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Qin, R.

Publications and source records attributed to Qin, R..

17 recordsLinked to original sources

AlaRS-mediated lactylation shields PARP1 from ubiquitination to promote HNSCC progression

Abstract textMetabolic reprogramming in solid tumors causes massive lactate accumulation, yet how this drives oncogenesis remains incompletely understood. Here, we identify alanyl-tRNA synthetase (AlaRS) as a cellular lactyltransferase that promotes head and neck squamous cell carcinoma (HNSCC) progression. AlaRS directly catalyzes site-specific lactylation of the DNA repair protein PARP1 at lysines K249 and K667. Crucially, we uncover a competitive post-translational crosstalk wherein this lactylation directly antagonizes PARP1 ubiquitination. This "lactyl-shield" prevents proteasomal degradation, hyper-stabilizing the PARP1-Mortalin complex and sustaining tumor proliferation via p53/p21 dysregulation. To therapeutically exploit this mechanism, we identified chelerythrine (CHE) as a potent, selective inhibitor that directly binds the AlaRS catalytic center. CHE abrogates AlaRS lactyltransferase activity, destabilizes PARP1, and robustly suppresses HNSCC xenograft growth in vivo. These findings establish a novel metabolic-post-translational axis linking lactate accumulation to oncoprotein stabilization, providing a blueprint for targeting tRNA synthetase moonlighting functions in cancer.

molecular biology↗

Quantal PCR: A Calibrator-Free Method for Determining the Unit for Nucleic Acid Quantification

Quantitative polymerase chain reaction (qPCR) is limited in measuring absolute nucleic acid copy numbers due to the inherent variability of calibrators. Here, we introduce the Quantal PCR (quPCR), a novel method that eliminates the need for calibrators by defining an intrinsic quantal unit derived from the thermodynamic and kinetic properties of the replication system. This approach first determines amplification efficiency at high template concentrations, which is then used as the replication probability to construct quantification cycle (Cq) distribution profiles. These profiles are compared with those from limiting dilution PCR to derive the Cq value for the minimal quantal-replication unit ("quCq"), enabling calculation of the sample copy number. Validation using a dual-target DNA template showed near-identical copy numbers using two distinct target-specific replication systems. Thus, quPCR represents a new method for absolute nucleic acid quantification at the single-molecule level, offering a calibrator-free alternative for absolute quantification.

biochemistry↗

A Syngeneic Immunocompetent Mouse Model of Gallbladder Cancer Reveals Tumorigenesis and Therapeutic Response

PurposeGallbladder cancer (GBC) is a rare but highly lethal malignancy with one of the poorest prognoses among cancers of the digestive system cancers. However, current experimental models of GBC face critical limitations, particularly their dependence on immunodeficient hosts, which precludes the investigation of the tumor microenvironment. We aimed to establish a novel syngeneic immunocompetent mouse model that recapitulates human GBC and enables the investigation of tumor-immune interactions. Experimental DesignWe engineered a murine cell line (mGBC1-ZH) from normal mouse gallbladder organoids expressing Kras and Trp53 (encoding mouse p53) mutations. Tumorigenic potential of mGBC1-ZH was evaluated by subcutaneous and orthotopic implantation. RNA-Seq and WES was used to demonstrate its characterization and similarity with human GBC. Immunohistochemistry, CCK8, and transwell assays wereused to investigate the role of CXCL5 in GBC. Therapeutic responses to standard first-line chemotherapeutic agents was evaluated in the syngeneic GBC model. ResultsThis model supports both subcutaneous and orthotopic tumor growth in immunocompetent C57BL/6J hosts while preserving hallmark features of human GBC, including biliary epithelial differentiation (CK7+/CK19+), aggressive histopathology, and an immunosuppressive "cold" tumor microenvironment. Genomic characterization revealed recurrent chromosomal instability and copy number alterations mirroring human GBC. Comprehensive transcriptomic profiling revealed profound gene expression changes during the model development, and resembled transcriptional features between mGBC1-ZH and human GBC cell lines and samples. CXCL5 was found to be upregulated in human GBC, and promote proliferation, metastasis, and neutrophils infiltration of GBC in the syngeneic mouse model. Functional validation of the syngeneic GBC model demonstrated therapeutic responsiveness to frontline chemotherapeutics gemcitabine and cisplatin with significant in vivo tumor regression. ConclusionsIn summary, we establised a novel syngeneic GBC mouse model, overcoming the limitations of traditional models by enabling studies in immunocompetent hosts. This model provides valuable insights into the molecular evolution from normal gallbladder cells to transformed cancer cells and establishes a robust platform for both mechanistic studies and therapeutic development.

