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Biology subjects

Gao, Q.

Publications and source records attributed to Gao, Q..

At least 55 records · Page 3Linked to original sources

Mechanistic Studies of Small Molecule Ligands Selective to RNA Single G Bulges

Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated Molecular Dynamics (GaMD) simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity-relationship (SAR) studies and transverse relaxation measurements by NMR spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Strikingly, small structure perturbations on these key contributors, such as the addition of a methyl group that disrupts the planarity of the ligand resulted in > 100-fold reduction in the binding affinity. Our work deepened the understanding of RNA-small molecule interactions and integrated a new generalizable platform for the rational design of selective small-molecule RNA binders.

biochemistry↗

Somatic mutation phasing and haplotype extension using linked-reads in multiple myeloma

Somatic mutation phasing informs our understanding of cancer-related events, like driver mutations. We generated linked-read whole genome sequencing data for 23 samples across disease stages from 14 multiple myeloma (MM) patients and systematically assigned somatic mutations to haplotypes using linked-reads. Here, we report the reconstructed cancer haplotypes and phase blocks from several MM samples and show how phase block length can be extended by integrating samples from the same individual. We also uncover phasing information in genes frequently mutated in MM, including DIS3, HIST1H1E, KRAS, NRAS, and TP53, phasing 79.4% of 20,705 high-confidence somatic mutations. In some cases, this enabled us to interpret clonal evolution models at higher resolution using pairs of phased somatic mutations. For example, our analysis of one patient suggested that two NRAS hotspot mutations occurred on the same haplotype but were independent events in different subclones. Given sufficient tumor purity and data quality, our framework illustrates how haplotype-aware analysis of somatic mutations in cancer can be beneficial for some cancer cases.

bioinformatics↗

Single-cell and spatial transcriptome characterize coinhibitory cell-cell communications during histological progression of lung adenocarcinoma

Lung adenocarcinoma, a prevalent and lethal malignancy globally, is characterized by significant tumor heterogeneity and a complex tumor immune microenvironment during its histologic pattern progression. Understanding the intricate interplay between tumor and immune cells is of paramount importance as it could potentially pave the way for the development of effective therapeutic strategies for lung adenocar-cinoma. In this study, we run comparative analysis of the single-cell transcriptomic data derived from tumor tissues exhibiting four distinct histologic patterns, lepidic, papillary, acinar and solid, in lung adeno-carcinoma. Our analysis unveiled several co-inhibitory receptor-ligand interactions, including PD1-PDL1, PVR-TIGIT and TIGIT-NECTIN2, that potentially exert a pivotal role in recruiting immunosuppressive cells such as M2 macrophages and Tregs into LUAD tumor, thereby establishing immunosuppressive microenvironment and inducing T cells to exhaustion state. Furthermore, The expression level of these co-inhibitory factors, such as NECTIN2 and PVR, were strongly correlated with low immune infiltration, unfavorable patient clinical outcomes and limited efficacy of immunotherapy. Furthermore, we conducted immunofluorescence assay and spatial transcriptomic sequencing to validated the spatial co-localization of typical co-inhibitory factors. We believe this study provides valuable insights into the heterogeneity of molecular, cellular interactions leading to immunosuppressive microenvironment during the histological progression of lung adenocarcinoma. The findings could facilitate the development of novel immunotherapy for lung cancer.

bioinformatics↗

Conserved mycobacterial sRNA B11 regulates lipooligosaccharide synthesis at post-transcriptional level

Extractable glycolipids of mycobacteria, such as lipooligosaccharides (LOS), play key roles in responding to environmental stress and altering the host immune response. However, although the biosynthesis of LOS is likely controlled at multiple levels to ensure proper composition of the cell wall, the key regulators are currently unknown. Here, we studied B11, a conserved mycobacterial sRNA, and found that it post-transcriptionally regulates LOS synthesis in Mycobacteria marinum. Deletion of B11 alters the colony morphology and RNA sequencing combined with mass spectrometry identified several genes in the LOS synthesis locus that are regulated by B11. We found that B11 uses the cytosine-rich loops of its rho-independent transcriptional terminator to interact with guanine-tracks adjacent to the ribosome binding sites of its target genes, thereby impeding translation and promoting mRNA degradation by RNase E. These comprehensive functional studies of mycobacterial sRNA B11 demonstrate sRNA-based regulation of cell wall synthesis in mycobacteria. ImportanceDespite being identified for more than a decade, the functional characterization and regulatory mechanisms of mycobacterial sRNAs remain largely unexplored. We present here the most comprehensive functional study of mycobacterial sRNAs to date, employing convincible target screening using multifaceted experimental approaches and phenotype analysis. Our work reveals how synthesis of mycobacterial lipooligosaccharides (LOS), one of the crucial extractable glycolipids involved in environmental stress response and host immune modulation, is regulated at the post-transcriptional level by the conserved sRNA B11. Furthermore, our discovery of a highly conserved sRNA exhibiting distinct functions across mycobacterial species exemplifies divergent functional evolution among sRNAs.

