Biology subjects

Qiao, X.

Publications and source records attributed to Qiao, X..

At least 19 recordsLinked to original sources

bioRxiv2026

Fine-tuning an intracellular allosteric pocket programs GPCR signaling bias

Biased signaling of G protein-coupled receptors (GPCRs) offers a route for precise therapeutics with fewer adverse effects. Intracellular allosteric ligands can impose such bias, yet how subtle chemical changes within these pockets reshape receptor-transducer coupling and downstream signaling remains unclear. Here, we systematically fine-tuned the intracellular allosteric pocket of neurotensin receptor 1 (NTSR1) through chemical modification of the {beta}-arrestin-biased ligand SBI-553. Minor changes to the ligand scaffold altered transducer-coupling preferences, generating distinct profiles of G-protein and {beta}-arrestin signaling. Cryo-electron microscopy structures of NTSR1-{beta}-arrestin2 complexes bound to designed allosteric probes revealed ligand-dependent remodeling of the intracellular cavity that reshapes the receptor-effector interface. Alanine scanning identified transducer-sensitive residues within and beyond the immediate ligand-contact region. In mice, SBI-553 and N065 produced distinct physiological profiles, with N065 improving survival in a lethal endotoxemia model. Finally, phosphoproteomic profiling revealed partially overlapping but distinct downstream signaling profiles among the three modulators. Together, these findings establish the intracellular allosteric pocket as a tunable determinant of transducer coupling and show that closely related modulators can generate distinct signaling and physiological profiles.

pharmacology and toxicology↗

bioRxiv2025

HUBMet: An integrative database and analytical platform for human blood metabolites and metabolite-protein associations

Understanding human blood metabolites is essential for deciphering systemic physiology and disease mechanisms, yet remains challenging due to diverse origins and dynamic regulation. In this study, we developed HUBMet (https://hubmet.app.bio-it.tech/home), an open-access web server that includes 3,950 metabolites and 129,814 metabolite-protein associations, with four analytical modules: Over-Representation Analysis (ORA) for enrichment analysis; Metabolite Set Enrichment Analysis (MSEA) for quantitative data analysis; Tissue Specificity Analysis (TSA) for assessing metabolite-tissue relevance; Metabolite-Protein Network Analysis (MPNet) for identifying key metabolite-protein associations and functional modules. HUBMets utility is demonstrated through a COVID-19 case study revealing metabolic signatures associated with disease severity.

bioinformatics↗

bioRxiv2025

BioinAI: a general bioinformatic framework for multi-level transcriptomic data analysis using multiple semi-agents

Clinical and biological insights from large-scale transcriptomic data are often limited by technical variability and analytical complexity. Here, we introduce BioinAI, a general bioinformatic framework designed for multi-level transcriptomic data analysis. As part of the BioinAI framework, two algorithms named DeepAdvancer and stNiche were developed to improve data integration and analytical efficiency. DeepAdvancer leverages a class-aware adversarial autoencoder to reconstruct gene-expression profiles from 49,738 samples across 131 skin conditions. These profiles revealed a conserved inflammatory axis and a transcriptomic continuum which link diverse diseases through shared immune responses and structural programs. stNiche leverages spatial graph networks and symmetry-aware matching to identify functional cellular niches and reveals microstructural alterations across development, homeostasis, and disease. For instance, it identified a fibroblast-immune niche surrounding hair follicles in healthy skin, which disappears in pathological states. In addition, BioinAI provides a user-friendly online analysis platform powered by multiple semi-agents (www.bioinai.com), significantly facilitating the extraction of biological insights to advance scientific research.

bioinformatics↗

bioRxiv2024

Whole-genome resequencing revealed the Origin and Domestication of Chinese Domestic Rabbits

