Biology subjects

Kong, Q.

Publications and source records attributed to Kong, Q..

14 recordsLinked to original sources

bioRxiv2026

Deep-learning-based design of an orthogonal self-labeling protein from K-Ras(G12C)

Self-labeling protein (SLP) tags enable versatile labeling of proteins in live cells, yet only two SLPs are commonly used, limiting multiplexing. Here, we repurposed the oncoprotein K-Ras(G12C) and its covalent inhibitors to create a third, orthogonal SLP system. We used a deep-learning-based approach to radically redesign the sequence of K-Ras(G12C) while preserving its covalent-inhibitor binding pocket. Our top design, LUCI-tag, is a 19 kDa, monomeric, thermostable SLP that rapidly and covalently reacts with commercially available K-Ras(G12C) inhibitors bearing diverse payloads. Unlike existing SLPs, LUCI-tag exhibited payload-agnostic labeling kinetics, outperforming HaloTag7 and SNAP-tag for a negatively charged payload. X-ray crystal structures of drug-bound and drug-free LUCI-tag showed the design was structurally accurate and contained a preorganized inhibitor-binding pocket that could explain its rapid labeling kinetics. Proteomics and cell-signaling experiments confirmed LUCI-tag is biologically inert. LUCI-tag enabled rapid, wash-free, live-cell imaging and simultaneous three-color multiplexed experiments with HaloTag7 and SNAP-tag. This work establishes LUCI-tag as an immediately useful orthogonal SLP and demonstrates that covalent drug-target pairs can be repurposed into a broadly applicable platform for protein labeling.

bioengineering↗

bioRxiv2026

Depleting prion protein using splice-switching small molecules

Prion diseases are fatal neurodegenerative disorders driven by prion protein (PrP) misfolding, and lowering cellular PrP represents a promising therapeutic strategy. Here we report a small-molecule approach that reduces PrP by modulating pre-mRNA splicing of the PRNP gene. Through chemical modification of the clinically approved splicing modulator risdiplam, we generated CP3, the first class of compounds that selectively activate a cryptic exon in PRNP and routes its mRNA product for degradation, reducing PrP by [~]70% in cells. We demonstrate that CP3 activity critically depends on alternative splicing factor Luc7L, revealing a novel requirement for alternative splicing factors in small molecule splicing modulation. Strikingly, co-administration of CP3 with a Luc7L activator PTC258 significantly lowers PrP levels in the brains of transgenic mice. These results establish splicing modulation as a powerful strategy for PrP reduction and highlight the potential of small-molecule cooperativity for therapeutic RNA targeting.

biochemistry↗

bioRxiv2026

Xylulose 5-Phosphate/Phosphate Translocator Mediates Carbon Allocation for Anabolic Metabolism in the Chlamydomonas Chloroplast

Metabolite movement into chloroplasts is essential for sustaining chloroplast anabolic metabolism and cellular growth, and yet how the specific factors/transporters that enable import and support metabolism under heterotrophic conditions (in the dark in the presence of fixed carbon) remain poorly understood. Here, we identify CreTPT10, a chloroplast envelope-localized transporter in the unicellular green alga Chlamydomonas reinhardtii (Chlamydomonas throughout) that, of the substrates tested, has the highest specificity for xylulose 5-phosphate (X5P). We also demonstrated that the loss of CreTPT10 caused a pronounced reduction in growth and respiratory activity in the dark, whereas no growth defects were observed in the tpt10 mutants when they were maintained in the light or under nutrient-limiting conditions. Furthermore, dark-grown tpt10 mutants exhibited markedly reduced levels of lipids, nucleotides, isoprenoids, and aromatic secondary metabolites, accompanied by coordinated repression of genes encoding enzymes associated with chloroplast-localized biosynthetic pathways. This metabolic suppression extended beyond the chloroplast, as genes associated with the mitochondrial respiratory chain and cell cycle progression were markedly downregulated in darkness. Together, these findings indicate that X5P import via CreTPT10 is critical for sustaining chloroplast anabolic metabolism and functionally coordinates chloroplast and mitochondrial energy metabolism to support heterotrophic growth.