cancer biology↗

Signatures of adaptive self-organization detected in swidden societies worldwide

Quantitative signatures of adaptive self-organization and the spatial scale of human management can be detected in anthropogenic landscapes. Yet, while abundant evidence for self-organization in physical and natural systems exists, there are few adaptive self-organization models that can explain coupled dynamics of human subsistence systems that have also been rigorously validated. Here, we analyze over 18,000 forest patches extracted from 18 remotely-sensed swidden mosaics from tropical and subtropical regions across the planet. We discover a power law signature of adaptive self-organization in the size of the patches and correlation distances that indicate the spatial scale of socioecological adaptation. To explain this pattern, we propose a mathematical model of swidden labor reciprocity, normative reasoning, field placement, forest disturbance and regrowth dynamics that explains the emergent spatial structure of swidden mosaics. Social self-organization can promote sustainable levels of forest disturbance when ecological dynamics such as facilitation, seed-dispersal and competition are conditioned by social dynamics, giving rise to power-law land-use patterns. We use simulations to explore the emergent properties of the model and identify two regimes: deforestation and sustainable swidden. When we analyze the relationship between the simulation results in the remote sensing data, we find that 16/18 of the study areas exhibit power-law distributions and spatial correlation patterns that match the sustainable swidden regime in the model. These findings support the hypothesis that adaptive self-organization may be a general characteristic of coupled human and natural systems.

ecology↗

Breakthrough infection elicits synergistic broadly neutralizing antibodies targeting non-dominant epitopes on RBD and NTD in an individual of inactivated SARS-CoV-2 vaccine

Background/ObjectivesIdentification and characterization of broadly neutralizing monoclonal antibodies from individuals exposed to SARS-CoV-2, either by infection or vaccination, can inform the development of next-generation vaccines and antibody therapeutics with pan-SARS-CoV-2 protection. MethodsThrough single B cell sorting and RT-PCR, monoclonal antibodies (mAbs) were isolated from a donor who experienced BA.5 or BF.7 breakthrough infection after three doses of inactivated vaccines. Their binding and neutralizing capacities were respectively measured with ELISA and pseudovirus-based neutralization assay. Their epitopes were mapped by competition ELISA and site- directed mutation. ResultsAmong a total of 67 spike-specific mAbs cloned from the donor, four mAbs (KXD643, KXD652, KXD681, and KXD686) can neutralize all tested SARS-CoV-2 variants from wild-type to KP.3. Moreover, KXD643, KXD652, and KXD681 belong to a clonotype encoded by IGHV5-51 and IGKV1-13, and recognize the cryptic and conserved RBD-8 epitope on the receptor-binding domain (RBD). In contrast, KXD686 is encoded by IGHV1-69 and IGKV3-20, and targets a conserved epitope (NTD Site iv) outside the antigenic supersite (NTD Site i) of the N-terminal domain (NTD). Notably, antibody cocktails containing these two groups of mAbs can neutralize SARS-CoV-2 more potently due to synergistic effects. In addition, bispecific antibodies derived from KXD643 and KXD686 demonstrate further improved neutralizing potency compared to antibody cocktails. ConclusionsThese four mAbs can be developed as candidates of pan-SARS-CoV-2 antibody therapeutics through further antibody engineering. On the other hand, vaccines designed to simultaneously elicit neutralizing antibodies towards RBD-8 and NTD Site iv have the potential to provide pan-SARS-CoV-2 protection.