The evolutionary and genetic origins of Chinese indigenous rabbits (Oryctolagus cuniculus) remain largely unclear, despite being among the most recently domesticated animals. We sequenced the whole genomes of 142 individual rabbits and collected 25 resequencing accessions from the NCBI, representing six Chinese indigenous breeds, three other domesticated breeds (serving as a bridge between European wild-type and Chinese domestic populations), and two wild rabbit populations from the Iberian Peninsula and Southern France. Population and demographic analyses suggest that Chinese domestic rabbits are most likely descendants of O. c. cuniculus, native to France 800-1500 years ago. These rabbits likely first arrived in the southeast coastal areas of China through trade before spreading to inland regions. Additionally, there may be other origins for Chinese domestic rabbits. We observed considerable variation in the genetic makeup of maternal ancestry between Chinese domestic rabbits and European wild populations, with Chinese rabbits possessing unique mitochondrial haplotypes. Our analysis also highlights selective sweeps on genes affecting brain and neuronal development, which may have been under strong positive selection during domestication; genes related to starch digestion and fat metabolism, suggesting an evolutionary adaptation to digest high-starch diets; and the white coat phenotype in rabbits, resulting from selection at the melanogenesis-associated transcription factor locus. Overall, our data provide comprehensive insights into the origin and domestication of rabbits and lay the foundation for genome-based breeding.

evolutionary biology↗

bioRxiv2024

CCQM-P199b: Interlaboratory comparability study of SARS-CoV-2 RNA copy number quantification

Nucleic acid amplification tests including reverse transcription quantitative PCR (RT-qPCR) are used to detect RNA from Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of the Coronavirus disease 2019 (COVID-19) pandemic. Standardized measurements of RNA can facilitate comparable performance of laboratory tests in the absence of existing reference measurement systems early on in a pandemic. Interlaboratory study CCQM P199b "SARS-CoV-2 RNA copy number quantification" was designed to test the fitness-for-purpose of developed candidate reference measurement procedures (RMPs) for SARS-CoV-2 genomic targets in purified RNA materials, and was conducted under the auspices of the Consultative Committee for Amount of Substance: Metrology in Chemistry and Biology (CCQM) to evaluate the measurement comparability of national metrology institutes (NMIs) and designated institutes (DIs), thereby supporting international standardization. Twenty-one laboratories participated in CCQM P199b and were requested to report the RNA copy number concentration, expressed in number of copies per microliter, of the SARS-CoV-2 nucleocapsid (N) gene partial region (NC_045512.2: 28274-29239) and envelope (E) gene (NC_045512.2: 26245-26472) (optional measurements) in samples consisting of in vitro transcribed RNA or purified RNA from lentiviral constructs. Materials were provided in two categories: lower concentration ({approx} (101-104) /L in aqueous solution containing human RNA background) and high concentration ({approx} 109 /L in aqueous solution without any other RNA background). For the measurement of N gene concentration in the lower concentration study materials, the majority of laboratories (n = 17) used one-step reverse transcription-digital PCR (RT-dPCR), with three laboratories applying two-step RT-dPCR and one laboratory RT-qPCR. Sixteen laboratories submitted results for E gene concentration. Reproducibility (% CV or equivalent) for RT-dPCR ranged from 19 % to 31 %. Measurements of the high concentration study material by orthogonal methods (isotope dilution-mass spectrometry and single molecule flow cytometry) and a gravimetrically linked lower concentration material were in a good agreement, suggesting a lack of overall bias in RT-dPCR measurements. However methodological factors such as primer and probe (assay) sequences, RT-dPCR reagents and dPCR partition volume were found to be potential sources of interlaboratory variation which need to be controlled when applying this technique. This study demonstrates that the accuracy of RT-dPCR is fit-for-purpose as a RMP for viral RNA target quantification in purified RNA materials and highlights where metrological approaches such as the use of in vitro transcribed controls, orthogonal methods and measurement uncertainty evaluation can support standardization of molecular methods.

molecular biology↗

bioRxiv2023

Deconer: A comprehensive and systematic evaluation toolkit for reference-based cell type deconvolution algorithms using gene expression data

In recent years, computational methods for quantifying cell type proportions from transcription data have gained significant attention, particularly those reference-based methods which have demonstrated high accuracy. However, there is currently a lack of comprehensive evaluation and guidance for available reference-based deconvolution methods in cell proportion deconvolution analysis. In this study, we propose a comprehensive evaluation toolkit, called Deconer, specifically designed for reference-based deconvolution methods. Deconer provides various simulated and real gene expression datasets, including both bulk and single-cell sequencing data, and offers multiple visualization interfaces. By utilizing Deconer, we conducted systematic comparisons of 14 reference-based deconvolution methods from different perspectives, including method robustness, accuracy in deconvolving rare components, signature gene selection, and building external reference. We also performed an in-depth analysis of the application scenarios and challenges in cell proportion deconvolution methods. Finally, we provided constructive suggestions for users in selecting and developing cell proportion deconvolution algorithms. This work presents novel insights to researchers, assisting them in choosing appropriate toolkits, applying solutions in clinical contexts, and advancing the development of deconvolution tools tailored to gene expression data.

