Biology subjects

Shen, M.

Publications and source records attributed to Shen, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Ultrahigh-Throughput Forster Resonance Energy Transfer-Activated Droplet Sorting for Terminator Polymerase Engineering

Droplet microfluidic screening systems enable high-throughput, labor-saving enzyme directed evolution by employing fluorescence, absorbance, and Raman-activated sorting strategies for library screening. Forster resonance energy transfer (FRET) - a nanoscale technique for monitoring intramolecular/intermolecular conformational changes - is yet to be integrated into this process. We upgraded a single-channel sorter to a dual-channel one without redesigning the microscopy setup, which can monitor FRET signals during enzyme reactions in droplets at kilohertz rates. We applied this upgraded sorter to improve the incorporation efficiency of KOD DNA polymerase towards reversible terminator deoxyribonucleotides, a property crucial for its application in next-generation sequencing (NGS). Our data show that a single-round sorting can achieve 30-fold enrichment of active variants. Five KOD variants enabling 100-cycle single-end runs of DNA sequencing were identified using a novel cyclic reversible termination (CRT) substrate featuring a terminator group {approx} 5-fold bulkier than the classical azidomethyl moiety. We also engineered a metagenome-derived novel polymerase, and a variant achieving 90% terminator incorporation efficiency within 2 minutes was identified after two rounds of enrichment. In sum, we provide a practical setup for dual-channel FRET-based droplet sorting, and demonstrate its ability in terminator polymerases engineering, thereby broaden the scope of microfluidic applications.

biochemistry↗

bioRxiv2025

A Combinatorial mRNA Therapy for Treating Rheumatoid Arthritis and Osteoarthritis by Inhibiting Inflammation and Promoting Cartilage Regeneration

Rheumatoid arthritis (RA) and osteoarthritis (OA) are debilitating joint disorders with distinct etiologies but share common pathological features of chronic inflammation and progressive cartilage damage. Current therapeutic options are largely palliative and yet fail to achieve desired effect. In this study, we developed a combinatorial mRNA therapy using a rationally engineered lipid nanoparticle (LNP) containing a novel ionizable lipid for enhanced cartilage penetration upon intra-articular administration. This LNP co-delivers mRNAs encoding two complementary therapeutic proteins: interleukin-1 receptor antagonist (IL-1Ra) for inflammation attenuation and a C-terminal truncated derivative of angiopoietin-like 3 (ANL3) for cartilage regeneration. In pre-clinical models including collagen-induced arthritis mice, TNF-transgenic mice with spontaneous RA and destabilization of medial meniscus (DMM) surgical OA model, this "one-shot" combinatorial therapy significantly ameliorated disease severity, reduced synovitis and bone erosion, and potently promoted the regeneration of hyaline-like cartilage. Mechanistically, transcriptomic profiling of joint specimens revealed that the combinatorial therapy concurrently suppressed inflammatory pathways and extracellular matrix degradation pathways, meanwhile upregulating anabolic genes facilitating chondrogenesis. Collectively, our study establishes a versatile and synergistic mRNA therapy that offers a potent disease-modifying immunomodulatory strategy capable of addressing the long-standing unmet needs in arthritis treatment.

immunology↗

bioRxiv2025

DAWN-SCAPE: Discovering Associations With Networks through Shared Contextual Analysis of Phenotype and Expression

The molecular basis of phenotypes is often explored by contrasting gene expression from relevant tissue taken from individuals classified into phenotypic extremes, such as affected versus unaffected individuals. Analysis of this differential expression (DE) typically identifies many genes of interest. However, it is not clear which genes differ between extremes because they alter phenotypic liability and which show differences as a result of the extreme phenotype itself. We propose a formal model to distinguish between genes that are upstream and "cause" differential expression versus those for which differential expression is a result of the initial manifestation of phenotype. Relying on two sets of p-values, one from differential expression analysis and one from gene-specific association with phenotype (AP), and a gene coexpression or other gene-based network that serves as a bridge, our method identifies communities of genes more likely upstream or downstream of the phenotype. Our method consists of three major steps: 1) gene network construction, 2) evaluation of DE and AP signal within the network to infer hidden states, and 3) detection of gene communities. We apply our method to data that were generated to assess the biological basis of autism spectrum disorder (ASD) and Alzheimers disease (AD). Our results highlight neuronal and synaptic biology as being upstream of ASD, whereas downstream processes are all non-neuronal. For AD, our results are consistent with existing hypotheses; yet, they also lend support for a recent unifying hypothesis involving cofilin/actin biology.

