Biology subjects

Gao, J.

Publications and source records attributed to Gao, J..

At least 127 records · Page 7Linked to original sources

bioRxiv2024

Genome-Wide Association Study in Outbred Heterogeneous Stock Rats Identifies Multiple Loci for the Incentive Salience of Reward Cues.

Addiction vulnerability is associated with the tendency to attribute incentive salience to reward predictive cues; both addiction and the attribution of incentive salience are influenced by environmental and genetic factors. To characterize the genetic contributions to incentive salience attribution, we performed a genome-wide association study (GWAS) in a cohort of 1,645 genetically diverse heterogeneous stock (HS) rats. We tested HS rats in a Pavlovian conditioned approach task, in which we characterized the individual responses to food-associated stimuli ("cues"). Rats exhibited either cue-directed "sign-tracking" behavior or food-cup directed "goal-tracking" behavior. We then used the conditioned reinforcement procedure to determine whether rats would perform a novel operant response for unrewarded presentations of the cue. We found that these measures were moderately heritable (SNP heritability, h2 = .189-.215). GWAS identified 14 quantitative trait loci (QTLs) for 11 of the 12 traits we examined. Interval sizes of these QTLs varied widely. 7 traits shared a QTL on chromosome 1 that contained a few genes (e.g. Tenm4, Mir708) that have been associated with substance use disorders and other mental health traits in humans. Other candidate genes (e.g. Wnt11, Pak1) in this region had coding variants and expression-QTLs in mesocorticolimbic regions of the brain. We also conducted a Phenome-Wide Association Study (PheWAS) on other behavioral measures in HS rats and found that regions containing QTLs on chromosome 1 were also associated with nicotine self-administration in a separate cohort of HS rats. These results provide a starting point for the molecular genetic dissection of incentive salience and provide further support for a relationship between attribution of incentive salience and drug abuse-related traits.

neuroscience↗

bioRxiv2024

CORACLE (COVID-19 liteRAture CompiLEr): A platform for efficient tracking and extraction of SARS-CoV-2 and COVID-19 literature, with examples from post-COVID with respiratory involvement

BackgroundDuring the COVID-19 pandemic there emerged a need to efficiently monitor and process large volumes of scientific literature on the subject. Currently, as the pandemic is winding down, the clinicians encountered a novel syndrome - Post-acute Sequelae of COVID- 19 (PASC) - that affects over 10% of those who contract SARS-CoV-2 and presents a significant and growing challenge in the medical field. The continuous influx of new research publications underscores a critical need for efficient tools for navigating the literature. ObjectivesWe aimed to develop an application which will allow monitoring and categorizing COVID-19-related literature through building publication networks and medical subject headings (MeSH) maps to be able to quickly identify key publications and publication networks. MethodsWe introduce CORACLE (COVID-19 liteRAture CompiLEr), an innovative web application designed for the analysis of COVID-19-related scientific articles and the identification of research trends. CORACLE features three primary interfaces: The "Search" interface, which displays research trends and citation links; the "Citation Map" interface, allowing users to create tailored citation networks from PubMed Identifiers (PMIDs) to uncover common references among selected articles; and the "MeSH" interface, highlighting current MeSH trends and associations between MeSH terms. ResultsOur web application, CORACLE, leverages regularly updated PubMed data to aggregate and categorize the extensive literature on COVID-19 and PASC, aiding in the identification of relevant research publication hubs. Using lung function in PASC patients as a search example, we demonstrate how to identify and visualize the interactions between the relevant publications. ConclusionCORACLE proves to be an effective tool for the extraction and analysis of literature. Its functionalities, including the MeSH trends and customizable citation mapping, facilitate the discovery of relevant information and emerging trends in COVID-19 and PASC research.