bioinformatics↗

bioRxiv2023

stGCL: A versatile cross-modality fusion method based on multi-modal graph contrastive learning for spatial transcriptomics

Advances in spatial transcriptomics (ST) technologies have provided unprecedented opportunities to depict transcriptomic and histological landscapes in the spatial context. Multi-modal ST data provide abundant and comprehensive information about cellular status, function, and organization. However, in dealing with the processing and analysis of spatial transcriptomics data, existing algorithms struggle to effectively fuse the multi-modal information contained within ST data. Here, we propose a graph contrastive learning-based cross-modality fusion model named stGCL for accurate and robust integrating gene expression, spatial information as well as histological profiles simultaneously. stGCL adopts a novel histology-based Vision Transformer (H-ViT) method to effectively encode histological features and combines multi-modal graph attention auto-encoder (GATE) with contrastive learning to fuse cross-modality features. In addition, stGCL introduces a pioneering spatial coordinate correcting and registering strategy for tissue slices integration, which can reduce batch effects and identify cross-sectional domains precisely. Compared with state-of-the-art methods on spatial transcriptomics data across platforms and resolutions, stGCL achieves a superior clustering performance and is more robust in unraveling spatial patterns of biological significance. Additionally, stGCL successfully reconstructed three-dimensional (3D) brain tissue structures by integrating vertical and horizontal slices respectively. Application of stGCL in human bronchiolar adenoma (BA) data reveals intratumor spatial heterogeneity and identifies candidate gene biomarkers. In summary, stGCL enables the fusion of various spatial modality data and is a powerful tool for analytical tasks such as spatial domain identification and multi-slice integration.

bioinformatics↗

bioRxiv2023

Nitrite deteriorates bioreactor performance by reducing growth of Ca. Brocadia sapporoensis instead of inhibiting the anammox activity

Effects of nitrite on anammox activities have been of widespread concern. However, the molecular mechanisms of specific microorganisms in anammox systems responding to nitrite remain unexplored. This study investigated the effects of excess nitrite on core metabolism of AnAOB and symbiotic bacteria, and further elucidated the response mechanism of these effects on microbial growth and nitrogen removal performance. Specifically, nitrogen removal process in a continuous-flow anaerobic ammonia oxidation membrane bioreactor completely collapsed when the nitrite concentration reached 243 mg N/L. Integrated meta-omics analyses demonstrated that excess nitrite disrupted the energy metabolism of Ca. Brocadia sapporoensis (AMXB1), reducing the energy available for establishing tolerance. It disrupted cell replication by impairing biosynthesis process of AMXB1, especially DNA replication and the formation of vital cell structures, e.g., cell membrane and cell wall, as well as the cellular protection system, leading to the collapse of the anammox system. In addition, the cross-feeding of glycogen, lipopolysaccharide and amino acid between AMXB1 and symbiotic bacteria was hindered by excess nitrite, which also contributed to the anomalous cell proliferation and metabolism of AMXB1. These findings contribute to our understanding of the ability of anammox consortia to respond to nitrite stress and process stability in engineered ecosystems. HighlightsO_LINO --N concentration of 243 mg N/L caused the performance collapse of a continuous-flow anammox MBR. C_LIO_LIExcess nitrite likely disrupted the energy metabolism of AMXB1, reducing the energy availability for mitigating nitrite toxicity. C_LIO_LIThe cross-feeding between AMXB1 and symbiotic bacteria was hindered by excess nitrite. C_LIO_LIThe hindrance of cross-feeding was reversed as the concentration of nitrite decreased. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/568540v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@6b199forg.highwire.dtl.DTLVardef@15f2a74org.highwire.dtl.DTLVardef@dc2d8eorg.highwire.dtl.DTLVardef@132deb1_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2023

Unravelling Biosynthesis and Biodegradation Potentials of Microbial Dark Matters in Hypersaline Lakes