microbiology↗

Propiconazole and Tianfengsu Regulated the Growth, Flavor, and Nutrition of Brassica rapa by Brassinosteroid Pathway

Propiconazole (PCZ) and Tianfengsu (TFS) are widely used plant growth regulators in vegetable production for improving crop growth, quality, and flavor. This study investigated the effects of PCZ and TFS, applied individually or in combination, on the growth, development, flavor quality, and nutritional components of choy sum (Brassica rapa) and Arabidopsis thaliana, as well as the underlying molecular mechanisms. The results showed that PCZ inhibited the growth of choy sum and Arabidopsis but enhanced the accumulation of flavor compounds such as soluble sugars, proteins, and vitamin C. In contrast, TFS promoted plant growth and increased the content of nutritional components, including chlorophyll and unsaturated fatty acids. Notably, the combined application of PCZ and TFS significantly improved overall plant quality, achieving the optimal balance of flavor and nutritional value while maintaining high yield. Transcriptomic analysis revealed the molecular mechanisms of PCZ and TFS in differentially regulating the expression of brassinosteroid (BR) signaling and downstream metabolism-related genes. Weighted gene co-expression network analysis (WGCNA) further identified key gene modules and hub genes controlling flavor metabolism in choy sum. This study elucidates the synergistic mechanisms of PCZ and TFS in regulating vegetable growth and quality formation, providing valuable insights for the safe production of high-quality choy sum and the development of novel plant growth regulators or elite varieties. HIGHLIGHTSO_LIPCZ and TFS treatments differentially modulate choy sum growth and development by regulating the BR pathway, with PCZ inhibiting while TFS promoting growth. C_LIO_LIPCZ enhances the accumulation of soluble sugars, soluble proteins, and vitamin C, while TFS increases photosynthetic pigments and unsaturated fatty acids, synergistically improving the flavor and nutritional quality of choy sum. C_LIO_LITranscriptomic analysis and WGCNA uncover key genes and modules controlling flavor metabolism in choy sum, providing potential targets for developing novel plant growth regulators or breeding elite varieties C_LI

plant biology↗

Histone variant H2BE enhances chromatin accessibility in neurons to promote synaptic gene expression and long-term memory

Regulation of histone proteins affects gene expression through multiple mechanisms including exchange with histone variants. However, widely expressed variants of H2B remain elusive. Recent findings link histone variants to neurological disorders, yet few are well studied in the brain. We applied new tools including novel antibodies, biochemical assays, and sequencing approaches to reveal broad expression of the H2B variant H2BE, and defined its role in regulating chromatin structure, neuronal transcription, and mouse behavior. We find that H2BE is enriched at promoters and a single unique amino acid allows it to dramatically enhance chromatin accessibility. Lastly, we show that H2BE is critical for synaptic gene expression and long-term memory. Together, these data reveal a novel mechanism linking histone variants to chromatin regulation, neuronal function, and memory. This work further identifies the first widely expressed H2B variant and uncovers a single histone amino acid with profound effects on genomic structure.

genetics↗

Precise single-cell transcriptomic mapping of normal and leukemic cell states reveals unconventional lineage priming in acute myeloid leukemia

In acute myeloid leukemia (AML), genetic mutations distort hematopoietic differentiation, resulting in the accumulation of leukemic blasts. Yet, it remains unclear how these mutations intersect with cellular origins and whether they converge upon similar differentiation patterns. Single-cell RNA sequencing (scRNA-seq) has enabled high-resolution mapping of the relationship between leukemia and normal cell states, yet this application is hampered by imprecise reference maps of normal hematopoiesis and small sample sizes among patient cohorts. As a first step we constructed a reference atlas of human bone marrow hematopoiesis from 263,519 single-cell transcriptomes spanning 55 cellular states, that was benchmarked against independent datasets of immunophenotypically pure hematopoietic stem and progenitor cells. Using this reference atlas, we mapped over 1.2 million single-cell transcriptomes spanning 318 AML, mixed phenotype acute leukemia (MPAL), and acute erythroid leukemia (AEL) samples. This large-scale analysis, together with systematic mapping of genotype-to-phenotype associations between driver mutations and differentiation landscapes, revealed convergence of diverse genetic alterations on twelve recurrent patterns of aberrant differentiation in AML. This included unconventional lymphoid and erythroid priming linked to RUNX1 and TP53 mutations, respectively. We also identified non-genetic determinants of AML differentiation such as two subgroups of KMT2A-rearranged AML that differ in the identity of their leukemic stem cells (LSCs), likely reflecting distinct cellular origins. Furthermore, distinct LSC-driven hierarchies can co-exist within individual patients, providing insights into AML evolution. Together, precise mapping of normal and malignant cell states provides a framework for advancing the study and disease classification of hematologic malignancies thereby informing therapy development.