bioinformatics↗

bioRxiv2024

Scalable and Efficient Generation of Mouse Primordial Germ Cell-like Cells

Primordial germ cells (PGCs) are the founder cells of the germline. The ability to generate PGC-like cells (PGCLCs) from pluripotent stem cells has advanced our knowledge of gametogenesis and holds promise for developing infertility treatments. However, generating an ample supply of PGCLCs for demanding applications such as large-scale genetic screens has been a limitation. Here, we demonstrated that simultaneous overexpression of 4 transcriptional factors - Nanog and three PGC master regulators Prdm1, Prdm14 and Tfap2c - in suspended mouse epiblast like cells (EpiLCs) and formative embryonic stem cells (ESCs) results in efficient and cost-effective production of PGCLCs. Nanog overexpression enhanced the PGC regulatory network, suppressed differentiation of somatic lineages, and maintained PGC fate. PGCLCs generated in this manner have transcriptomes similar to in vivo PGCs and are more advanced than cytokine-induced PGCLCs. These differentiated PGCLCs could be sustained over prolonged periods of culture and could differentiate into spermatogonia-like cells in vitro. We exploited this platform to conduct a bulk epigenome-wide CRISPRi screen to identify genes that decreased the efficiency of PGCLC formation when downregulated. One of the identified candidates was Ncor2, a transcriptional repressor that acts via recruitment of Class I and Class IIa histone deacetylases (HDACs). Consistently with this finding, the HDAC inhibitors valproic acid (VPA; an anti-convulsant) and sodium butyrate (SB; a widely-used dietary supplement) suppressed PGCLC differentiation. Furthermore, exposure of developing mouse embryos to SB or VPA caused hypospermatogenesis. This work demonstrates the feasibility of this platform to efficiently conduct large-scale functional screens of genes, chemicals, or other agents that may impact germline development.

cell biology↗

bioRxiv2024

iSCORE-PD: an isogenic stem cell collection to research Parkinson Disease

Parkinsons disease (PD) is a neurodegenerative disorder caused by complex genetic and environmental factors. Genome-edited human pluripotent stem cells (hPSCs) offer a unique experimental platform to advance our understanding of PD etiology by enabling the generation of disease-relevant cell types carrying patient mutations along with isogenic control cells. To facilitate this approach, we generated a collection of 65 human stem cell lines genetically engineered to harbor high risk or causal variants in genes associated with PD (SNCA A53T, SNCA A30P, PRKN Ex3del, PINK1 Q129X, DJ1/PARK7 Ex1-5del, LRRK2 G2019S, ATP13A2 FS, FBXO7 R498X/FS, DNAJC6 c.801 A>G/FS, SYNJ1 R258Q/FS, VPS13C A444P/FS, VPS13C W395C/FS, GBA1 IVS2+1/FS). All mutations were introduced into a fully characterized and sequenced female human embryonic stem cell (hESC) line (WIBR3; NIH approval number NIHhESC-10-0079) using different genome editing techniques. To ensure the genetic integrity of these cell lines, we implemented rigorous quality controls, including whole-genome sequencing of each line. Our analysis of the genetic variation in this cell line collection revealed that while genome editing, particularly using CRISPR/Cas9, can introduce rare off-target mutations, the predominant source of genetic variants arises from routine cell culture and are fixed in cell lines during clonal isolation. The observed genetic variation was minimal compared to that typically found in patient-derived iPSC experiments and predominantly affected non-coding regions of the genome. Importantly, our analysis outlines strategies for effectively managing genetic variation through stringent quality control measures and careful experimental design. This systematic approach ensures the high quality of our stem cell collection, highlights advantages of prime editing over conventional CRISPR/Cas9 methods and provides a roadmap for the generation of gene-edited hPSC collections at scale in an academic setting. Our iSCORE-PD collection represents an easily accessible and valuable platform to study PD, which can be used by investigators to understand the molecular pathophysiology of PD in a human cellular setting.

neuroscience↗

bioRxiv2024

Differences in milk microbiota between healthy cows and cows with recurring Klebsiella mastitis