genomics↗

bioRxiv2025

A Novel Cell-Type Specific Circadian Reporter Mouse Reveals Self-Sustained Food Entrainable Nature in Enteric Neurons

Global luciferase reporter gene technology is an important real-time readout for the analysis of circadian oscillations. However, because nearly all cells in the body possess cell-autonomous circadian oscillators, developing cell-type-specific reporter systems is essential to dissect how these oscillators interact within complex multicellular tissues and are modulated by brain-body circadian signals. The intestine is a complex organ composed of diverse cell types with distinct origins and functions, and it exhibits robust daily rhythms in physiological activities driven by intrinsic circadian clocks. While the circadian regulation of the mucosal compartment, including the intestinal epithelium, has been relatively well characterized, the mechanisms governing the circadian rhythms in the cells of the muscularis externa remain largely unexplored. Here, we report a novel Cre-dependent Per2-luciferase reporter mouse that enables precise measurement of circadian oscillations in specific peripheral cell populations ex vivo and demonstrate its utility in revealing the hierarchical circadian chrono-architecture within the intestine. Ex vivo gut explants from mice expressing the reporter in one of five major cell types of the muscularis externa--enteric neurons (ENs), enteric glial cells (EGCs), interstitial cells of Cajal (ICCs), smooth muscle cells (SMCs), and muscularis macrophages (MMs)--exhibited robust, self-sustained circadian bioluminescence rhythms, indicating that all of these cell types possess cell-autonomous circadian oscillators. Notably, ENs in the small intestine entrained more rapidly to feeding schedules than did those in the colon, revealing regional differences in food entrainment among the gut clocks. Moreover, the clocks of ENs, SMCs, and MMs shifted their phase in response to daytime-restricted feeding, whereas ICC clocks remained unaffected even after three weeks of restricted feeding. These findings demonstrate that distinct intestinal cell types possess unique entrainment properties and that feeding rhythms can induce heterogeneous phase shifts within the gut clocks. Given that circadian disruption, such as that caused by shift work, contributes to intestinal disorders, this reporter system could provide a powerful platform to dissect the mechanisms linking intercellular circadian desynchrony to intestinal homeostasis. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/688705v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@11250fforg.highwire.dtl.DTLVardef@18397f2org.highwire.dtl.DTLVardef@6ccd24org.highwire.dtl.DTLVardef@10fffef_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA cell-type-specific circadian reporter mouse enables dissection of the chronoarchitecture of complex multicellular organs (e.g., the intestine) C_LIO_LIAll five major intestinal cell types contain autonomous circadian oscillators peaking at night C_LIO_LIEnteric neurons in small intestine entrain to feeding cycles faster than that in colon C_LIO_LIInterstitial cells of Cajal in both the small intestine and colon do not entrain to feeding cycles C_LIO_LIChemogenetic activation of enteric neurons mimics food entrainment, shifting their circadian phase. C_LI

neuroscience↗

bioRxiv2025

Large Language Models for Accessible Reporting of Bioinformatics Analyses in Interdisciplinary Contexts

Health and life scientists frequently rely on quantitative experts to perform complex data analyses, yet interpretation of these results often becomes a bottleneck due to communication barriers across disciplines. Large Language Models (LLMs) have the potential to act as intermediaries that translate analytical outputs into accessible scientific narratives, but their ability to reliably interpret outputs from real-world biomedical data analyses across disciplines remains unclear. In this study, we investigate how state-of-the-art LLMs behave when integrated into real bioinformatics analysis workflows as report-generation assistants for interdisciplinary teams. We evaluated LLM-generated summaries using both automated and human evaluation frameworks to ensure holistic evaluation. Automated assessment employed multiple choice questions designed using Bloom's taxonomy to assess multiple levels of understanding, while human evaluation tasked scientists to score summaries for factual consistency, lack of harmfulness, comprehensiveness, and coherence. All generally produced readable and largely safe summaries, confirming their value for first-pass translation of technical analyses, however frequently misinterpreted visualisations, produced verbose summaries and rarely offered novel insights beyond what was already contained in the analytics. Our findings suggest that LLMs are best suited for easing interdisciplinary communication rather than replacing domain expertise and human oversight remains essential to guarantee accuracy, interpretative depth, and the generation of genuinely novel scientific insights.

bioinformatics↗

bioRxiv2025

Ampyrone (4-Aminoantipyrine) is a Direct Agonist of Human Tyrosinase and Potential Therapeutic for Oculocutaneous Albinism and Disorders of Hypopigmentation.