immunology↗

Synthesizing human-specific spike-in standards for RNA-seq experiments and assessing their technical performance

Using spike-in standards for RNA-seq experiments is critical to evaluate technical bias introduced during sample preparation, sequencing and analysis. Although some external RNA spike-in standards have been developed, species-specific spike-in standard was not reported yet. Here we developed the human-specific spike-in standards with 65 controls. We first extracted human endogenous RNAs with various lengths and GC contents, introduced random mutations approximately every 75 bp in each RNA, and then synthesized these RNAs as spike-in RNAs. After that, four mixtures of these spike-in RNAs covering a 220 dynamic range were obtained. To ensure the accuracy of RNA concentration, two rounds of ddPCR were conducted for each spike-in RNA and the intraclass correlation coefficient between two ddPCRs ranged from 0.9954 to 0.9971 after removing the two spike-in RNAs with the largest concentration difference. Furthermore, we showed that the sequencing error profiles were distinct between platforms and the library preparation procedures were related with the discrepancies in spike-in RNA read percent, transcript abundance, sequence coverage distribution, and differential gene expression. In addition, two regression models of sequence coverage were built based on RNA second structure and GC content, and 86.62%-91.78% of the variation can be explained. Our study demonstrates the technical performance of the human-specific spike-in standards for RNA-seq experiments and illustrates the biases across different libraries, platforms, and laboratories.

bioinformatics↗

The Landscape Ecology of Swidden: A Global Comparison Indicates Swidden Landscape Mosaics Contribute to Vegetation Diversity at Intermediate Levels of Disturbance

Swidden agriculture is a widespread anthropogenic disturbance regime in tropical forests. Swidden research often posits that aggregate levels of forest disturbance correlate with increased land degradation, however a landscape configuration approach may distinguish when swidden degrades landscapes and when it diversifies them. Here we analyze how the configuration of swidden mosaics relates to vegetation diversity. Using satellite imagery from 18 swidden societies across the African, Southeast Asian, and American tropics, we quantify patch geometry using landscape metrics and estimate vegetation diversity from spectral variation and develop a nonlinear hierarchical Bayesian model that links the structure of swidden mosaics with vegetation diversity. Our analyses reveal three dominant gradients of swidden mosaic patterns: (1) aggregation versus interspersion of land-cover types; (2) spatial dispersion versus synchronization of disturbed patches; and (3) alternative modes of landscape connectivity. Across sites, vegetation diversity exhibits a consistent nonlinear response, peaking at intermediate levels of disturbance intensity. These results demonstrate that swidden agriculture does not produce a singular, degradative outcome. Instead, its effects on vegetation diversity depend on how disturbance is spatially configured. By shifting attention from area-based measures of deforestation to landscape configuration, this study reframes swidden as a spatial process with the potential for diversity-enhancing outcomes.

ecology↗

PlateletBase: A Comprehensive Knowledgebase for Platelet Research and Disease Insights

Platelets are vital in many pathophysiological processes, yet there is a lack of a comprehensive resource dedicated specifically to platelet research. To fill this gap, we have developed PlateletBase, a knowledge base aimed at enhancing the understanding and study of platelets and related diseases. Our team retrieved information from various public databases, specifically extracting and analyzing RNA-seq data from 3,711 samples across 41 different conditions available on NCBI. PlateletBase offers six analytical and visualization tools, enabling users to perform gene similarity analysis, pair correlation, multi-correlation, expression ranking, clinical information association, and gene annotation for platelets. The current version of PlateletBase includes 10,278 genomic entries, 31,758 transcriptomic entries, 4,869 proteomic entries, 2,614 omics knowledge entries, 1,833 drugs, 97 platelet resources, 438 diseases/traits, and six analysis modules. Each entry has been carefully curated and supported by experimental evidence. Additionally, PlateletBase features a user-friendly interface designed for efficient querying, manipulation, browsing, visualization, and analysis of detailed platelet protein and gene information. Case study results, such as those from gray platelet syndrome and angina pectoris, demonstrate that this tool can aid in identifying diagnostic biomarkers and exploring disease mechanisms, significantly advancing research in platelet functionality and its applications. PlateletBase is accessible at http://plateletbase.clinlabomics.org.cn/.