Klebsiella spp. infections continue to have a significant economic impact on the dairy industry, being an important cause of severe clinical mastitis, recurrent infections, and demonstrating poor response to antimicrobials. It is, therefore, essential to investigate the underlying causes of Klebsiella spp. infections. Here we used high-throughput DNA sequencing to characterize the milk microbiota of healthy dairy cows (HDC) and cows with history of recurrent Klebsiella mastitis (KLB). Our goal was to identify potential pathogenic genera associated with recurrent Klebsiella infections in cows. The relative abundance of Firmicutes and Faecalibacterium was greater in the KLB group than in the HDC group. In contrast, Proteobacteria and Labrenzia were less abundant than in the HDC group. Although the species distributions differed between groups, diversity and abundance of communities were comparable. Notably, genera of increased occurrence in the KLB group were mostly intestinal-associated, which suggests that cows in the KLB group resided in a contaminated environment or had increased teat-end exposure to fecal bacteria. We did not detect major differences in microbiota among quarters, and also between fore-strip milk and milk collected after fore-stripping. Conversely, milk of heifers had increased alpha diversity in comparison to milk of multiparous cows.

microbiology↗

bioRxiv2024

PI3K/HSCB axis facilitates FOG1 nuclear translocation to promote erythropoiesis and megakaryopoiesis

Erythropoiesis and megakaryopoiesis are stringently regulated by signaling pathways. However, the precise molecular mechanisms through which signaling pathways regulate key transcription factors controlling erythropoiesis and megakaryopoiesis remain partially understood. Herein, we identified heat shock cognate B (HSCB), which is well known for its iron-sulfur cluster delivery function, as an indispensable protein for friend of GATA 1 (FOG1) nuclear translocation during erythropoiesis of K562 human erythroleukemia cells and cord-blood-derived human CD34+CD90+ hematopoietic stem cells (HSCs), as well as during megakaryopoiesis of the CD34+CD90+ HSCs. Mechanistically, HSCB could be phosphorylated by phosphoinositol-3-kinase (PI3K) to bind with and mediate the proteasomal degradation of transforming acidic coiled-coil containing protein 3 (TACC3), which otherwise detained FOG1 in the cytoplasm, thereby facilitating FOG1 nuclear translocation. Given that PI3K is activated during both erythropoiesis and megakaryopoiesis, and that FOG1 is a key transcription factor for these processes, our findings elucidate an important, previously unrecognized iron-sulfur cluster delivery independent function of HSCB in erythropoiesis and megakaryopoiesis.

molecular biology↗

bioRxiv2024

Binding profiles for 954 Drosophila and C. elegans transcription factors revealtissue specific regulatory relationships

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the modERN (model organism Encyclopedia of Regulatory Networks) consortium that systematically assayed TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). We describe key features of these datasets, comprising 604 TFs identifying 3.6M sites in the fly and 350 TFs identifying 0.9 M sites in the worm. Applying a machine learning model to these data identifies sets of TFs with a prominent role in promoting target gene expression in specific cell types. TF binding data are available through the ENCODE Data Coordinating Center and at https://epic.gs.washington.edu/modERNresource, which provides access to processed and summary data, as well as widgets to probe cell type-specific TF-target relationships. These data are a rich resource that should fuel investigations into TF function during development.

genomics↗

bioRxiv2024

A mouse model to study glutathione limitation in vivo

Glutathione (GSH) is a highly abundant tripeptide thiol that performs diverse protective and biosynthetic functions in cells. While changes in GSH availability are linked to many diseases, including cancer and neurodegenerative disorders, determining the function of GSH in physiology and disease has been challenging due to its tight regulation. To address this, we generated cell and mouse models that express a bifunctional glutathione-synthesizing enzyme from Streptococcus Thermophilus (GshF). GshF expression allows efficient production of GSH in the cytosol and mitochondria and prevents cell death in response to GSH depletion, but not ferroptosis, indicating that GSH is not a limiting factor under lipid peroxidation. CRISPR screens using engineered enzymes revealed metabolic liabilities under compartmentalized GSH depletion. Finally, GshF expression in mice is embryonically lethal but sustains postnatal viability when restricted to adulthood. Overall, our work identifies a conditional mouse model to investigate the role of GSH availability in physiology and disease.