Significant loss of pigmentation can increase visual disability, skin cancer risk, and psychosocial stress. Tyrosinase (TYR) catalyzes the first and rate-limiting step of melanin synthesis. Inhibitors of TYR are well established and are currently used in clinical settings; however, there is a dearth of direct activators of TYR. Here, using a unique human TYR construct, high-throughput screening, and computational analysis techniques, we identified ampyrone as a TYR activator. Ampyrone increased the in vitro catalytic activity of the intramelanosomal domain of human TYR (hTYR) and its hypomorphic variant, P406L, a cause of oculocutaneous albinism type 1B (OCA1B). Moreover, ampyrone induced melanin synthesis in both wild-type and OCA1B human melanocytes, as well as 3-dimension (3D) human skin cultures. Our results reveal ampyrone as a lead compound for first-in-class TYR activators, potentially accelerating the discovery of novel therapies for patients with genetic and acquired diseases of hypopigmentation.

pharmacology and toxicology↗

bioRxiv2025

SUGP1 associates Y-box protein to regulate piRNA biogenesis in Bombyx mori

PIWI-interacting RNAs (piRNAs) are critical for transposon silencing and genome integrity, as well as gene expression regulation and antiviral immunity in metazoans, yet the molecular mechanisms governing their biogenesis remain incompletely understood. The participation of the splicing-associated process in piRNA biogenesis has been emphasized in multiple species, but the key factors and mechanisms remain elusive. Here, we identified SUGP1 (SURP and G-Patch Domain Containing 1) in BmE (a unique model cell system with a complete piRNA biogenesis pathway) as a key splicing factor that functions in piRNA biogenesis. Through CRISPR-Cas9-mediated gene knockdown in cultured cells combined with RNA-seq, small RNA-seq, and IP-mass spectrometry (IP-MS), our results reveal that SUGP1 deficiency disrupts piRNA accumulation, alters mature piRNA length distributions, and activates transposon expression. Immunofluorescence and Western blot (WB) analyses further demonstrate that SUGP1 interacts with Y-box protein (YBP), which is key regulators of RNA metabolism. Functional validation in Drosophila SUGP1-RNAi lines highlights evolutionary conserved and species-specific roles of SUGP1 in piRNA maturation. Collectively, our data uncover a dual role for silkworm SUGP1 in coordinating YBP-dependent piRNA biogenesis, thus elucidating a novel mechanistic framework for piRNA pathway regulation. Our work also underscores the silkworm as a unique model for studying non-canonical piRNA biogenesis mechanisms, with implications for treating transposon dysregulation-linked diseases. Author summaryDisruption of piRNA synthesis leads to abnormal consequences such as transposon de-repression, posing a significant threat to genomic stability. It is therefore essential to in-depth analysis of the piRNA biosynthetic mechanism. Previous studies have highlighted the involvement of splicing-related processes in piRNA biosynthesis, yet key factors and mechanisms remain poorly understood. This study employed the silkworm cell system, which possesses a complete piRNA biosynthetic pathway. Utilizing CRISPR-Cas9-mediated gene knockout technology combined with RNA sequencing, small RNA sequencing, and immunoprecipitation-mass spectrometry (IP-MS), we discovered that SUGP1 deficiency disrupts piRNA accumulation, alters the length distribution of mature piRNAs, and activates transposon expression. Furthermore, immunofluorescence and Western blot analyses confirmed an interaction between SUGP1 and Y-box proteins (YBPs), key regulators of RNA metabolism. Functional validation using Drosophila SUGP1-RNAi lines revealed that SUGP1 plays dual roles in piRNA maturation. Our study reveals that the silkworm scissor-related factor SUGP1 has dual functions in coordinating YBP-dependent piRNA biosynthesis.