bioinformatics↗

Longitudinal profiling of B cells primed by mRNA vaccine and recalled by Omicron variants uncovers antibodies broadly neutralizing sarbecoviruses

A key question on ancestral SARS-CoV-2 immune imprinting is to what extent imprinted B cells can develop neutralizing breadth and potency in immune recalls. Here, we longitudinally tracked B cells recognizing wild-type spike in two individuals, who were sequentially infected by Omicron variants after receiving mRNA vaccines. Functional and genetic analysis of 632 monoclonal antibodies (mAbs) from those B cells reveals that mAbs cloned after second infection have dramatically enhanced neutralizing breadth and potency, which is attributed to recall and maturation of pre-existing memory B cells. Among the 11 mAbs that potently neutralize SARS-CoV-2 variants from wild-type to KP.3, 5 mAbs are classified into public clonotypes encoded by IGHV3-53 or IGHV3-66, whereas the rest belong to a rarely reported clonotype encoded by IGHV3-74. Notably, IGHV3-74 mAbs can also broadly neutralize other sarbecoviruses by targeting a novel epitope on receptor-binding domain of spike. These results support that ancestral SARS-CoV-2 immune imprinting can be harnessed in developing pan-SARS-CoV-2 and even pan-sarbecovirus vaccines. SummaryChen et al. demonstrate that B cells imprinted by ancestral SARS-CoV-2 have tremendous potential to develop neutralizing breadth and potency in repeated immune recalls driven by Omicron variants, implicating that ancestral SARS-CoV-2 immune imprinting can be harnessed in developing pan-SARS-CoV-2 and even pan-sarbecovirus vaccines.

immunology↗

Deep Learning Driven Cell-Type-Specific Embedding for Inference of Single-Cell Co-expression Networks

The inference of gene co-expression module in specific cell types is important for understanding of cell-type-specific biological processes. We have developed DeepCSCN, an unsupervised deep-learning framework, to infer gene co-expression modules from single-cell RNA sequencing (scRNA-seq) data. Utilizing a global-to-local network construction approach, DeepCSCN can infer co-expression at the whole sample level and construct cell-type-specific co-expression networks. Systematic evaluations on eight public scRNA-seq datasets show that DeepCSCN significantly outperforms eight existing methods in co-expression network construction. Furthermore, DeepCSCN effectively identifies cell-type-specific co-expression networks that are more enriched for cell-specific functional pathways compared to current methods. Finally, application of DeepCSCN on public scRNA-seq data revealed 280 cell-specific gene modules across 27 cell types, including epithelial cells, immune cells, and myonuclei, demonstrating its versatility and accuracy in elucidating cell-type-specific gene co-expression regulation. DeepCSCN offers a powerful tool for researchers to dissect the intricate gene co-expression networks within distinct cell types.

bioinformatics↗

Ancestral SARS-CoV-2 immune imprinting persists on RBD but not NTD after sequential Omicron infections

Whether Omicron exposures could overcome ancestral SARS-CoV-2 immune imprinting remains controversial. Here we analyzed B cell responses evoked by sequential Omicron infections in vaccinated and unvaccinated individuals. Plasma neutralizing antibody titers against ancestral SARS-CoV-2 and variants indicate that immune imprinting is not consistently induced by inactivated or recombinant protein vaccines. However, once induced, immune imprinting is not countered by successive Omicron challenges. We compared binding specificities, neutralizing capacities, developing origins and targeting epitopes of monoclonal antibodies from individuals with or without immune imprinting. Although receptor-binding domain (RBD) and N-terminal domain (NTD) of spike are both primary targets for neutralizing antibodies, immune imprinting only shapes antibody responses to RBD by impeding the production of Omicron-specific neutralizing antibodies while facilitating the development of broadly neutralizing antibodies. We propose that immune imprinting can be either neglected by NTD-based vaccines to induce variant-specific antibodies or leveraged by RBD-based vaccines to induce broadly neutralizing antibodies.