plant biology↗

bioRxiv2025

PepSeek: Universal Functional Peptide Discovery with Cooperation Between Specialized Deep Learning Models and Large Language Model

Recent computational foundation models have revitalized the scientific discovery pipeline. However, developing foundational models for functional peptide discovery is costly due to the scarcity of wet-lab validated data. Meanwhile, conventional deep learning models are hard to generalize to unseen tasks or data distribution. Here, we introduce PepSeek, a universal approach for peptide discovery that synergistically integrates the most advanced large language model (LLM) with specialized small models. PepSeek harnesses the robust reasoning and generalization capabilities of LLM while leveraging the high predictive accuracy of specialized models trained for tasks such as antimicrobial activity regression and functional peptide generation. We have devised multiple collaborative strategies and task-specific modules demonstrating leading performance in peptide identification and generation. Notably, PepSeek achieves remarkable zero-shot prediction accuracy for peptides with diverse functionalities. We used PepSeek to identify a group of broad-spectrum antimicrobial peptide that exhibits low toxicity and high activity against drug-resistant bacteria, with the best surpassing all peptides currently undergoing clinical trials. Our framework establishes a new pipeline for scientific discovery with the help of LLM and specialized models.

bioinformatics↗

bioRxiv2024

Phosphotyrosine Signal Profiling of Clinical CAR-T Reveals Tonic Signaling Associated with Therapeutic Efficacy

Chimeric Antigen Receptor T (CAR-T) therapies have revolutionized the treatment of cancers such as relapsed and refractory B cell malignancies. However, the precise therapeutic mechanism of CAR-T action remain to be elucidated. In this study, we systematically analyzed CAR signaling via phosphotyrosine (pTyr) proteomics in CAR-T cells from both clinical patients and healthy donors. We found that CAR-T products from clinical patients displayed heightened tyrosine phosphorylation, particularly in the JAK-STAT, MAPK and TCR signaling cascades. We also identified the significantly regulated pTyr sites in primary CAR-T cells under tonic signaling or upon stimulation by antigen-presenting CD19-K562 cells. Although both CD28{zeta} and 4-1BB{zeta} CAR-T cells exhibited comparable pTyr changes, CD28{zeta} CAR-T cells displayed a more pronounced activation in the TCR signaling pathway. Additionally, comparative analysis between clinical and primary CAR-T cells suggested that CAR-T products were subject to heightened tonic signaling, which may be related to therapeutic relapse. Our findings reveal the state of clinical CAR-T products and refine the CAR-T signal transduction network, providing comprehensive insights and informed guidance for CAR-T therapies.

immunology↗

bioRxiv2024

Spatial-DC: a robust deep learning-based method for deconvolution of spatial proteomics

Spatial proteomics studies the spatial distribution of proteins within cells or tissues, providing a new perspective for comprehending cellular processes and disease mechanisms. One important challenge of current spatial proteomics technologies is low resolution, resulting in multiple cells in each spatial proteomics spot. While methods have been proposed to infer the composition of potential cell types in such spots for spatial transcriptomics, the depressed correlation and divergent quantification between transcriptome and proteome limits their capability in spatial proteomics. To enhance the utility of spatial proteomics data, we propose Spatial-DC (Spatial Digital Cytometry), a deep learning-based framework that infers cell-type composition in each spot and reconstructs spatially and cell-type resolved proteomic profiles. We achieve this by utilizing transfer learning and self-supervised learning with graph convolutional networks (GCN), which enables the incorporation of target spatial proteomics with reference single-cell or single-cell-type proteomics data. Through extensive simulations of spatial proteomics data, we demonstrate that Spatial-DC outperforms eight state-of-the-art methods in estimating cell-type composition and provides meaningful reconstructions of proteomic profiles for individual cell types. We apply Spatial-DC to different tissues measured using both multiplexed antibody-based and mass spectrometry (MS)-based spatial proteomics technologies. The results showcase Spatial-DCs superior sensitivity in providing more refined cell-type distribution maps compared to cell-type-specific marker-based distributions and its feasibility in reconstructing spatially and cell-type resolved proteomic profiles from real-world spatial proteomics data. Moreover, we validate Spatial-DC with a newly self-collected pancreatic cancer spatial proteomics data characterized by complex tumor microenvironment (TME) and identify the signaling direction and strength at both spatial and cell-type levels within the TME, suggesting cell-type-specific and spatially-resolved interactions linked to tumor outcomes. Our results highlight Spatial-DC as a versatile tool for the deconvolution of spatial proteomics data across various tissue slices, providing a reliable foundation for downstream analysis.