molecular biology↗

bioRxiv2025

Epithelial cell fusion is required for tissue repair following UV-A irradiation

Cell cycle-dependent and independent mechanisms lead to the generation of mononucleated and multinucleated, polyploid cells. The more than doubling of a cells nuclear genome by endoreplication has been found to be an adaptation to genotoxic stress, enabling cell survival despite DNA damage. However, it remains unknown whether cells that increase ploidy via multinucleation also arise in response to genotoxic stress. Here, we use ultraviolet light A (UV-A) to induce permanent DNA damage in cells within the adult fruit fly epithelium. UV-A irradiation causes an injury-like response where giant multinucleated, polyploid cells arise following cell death. The epithelial cells undergo endoreplication, which is required to restore tissue mass, but is surprisingly dispensable for tissue repair. UV-A irradiation also induces cell fusion, which generates multinucleated cells that encompass almost the entire epithelial area post injury. Cell fusion can be inhibited by expression of a dominant negative Rac or Cdc42 GTPase, which then blocks epithelial tissue repair post irradiation. Apoptotic nuclei were detected at the site of cell junction breakdown suggesting that apoptosis itself or an apoptotic signal is required for polyploidization in this model. Expression of the effector caspase inhibitor, p35, led to inhibition of apoptosis, the endocycle, and cell fusion post UV-A. Therefore, we have discovered that caspase activation is necessary for polyploidization post injury and enhancing cell ploidy via multinucleation is another strategy to enable cell survival and tissue repair following genotoxic stress. Significance StatementPolyploid cells are lifes stress responders as the more than doubling of a cells genome has been shown to enable resistance to genotoxic stress. Cells are exposed to various sources of genotoxic stress, including from ultraviolet light. Here we find that ultraviolet light induces DNA damage causing apoptosis and the subsequent generation of giant, multinucleated polyploid cells in the fruit fly epithelium. Unlike in other models studied to date, cell fusion is the predominant response to genotoxic stress and appears to be essential for tissue repair. This study also determines that polyploidization post UV stress is dependent on caspase activation, suggesting a conserved mechanism to initiate cellular multinucleation both in development as well as in response to lifes stressors.

cell biology↗

bioRxiv2025

Land use influences on freshwater biodiversity

Land-use change is a major driver of biodiversity loss, but most generalizations about its effects come from terrestrial ecosystems. In freshwater systems, impacts are often indirect, driven by changes in the surrounding landscape that alter flow, chemistry, and connectivity. Using species-level abundance data from 163 studies across 6 biological groups, we examined how urban, agricultural, and forestry land uses affect freshwater biodiversity at local and regional scales. All three land-use types reduced species richness and altered relative abundance structure compared to natural vegetation, with urban systems showing the strongest and most consistent declines. Only urbanization was associated with biotic homogenization, particularly among abundant species. Biodiversity responses to land-use change also varied with latitude and taxonomic group: tropical assemblages tended to differentiate across sites, while homogenization was more common at higher latitudes. Macroinvertebrates and fish showed the strongest overall declines. These findings challenge assumptions of generality across ecosystems and highlight the need to explicitly incorporate freshwater biodiversity into global change research and policy.

ecology↗

bioRxiv2025

Illuminating the Druggable Proteome with an AI Protein Profiling Platform

Most human proteins lack chemical probes or pharmaceutical modulators, leaving much of the proteome unexplored. 1,2 Activity-based protein profiling has enabled proteome-scale discovery of protein-ligand interactions and covalent inhibitors, 3-5 but remains limited by probe chemistry, protein abundance, and discordant ligandability assignments across studies. 6-9 Machine-learning (ML) models can in principle generate proteomewide ligandability maps, but the predictive utility of current models is limited by the requirement for structures and the use of incomplete and weak training labels. 9-12 Here we developed an artificial intelligence protein profiling (AiPP), a sequence-based multitask platform built on the ESMC protein language model, 13,14 to accelerate proteomewide therapeutic discovery and target identification. While its primary task is identification of covalently ligandable cysteines, seven additional task heads and two external modules provide broader context by annotating reversible ligand-binding residues, disordered molecular recognition features, cysteine functional context, and reactivities. Central to the development is the LatentLift clustering approach, which leverages latent space similarities to reconcile conflicting experimental labels and facilitate model training. Applied to the human proteome, AiPP generated a cysteine-directed ligandability atlas that overcomes the limitations of current chemo-proteomic maps. As a proof of concept, we demonstrate that AiPP can guide the discovery of covalent allosteric inhibitors targeting the previously undruggable protein tyrosine phosphatase PTPN6. By linking sequence, ligandability and biological context, AiPP provides an open resource for therapeutic discovery, while LatentLift offers a general strategy for harmonizing proteomics data for ML applications.