immunology↗

Deep Learning Explains the Biology of Branched Glycans from Single-Cell Sequencing Data

Glycosylation is ubiquitous and often dysregulated in disease. However, the regulation and functional significance of various types of glycosylation at cellular levels is hard to unravel experimentally. Multi-omics, single-cell measurements such as SUGAR-seq, which quantifies transcriptomes and cell surface glycans, facilitate addressing this issue. Using SUGAR-seq data, we pioneered a deep learning model to predict the glycan phenotypes of cells (mouse T lymphocytes) from transcripts, with the example of predicting {beta}1,6GlcNAc-branching across T cell subtypes (test set F1 score: 0.9351). Model interpretation via SHAP (SHapley Additive exPlanations) identified highly predictive genes, in part known to impact (i) branched glycan levels and (ii) the biology of branched glycans. These genes included physiologically relevant low-abundance genes that were not captured by conventional differential expression analysis. Our work shows that interpretable deep learning models are promising for uncovering novel functions and regulatory mechanisms of glycans from integrated transcriptomic and glycomic datasets.

bioinformatics↗

The brassinosteroid biosynthesis gene TaD11-2A controls grain size and its elite haplotype improves wheat grain yields

Brassinosteroids (BRs) control many important agronomic traits, therefore the manipulation of BR components could improve crop productivity and performance. However, the potential effects of BR-related genes on yield-related traits and stress tolerance in wheat (Triticum aestivum L.) remain poorly understood. Here, we identified TaD11 genes in wheat (rice D11 orthologs) that encoded enzymes involved in BR biosynthesis. TaD11 genes were highly expressed in roots (Zadoks scale: Z11) and grains (Z75), while expression was significantly suppressed by exogenous BR (24-epiBL). Ectopic expression of TaD11-2A rescued the abnormal panicle structure and plant height (PH) of the cpb1 mutant, and also increased endogenous BR levels, resulting in improved grain yields and grain quality in rice. Natural variations in TaD11-2A were associated with significant differences in yield-related traits, including PH, grain width (GW), 1000-grain weight (TGW), and grain yield per plant (GYPP), and its favorable haplotype, TaD11-2A-HapI was subjected to positive selection during wheat breeding. Additionally, TaD11-2A influenced root length and salt tolerance in rice and wheat at seedling stages. These results indicated the important role of BR TaD11 biosynthetic genes in controlling grain size and root length, and also highlighted their potential in the molecular biological analysis of wheat. HighlightThe brassinosteroid biosynthesis gene TaD11-2A regulates grain size and root length and its haplotype favorably improves grain yields and salt tolerance in wheat.

plant biology↗

A Chromosome-level Assembly of a Wild Castor Genome Provides New Insights into the Adaptive Evolution in a Tropical Desert

Wild castor grows in the high-altitude tropical desert of the African Plateau, a region known for high ultraviolet radiations, strong lights and extremely dry conditions. To investigate the potential genetic basis of adaptation to both highland and tropical deserts, we generated a chromosome-level genome sequence of the wild castor accession WT05, with genome size of 316 Mb and scaffold and contig N50 sizes of 31.93 Mb and 8.96 Mb, respectively. Compared with cultivated castor and other Euphorbiaceae species, the wild castor exhibits positive selection and gene family expansion for genes involved in DNA repair, photosynthesis and abiotic stress responses. Genetic variations associated with positive selection were identified in several key genes, such as LIG1, DDB2, and RECG1, involved in nucleotide excision repair. Moreover, a study of genomic diversity among wild and cultivated accessions revealed genomic regions containing selection signatures associated with the adaptation to extreme environments. The identification of the genes and alleles with selection signatures provides insights into the genetic mechanisms underlying the adaptation of wild castor to the high-altitude tropical desert and would facilitate direct improvement of modern castor varieties.