bioinformatics↗

bioRxiv2024

BioInformatics Agent (BIA): Unleashing the Power of Large Language Models to Reshape Bioinformatics Workflow

Bioinformatics plays a crucial role in understanding biological phenomena, yet the exponential growth of biological data and rapid technological advancements have heightened the barriers to in-depth exploration of this domain. Thereby, we propose Bio-Informatics Agent (BIA), an intelligent agent leveraging Large Language Models (LLMs) technology, to facilitate autonomous bioinformatic analysis through natural language. The primary functionalities of BIA encompass extraction and processing of raw data and metadata, querying both locally deployed and public databases for information. It further undertakes the formulation of workflow designs, generates executable code, and delivers comprehensive reports. Focused on the single-cell RNA sequencing (scRNA-seq) data, this paper demonstrates BIAs remarkable proficiency in information processing and analysis, as well as executing sophisticated tasks and interactions. Additionally, we analyzed failed executions from the agent and demonstrate prospective enhancement strategies including selfrefinement and domain adaptation. The future outlook includes expanding BIAs practical implementations across multi-omics data, to alleviating the workload burden for the bioinformatics community and empowering more profound investigations into the mysteries of life sciences. BIA is available at: https://github.com/biagent-dev/biagent.

bioinformatics↗

bioRxiv2024

De novo multi-mechanism antimicrobial peptide design via multimodal deep learning

Artificial intelligence (AI)-driven discovery of antimicrobial peptides (AMPs) is yet to fully utilise their three-dimensional (3D) structural characteristics, microbial specie-specific antimicrobial activities and mechanisms. Here, we constructed a QLAPD database comprising the sequence, structures and antimicrobial properties of 12,914 AMPs. QLAPD underlies a multimodal, multitask, multilabel, and conditionally controlled AMP discovery (M3-CAD) pipeline, which is proposed for the de novo design of multi-mechanism AMPs to combat multidrug-resistant organisms (MDROs). This pipeline integrates the generation, regression, and classification modules, using a innovative 3D voxel coloring method to capture the nuanced physicochemical context of amino acids, significantly enhancing structural characterizations. QL-AMP-1, discovered by M3-CAD, which possesses four antimicrobial mechanisms, exhibited low toxicity and significant activity against MDROs. The skin wound infection model demonstrates its considerable antimicrobial effects and negligible toxicity. Altogether, integrating 3D features, specie-specific antimicrobial activities and mechanisms enhanced AI-driven AMP discovery, making the M3-CAD pipeline a viable tool for de novo AMP design.

bioengineering↗

bioRxiv2023

Bi-parental graph strategy to represent and analyze hybrid plant genomes

Hybrid plants are universally existed in wild and often exhibit greater performance of complex traits compared with their parents and other selfing plants. This phenomenon, known as heterosis, has been extensively applied in plant breeding for decades. However, the process of decoding hybrid plant genomes has seriously lagged due to the challenges in their genome assembling and the lack of proper methods to further represent and analyze them. Here we report the assembly and analysis of two hybrids: an intraspecific hybrid between two maize inbred lines and an interspecific hybrid between maize and its wild relative teosinte, based on the combination of PacBio High Fidelity (HiFi) sequencing and chromatin conformation capture sequencing data. The haplotypic assemblies are well-phased at chromosomal scale, successfully resolving the complex loci with extensive parental structural variations (SVs). By integrating into a bi-parental genome graph, the haplotypic assemblies can facilitate downstream short-reads based SV calling and allele-specific gene expression analysis, demonstrating outstanding advantages over one single linear genome. Our work provides an entire workflow which hopefully can promote the deciphering of the large numbers of hybrid plant genomes, especially those whose parents are unknown or unavailable and help to understand genome evolution and heterosis.