genetics↗

bioRxiv2024

Tractography-based automated identification of the retinogeniculate visual pathway with novel microstructure-informed supervised contrastive learning

The retinogeniculate visual pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP are important in studying the anatomy of the visual system and can inform the treatment of related brain diseases. Diffusion MRI (dMRI) tractography is an advanced imaging method that uniquely enables in vivo mapping of the 3D trajectory of the RGVP. Currently, identification of the RGVP from tractography data relies on expert (manual) selection of tractography streamlines, which is time-consuming, has high clinical and expert labor costs, and is affected by inter-observer variability. In this paper, we present a novel deep learning framework, DeepRGVP, to enable fast and accurate identification of the RGVP from dMRI tractography data. We design a novel microstructure-informed supervised contrastive learning method that leverages both streamline label and tissue microstructure information to determine positive and negative pairs. We propose a simple and successful streamline-level data augmentation method to address highly imbalanced training data, where the number of RGVP streamlines is much lower than that of non-RGVP streamlines. We perform comparisons with several state-of-the-art deep learning methods that were designed for tractography parcellation, and we show superior RGVP identification results using DeepRGVP. In addition, we demonstrate a good generalizability of DeepRGVP to dMRI tractography data from neurosurgical patients with pituitary tumors and we show DeepRGVP can successfully identify RGVPs despite the effect of lesions affecting the RGVPs. Overall, our study shows the high potential of using deep learning to automatically identify the RGVP.

neuroscience↗

bioRxiv2024

STING Licensing of Type I Dendritic Cells Potentiates Antitumor Immunity

Stimulator of interferon genes (STING) is an immune adaptor protein that senses cyclic GMP-AMP (cGAMP) in response to self or microbial cytosolic DNA as a danger signal. STING is ubiquitously expressed in diverse cell populations including cancer cells with distinct cellular functions such as activation of type I interferons, autophagy induction, or triggering apoptosis. It is not well understood whether and which subsets of immune cells, stromal cells, or cancer cells are particularly important for STING-mediated antitumor immunity. Here using a polymeric STING-activating nanoparticle (PolySTING) with a "shock-and-lock" dual activation mechanism, we show type 1 conventional dendritic cell (cDC1) is essential for STING-mediated rejection of multiple established and metastatic murine tumors. STING status in the host but not in the cancer cells (Tmem173-/-) is important for antitumor efficacy. Specific depletion of cDC1 (Batf3-/-) or STING deficiency in cDC1 (XCR1creSTINGfl/fl) abolished PolySTING efficacy, whereas depletion of other myeloid cells had little effect. Adoptive transfer of wildtype cDC1 in Batf3-/- mice restored antitumor efficacy while transfer of cDC1 with STING or IRF3 deficiency failed to rescue. PolySTING induced a specific chemokine signature in wildtype but not Batf3-/- mice. Multiplexed immunohistochemistry analysis of STING-activating cDC1s in resected tumors correlates with patient survival while also showing increased expressions after neoadjuvant pembrolizumab therapy in non-small cell lung cancer patients. Therefore, we have defined that a subset of myeloid cells is essential for STING-mediated antitumor immunity with associated biomarkers for prognosis. One Sentence SummaryA "shock-and-lock" nanoparticle agonist induces direct STING signaling in type 1 conventional dendritic cells to drive antitumor immunity with defined biomarkers

