Biology subjects

Joshi, K.

Publications and source records attributed to Joshi, K..

At least 19 recordsLinked to original sources

bioRxiv2026

Activation of Disease-Associated Polycystin-1 Mutants by Binding of Stalk-derived Agonist Peptides

Polycystin-1 (PC1) functions as an atypical G-protein-coupled receptor (GPCR) with an autocatalytic GAIN domain that cleaves PC1 into extracellular N-terminal (NTF) and membrane-embedded C-terminal (CTF) fragments. Mutations in PC1 are responsible for 85% of autosomal dominant polycystic kidney disease (ADPKD) cases. Activation of signaling by PC1 CTF has been shown to be allosterically mediated by a stalk tethered agonist (TA) and to be prevented by mutations of the stalk. Soluble, synthetic peptides derived from the PC1 stalk were also shown to re-activate signaling by a stalkless CTF mutant. Here, we have investigated the ability of selected stalk peptide agonists p9, p15 or p17 to re-activate signaling by PC1 CTF with ADPKD-associated missense mutations, G3052R or R3063C. Biochemical experimental data showed that each of the three stalk peptides was able to significantly reactivate signaling by the CTF-R3063C mutant. In contrast, signaling by CTF-G3052R could only be rescued by treatment with p17. In parallel, we employed peptide docking and novel Peptide Gaussian-accelerated Molecular Dynamics (Pep-GaMD) simulations to elucidate the binding conformations of p9, p15 and p17 to the PC1 mutants. The simulation findings were highly consistent with experimental data. Furthermore, Pep-GaMD revealed binding conformations of the agonist peptides and important low-energy conformational states of the PC1 CTF, as well as their critical residue interactions. Overall, our complementary approach provides important mechanistic insights into the re-activation of PC1 disease-associated mutants by stalk-derived peptide agonists. Such insights are expected to be valuable for the future design and development of peptide modulators targeting PC1 for an effective ADPKD therapeutic treatment.

bioinformatics↗

bioRxiv2026

The Neural Impact Score benchmarks drugs in Multi-Region Brain Organoids

Only about 10 percent of drugs that clear animal testing succeed in humans, and central nervous system programs carry an even steeper translational gap. Human-relevant NAMs are gaining global regulatory and funding support, creating an urgent need for interpretable preclinical systems that can generate comparable, decision-ready evidence across assays, models, and species. Yet the multimodal treatment-response data produced by these systems are still evaluated assay by assay, with no unified metric showing whether a compound moves neural tissue toward a desirable or undesirable state. Here we present the Neural Impact Score (NIS), a framework that translates multimodal CNS drug-response data into a bidirectional score across four predefined biological categories: neurodevelopment, neuroinflammation, neurodegeneration, and longevity. A positive score indicates a desirable shift, whereas a negative score indicates the opposite, placing compounds on a single scale across assays, model systems, and species. To demonstrate NIS, we analyzed a vascularized human day-200 multi-region brain organoid (MRBO) composed of cortical, endothelial, and brainstem lineages and mimicking a mid-gestational cortical window (GW18-GW22). We tested five compounds with distinct mechanisms of action: a glucagon-like peptide-1 receptor agonist (GLP-1RA), a norepinephrine-dopamine reuptake inhibitor (NDRI), a selective serotonin reuptake inhibitor (SSRI), a sphingosine-1-phosphate receptor modulator, and an Akt activator. We profiled responses using single-nucleus RNA sequencing, bulk RNA sequencing, proteomics, and multi-electrode array electrophysiology. NIS integrated these readouts into category-specific and composite scores, separating beneficial from adverse effects for each compound and sorting compounds into interpretation tiers. Applying the same framework to independent human and rodent datasets without retraining, we recovered conserved human antidepressant responses despite near-chance gene-level agreement between human MRBO and rat brain, and identified an endothelial-dependent, human-specific GLP-1 response absent from the murine dorsal vagal complex. NIS therefore provides a human-relevant framework for drug evaluation and cross-species benchmarking, with a design extensible to other neural systems.