biophysics↗

bioRxiv2025

CHD1 is a synthetic lethal vulnerability in MYC-driven breast cancer

The MYC transcription factor is a key regulator of growth during development and a potent cancer driver when its expression is dysregulated. Strategies to inhibit MYC oncogenic activity would mark a significant advance, but decades of efforts to target MYC directly have not been fruitful. Understanding how MYC drives transformation and tumor growth may provide new therapeutic avenues in a variety of cancers. By intersecting two independent genome-wide screens, we identified loss of the chromatin remodeler Chromodomain-Helicase DNA-binding 1 (CHD1) as a potential synthetic lethal target in MYC-driven breast cancer. Knockdown of CHD1 in a xenograft model of MYC-driven breast cancer suppresses tumor growth in vivo. In tissue culture models, we found that knockdown of CHD1 suppresses cell proliferation and induces cell death, specifically when MYC is overexpressed. Mechanistically, we found that CHD1 is required to maintain an open chromatin landscape and a transcriptional program associated with cancer progression in MYC overexpressing breast cells. Follow-up experiments indicate that this synthetic lethality may arise from nucleolar stress and p53 activation. These findings provide new insights on the chromatin-level regulation of MYC-driven breast cancer and uncover CHD1 as a novel synthetic vulnerability and potential therapeutic target.

cancer biology↗

bioRxiv2025

Identification of antibody-drug conjugate payloads which are substrates of ATP-binding cassette drug efflux transporters

AimAntibody-drug conjugates (ADCs) feature an antibody recognizing a specific protein joined to a potent toxic payload. Numerous antibody-drug conjugates have received FDA approval; however, clinical resistance arises. Resistance mechanisms include decreased expression or mutation of the antibody target, impaired payload release, or increased expression of ATP-binding cassette (ABC) efflux transporters associated with multidrug resistance. We therefore sought to characterize the interactions of ABC multidrug transporters with ADC payloads. MethodsWe performed a high-throughput screen with 27 common ADC payloads using cells lines expressing ABC transporters P-glycoprotein (P-gp, encoded by ABCB1) or ABCG2 (encoded by ABCG2). Confirmatory assays were also performed using cells transfected to express P-gp, ABCG2, or MRP1 (encoded by ABCC1). ResultsSeveral commonly used ADC payloads were substrates of P-gp, including calicheamicin gamma1, monomethyl auristatin E, DM1, and DM4. All the pyrrolobenzodiazepines tested--SJG136, SGD-1882, SG2057, and SG3199--were substrates of P-gp, ABCG2, and MRP1. The modified anthracyclines nemorubicin and its metabolite PNU-159682 were poorly transported by both ABCB1 and ABCG2 and displayed nanomolar to picomolar toxicity. Further, we found that the efficacy of the FDA-approved ADC mirvetuximab soravtansine, with DM4 as the toxic payload, was decreased in cell lines expressing P-gp. Duocarmycin DM and PNU-159682 were exquisitely toxic to a panel of 99 cancer cell lines of varying origins. ConclusionSeveral commonly used ADC payloads can be transported by ABC transporters, potentially leading to transporter-mediated drug resistance in patients. Future ADCs should be developed using payloads that are not ABC transporter substrates.