Biosynthesis and biodegradation of microorganisms critically underpin the development of biotechnology, new drugs and therapies, and environmental remediation. However, the vast majority of uncultured microbial species along with their metabolic capacities in extreme environments remain obscured. To unravel the metabolic potentials of these microbial dark matters (MDMs), we investigated four deep-inland hypersaline lakes with largely diversified environmental parameters in Xinjiang Uygur Zizhiqu, China. Metagenomic binning obtained 3,030 metagenome-assembled genomes (MAGs) spanning 82 phyla, of which 2,363 MAGs could not be assigned to a known genus. These unknown MAGs were abundantly observed with distinct taxa among lakes, possibly linked to the diversification of physiochemical conditions. Analysis of biosynthetic potentials identified 9,635 biosynthesis gene clusters (BGCs), of which 9,403 BGCs were considered novel. We found that some MAGs from putatively novel phyla consistently comprised enriched BGCs, which may have substantial potentials in biotechnological applications. In addition, biodegradation potentials such as dehalogenation, anaerobic ammonium oxidation (Anammox), polycyclic aromatic hydrocarbon (PAH), and plastic degradation were found in new microbial clades from hypersaline lakes. These findings substantially expanded the genetic repository of biosynthesis and biodegradation potentials, which can further assist the development of new and innovative applications in biotechnology.

microbiology↗

bioRxiv2022

Dalpiciclib Partially Abrogates ER Signaling Activation Induced by Pyrotinib In HER2+HR+ Breast Cancer

BackgroundRecent evidences from clinical trials (NCT04486911) revealed that the combination of pyrotinib, letrozole and dalpiciclib exerted optimistic therapeutic effect to treat HER2+HR+ breast cancer, however, the underlying molecular mechanism remained further investigation. MethodsThrough the drug sensitivity test, the drug combination efficacy of pyrotinib, tamoxifen and dalpiciclib to BT474 cells were tested. The underlying molecular mechanisms were investigated using immunofluorescence, western blot analysis, immunohistochemical staining and cell cycle analysis. Potential risk factor which may indicate the responsiveness to drug treatment in HER2+/HR+ breast cancer was selected out using RNA-sequence and tested using immunohistochemical staining and in vivo drug susceptibility test. ResultsWe found that pyrotinib combined with dalpiciclib exerted better cytotoxic efficacy than pyrotinib combined with tamoxifen in BT474 cells. Degradation of HER2 could enhance ER nuclear transportation, activating ER signaling pathway in BT474 cells whereas dalpiciclib could partially abrogate this process. This may be the underlying mechanism by which combination of pyrotinib, tamoxifen and dalpiciclib exerted best cytotoxic effect. Furthermore, CALML5 was revealed to be a risk factor in the treatment of HER2+/HR+ breast cancer and the usage of dalpiciclib might overcome this. ConclusionOur study provided evidence that the usage of dalpiciclib in the treatment of HER2+/HR+ breast cancer could partially abrogate the estrogen signaling pathway activation caused by anti-HER2 therapy and revealed that CALML5 could serve as a risk factor in the treatment of HER2+/HR+ breast cancer. FundingThis study was supported by the National Natural Science Foundation of China (#U20A20381, #81872159)

cancer biology↗

bioRxiv2022

Latitude influences stability via stabilizing mechanisms in naturally-assembled forest ecosystems at different spatial grains

Ecosystem stability reveals how ecosystems respond to global change over time. Yet, the focus of past research on small spatial grains and extents overlooks scale dependence and how broad-scale environmental gradients shape stability. Here, we use forest inventory data covering a broad latitudinal gradient from the temperate to the tropical zone to examine cross-scale variation in stability of aboveground biomass and underlying stabilizing mechanisms. While stability did not shift systematically with latitude at either spatial grain, we found evidence that species asynchrony increased towards the tropics at the small spatial grain while species stability decreased at both spatial grains. Moreover, latitude stabilized forest communities via its effects on both stabilizing mechanisms, which compensated for the weak and destabilizing effects of species richness. Yet, the trade-off in the relative importance of species stability and species asynchrony for stability was not mediated by latitude, suggesting that context-dependent factors - to a greater extent than macroecological ones - underlie large-scale patterns of stability. Our results highlight the crucial role of species asynchrony and species stability in determining ecosystem stability across broad-scale environmental gradients, suggesting that conserving biodiversity alone may not be sufficient for stabilizing naturally-assembled forest ecosystems.