immunology↗

bioRxiv2023

Iterative Prompt Refinement for Mining Gene Relationships from ChatGPT

ChatGPT has demonstrated its potential as a surrogate knowledge graph. Trained on extensive data sources, including open-access publications, peer-reviewed research articles and biomedical websites, ChatGPT extracted information on gene relationships and biological pathways. However, a major challenge is model hallucination, i.e., high false positive rates. To assess and address this challenge, we systematically evaluated ChatGPTs capacity for predicting gene relationships using GPT-3.5-turbo and GPT-4. Benchmarking against the KEGG Pathway Database as the ground truth, we experimented with diverse prompting strategies, targeting gene relationships of activation, inhibition, and phosphorylation. We introduced an innovative iterative prompt refinement technique. By assessing prompt efficacy using metrics like F-1 score, precision, and recall, GPT-4 was re-engaged to suggest improved prompts. A refined prompt, which combines a specialized role with explanatory text, significantly enhances the performance. Going beyond pairwise gene relationships, we also deciphered complex gene interplays, such as gene interaction chains and pathways pertinent to diseases like non-small cell lung cancer. Direct prompts showed limited success, but "least-to-most" prompting exhibited significant potentials for such network constructions. The methods in this study may be used for some other bioinformatics prediction problems.

bioinformatics↗

bioRxiv2023

DomainFit: Identification of Protein Domains in cryo-EM maps at Intermediate Resolution using AlphaFold2-predicted Models

Cryo-electron microscopy (cryo-EM) has revolutionized our understanding of macromolecular complexes, enabling high-resolution structure determination. With the paradigm shift to in situ structural biology recently driven by the ground-breaking development of cryo-focused ion beam milling and cryo-electron tomography, there are an increasing number of structures at sub-nanometer resolution of complexes solved directly within their cellular environment. These cellular complexes often contain unidentified proteins, related to different cellular states or processes. Identifying proteins at resolutions lower than 4 [A] remains challenging because the side chains cannot be visualized reliably. Here, we present DomainFit, a program for automated domain-level protein identification from cryo-EM maps at resolutions lower than 4 [A]. By fitting domains from artificial intelligence-predicted models such as AlphaFold2-predicted models into cryo-EM maps, the program performs statistical analyses and attempts to identify the proteins forming the density. Using DomainFit, we identified two microtubule inner proteins, one of them, a CCDC81 domain-containing protein, is exclusively localized in the proximal region of the doublet microtubule from the ciliate Tetrahymena thermophila. The flexibility and capability of DomainFit makes it a valuable tool for analyzing in situ structures.

biochemistry↗

bioRxiv2023

scfetch: an R package to access and format single-cell RNA sequencing datasets from public repositories

BackgroundDownloading and reanalyzing the existing single-cell RNA sequencing (scRNA-seq) data provides an efficient choice to gain clues and new insights. However, no tool can fetch the diverse scRNA-seq data types (raw data, count matrix, and processed object) distributed in various repositories, process and load the downloaded data to R, convert formats between scRNA-seq objects, and benchmark the format conversion tools. FindingsHere, we present GEfetch2R, an R package with Docker image to (i) download diverse scRNA-seq data types, including raw data (SRA and ENA), count matrices (GEO, UCSC Cell Browser, and PanglaoDB), and processed objects (Zenodo, CELLxGENE, and HCA); (ii) process the downloaded data, load output/downloaded count matrices and annotations to R (SeuratObject/DESeqDataSet), filter the SeuratObject based on cell metadata and genes, and merge multiple SeuratObjects if applicable; (iii) convert formats between the widely used scRNA-seq objects, including SeuratObject, AnnData, SingleCellExperiment, CellDataSet/cell_data_set, and loom, and benchmark format conversion tools in terms of information kept, usability, running time, and scalability to guide the tool selection. Furthermore, GEfetch2R can also download, process, and load bulk RNA-seq raw data (SRA and ENA) and count matrices (GEO) to R (DESeqDataSet). ConclusionsGEfetch2R is an R package dedicated to facilitating researchers to access and explore the existing gene expression data from various public repositories. It can function as a data downloader (supports all three scRNA-seq and two bulk RNA-seq data types), a data processor (processes and loads the output/downloaded count matrices and annotations to R), and an object format converter (between the widely used scRNA-seq objects).