cancer biology↗

Single cell dissection of developmental origins and transcriptional heterogeneity in B-cell acute lymphoblastic leukemia

Sequencing of bulk tumor populations has improved genetic classification and risk assessment of B-ALL, but does not directly examine intratumor heterogeneity or infer leukemia cellular origins. We profiled 89 B-ALL samples by single-cell RNA-seq (scRNA-seq) and compared them to a reference map of normal human B-cell development established using both functional and molecular assays. Intra-sample heterogeneity was driven by cell cycle, metabolism, differentiation, and inflammation transcriptional programs. By inference of B lineage developmental state composition, nearly all samples possessed a high abundance of pro-B cells, with variation between samples mainly driven by sub-populations. However, ZNF384-r and DUX4- r B-ALL showed composition enrichment of hematopoietic stem cells, BCR::ABL1 and KMT2A-r ALL of Early Lymphoid progenitors, MEF2D-r and TCF3::PBX1 of Pre-B cells. Enrichment of Early Lymphoid progenitors correlated with high-risk clinical features. Understanding variation in transcriptional programs and developmental states of B-ALL by scRNA-seq refines existing clinical and genomic classifications and improves prediction of treatment outcome.

cancer biology↗

Distinct functions of the kinesin-9 family in mammalian motile cilia

Ciliary beat and intraflagellar transport (IFT) depend on dynein and kinesin motors. Kinesin-9 family members Kif6 and Kif9 are implicated in ciliary motilities across protists and mammals. How they function and whether they act redundantly, however, remain unclear. Here, we show that they play distinct roles in mammals. Kif6 forms puncta that move bidirectionally without or with IFT-B particles along axonemes, whereas Kif9 is immobilized on ciliary central apparatus. Only Kif6 binds to and glides microtubules, and the activities are self-inhibited. Kif6 deficiency in mice impairs directional ciliary beat across ependymal tissues and cerebrospinal fluid flow, resulting in severe hydrocephalus and high mortality, whereas Kif9 deficiency induces mild hydrocephalus without obviously defective ciliary beat and life span. Both Kif6-/- and Kif9-/- males are infertile but show respectively oligozoospermia with poor sperm motility and defective forward motion of sperms. These results suggest Kif6 as a motile cilia-specific IFT motor and Kif9 as a central apparatus regulator.

cell biology↗

Genetically encoded transcriptional plasticity underlies stress adaptation in Mycobacterium tuberculosis

Transcriptional regulation is a critical adaptive mechanism that allows bacteria to respond to changing environments, yet the concept of transcriptional plasticity (TP) remains largely unexplored. In this study, we investigate the genome-wide TP profiles of Mycobacterium tuberculosis (Mtb) genes by analyzing 894 RNA sequencing samples derived from 73 different environmental conditions. Our data reveal that Mtb genes exhibit significant TP variation that correlates with gene function and gene essentiality. We also found that critical genetic features, such as gene length, GC content, and operon size independently impose constraints on TP, beyond trans-regulation. By extending our analysis to include two other Mycobacterium species -- M. smegmatis and M. abscessus -- we demonstrate a striking conservation of the TP landscape. This study provides a comprehensive understanding of the TP exhibited by mycobacteria genes, shedding light on this significant, yet understudied, genetic feature encoded in bacterial genomes.

microbiology↗

SifiNet: A robust and accurate method to identify feature gene sets and annotate cells

SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multiomic cellular profiles. It is conveniently available as an open-source R package.