bioengineering↗

bioRxiv2026

Coevolution of Codependent Hosts and Symbionts

Many endosymbioses in eukaryotes superficially appear to be beneficial to both participants. However, there is little direct evidence for this, and symbioses naturally set up conditions in which each member of the pair is under selection to extract resources from the other. Ultimately, the endosymbiont either evolves to be in conflict with the interests of the host or to act cooperatively with the host contrary to its own best interests. Focusing on obligate symbioses, we develop theory to clarify the population-genetic conditions favoring the alternative outcomes. The balance is usually tipped in favor of exploitation by the symbiont, particularly when the number of symbionts within host cells is high, selection is strong on symbionts relative to hosts, there is horizontal transfer of symbionts, and/or the symbionts have accelerated mutation rates or turnover times. If the symbiont conditions the host-cell biology to enhance within-host population sizes, selection for selfish symbionts will be further enhanced by the diminished level of within-host drift. Although the host evolves in parallel to exploit resources from the endosymbiont, the net result is often a stalemate in which the host is no better off than prior to host-symbiont coevolution. Strict vertical inheritance can result in an evolutionary alignment of interests of the endosymbiont and the host, as this minimizes the possibility of within-host selection, but even here there is a critical host population size below which the symbiont evolves to exploit the host. These results suggest that the evolutionary enslavement of a symbiont to benefit a host species requires a narrow mix of population-biological features of both participants.

evolutionary biology↗

bioRxiv2026

Fixation Probabilities of Mutant Alleles in an Ecological Context

For decades, population geneticists have relied upon a formula derived by Malecot and by Kimura to estimate the fixation probability of mutant alleles ({phi}). Among other things, this formula leads to the conclusion that in sufficiently large populations{phi} asymptotically approaches 2s(Ne/N ) (for small s), where s is the relative selective advantage of the mutant allele, and Ne and N respectively denote the effective and absolute (haploid) population sizes. In contrast, in sufficiently small populations,{phi} = 1/N, with the two domains of behavior being separated at the point where s [bsime] 1/(2Ne). These results hold when s, N, and Ne remain constant during the fixation process, but require modification when populations are changing in size. Here, we show that if there are ecological effects associated with competing alleles, such that the genetic composition of the population influences the total population size, the fixation probability of a beneficial allele can substantially deviate from the levels suggested above, even in the domain of effective neutrality (i.e., | s | [lsim]1/(2Ne)). We obtain analytical results for a variety of frequency-dependent functions for the overall population size, and show that the overall effect is largely a function of the response at low mutant-allele frequency. We also derive expressions for times to fixation and for fixation probabilities of deleterious alleles, and show how our results relate to prior work for the situation in which population sizes change in frequency-independent manners.

evolutionary biology↗

bioRxiv2026

Structural basis of MK-97 positive allosteric modulation at the M4 mAChR

Positive allosteric modulators (PAMs) of the M4 muscarinic acetylcholine receptor (mAChR) represent a promising therapeutic strategy for treating cognitive deficits and neuropsychiatric disorders. While first-generation M4 mAChR PAMs, like LY2033298, demonstrated proof-of-concept, second-generation compounds, such as MK-97, exhibit substantially improved potency and reduced species variability. Here we report the cryo-EM structure of the M4 mAChR bound to the endogenous agonist, acetylcholine, and MK-97 at 2.7 [A] resolution, revealing the molecular basis for improved M4 mAChR PAM activity. MK-97 adopts a distinctive boomerang-shaped conformation within the extracellular-facing allosteric binding site, with a central pyridine vertex, a lower cyclopentylmethylpyrazole arm extending toward the floor of the orthosteric site, and an upper isoindolinone arm projecting toward extracellular loop 2 (ECL2). This extended binding mode establishes a distributed interaction network across transmembrane helices TM2, TM3, TM5, TM6, and TM7, with key contacts including a hydrogen bond with Y922.64 and a {pi}-{pi} stacking interaction with W4357.35. Integration of structural data, molecular dynamics simulations, and mutagenesis validation reveals that the high affinity of MK-97 derives from optimized engagement across all three binding regions rather than dependence on any single critical contact. Insights from comprehensive structure-activity relationship (SAR) studies provide a molecular framework for the rational design of next-generation M4 mAChR PAMs with improved pharmacological properties. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=70 SRC="FIGDIR/small/723386v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@75cb90org.highwire.dtl.DTLVardef@1876c9corg.highwire.dtl.DTLVardef@1eba8d0org.highwire.dtl.DTLVardef@9818ad_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2026