pharmacology and toxicology↗

bioRxiv2025

Protein Electrostatic Properties are Fine-Tuned Through Evolution

Ionization states play crucial roles in protein function, yet predicting protein pKa values remains a formidable challenge despite decades of research. Here we present KaML-ESM2 and KaML-ESMC, neural network task heads built on ESM protein language models (pLMs) and trained on the PKAD-3r experimental dataset augmented via GAINES, a latent-space sampling strategy for addressing data scarcity. KaML-ESM2/ESMC significantly outperform current structure- and sequence-based approaches across four benchmarks, achieving root-mean-square errors of about 0.5 units across six titratable residue types in native proteins. Performance degradation on 89 buried engineered OBTRUDEs (iOnizable suBsTitutions foR bUrieD rEsidues) that lack evolutionary support (KaML-ESMC RMSE = 1.89) reveals a key limitation of the current framework, which may be overcome through supervised training. Based on these and other data presented in the work, we hypothesize that protein sequence, through its evolutionary context, encodes not only structure and function but indirectly also electrostatic characteristics. We applied KaML-ESM2 to the human proteome, demonstrating that predicted pKa values can potentially identify functional sites and infer catalytic mechanisms. We offer KaML, a sequence-based, end-to-end platform to support applications spanning biological exploration, drug design, protein engineering, and biomolecular simulation. Although additional research is needed, GAINES could offer a general framework for addressing data scarcity in machine learning approaches for protein-related problems.

biophysics↗

bioRxiv2025

Causal differential expression analysis under unmeasured confounders with causarray

Advances in single-cell sequencing and CRISPR technologies have enabled detailed case-control comparisons and experimental perturbations at single-cell resolution. However, uncovering causal relationships in observational genomic data remains challenging due to selection bias and inadequate adjustment for unmeasured confounders, particularly in heterogeneous datasets. To address these challenges, we introduce causarray, a robust causal inference framework for analyzing array-based genomic data at both pseudo-bulk and single-cell levels under unmeasured confounding. causarray integrates a generalized confounder adjustment method to account for unmeasured confounders and employs semiparametric inference with flexible machine learning techniques to ensure robust statistical estimation of treatment effects. Benchmarking results show that causarray robustly separates treatment effects from confounders while preserving biological signals across diverse settings. We also apply causarray to two single-cell genomic studies: (1) an in vivo Perturb-seq study of autism risk genes in developing mouse brains and (2) a case-control study of Alzheimers disease using three human brain transcriptomic datasets. In these applications, causarray identifies clustered causal effects of multiple autism risk genes and consistent causally affected genes across Alzheimers disease datasets, uncovering biologically relevant pathways directly linked to neuronal development and synaptic functions that are critical for understanding disease pathology.

genomics↗

bioRxiv2024

Identification of potent HSV antivirals using 3D bioprinted human skin equivalents

Herpes simplex virus (HSV) infection has worldwide public health concerns and lifelong medical impacts. The standard therapy, acyclovir, has limited efficacy in preventing HSV subclinical virus shedding, and drug resistance occurs in immunocompromised patients, highlighting the need for novel therapeutics. HSV manifests in the skin and mucosal epithelium. Here, we found acyclovir significantly less effective in skin-derived keratinocytes than donor-matched fibroblasts. To recapitulate in vivo tissue architecture, we 3D bioprinted human skin equivalents (HSE) in a 96-well plate format amenable for antiviral screening and preclinical testing. We screened a library of 738 compounds with broad targets and mechanisms of action and identified potent antivirals, including 23 known or experimental HSV treatments, validating the translational relevance of our assay. Unlike acyclovir, antivirals against HSV helicase/primase or host replication pathways displayed similar potency across cell types and donor sources in 2D and 3D models. Our 3D bioprinted platform allowed for integrating patient-derived cells and incorporating genetic variability early in drug development. The reduced potency in keratinocytes helps explain the limited benefit acyclovir and its congeners play in reducing sexual transmission. These data indicate that the 3D bioprinted HSE assay platform provides a more physiologically relevant approach to identifying potential antivirals for HSV. One Sentence SummaryHigh-throughput screen using 3D bioprinted human skin equivalents to identify antivirals against HSV and evaluate cell-type specific effects.

bioengineering↗

bioRxiv2024

Discovery of Novel and Selective GPR17 Antagonists as Pharmacological Tools for Developing New Therapeutic Strategies in Diabetes and Obesity