genomics↗

Heat Stress Interferes with Formation of Double-Strand Breaks and Homology Synapsis in Arabidopsis thaliana

Meiotic recombination (MR) drives novel combination of alleles and contributes to genomic diversity in eukaryotes. In this study, we showed that heat stress (36-38{degrees}C) over fertile threshold fully abolished crossover (CO) formation in Arabidopsis. Cytological and genetic studies in wild-type plants, and the syn1 and rad51 mutants suggested that heat stress reduces generation of SPO11-dependent double-strand breaks (DSBs). In support, the abundance of recombinase DMC1, which is required for MR-specific DSB repair, was significantly reduced under heat stress. In addition, we showed that high temperatures induced disassembly and/or instability of ASY4-but not SYN1-mediated chromosome axis. At the same time, ASY1-associated lateral element of synaptonemal complex (SC) was partially affected, while the ZYP1-dependent central element of SC was disrupted, indicating that heat stress impairs SC formation. Moreover, quantitative RT-PCR revealed that genes involved in DSB formation; e.g. SPO11-1, PRD1, 2 and 3, were not impacted; however, recombinase RAD51 and chromosome axis factors ASY3 and ASY4 were significantly downregulated under heat stress. Taken together, these findings revealed that heat stress inhibits MR via compromised DSB formation and homolog synapsis, which are possible downstream effects of the impacted chromosome axis. Our study thus provides evidence shedding light on how increase of environmental temperature influences MR in Arabidopsis.

plant biology↗

Molecular basis of differential parasitism between non-encapsulated and encapsulated Trichinella revealed by a high-quality genome assembly

Understanding roles of repetitive sequences in genomes of parasites could offer insights into their evolution, speciation, and parasitism. As a unique intracellular nematode, Trichinella consists of two clades, encapsulated and non-encapsulated. Genomic correlation to the distinct differences between the two clades is still unclear. Here we report an annotated draft reference genome of non-encapsulated Trichinella, T. pseudospiralis, and performed comparative analyses with encapsulated T. spiralis. Genome analysis revealed that, during Trichinella evolution, repetitive sequence insertions played an important role in gene family expansion in synergy with DNA methylation, especially for the DNase II members of the phospholipase D superfamily and Glutathione S-transferases. We further identify the genomic and epigenomic regulation of excretory/secretory products in relation to differences in parasitism, pathology and immunology between the two clades Trichinella. The present study provided a foundation for further elucidation of mechanism of nurse cell formation and immunoevasion as well as identification of phamarcological and diagnostic targets of trichinellosis.

genomics↗

Tumor suppressor DAPK1 catalyzes adhesion assembly on rigid but anoikis on soft matrices

Cancer cells will normally grow on soft surfaces, but if rigidity sensing modules are restored in cancer cells, they will undergo apoptosis on soft surfaces (anoikis) like most normal cells. DAPK1 is a major tumor suppressor that activates cell death, but it is unclear how DAPK1 could activate anoikis through rigidity sensing. Here we find that when rigidity sensing is decreased through inhibition of DAPK1 activity, cells are transformed for growth on soft matrices. Further, DAPK1 catalyzes matrix adhesion assembly and is part of adhesions on rigid surfaces. Additional factors include DAPK1 phosphorylation of tropomyosin2.1, talin1 head domain and tyrosine phosphorylation of DAPK1 by Src. On soft surfaces, DAPK1 rapidly dissociates from the adhesion complexes and activates apoptosis that requires PTPN12 activity and talin1 head. Thus, DAPK1 is important for adhesion assembly on rigid surfaces and the activation of anoikis on soft surfaces through its binding to rigidity-sensing modules.

cell biology↗