TRACKING THE COMPOSITION AND STABILITY OF MICROBIOME ACROSS INDIAN SOCIAL HONEYBEES FORAGING IN A HOMOGENOUS RESOURCE LANDSCAPE

Microbial communities are essential for host health and ecosystem stability. However, whether host identity or shared foraging resources shapes microbiome structure among co-occurring species remains poorly understood. We studied bacterial and fungal communities of four Indian honeybee species in a mustard monoculture resource condition, integrating behavioural observation-based pollinator data with microbial co-occurrence networks derived from metabarcoding. Microbiome composition was linked to host identity rather than foraging behaviour, bee abundance, or landscape use. While core bacterial taxa were shared, relationships among bacterial cobionts, unlike those among fungal genera, remained species-specific. Microbial diversity, along with community structure and function, influenced network stability, with a highly modular microbial network of Apis cerana exhibiting more resilience to simulated perturbations. In summary, host-specific filtering shaped the microbiome more than resource homogenisation, with closely related species facing unique risks of microbial collapse, with broader implications for vulnerability to microbiome imbalance, environmental stress, and emerging infections.

ecology↗

bioRxiv2026

Contemporaneity of the past in stochastic intergenerational homeostasis

What recurring patterns of behaviors are hidden in the stochastic intergenerational dynamics of individual bacterial cells in different environments? Embracing the inherently stochastic nature of the homeostasis process, first we reconceptualize homeostasis as representing a "standing pattern of variation in trajectory space" of a naturally occurring adaptive complex system (rather than the simple "set-point" of a self-regulating apparatus), then delineate two mechanistically distinct potential routes to achieving homeostasis (either elastic, reflexive, memory-free adaptation or plastic, reflective, memoryful adaptation) and show that both schemes are simultaneously utilized during multigenerational stochastic growth and division of an individual cell. From experimental data we identify an intergenerational scaling law which directly yields the exact stochastic map governing stochastic intergenerational cell size homeostasis of individual bacterial cells. Its broad applicability across bacterial species, growth conditions, and microenvironments suggests that the organizational motif representing the nature of coupling of growth to division is effectively the same in all of these scenarios, despite apparent differences in actualization through molecular circuitry. The precise parameters characterizing the intergenerational scaling law vary from condition to condition and provide early hints of two tradeoffs: precision-speed and precision-energy.

biophysics↗

bioRxiv2026

Impaired acid stress resistance in Salmonella Typhi Ty2

Salmonella enterica encounters acid stress during gastrointestinal transit and within the phagosomal environment of macrophages. Acid stress resistance has been well characterized in Salmonella enterica serovar Typhimurium, but comparative studies in the human-adapted Salmonella enterica serovar Typhi are limited. We compared the growth of S. Typhimurium 14028s and S. Typhi Ty2 at pH values ranging from 3-8 and observed that Salmonella enterica serovar Typhimurium exhibits enhanced growth at pH 4.5 compared to S. Typhi. Comparative transcriptomic profiling of S. Typhimurium and S. Typhi at pH 4.5 and 7.5 identified numerous differentially expressed acid-induced genes (DEGs), including genes encoding membrane proteins (OmpC, PhoE, HydB), a transcriptional regulator (RpoS), and stress response proteins (YciG, STM14_1829, YmdF). Targeted deletion of selected genes in S. Typhimurium significantly suppressed growth at acidic pH, confirming their role in acid stress resistance. These resistance mechanisms are compromised in S. Typhi due to pseudogenization. Heterologous expression of pseudogenized genes in S. Typhi restored acid tolerance. Collectively, these findings suggest that S. Typhi has lost the ability to withstand acid stress due to genomic decay and the loss of multiple genes essential for acid survival in S. Typhimurium, reflecting divergent evolutionary paths in these two serovars. ImportanceSalmonella Typhimurium must adapt to acidic pH conditions in the intestinal tract and the intracellular environment to cause infection. In this study, we show that the enteric fever serovar Salmonella Typhi exhibits impaired growth at pH 4.5, in comparison to Salmonella Typhimurium. We further show that the loss of specific membrane proteins, a transcriptional regulator, and a family of stress response proteins in Salmonella Typhi are responsible for this difference. Collectively, these observations suggest that Salmonella Typhi has evolutionarily lost the ability to withstand acid stress due to differences in its interaction with the human host. This has important implications for the pathogenesis of typhoid fever.