G protein coupled receptors (GPCRs) are promising targets for diabetes and obesity therapy due to their roles in metabolism and excellent potential for pharmacological manipulation. We previously reported that Gpr17 ablation in the brain-gut axis leads to improved metabolic homeostasis, suggesting GPR17 antagonism could be developed for diabetes and obesity treatment. Here, we performed high throughput screening (HTS) and identified two new GPR17 antagonists (compound 978 and 527). Both compounds antagonized downstream Gi/o, Gq and {beta}-arrestin signaling with high selectivity for GPR17, but not the closely related purinergic and cysteinyl leukotriene receptors. The molecular mechanisms of antagonism were revealed through Schild analysis, structure-activity relationship (SAR) studies and homology modelling. Compound 978 and its analog (793) attenuated GPR17 signaling and promoted glucagon-like peptide-1 (GLP-1) secretion in enteroendocrine cells. In summary, we identified selective GPR17 antagonists through HTS, which represent promising pharmacological tools for developing new therapeutic strategies in diabetes and obesity. SignificanceOur work highlights the therapeutic potential of GPR17 antagonism in the treatment of diabetes and obesity by leveraging its role in metabolic regulation. In previous studies, we have shown that Gpr17 ablation improves metabolic homeostasis, and here we expanded our research by identifying two novel small molecule antagonists of GPR17 through high-throughput screening. The compounds inhibited multiple downstream signaling pathways of GPR17 with high selectivity over other closely related receptors. Of particular significance, compound 978 and its analogs not only attenuated GPR17 signaling but also increased glucagon-like peptide-1 (GLP-1) secretion, a critical hormone for glucose homeostasis and appetite regulation. These findings shed new light into the molecular mechanisms of GPR17 antagonism and introduce valuable pharmacological tools for further exploration of therapeutic strategies in diabetes and obesity.

pharmacology and toxicology↗

bioRxiv2024

KaMLs for Predicting Protein pKa Values andIonization States: Are Trees All You Need?

Despite its importance in understanding biology and computer-aided drug discovery, the accurate prediction of protein ionization states remains a formidable challenge. Physics-based approaches struggle to capture the small, competing contributions in the complex protein environment, while machine learning (ML) is hampered by scarcity of experimental data. Here we report the development of pKa ML (KaML) models based on decision trees and graph attention networks (GAT), exploiting physicochemical understanding and a new experiment pKa database (PKAD-3) enriched with highly shifted pKas. KaML-CBtree significantly outperforms the current state of the art in predicting pKa values and ionization states across all six titratable amino acids, notably achieving accurate predictions for deprotonated cysteines and lysines - a blind spot in previous models. The superior performance of KaMLs is achieved in part through several innovations, including separate treatment of acid and base, data augmentation using AlphaFold structures, and model pretraining on a theoretical pKa database. We also introduce the classification of protonation states as a metric for evaluating pKa prediction models. A meta-feature analysis suggests a possible reason for the lightweight tree model to outperform the more complex deep learning GAT. We release an end-to-end pKa predictor based on KaML-CBtree and the new PKAD-3 database, which facilitates a variety of applications and provides the foundation for further advances in protein electrostatics research. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/622800v3_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@15d2256org.highwire.dtl.DTLVardef@1795151org.highwire.dtl.DTLVardef@1c9ae02org.highwire.dtl.DTLVardef@1bf17a9_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

Revolutionizing large-scale DNA synthesis with microchip-based massive in parallel synthesis system

DNA synthesis serves as the fundamental enabling technology of engineering biology, aiming to provide DNA molecules of designed composition, length, and complexity at scale and low cost. Current high-throughput DNA synthesis technologies rely on intricate chip manufacturing and microfluidic systems to provide large-scale synthetic oligonucleotides, at the expense of low concentration and limited compatibility in the processing of longer DNA constructs assembly. Here, we report a microchip-based massive in parallel synthesis (mMPS), pioneering an "identification-sorting-synthesis-recycling" iteration mechanism to microchips for high throughput DNA synthesis. In comparison to microarray-based methods, we demonstrate that our method can increase the DNA product concentration by 4 magnitudes (to picomole-scale per sequence) and greatly simplifies the downstream processes for large-scale gene synthesis construction. By the construction of 1.97 million-diversity variant libraries that cover 1,254 human protein domains, we demonstrated the uniformity of the constructed variant libraries using mMPS-derived oligos is greatly improved, with amino acid distribution highly consistent as designed. In addition, by synthesizing 285 1kb-to-3kb genes with varying degrees of sequence complexity from previously reported strains A501 and 3DAC, potential ancestor of early archaea and bacteria, our result shows that the overall gene assembly success rate using mMPS-derived oligos is increased by 10-fold in comparison to other methods. Our mMPS technology holds the potential to close the gap between the quality and cost of writing DNA in increasing demand across many sectors of research and industrial activities.

synthetic biology↗