bioinformatics↗

bioRxiv2023

Maternal H3.3-Mediated Paternal Genome Reprogramming Contributes to Minor Zygotic Genome Activation

In mice, zygotic genome activation (ZGA) is initiated at the late-one-cell stage, accompanied by an extensive incorporation of the histone variant H3.3 into the parental genomes. However, it is unclear how H3.3 engages in the onset of ZGA. Here, using the H3.3B-HA-tagged mouse model, we found that the paternal and maternal genomes are activated asynchronously. Paternally expressed H3.3 begins deposition on the zygotic genome at the early two-cell stage, whereas the deposition of maternally expressed H3.3 is delayed until the four-cell stage. Oocyte-stored maternal H3.3 (mH3.3) is crucial for cleavage development and minor ZGA. Deposition of mH3.3 on the paternal genome occurs globally during the protamine-to-histone transition but shows preferential enrichment at CpG-rich TSSs after the initial round of DNA replication. Depletion of mH3.3 can lead to a loss of H3K27ac, resulting in minor ZGA failure and early embryonic arrest. Mechanistically, mH3.3 deposition on the sperm genome removes repressive histone modifications, promotes the establishment of active histone modifications, and in turn enables the initiation of minor ZGA from the paternal genome. Our study highlights the pivotal role of mH3.3 in paternal genome reprogramming and minor ZGA initiation.

genetics↗

bioRxiv2023

Targeting GDF15 as a potential therapy for low back pain originating from endplate

The overactivation of osteoclasts in the endplate is one of the most important causes of low back pain (LBP) originating from endplate. Transforming growth factor-{beta} family has been demonstrated to play an important role during osteoclast differentiation. GDF15 was reported to participate in several pathological states. In this study, we reported that the lumbar spine instability (LSI) induced the overactivation of osteoclasts and CD31hiEmcnhi endothelial vessels in the bony endplate. In addition, the expression of GDF15 in human disc samples and mice models were also increased. GDF15 could promote the fusion of preosteoclasts via Rac1/Cdc42/PAK/Cofilin axis, and facilitate the angiogenesis via the secretion of PDGF-BB. Furthermore, we proved that the GDF15 inhibitor, CTL-002 could reduce the expression of GDF15 in the endplate and alleviate the overactivation of osteoclasts and CD31hiEmcnhi endothelial vessels induced by LSI in vivo. In conclusion, we demonstrated that GDF15 could regulates the fusion of preosteoclasts and targeting GDF15 in the endplate served as a novel anabolic therapy for low back pain treatment.

cell biology↗

bioRxiv2022

The BRCA1 isoform, BRCA1-IRIS, operates independently of the full-length BRCA1 in the Fanconi anemia pathway