microbiology↗

bioRxiv2026

Subcellular Localization Constrains Protein Detectability and Reveals Systematic RNA-Protein Discordance Across Cancers

Transcript abundance is widely used as a proxy for protein expression in cancer studies; however, mRNA levels often fail to predict protein detectability due to post-transcriptional and compartment-specific regulatory processes. Here, we present a machine learning framework that integrates RNA expression, gene-level attributes, and subcellular localization to model protein detectability across human cancers. Leveraging transcriptomic data from TCGA, TARGET, and GTEx, and protein annotations from the Human Protein Atlas, we constructed a dataset comprising over 100,000 gene-cancer pairs across seven tumor types. Models based on RNA features alone achieved moderate predictive performance (ROC-AUC ~0.71), whereas incorporating subcellular localization significantly improved accuracy (ROC-AUC ~0.82). Paired bootstrap analysis confirmed that these gains were statistically robust. We further identify a substantial set of genes with high transcript abundance yet absent protein detection, revealing widespread RNA-protein decoupling. These discordant genes are enriched in mitochondrial, metabolic, and translational regulatory pathways, suggesting that discordance reflects structured biological processes rather than stochastic variation. Together, our results demonstrate that cellular context, particularly subcellular localization, is a key determinant of protein detectability and underscore the limitations of transcript-centric interpretations in cancer genomics.

bioinformatics↗

bioRxiv2026

Dual Transcriptomic and Epigenomic Signatures of THC Exposure in Human Prefrontal Cortex Development

Prenatal cannabis use is increasing globally, with estimates up to 35% in North America. Fetal exposure to {Delta}9-tetrahydrocannabinol (THC) has been linked to neurodevelopmental deficits. Yet mechanistic understanding remains limited because animal models incompletely recapitulate human fetal development, and human-relevant in vitro platforms are scarce. To address this gap, we generated human iPSC-derived prefrontal cortex organoids (PFCOs) and used an integrated multi-omics approach combining bulk RNA-seq, whole-genome bisulfite sequencing (WGBS), and electrophysiology to characterize early molecular and functional responses to acute THC exposure at a developmentally relevant stage. THC induced a rapid, transient shift toward excitatory and neurodevelopmental gene expression programs while simultaneously suppressing extracellular matrix and adhesion pathways critical for structural support. Concurrent epigenetic remodeling selectively targeted synaptic assembly, postsynaptic organization, and axonal guidance genes, creating a mismatch between early activation of neuronal programs and epigenetic repression of the scaffolding required for their proper integration. Functionally, these disruptions manifested as delayed but reversible increases in burst duration at 24 hours, indicating altered coordination of network activity. Transcriptional and epigenetic responses converged on autism spectrum disorder (ASD) associated gene networks, with strong enrichment among high-confidence and strong-candidate ASD risk genes, suggesting that THC preferentially perturbs neurodevelopmentally vulnerable pathways. Together, these findings define a mechanistic framework in which THC disrupts early human cortical development through a cycle of transient excitatory activation, compromised structural support, and persistent epigenetic alterations, which are features specifically revealed by human PFCOs.

genomics↗

bioRxiv2025

Emergent simplicities in an individual cell's stochastic response to disruptive change

Here we seek and find recurring patterns of behaviors in the stochastic response of an individual bacterial cell to a disruptive change in growth conditions. Building on the known scaling law that a single timescale, a cellular unit of time, governs stochastic growth and division of individual bacterial cells under constant growth conditions, here we show using experimental data that a dynamic rescaling of the cellular unit of time captures the predominant effect of temporal variations in environmental conditions. Furthermore, we identify the instantaneous exponential growth rate as the scaling factor that scales the internal clocks of the cells to the laboratory time. Our results reveal the natural representation for these time-dependent dynamics. When recast in its terms the cell age distribution for suitable initial conditions evolves under time-invariant rules even as growth conditions remain dynamic! Through the experimental realization at different temperatures of otherwise identical disruptive changes, we not only substantiate the general applicability of the cellular frame of reference but also uncover more emergent simplicities. Motivated by this representation, when time and instantaneous growth rate are expressed in terms of their naturally dimensionless counterparts, remarkably consistent patterns are revealed. These include a unimodal-bimodal-unimodal transition in the shape of the instantaneous growth rate distribution as cells initially in homeostasis experience a disruptive change in nutrient quality and subsequently recover and attain a new homeostasis. The remarkable scaling of the pattern of responses across temperatures suggests that the organizational rules and processes governing the response to disruptive change in nutrient quality remain the same at different temperatures. While the progression of the response appears to proceed at different tempos at different temperatures, upon shifting from the laboratory to the cellular frame of reference these changes progress at the same pace even at different temperatures.

