability of dissecting atherosclerosis. Applications to a range of biological systems, such as mouse embryo, mouse brain, Drosophila embryo, and human developmental heart, demonstrate that iSORT can utilize both scRNA-seq and ST datasets to uncover multilayer spatial information of single cells.

bioinformatics↗

bioRxiv2024

Beyond Glycolysis: Aldolase A is a Novel Effector in Reelin Mediated Dendritic Development

Reelin, a secreted glycoprotein, plays a crucial role in guiding neocortical neuronal migration, dendritic outgrowth and arborization, and synaptic plasticity in the adult brain. Reelin primarily operates through the canonical lipoprotein receptors apolipoprotein E receptor 2 (Apoer2) and very low-density lipoprotein receptor (Vldlr). Reelin also engages with non-canonical receptors and unidentified co-receptors; however, the effects of which are less understood. Using high-throughput tandem mass tag LC-MS/MS-based proteomics and gene set enrichment analysis, we identified both shared and unique intracellular pathways activated by Reelin through its canonical and non-canonical signaling in primary murine neurons during dendritic growth and arborization. We observed pathway crosstalk related to regulation of cytoskeleton, neuron projection development, protein transport, and actin filament-based process. We also found enriched gene sets exclusively by the non-canonical Reelin pathway including protein translation, mRNA metabolic process and ribonucleoprotein complex biogenesis suggesting Reelin fine-tunes neuronal structure through distinct signaling pathways. A key discovery is the identification of aldolase A, a glycolytic enzyme and actin binding protein, as a novel effector of Reelin signaling. Reelin induced de novo translation and mobilization of aldolase A from the actin cytoskeleton. We demonstrated that aldolase A is necessary for Reelin-mediated dendrite growth and arborization in primary murine neurons and mouse brain cortical neurons. Interestingly, the function of aldolase A in dendrite development is independent of its known role in glycolysis. Altogether, our findings provide new insights into the Reelin-dependent signaling pathways and effector proteins that are crucial for actin remodeling and dendritic development. SignificanceReelin is an extracellular glycoprotein and exerts its function primarily by binding to the canonical lipoprotein receptors Apoer2 and Vldlr. Reelin is best known for its role in neuronal migration during prenatal brain development. Reelin also signals through a non-canonical pathway outside of Apoer2/Vldlr; however, these receptors and signal transduction pathways are less defined. Here, we examined Reelins role during dendritic outgrowth in primary murine neurons and identified shared and distinct pathways activated by canonical and non-canonical Reelin signaling. We also found aldolase A as a novel effector of Reelin signaling, that functions independently of its known metabolic role, highlighting Reelins influence on actin dynamics and neuronal structure and growth.

neuroscience↗

bioRxiv2024

Protein SUMOylation promotes cAMP-independent EPAC1 activation

Exchange protein directly activated by cAMP (EPAC1) mediates the intracellular functions of a critical stress-response second messenger, cAMP. Herein, we report that EPAC1 is a cellular substrate of protein SUMOylation, a prevalent stress-response posttranslational modification. Site-specific mapping of SUMOylation by mass spectrometer leads to identifying K561 as a primary SUMOylation site in EPAC1. Sequence and site-directed mutagenesis analyses reveal a functional SUMO-interacting motif required for cellular SUMOylation of EPAC1. SUMO modification of EPAC1 mediates its heat shock-induced Rap1/2 activation in a cAMP-independent manner. Structural modeling and molecular dynamics simulation studies demonstrate that SUMO substituent on K561 of EPAC1 promotes Rap1 interaction by increasing the buried surface area between the SUMOylated receptor and its effector. Our studies identify a functional SUMOylation site in EPAC1 and unveil a novel mechanism in which SUMOylation of EPAC1 leads to its autonomous activation. The findings of SUMOylation-mediated activation of EPAC1 not only provide new insights into our understanding of cellular regulation of EPAC1 but also will open up a new field of experimentation concerning the cross-talk between cAMP/EPAC1 signaling and protein SUMOylation, two major cellular stress response pathways, during cellular homeostasis.

cell biology↗

bioRxiv2023

DFNA5-mediated pyroptosis is a driver for venetoclax and azacytidine synergy in myeloid leukemia