bioinformatics↗

bioRxiv2023

FFCM-MRF: An accurate and generalizable cerebrovascular segmentation pipeline for humans and rhesus monkeys based on TOF-MRA

PurposeCerebrovascular segmentation and quantification of vascular morphological features on humans and rhesus monkeys are essential for prevention, diagnosis, and treatment of brain diseases. However, current automated whole-brain vessel segmentation methods are often not generalizable to independent datasets, limiting their usefulness in real-world environments with their heterogeneity in participants, scanners, and species. Materials and MethodsIn this study, we proposed an automated, accurate and generalizable segmentation method for magnetic resonance angiography images called FFCM-MRF. This method integrates fast fuzzy c-means clustering and Markov random field optimization using blood vessel shape priors and spatial constraints. We used a total of 123 human and 44 macaque MRA images scanned at 1.5 T, 3 T, and 7 T MRI from 9 datasets to develop and validate the method. ResultsThe average Dice score coefficients for multiple independent datasets were 69.16-89.63%, with the improvements in FFCM-MRF ranged from 0.16-16.14% compared with state-of-the-art machine learning methods. Quantitative analysis showed that FFCM-MRF can accurately segment major arteries in the Circle of Willis at the base of the brain and smaller distal pial arteries while effectively suppressing noise. Test-retest analysis showed that the model yielded high vascular volume and diameter reliability. ConclusionsOur results demonstrate that the proposed method is highly accurate and reliable and largely independent of variations in field strength, scanner platforms, acquisition parameters, and species. The macaque MRA data and user-friendly open-source toolbox are freely available at OpenNeuro and GitHub to facilitate studies of imaging biomarkers for cerebrovascular and neurodegenerative diseases.

neuroscience↗

bioRxiv2023

An injectable in situ crosslinkable platform for ultra-long-acting delivery of hydrophilic therapeutics

Achieving ultra-long-term release of hydrophilic drugs over several months remains a significant challenge for existing long-acting injectables (LAIs). Existing platforms, such as in situ forming implants (ISFI), exhibit high burst release due to solvent efflux and microsphere-based approaches lead to rapid drug diffusion due to significant water exchange and large pores. Addressing these challenges, we have developed an injectable platform that, for the first time, achieves ultra-long-term release of hydrophilic drugs for over six months. This system employs a methacrylated ultra-low molecular weight pre-polymer (polycaprolactone) to create in situ cross-linked depots (ISCD). The ISCDs solvent-free design and dense mesh network, both attributed to the ultra-low molecular weight of the pre-polymer, effectively minimizes burst release and water influx/efflux. In vivo studies in rats demonstrate that ISCD outperforms ISFI by achieving lower burst release and prolonged drug release. We demonstrated the versatility of ISCD by showcasing ultra-long-term delivery of several hydrophilic drugs, including antiretrovirals (tenofovir alafenamide, emtricitabine, abacavir, and lamivudine), antibiotics (vancomycin and amoxicillin) and an opioid antagonist naltrexone. Additionally, ISCD achieved ultra-long-term release of the hydrophobic drug tacrolimus and enabled co-delivery of hydrophilic drug combinations encapsulated in a single depot. We also identified design parameters to tailor the polymer network, tuning drug release kinetics and ISCD degradation. Pharmacokinetic modeling predicted over six months of drug release in humans, significantly surpassing the one-month standard achievable for hydrophilic drugs with existing LAIs. The platforms biodegradability, retrievability, and biocompatibility further underscore its potential for improving treatment adherence in chronic conditions.

bioengineering↗

bioRxiv2023

A Drug-Free Pathogen Capture and Neutralizing Nasal Spray to Prevent Emerging Respiratory Infections