biophysics↗

bioRxiv2025

A proteogenomic approach to discover novel lncRNA-derived peptides and their potential clinical utility in hepatocellular carcinoma

Peptides are increasingly recognized for their versatile functions in biological contexts but their clinical relevance and utility remain largely unexplored. Proteogenomic approaches can accelerate peptide discovery in clinical samples by integrating proteomic data with genomics and transcriptomics evidence. However, long noncoding RNA (lncRNA)-derived peptides (lncPeps) remain largely unidentified, resulting in unmatchable MS/MS spectra. To solve this problem, we have used high-quality Ribo-seq translatomic datasets to generate an extensive database of human liver lncPeps, which we subsequently applied to proteomics data of tumor-adjacent normal tissue pairs from hepatocellular carcinoma (HCC) patients. Using the new database, we discovered 105 novel lncPeps including lncPeps differentially expressed between tumor and non-tumor tissues, and lncPeps with significant correlation with prognosis. Remarkably, combining the expression of lncPeps with canonical proteins in a LASSO regression model improved predictive performance for recurrence, increasing the AUC by 0.005 to 0.085 across three recurrence time points. These findings suggest that lncPeps discovery contributes to our understanding of the molecular heterogeneity and progression of HCC, and broadens the range of potential biomarker candidates or treatment targets for the disease.

bioinformatics↗

bioRxiv2025

Hi-GREx: A 3D Genome Guided Framework for enhancing Gene Expression Prediction Using Hi-C Selected Distal SNPs

Genome-Wide Association Study (GWAS) method has been successfully used to map thousands of loci associated with complex traits, but its ability to reveal the molecular mechanisms altered in complex diseases has been limited due to not including combinations and interactions between markers when predicting a disease. Transcriptome-Wide Association Studies (TWAS) estimate the aggregate effects of multiple genetic variants on complex diseases and represent a promising approach to address the limitations of GWAS. In particular, TWAS provides insights into the functional consequences of disease-associated SNPs by linking them to gene transcription, thereby offering a mechanistic understanding that GWAS alone cannot provide. However, TWAS associated variants have been annotated with the closest or most biologically relevant candidate gene within arbitrarily defined distances but fails to account for long distance SNPs which can affect many genes and have a widespread impact on regulatory networks. Therefore, there is a need to leverage these observed enrichments and build a method that incorporates both short and long distance-associations between SNPs and complex phenotypes. Here we present a method which can utilize Hi-C data to capture "informative" long-distance SNPs and aim to improve prediction accuracy of previous TWAS method. We benchmarked our method on GTEx brain cortex genotype and expression data together with the corresponding Hi-C data. By using the "informative" long distance SNPs selected based on Hi-C, our method improved prediction accuracy of gene expression for 77.4% of the active genes across the entire genome. Particularly, our method can build significant expression models for 18% of genes which were missed by using only short-distance SNPs. Our method has demonstrated the efficiency and importance of utilizing long-distance SNPs in predicting gene expression and can further enhance the power of TWAS methods.