bioinformatics↗

Discovery of new deaminase functions by structure-based protein clustering

The elucidation of protein function and its exploitation in bioengineering have greatly contributed to the development of the life sciences. Existing protein mining efforts generally rely on amino acid sequences rather than protein structures due to technical difficulties in structural elucidation. We describe here for the use of AlphaFold2 to predict and subsequently cluster an entire protein family based on predicted structure similarities. We selected the deaminase family of proteins to analyze and through this approach identified many previously unknown deaminase properties. We applied these new deaminases to the development of new cytosine base editors with distinct features. Although we found many new double-stranded DNA deaminases from the DddA-like protein clade, we were surprised to find that most of the proteins in this family were not actually double-stranded DNA cytidine deaminases. From this protein clade, we engineered the smallest single-strand specific cytidine deaminase, which facilitates the first efficient cytosine base editor to be packaged into a single AAV vector. Importantly, we also profiled a deaminase from this clade that edits robustly in soybean plants, which previously suffered from poor editing by cytosine base editors. These newly discovered deaminases based on AI-assisted structural predictions greatly expand the utility of base editors for therapeutic and agricultural applications.

molecular biology↗

Protein language model-based end-to-end type II polyketide prediction without sequence alignment

Natural products are important sources for drug development, and the precise prediction of their structures assembled by modular proteins is an area of great interest. In this study, we introduce DeepT2, an end-to-end, cost-effective, and accurate machine learning platform to accelerate the identification of type II polyketides (T2PKs), which represent a significant portion of the natural product world. Our algorithm is based on advanced natural language processing models and utilizes the core biosynthetic enzyme, chain length factor (CLF or KS{beta}), as computing inputs. The process involves sequence embedding, data labeling, classifier development, and novelty detection, which enable precise classification and prediction directly from KS{beta} without sequence alignments. Combined with metagenomics and metabolomics, we evaluated the ability of DeepT2 and found this model could easily detect and classify KS{beta} either as a single sequence or a mixture of bacterial genomes, and subsequently identify the corresponding T2PKs in a labeled categorized class or as novel. Our work highlights deep learning as a promising framework for genome mining and therefore provides a meaningful platform for discovering medically important natural products.

evolutionary biology↗

A burns and COVID-19 shared stress responding gene network deciphers CD1C-CD141- DCs as the key cellular components in septic prognosis

Differential body responses to various stresses, infectious or noninfectious, govern clinical outcomes ranging from asymptoma to death. However, the common molecular and cellular nature of the stress responsome across different stimuli is not described. In this study, we compared the expression behaviors between burns and COVID-19 infection by choosing the transcriptome of peripheral blood from related patients as the analytic target since the blood cells reflect the systemic landscape of immune homeostasis. We identified an immune co-stimulator (CD86)-centered network, named stress-response core (SRC), which coordinated multiple immune processes and was robust in membership and highly related to the clinical traits in both burns and COVID-19. An independent whole blood single-cell RNA sequencing of COVID-19 patients demonstrated that the monocyte-dendritic cell (Mono-DC) wing was the major cellular source of the SRC, among which the higher expression of the SRC in the monocyte was associated with the asymptomatic COVID-19 patients, while the quantity-restricted and function-defected CD1C-CD141-DCs were recognized as the key signature which linked to bad consequences in COVID-19. Specifically, the proportion of the CD1C-CD141-DCs and their SRC expression levels were step-wise reduced along with worse clinic conditions while the sub-cluster of CD1C-CD141-DCs of the critical COVID-19 patients was characterized of IFN signaling quiescence, high mitochondrial metabolism and immune-communication inactivation. Thus, our study identified an expression-synchronized and function-focused gene network which was decreased under burns and COVID-19 stress and argued the CD1C-CD141-DC as the prognosis-related cell population which might serve as a new target of diagnosis and therapy.

immunology↗

Deep learning prediction boosts phosphoproteomics-based discoveries through improved phosphopeptide identification

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples, but low phosphopeptide identification rate in data analysis limits the potential of this technology. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19%-46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

bioinformatics↗

The mutational signatures of poor treatment outcomes on the drug-susceptible Mycobacterium tuberculosis genome