Acute myeloid leukemia (AML) remains the deadliest adult leukemia with dismal clinical outcomes. Since 2020, a combination of BCL-2 inhibitor (venetoclax, VEN) with hypomethylating agent (azacytidine/decitabine, AZA/DAC) has become a new standard of care in elderly or unfit AML patients. However, the underlying mechanism of synergy between venetoclax and azacytidine combination is not well understood. While apoptosis is regarded as the primary mode of cell death mechanism caused by the venetoclax and azacytidine combination, we provide novel evidence for pyroptosis as additional cell death mechanisms in response to venetoclax and azacytidine combination therapy. We found that long-term treatment with azacytidine caused hypomethylation and significant upregulation in DFNA5/GSDME, pore forming Gasdermin family gene that is otherwise silent in myeloid leukemia. We found that azacytidine mediates N-terminal pore-forming DFNA5 cleavage, membrane rupture, and subsequent pyroptosis of DFNA5 overexpressing cells in response to venetoclax and azacytidine. Deletion of DFNA5 reduced total cell viability, where DFNA5 KO cells exclusively underwent apoptosis while DFNA5 OE cells showed increased propidium iodide uptake, a marker for membrane rupture. Overall, our study establishes DFNA5 as an important mediator of venetoclax and azacytidine-induced cell death via non-apoptotic mechanisms.

cancer biology↗

bioRxiv2023

PANAMA enabled high sensitivity dual nanoflow LC/MS metabolomics and proteomics analysis

High sensitivity nanoflow liquid chromatography (nLC) is seldom employed in untargeted metabolomics because current sample preparation techniques are inefficient to prevent nanocapillary column performance degradation. Here, we describe an nLC-based tandem mass spectrometry workflow that enables seamless joint analysis and integration of metabolomics (including lipidomics) and proteomics from the same samples without instrument duplication. This workflow is based on robust solid phase micro-extraction step for routine sample clean-up and bioactive molecule enrichment. Our method, termed PANAMA, improves compound resolution and detection sensitivity without compromising depth of coverage as compared with existing widely used analytical procedures. Notably, PANAMA can be applied to a broad array of specimens including biofluids, cell line and tissue samples. It generates high quality, information rich metabolite-protein datasets while bypassing the need for specialized instrumentation. MotivationThe ability to routinely, sensitively and reproducibly analyze both cellular proteins and metabolite mixtures from the same biospecimens can enhance the discovery of biomolecules associated with basic biochemical processes and pathobiological states. Yet existing mass spectrometry-based profiling methods rely on specialized protocols and duplicated instrumentation platforms, resulting in increased time, sample consumption and costs. We sought to generate an effective platform for both metabolomic and proteomic studies on the same samples by enabling nanoflow liquid chromatography for small molecules. The resulting approach was extensively optimized and benchmarked to provide in depth molecular coverage, along with improved chromatographic separations, sensitivity and reliability as compared to existing methods. The cost benefit ratio of PANAMA is substantial because the platform bypasses the need for specialized instrumentation stemming from incompatible procedures.

systems biology↗

bioRxiv2023

Mesoscale functional organization and connectivity of color, disparity, and naturalistic texture in human second visual area

Although parallel processing has been extensively studied in the low-level geniculostriate pathway and the high-level dorsal and ventral visual streams, less is known at the intermediate-level visual areas. In this study, we employed high-resolution fMRI at 7 Tesla to investigate the columnar and laminar organizations for color, disparity, and naturalistic texture in the human secondary visual cortex (V2), and their informational connectivity with lower and higher order visual areas. Although fMRI activations in V2 showed reproducible interdigitated color-selective thin and disparity-selective thick "stripe" columns, we found no clear evidence of columnar organization for naturalistic textures. Cortical depth-dependent analyses revealed the strongest color-selectivity in the superficial layers of V2, along with both feedforward and feedback informational connectivity with V1 and V4. Disparity selectivity was similar across different cortical depths of V2, which showed significant feedforward and feedback connectivity with V1 and V3ab. Interestingly, the selectivity for naturalistic texture was strongest in the deep layers of V2, with significant feedback connectivity from V4. Thus, while local circuitry within cortical columns is crucial for processing color and disparity information, feedback modulations from V4 play a dominant role in processing naturalistic textures in area V2.

neuroscience↗

bioRxiv2023

Enabling brain-wide mapping of directed functional connectivity at 3T via layer-dependent fMRI with draining-vein suppression