ecology↗

bioRxiv2022

Conventional dendritic cells 2, the targeted antigen-presenting-cell, induces enhanced type 1 immune responses in mice immunized with CVC1302 in oil formulation

Multifunctional CD4+ T helper 1 (Th1) cells, producing IFN-{gamma}, TNF- and IL-2, define a correlate of vaccine-mediated protection against intracellular infection. In our previous study, we found that CVC1302 in oil formulation promoted the differentiation of IFN-{gamma}+/TNF-+/IL-2+ Th1 cells. In order to extend the application of CVC1302 in oil formulation, this study aimed to elucidate the mechanism of action in improving the Th1 immune response. Considering the signals required for the differentiation of CD4+ T cells to Th1 cells, we detected the distribution of innate immune cells and the model antigen OVA-FITC in lymph node (LN), as well as the quantity of cytokines produced by the innate immune cells. The results of these experiments show that, cDC2 and OVA-FITC localized to inter-follicular region (IFR) of the draining lymph nodes, inflammatory monocytes localized to both IFR and T cell zone, which mainly infiltrate from the blood. In this inflammatory niche within LN, CD4+ T cells were attracted into IFR by CXCL10, secreting by inflammatory monocytes, then activated by IL-12-secreting cDC2. Above all, CVC1302 in oil formulation, on the one hand, targeted antigen and inflammatory monocyte into the LN IFN in order to attract CD4+ T cells, on the other hand, targeted cDC2 to produce IL-12 in order to promote optimal Th1 differentiation. The new finding will provide a blueprint for application of immunopotentiators in optimal formulations. ImportanceAlong with the development of veterinary immunology, immunopotentiator and delivery system were not simply mixed with antigen, more and more attentions paid on the optimal compatibility in order to induce multifunctional immune responses. As reported, LPS formulated in IFA targeted antigens to the IFR of the LN, and recruited Mo into the IFR, then attracted antigen-specific CD4+ T cells, which differentiated into Th1 cells under the IL-12 produced by DC-SIGN+ DC(1). Herein, we further found that CVC1302 formulated with Marcol 52 induced enhanced Th1 immunity. Combined with our previous finding that CVC1302 in oil formulation induced improved humoral immunity, we concluded that CVC1302 in oil formulation provided multifunctional immunity, not only higher antibody titers to prevent pathogen infection, but also cellular immunity cytokine to prevent viral shedding.

immunology↗

bioRxiv2022

Diversity and biogeography of plant leaf bacteria along a latitudinal gradient

Plant-associated microbes are essential for promoting plant well-being, maintaining biodiversity, and supporting ecosystem function. However, little is known about the geographic distribution of plant-microbe symbioses and how they are formed and change along latitudinal gradients. Here we identified leaf bacteria for 328 plant species sampled from 10 forests along a tropical to temperate gradient in China. We analyzed the diversity and composition of plant leaf-associated bacteria and quantified the contributions of hosts, habitats, and neighborhood plants to the plant-bacterial symbiosis. We found a strong latitudinal gradient in leaf bacterial diversity and composition. Bacterial assemblages on leaves were most strongly selected by host plants, and the selection pressure increased with latitude. In contrast, at low latitudes and at large geographical scales multiple factors were found to jointly regulate bacterial community composition. Our result also showed that plant-bacteria symbiotic networks were structured by network hub bacteria taxa with high co-occurrence network centrality, and the abundance of temperate hub taxa was more influenced by host plants than that in tropical forests. For the first time, we documented a previously unrecognized latitudinal gradient in plant-bacterial symbioses that was regulated by a joint effect of multiple factors at low latitudes but mostly by host selection at high latitudes, implying that leaf microbiomes are likely to respond differently to global change along the latitudinal gradient.

ecology↗

bioRxiv2022

Pharmacological PP2A reactivation overcomes multikinase inhibitor tolerance across brain tumor cell models