bioinformatics↗

bioRxiv2025

Mechanism of Tethered Agonist Binding to an Adhesion G-Protein-Coupled Receptor

Adhesion GPCRs (ADGRs) contain a GPCR autoproteolysis-inducing (GAIN) domain that is proximal to the receptor N-terminus and undergoes autoproteolysis at a highly conserved GPCR proteolysis (GPS) site to generate the N-terminal fragment (NTF) and transmembrane C-terminal fragment (CTF). Dissociation of NTF reveals a peptide tethered agonist (TA) which is responsible for the activation of the ADGRs. The NTF-bound ADGRs contain the encrypted TA that assumes a {beta}-strand configuration within the GAIN domain, which is markedly different from a U-shaped -helical configuration of TA in the active cryo-EM structures of ADGRs. However, how the TA dramatically changes its configuration and binds to the ADGR CTF remains unknown. In this study, we have performed all-atom enhanced sampling simulations using a novel Peptide-Gaussian accelerated Molecular Dynamics (Pep-GaMD) method on TA binding to the ADGRD1. The Pep-GaMD simulations captured spontaneous binding of the TA into orthosteric pocket of the ADGRD1 and its large conformational transition from the extended {beta} strand to the U-shaped helical configuration. We were able to identify important low-energy conformations of the TA in the binding pathway, as well as different active and inactive states of ADGRD1, in the presence and absence of the Gs protein. Therefore, our Pep-GaMD simulations have revealed dynamic mechanism of the TA binding to an ADGR, which will facilitate rational design of peptide regulators of ADGRs. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/668378v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@15e1fborg.highwire.dtl.DTLVardef@a73738org.highwire.dtl.DTLVardef@1a63d2org.highwire.dtl.DTLVardef@8f848f_HPS_FORMAT_FIGEXP M_FIG C_FIG Peptide-Gaussian accelerated Molecular Dynamics (Pep-GaMD) simulations remarkably captured spontaneous binding of tethered agonist (TA) into the orthosteric pocket of adhesion G-protein-coupled receptor (ADGRD1) and large conformational transition of the TA from an extended {beta}-strand to a U-shaped -helical configuration. We were able to identify important low-energy conformations of the TA in the binding pathway and different states of the receptor from the Pep-GaMD simulations.

bioinformatics↗

bioRxiv2025

Individuals matter: habitat factors and plant traits shape individual-level pollinator interactions in a semi-arid landscape

BackgroundPlant-pollinator interactions are vital for understanding ecological processes influencing reproductive success in plant communities. While species-level pollinator interactions are important for predicting community stability, it remains equally crucial to understand individual-level interactions of keystone species in the community. This study examined the role of habitat factors and floral traits in shaping pollinator interactions at the individual plant scale of Maytenus senegalensis, a dominant native species in the semi-arid Aravalli Hills. We measured flower production, nectar sugar concentration, flower diameter, and external factors such as percentage soil moisture, distance to habitat edge, and density of co-flowering conspecifics to assess their impact on pollinator interactions and reproductive success. ResultsWe found significant variation in reproductive investment in the form of flower production and a trade-off with reward quality, where plants with higher flower production were found to have a lower nectar sugar concentration. Higher flower production negatively influenced reproductive success, suggesting the likelihood of increased within-plant visitation. Eristalinus and Apis were the dominant pollinator genera, and overall, Dipterans were found to play a critical role in maintaining the network stability. The presence of flowering conspecific plants in the neighborhood reduced the pollen deposition, suggesting competitive interactions. Moreover, individual plants were found to show some amount of specialization in their interaction niches. We predict that this could lead to further divergence of interaction niches due to pollinator-mediated competition. Any perturbation to interactions of plants with a high degree of pollinator connectance was found to disproportionately influence the network. ConclusionsOverall, our results link microhabitat (soil moisture) and neighborhood context to individual interaction niches, demonstrating that allocation trade-offs and conspecific competition jointly shape pollination and fitness. In semi-arid systems, which are undergoing considerable anthropogenic and climatic changes, our study provides insights into individual pollinator interaction niches and the role of microhabitat factors in species persistence within a community.