Layer-dependent functional magnetic resonance imaging (fMRI) is a promising yet challenging approach for investigating layer-specific functional connectivity (FC). Achieving a brain-wide mapping of layer-specific FC requires several technical advancements, including sub-millimeter spatial resolution, sufficient temporal resolution, functional sensitivity, global brain coverage, and high spatial specificity. Although gradient echo (GE)-based echo planar imaging (EPI) is commonly used for rapid fMRI acquisition, it faces significant challenges due to the draining-vein contamination. In this study, we addressed these limitations by integrating velocity-nulling (VN) gradients into a GE-BOLD fMRI sequence to suppress vascular signals from the vessels with fast-flowing velocity. The extravascular contamination from pial veins was mitigated using a GE-EPI sequence at 3T rather than 7T, combined with phase regression methods. Additionally, we incorporated advanced techniques, including simultaneous multi-slice (SMS) acceleration and NOise Reduction with DIstribution Corrected principal component analysis (NORDIC PCA) denoising, to improve temporal resolution, spatial coverage, and signal sensitivity. This resulted in a VN fMRI sequence with 0.9-mm isotropic spatial resolution, a repetition time (TR) of 4 seconds, and brain-wide coverage. The VN gradient strength was determined based on results from a button-pressing task. Using resting-state data, we validated layer-specific FC through seed-based analyses, identifying distinct connectivity patterns in the superficial and deep layers of the primary motor cortex (M1), with significant inter-layer differences. Further analyses with a seed in the primary sensory cortex (S1) demonstrated the reliability of the method. Brain-wide layer-dependent FC analyses yielded results consistent with prior literature, reinforcing the efficacy of VN fMRI in resolving layer-specific functional connectivity. Given the widespread availability of 3T scanners, this technical advancement has the potential for significant impact across multiple domains of neuroscience research.

neuroscience↗

bioRxiv2023

Quantitative Learning of Cellular Features From Single-cell Transcriptomics Data Facilitates Effective Drug Repurposing

In this study, we have devised a computational framework SuperFeat that allows for the training of a machine learning model and evaluate the canonical cellular states/features in pathological tissues that underlie the progression of disease. This framework also enables the identification of potential drugs that target the presumed detrimental cellular features. This framework was constructed on the basis of an artificial neural network with the gene expression profiles serving as input nodes. The training data comprised single-cell RNA-seq datasets that encompassed the specific cell lineage during the developmental progression of cell features. A few models of the canonical cancer-involved cellular states/features were tested by such framework. Finally, we have illustrated the drug repurposing pipeline, utilizing the training parameters derived from the adverse cellular states/features, which has yielded successful validation results both in vitro and in vivo. SuperFeat is accessible at https://github.com/weilin-genomics/rSuperFeat.

cell biology↗

bioRxiv2023

omicsMIC: a Comprehensive Benchmarking Platform for Robust Comparison of Imputation Methods in Mass Spectrometry-based Omics Data

Mass spectrometry is a powerful and widely used tool for generating proteomics, lipidomics, and metabolomics profiles, which is pivotal for elucidating biological processes and identifying biomarkers. However, missing values in spectrometry-based omics data may pose a critical challenge for the comprehensive identification of biomarkers and elucidation of the biological processes underlying human complex disorders. To alleviate this issue, various imputation methods for mass spectrometry-based omics data have been developed. However, a comprehensive and systematic comparison of these imputation methods is still lacking, and researchers are frequently confronted with a multitude of options without a clear rationale for method selection. To address this pressing need, we developed omicsMIC (mass spectrometrybased omics with Missing values Imputation methods Comparison platform), an interactive platform that provides researchers with a versatile framework to simulate and evaluate the performance of 28 diverse imputation methods. omicsMIC offers a nuanced perspective, acknowledging the inherent heterogeneity in biological data and the unique attributes of each dataset. Our platform empowers researchers to make data-driven decisions in imputation method selection based on real-time visualizations of the outcomes associated with different imputation strategies. The comprehensive benchmarking and versatility of omicsMIC make it a valuable tool for the scientific community engaged in mass spectrometry-based omics research. OmicsMIC is freely available at https://github.com/WQLin8/omicsMIC.

bioinformatics↗

bioRxiv2023

Accurate Prediction of Antibody Function and Structure Using Bio-Inspired Antibody Language Model

In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Anti-body Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% non-redundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold, and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials.

bioinformatics↗

bioRxiv2023

Genetic regulatory effects in response to a high cholesterol, high fat diet in baboons

Steady-state expression quantitative trait loci (eQTLs) explain only a fraction of disease-associated loci identified through genome-wide association studies (GWAS), while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Using a baboon model, we found hundreds of eQTLs that emerge in adipose, liver, and muscle after prolonged exposure to high dietary fat and cholesterol. Diet-responsive eQTLs exhibit genomic localization and genic features that are distinct from steady-state eQTLs. Furthermore, the human orthologs associated with diet-responsive eQTLs are enriched for GWAS genes associated with human metabolic traits, suggesting that context-responsive eQTLs with more complex regulatory effects are likely to explain GWAS hits that do not seem to overlap with standard eQTLs. Our results highlight the complexity of genetic regulatory effects and the potential of eQTLs with disease-relevant GxE interactions in enhancing the understanding of GWAS signals for human complex disease using nonhuman primate models.

genomics↗