The tumor suppressor BRCA1 encodes multiple protein products including the canonical BRCA1-p220 (p220), which plays important roles in repair of diverse types of DNA damage. However, contributions of other BRCA1-encoded protein isoforms to DNA damage repair are less clear. Here, we report that the BRCA1-IRIS (IRIS) isoform has critical functions in the Fanconi anemia (FA) pathway and in repair of DNA interstrand crosslinks (ICLs). Loss of IRIS expression sensitizes cells to ICLs and impairs ICL repair. ICL formation stimulates association of IRIS with both FANCD2 and the FA core complex, which promotes FANCD2 recruitment to damage sites. The unique, BRCA1 intron 11-encoded C-terminal tail of IRIS is required for complex formation with FANCD2 and for ICL-inducible FANCD2 mono-ubiquitylation. Collectively, our findings reveal that IRIS plays an essential role, upstream of the p220-directed HR, in the FA pathway through a previously unrecognized mechanism that depends on the IRIS-FANCA-FANCD2 interaction. HighlightsO_LIBRCA1 splicing isoform BRCA1-IRIS is required for interstrand crosslink (ICL) repair. C_LIO_LIBRCA1-IRIS interacts with FANCD2 and promotes its recruitment to sites of ICL damage. C_LIO_LIBRCA1-IRIS, but not BRCA1-p220, promotes ICL-inducible FANCD2 mono-ubiquitylation. C_LIO_LIThe unique C-terminal tail of BRCA1-IRIS is essential for its function in ICL repair. C_LI

molecular biology↗

bioRxiv2022

Metabolic control of histone acetylation for precise and timely regulation of minor ZGA in early mammalian embryos

Metabolism feeds into the regulation of epigenetics via metabolic enzymes and metabolites. However, metabolic features, and their impact on epigenetic remodeling during mammalian pre-implantation development, remain poorly understood. In this study, we established the metabolic landscape of mouse pre-implantation embryos from zygote to blastocyst, and quantified some absolute carbohydrate metabolites. We integrated these data with transcriptomic and proteomic data, and discovered the metabolic characteristics of the development process, including the activation of methionine cycle from 8-cell embryo to blastocyst, high glutaminolysis metabolism at blastocyst stage, enhanced TCA cycle activity from the 8-cell embryo stage, and active glycolysis in the blastocyst. We further demonstrated that oxidized nicotinamide adenine dinucleotide (NAD+) synthesis is indispensable for mouse pre-implantation development. Mechanistically, in part, NAD+ is required for the exit of minor zygotic gene activation (ZGA) by cooperating with SIRT1 to remove zygotic H3K27ac. In human, NAD+ supplement can promote the removal of zygotic H3K27ac and benefit pre-implantation development. Our findings demonstrate that precise and timely regulation of minor ZGA is controlled by metabolic dynamics, and enhance our understanding of the metabolism of mammalian early embryos. HighlightsO_LIWe identified the metabolic features of mouse pre-implantation embryo development. C_LIO_LINAD+ synthesis is indispensable for mouse embryo pre-implantation development. C_LIO_LINAD+-mediated erasure of zygotic H3K27ac is required for the exit of minor ZGA. C_LIO_LINAD+ supplement promotes the removal of zygotic H3K27ac and benefits preimplantation development of human embryos. C_LI

developmental biology↗

bioRxiv2019

Long noncoding RNAs sustain high expression of exogenous Oct4 by sponging miRNA during reprogramming

Long noncoding RNAs (lncRNAs) modulate gene expression as competing endogenous RNAs (ceRNAs) via sponging microRNAs (miRNAs). However, the extent and functional consequences of ceRNAs in diverse cellular context still need to be proven. Using a doxycycline inducible expression of Yamanaka four factors to generate induced pluripotent stem cells (iPSCs) from mouse embryonic fibroblasts (MEFs), we found the miRNAs from MEFs remained highly expressed from day 0 to day 6 after doxycycline induction; unexpectedly, many genes targeted by these miRNAs were actually up-regulated; meanwhile, long intergenic noncoding RNAs (lincRNAs) and circular RNAs (circRNAs) which have complementary binding sites with the miRNAs were highly expressed, indicating lincRNAs and circRNAs (linc/circRNAs) may serve as sponges for miRNAs to block their activities during reprogramming. Intriguingly, the knockdown of the linc/circRNAs sponging the miRNAs targeting Oct4 mRNA resulted in down-regulation of exogenous Oct4 expression, decrease of reprogramming efficiency, and low-grade chimera forming iPSCs. Our results suggest that the ceRNA network plays an important role in reprogramming somatic cells to pluripotent stem cells.

cell biology↗