Drug resistance is a known risk factor for poor tuberculosis (TB) treatment outcomes, but the contribution of other bacterial factors to poor outcomes in drug susceptible TB is less understood. Here, we generate a population-based dataset of drug-susceptible Mycobacterium tuberculosis (MTB) isolates from China to identify factors associated with poor treatment outcomes. We sequenced the whole genome of 3496 MTB strains and linked genomes to patient epidemiological data. A genome-wide association study (GWAS) was performed to identify bacterial genomic variants associated with poor outcomes. Risk factors identified by logistic regression analysis were used in clinical models to predict treatment outcomes and their associations were assessed with structural equation models (SEM). GWAS identified fourteen MTB variants (24.2% vs 7.5%, P<0.001) and a de novo reactive oxygen species (ROS) mutational signature (26.3%{+/-}18.2% vs 22.9%{+/-}13.8%, P=0.027) that were more frequent in patients with poor treatment outcomes. Patient age, sex, and duration of diagnostic delay were also independently associated with poor outcomes. The best clinical prediction model, with an AUC of 0.74, incorporates both host and bacterial risk factors, and host factors are more important. Together, our results reveal that although host factors are the most important determinants for poor treatment outcomes, the genomic characteristics of the infecting MTB strain may also contribute significantly to poor treatment outcomes. Fourteen genetic variants were statistically associated with poor TB treatment outcomes, but the optimal model for predicting treatment outcomes includes both patient characteristics and bacterial genomic determinants.

genomics↗

COMBINATION THERAPIES TARGETING ALK-ABERRANT NEUROBLASTOMA IN PRECLINICAL MODELS.

BackgroundALK activating mutations are identified in approximately 10% of newly diagnosed neuroblastomas and ALK amplifications in a further 1-2% of cases. Lorlatinib, a third generation ALK inhibitor, will soon be given alongside induction chemotherapy for children with ALK-aberrant neuroblastoma. However, resistance to single agent treatment has been reported and therapies that improve the response duration are urgently required. We studied the preclinical combination of lorlatinib with chemotherapy, or with the MDM2 inhibitor, idasanutlin, as recent data has suggested that ALK inhibitor resistance can be overcome through activation of the p53-MDM2 pathway. AimsTo study the preclinical activity of ALK inhibitors alone and in combination with chemotherapy or idasanutlin. MethodsWe compared different ALK inhibitors in preclinical models prior to evaluating lorlatinib in combination with chemotherapy or idasanutlin. We developed a triple chemotherapy (CAV: cyclophosphamide, doxorubicin and vincristine) in vivo dosing schedule and applied this to both neuroblastoma genetically engineered mouse models (GEMM) and patient derived xenografts (PDX). ResultsLorlatinib in combination with chemotherapy was synergistic in immunocompetent neuroblastoma GEMM. Significant growth inhibition in response to lorlatinib was only observed in the ALK-amplified PDX model with the highest ALK expression. In this PDX lorlatinib combined with idasanutlin resulted in complete tumor regression and significantly delayed tumor regrowth. ConclusionOur study suggests that in neuroblastoma, high ALK expression could be associated with response to lorlatinib and either chemotherapy or idasanutlin. The synergy between MDM2 inhibition and ALK inhibition warrants further evaluation of this combination as a potential clinical approach for children with neuroblastoma. STATEMENT OF TRANSLATIONAL RELEVANCENeuroblastoma is a pediatric tumor of the developing sympathetic nervous system. Around 50% of high-risk neuroblastoma patients are curable. Mutations or amplification of Anaplastic Lymphoma Kinase (ALK) have emerged as a marker with which to further risk-stratify patients. The ALK inhibitor lorlatinib will soon be used alongside chemotherapy in upfront treatment of high-risk patients with ALK-aberrant disease. In this preclinical study, we used a panel of ALK aberrant neuroblastoma models to evaluate ALK inhibitors focusing on lorlatinib in combination with conventional chemotherapy and the small molecule MDM2 inhibitor idasanutlin. In both approaches we found synergy in models with high basal ALK expression without MAPK pathway alterations. We conclude that in neuroblastoma the level of ALK expression could be an additional biomarker predictive of clinical response to ALK inhibitors.

cancer biology↗

Born with intronless ERF transcriptional factors: C4 photosynthesis inherits a legacy dating back 450 million years

The genus Flaveria, containing species at different evolutionary stages of the progression from C3 to C4 photosynthesis, is used as a model system to study the evolution of C4 photosynthesis. Here, we report chromosome-scale genome sequences for five Flaveria species, including C3, C4, and intermediate species. Our analyses revealed that both acquiring additional gene copies and recruiting ethylene responsive factor (ERF) cis-regulatory elements (CREs) contributed to the emergence of C4 photosynthesis. ERF transcriptional factors (TFs), especially intronless ERF TFs, were co-opted in dicotyledonous C4 species and monocotyledonous C4 species in parallel. These C4 species co-opted intronless ERF TFs originated from the Late Ordovician mass extinction that occurred [~]450 million years ago in coping with environmental stress. Therefore, this study demonstrated that intronless ERF TFs were acquired during the early evolution of plants and provided the molecular toolbox facilitating multiple subsequent independent evolutions of C4 photosynthesis.

evolutionary biology↗