ecology↗

bioRxiv2025

Cryo-EM reveals a new allosteric binding site at the M5 mAChR

The M5 muscarinic acetylcholine receptor (M5 mAChR) represents a promising therapeutic target for neurological disorders. However, the high conservation of its orthosteric binding site has posed significant challenges for drug development. While selective positive allosteric modulators (PAMs) offer a potential solution, a structural understanding of the M5 mAChR and its allosteric binding sites has remained limited. Here, we present a 2.8 [A] cryo-electron microscopy structure of the M5 mAChR complexed with heterotrimeric Gq protein and the agonist iperoxo, completing the active-state structural characterization of the mAChR family. To identify the binding site of M5-selective PAMs, we implemented an integrated approach combining mutagenesis, pharmacological assays, structural biology, and molecular dynamics simulations. Our mutagenesis studies revealed that selective M5 PAMs bind outside previously characterized M5 mAChR allosteric sites. Subsequently, we obtained a 2.1 [A] structure of M5 mAChR co-bound with acetylcholine and the selective PAM VU6007678, revealing a novel allosteric pocket at the extrahelical interface between transmembrane domains 3 and 4 that was confirmed through mutagenesis and simulations. These findings demonstrate the diverse mechanisms of allosteric regulation in mAChRs and highlight the value of integrating pharmacological and structural approaches to identify novel allosteric binding sites.

pharmacology and toxicology↗

bioRxiv2024

Characterization of A Bronchoscopically Induced Transgenic Lung Cancer Pig Model for Human Translatability

BackgroundThere remains a need for animal models with human translatability in lung cancer (LC) research. Findings in pigs have high impact on humans due to similar anatomy and physiology. We present the characterization of a bronchoscopically-induced LC model in Oncopigs carrying inducible KRASG12D and TP53R167H mutations. MethodsTwelve Oncopigs underwent 29 injections via flexible bronchoscopy. Eighteen Adenovirus-Cre recombinase gene (AdCre) inductions were performed endobronchially (n=6) and transbronchially with a needle (n=12). Eleven control injections were performed without AdCre. Oncopigs underwent serial contrast-enhanced chest CT with clinical follow-up for 29 weeks. Following autopsy, lung and organ tissues underwent histopathology, immunohistochemistry, and RNA-sequencing with comparative analysis with The Cancer Genome Atlas (TCGA) human LC data. ResultsAll 18 sites of AdCre injections had lung consolidations on CT imaging. Transbronchial injections led to histopathologic invasive cancer and/or carcinoma in situ (CIS) in 11/12 (91.7%), and invasive cancer (excluding CIS) in 8/12 (66.6%). Endobronchial inductions led to invasive cancer in 3/6 (50%). A soft tissue metastasis was observed in one Oncopig. Immunohistochemistry confirmed expression of Pan-CK+/epithelial cancer cells, with macrophages and T cells infiltration in the tumor microenvironment. Transcriptome comparison showed 54.3% overlap with human LC (TCGA), in contrast to 29.88% overlap of KRAS-mutant mouse LC with human LC. ConclusionsThe transgenic and immunocompetent Oncopig model has a high rate of LC following bronchoscopic transbronchial induction. Overlap of the Oncopig LC transcriptome with human LC transcriptome was noted. This pig model is expected to have high clinical translatability to the human LC patient.

cancer biology↗

bioRxiv2024

Mechanisms of peptide agonist dissociation and deactivation of adhesion G-protein-coupled receptors

Adhesion G protein-coupled receptors (ADGRs) belong to Class B2 of GPCRs and are involved in a wide array of important physiological processes. ADGRs contain a GPCR autoproteolysis-inducing (GAIN) domain that is proximal to the receptor N-terminus and undergoes autoproteolysis during biosynthesis to generate two fragments: the N-terminal fragment (NTF) and C-terminal fragment (CTF). Dissociation of NTF reveals a tethered agonist to activate CTF of ADGRs for G protein signaling. Synthetic peptides that mimic the tethered agonist can also activate the ADGRs. However, mechanisms of peptide agonist dissociation and deactivation of ADGRs remain poorly understood. In this study, we have performed all-atom enhanced sampling simulations using a novel Protein-Protein Interaction-Gaussian accelerated Molecular Dynamics (PPI-GaMD) method on the ADGRG2-IP15 and ADGRG1-P7 complexes. The PPI-GaMD simulations captured dissociation of the IP15 and P7 peptide agonists from their target receptors. We were able to identify important low-energy conformations of ADGRG2 and ADGRG1 in the active, intermediate, and inactive states, as well as exploring different states of the peptide agonists IP15 and P7 during dissociation. Therefore, our PPI-GaMD simulations have revealed dynamic mechanisms of peptide agonist dissociation and deactivation of ADGRG1 and ADGRG2, which will facilitate rational design of peptide regulators of the two receptors and other ADGRs.

bioinformatics↗