BackgroundGlioblastoma is characterized by hyperactivation of kinase signaling pathways. Regardless, most glioblastoma clinical trials targeting kinase signaling have failed. We hypothesized that overcoming the glioblastoma kinase inhibitor tolerance requires efficient shut-down of phosphorylation-dependent signaling rewiring by simultaneous inhibition of multiple critical kinases combined with reactivation of Protein Phosphatase 2A (PP2A). MethodsLive-cell imaging and colony growth assays were used to determine long-term impact of therapy effects on ten brain tumor cell models. Immunoblotting, MS-phosphoproteomics, and Seahorse metabolic assay were used for analysis of therapy-induced signaling rewiring. BH3 profiling was used to understand the mitochondrial apoptosis mechanisms. Medulloblastoma models were used to expand the importance to other brain cancer. Intracranial xenografts were used to validate the in vivo therapeutic impact of the triplet therapy. ResultsCollectively all tested ten glioblastoma and medulloblastoma cell models were effectively eradicated by the newly discovered triplet therapy combining inhibition of AKT and PDK1-4 kinases with pharmacological PP2A reactivation. Mechanistically, the brain tumor cell selective lethality of the triplet therapy could be explained by its combinatorial effects on therapy-induced signaling rewiring, OXPHOS, and apoptosis priming. The brain-penetrant triplet combination had a significant in vivo efficacy in intracranial glioblastoma and medulloblastoma models. ConclusionThe results confirm highly heterogenous responses of brain cancer cells to mono - and doublet combination therapies targeting phosphorylation-dependent signaling. However, the brain cancer cells cannot escape the triplet therapy targeting of AKT, PDK1-4, and PP2A. The results encourage evaluation of brain tumor PP2A status for design of future kinase inhibitor combination trials. Key PointsO_LIDevelopment of triplet kinase-phosphatase targeting therapy strategy for overcoming therapy tolerance across brain tumor models. C_LIO_LIIdentification of interplay between therapy-induced signaling rewiring, OXPHOS, and BH3 protein-mediated apoptosis priming as a cause for kinase inhibitor tolerance in brain cancers. C_LIO_LIValidation of the results in intracranial in vivo models with orally bioavailable and brain penetrant triplet therapy combination. C_LI Importance of the StudyBased on current genetic knowledge, glioblastoma should be particularly suitable target for kinase inhibitor therapies, However, in glioblastoma alone over 180 clinical trials with kinase inhibitors have failed. In this manuscript, we recapitulate this clinical observation by demonstrating broad tolerance of brain cancer cell models to kinase inhibitors even when combined with reactivation of PP2A. However, we discover that the therapy-induced signaling rewiring, and therapy tolerance, can be overcome by triplet targeting of AKT, PDK1-4 and PP2A. We provide strong evidence for the translatability of the findings by orally dosed brain penetrant triplet therapy combination in intracranial brain cancer models. The results encourage biomarker profiling of brain tumors for their PP2A status for clinical trials with combination of AKT and PDK1-4 inhibitors. Further, the results indicate that rapidly developing PP2A reactivation therapies will constitute an attractive future therapy option for brain tumors when combined with multi-kinase inhibition.

cancer biology↗

bioRxiv2022

Triplet kinase-phosphatase targeting to overcome kinase inhibitor tolerance in brain tumor cells

Therapeutic resistance to kinase inhibitors constitutes a major unresolved clinical challenge in cancer and especially in glioblastoma. Multi-kinase inhibitors may be used for simultaneous targeting of multiple target kinase and thereby potentially overcome kinase inhibitor resistance. However, in most cases identification of the target kinases mediating therapeutic effects of multi-kinase inhibitors has been challenging. To tackle this important problem, we developed an Actionable Targets of Multi-kinase Inhibitors (AToMI) strategy and used it for characterization of glioblastoma target kinases of staurosporine derivatives displaying synergy with protein phosphatase 2A (PP2A) reactivation. AToMI consists of interchangeable modules combining drug-kinase interaction assay, siRNA high-throughput screening, bioinformatics analysis and validation screening with more selective target kinase inhibitors. As a result, AToMI analysis revealed AKT and mitochondrial pyruvate dehydrogenase kinase PDK1 and PDK4 as kinase targets of staurosporine derivatives UCN-01, CEP-701, and K252a that synergized with PP2A activation across heterogeneous glioblastoma cells. Based on these proof-of-principle results we propose that application and further development of AToMI for clinically applicable multi-kinase inhibitors could provide significant benefits in overcoming the challenge of lack of knowledge of target specificity of multi-kinase inhibitors.