Respiratory infections pose a global health crisis. Vaccines are pathogen specific, and new vaccines are needed for mutants and emerging pathogens. Here, we report a "drug free" prophylactic platform - a "Pathogen Capture and Neutralizing Spray" (PCANS) that acts via a multi-pronged approach to prevent a broad spectrum of respiratory infections. PCANS forms a protective coating in the nasal cavity that enhances the capture of large respiratory droplets. The coating acts as a physical barrier against a broad spectrum of viruses and bacteria, and rapidly neutralizes them, reducing the pathogen load by >99.99%. In mice, PCANS showed nasal retention for at least 8 h and was safe for daily administration. A single prophylactic dose of PCANS protected mice against supra-lethal dosages of a mouse-adapted H1N1 Influenza virus (PR8), reduced lung viral titer by >99.99%, improved survival, and suppressed pathological manifestations. Together, our data suggest PCANS as a promising daily-use prophylactic approach against current and emerging respiratory infections.

bioengineering↗

bioRxiv2023

Mechanisms analysis for Formononetin counteracted-Osimertinib resistance in Non-small-cell lung cancer cells: from the insight into the gene transcriptional level

BackgroundsOsimertinib resistance in Non-Small-Cell Lung Cancers (NSCLC) is a difficult problem to be solved in clinic. Formononetin is one of the main isoflavone components, which has strong anti-cancer effects in NSCLC. However, the potential effects and the mechanisms of Formononetin to counteract the Osimertinib resistant in NSCLC is remain to be uncovered. MethodsOsimertinib-resistant NSCLC cell line (H1975_OR) was generated by increasingly adding of Osimertinib in H1975 cell culture medium. The Formononetin was used to induce H1975_OR cell apoptosis an to inhibit cell proliferation and clonal formation. The RNA-sequencing was used to study the potential mechanisms for Formononetin to counteract the Osimertinib resistant in NSCLC. ResultsFormononetin could significantly induced cell apoptosis, whereas, dramatically inhibited cell proliferation and clinal formation in H1975_OR cells. Formononetin induced tremendous alterations of gene expression in H1975_OR cells and these genes can be clustered into unique GO, KEGG and GSEA pathways. ConclusionOur results preliminarily uncovered the underlying mechanisms for Formononetin counteracted Osimertinib-resistance in NSCLC cells and provided a potential treatment method for Osimertinib resistant NSCLC patients.

cancer biology↗

bioRxiv2023

The αC-β4 loop controls the allosteric cooperativity between nucleotide and substrate in the catalytic subunit of protein kinase A

Allosteric cooperativity between ATP and substrates is a prominent characteristic of the cAMP-dependent catalytic subunit of protein kinase A (PKA). Not only this long-range synergistic action is involved in substrate recognition and fidelity, but it is also likely to regulate PKA association with regulatory subunits and other binding partners. To date, a complete understanding of the molecular determinants for this intramolecular mechanism is still lacking. Here, we integrated NMR-restrained molecular dynamics simulations and a Markov State Model to characterize the free energy landscape and conformational transitions of the catalytic subunit of protein kinase A (PKA-C). We found that the apoenzyme populates a broad free energy basin featuring a conformational ensemble of the active state of PKA-C (ground state) and other basins with lower populations (excited states). The first excited state corresponds to a previously characterized inactive state of PKA-C with the C helix swinging outward. The second excited state displays a disrupted hydrophobic packing around the regulatory (R) spine, with a flipped configuration of the F100 and F102 residues at the C-{beta}4 loop. To experimentally validate the second excited state, we mutated F100 into alanine (F100A) and used NMR spectroscopy to characterize the structural response of the kinase to ATP and substrate binding. While the catalytic efficiency of PKA-CF100A with a canonical peptide substrate remains unaltered, this mutation rearranges the C-{beta}4 loop conformation, interrupting the structural coupling of the two lobes and abolishing the allosteric binding cooperativity of the enzyme. The highly conserved C-{beta}4 loop emerges as a pivotal element able to control the synergistic binding between nucleotide and substrate. These results may explain how mutations or insertions near or within this motif affect the function and drug sensitivity in other homologous kinases.

biophysics↗