cancer biology↗

bioRxiv2021

pGlycoQuant with a deep residual network for precise and minuscule-missing-value quantitative glycoproteomics enabling the functional exploration of site-specific glycosylation

Interpreting large-scale glycoproteomic data for intact glycopeptide identification has been tremendously advanced by software tools. However, software tools for quantitative analysis of intact glycopeptides remain lagging behind, which greatly hinders exploring the differential expression and functions of site-specific glycosylation in organisms. Here, we report pGlycoQuant, a generic software tool for accurate and convenient quantitative intact glycopeptide analysis, supporting both primary and tandem mass spectrometry quantitation for multiple quantitative strategies. pGlycoQuant enables intact glycopeptide quantitation with very low missing values via a deep residual network, thus greatly expanding the quantitative function of several powerful search engines, currently including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. The pGlycoQuant-based site-specific N-glycoproteomic study conducted here quantifies 6435 intact N-glycopeptides in three hepatocellular carcinoma cell lines with different metastatic potentials and, together with in vitro molecular biology experiments, illustrates core fucosylation at site 979 of the L1 cell adhesion molecule (L1CAM) as a potential regulator of HCC metastasis. pGlycoQuant is freely available at https://github.com/expellir-arma/pGlycoQuant/releases/. We have demonstrated pGlycoQuant to be a powerful tool for the quantitative analysis of site-specific glycosylation and the exploration of potential glycosylation-related biomarker candidates, and we expect further applications in glycoproteomic studies.

systems biology↗

bioRxiv2021

Scaling between DNA and cell size governs bacterial growth homeostasis and resource allocation

Bacteria maintain a stable cell size and a certain DNA content through proliferation as described by classic growth laws. How cells behave when this inherent scaling is broken, however, has rarely been interrogated. Here we engineered Escherichia coli cells with extremely low DNA contents using a tunable synthetic tool CRISPRori that temporarily inhibited chromosome replication initiation. A detailed mechanistic model coupling DNA replication, cell growth, and division revealed a fundamental DNA-centric growth law, which was validated by two observations. First, lineage dynamics were robust to large CRISPRori perturbations with division cycles rapidly restoring through a timer mechanism rather than the adder rule. Second, cellular growth transitioned into a linear regime at low DNA-cytoplasm ratios. Experiments and theory showed that in this regime, cellular resource was redirected to plasmid-borne gene expression. Together with the ability of CRISPRori to bi-directionally modulate plasmid copy numbers, these findings suggest a novel strategy for bio-production enhancement.

systems biology↗

bioRxiv2021

Nicotinic modulation insecticides act on diverse receptor subtypes with distinct subunit compositions

Insect nicotinic acetylcholine receptors (nAChRs) are ligand gated ion channels mainly expressed in the central nervous system of insects. They are the directed targets of nicotinic modulation insecticides including neonicotinoids, the most widely used insecticides in the world. However, the resistance development from pests and the negative impacts on the pollinators affect their applications and create demand for the alternatives. Thus, it is very important to understand the mode of action of these insecticides at the molecular level, which is actually unclear for more than 30 years. In this study, we systematically examined the susceptibility of ten Drosophila melanogaster nAChR subunits mutants against eleven nicotinic modulation insecticides. Our results showed that there are several subtypes of nAChRs with distinct subunits compositions that are responsible for the toxicity of different insecticides, respectively. At least three of them are the major molecular targets of seven structurally similar neonicotinoids in vivo. On the other hand, the spinosyns may exclusively act on the 6 homomeric nAChR but not any other heteromeric pentamers. Behavioral assays using thermogenetic tools further confirmed the bioassay results and support the idea that receptor activation rather than inhibition leads to the insecticidal effects of neonicotinoids. The present findings reveal native nAChR subunit interactions with various insecticides and have important implications for resistance management and the development of novel insecticides targeting this important ion channels. Author SummaryThe neonicotinoids and spinosyns make up about 27% of the insecticides by world market value. Novel insecticides like sulfoxaflor, flupyradifurone and triflumezopyrim are developed as alternatives due to the negative effects of neonicotinoids on pollinators. Although all act via insect nicotinic acetylcholine receptors, the mode of action is unclear. Our work shows that these insecticides act on diverse receptor subtypes with distinct subunit compositions. This finding could lead to the development of more selective insecticides to control pests with minimal effects on beneficial insects.

genetics↗