Biology subjects

Huang, D.

Publications and source records attributed to Huang, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Monocyte single cell-type gene expression measured in peripheral blood by DIRECT LS-TA method: the ratio-based biomarkers of (IFI27/PSAP) showed superior performance than interferon score in triage patients with viral infection

A rapid method to triage febrile patients into different categories of etiologies remains a significant challenge even nowadays, when many molecular tests for pathogens are available. Routine serum protein tests like C-reactive protein and procalcitonin have limited specificity. Host response gene signatures are promising biomarkers but they usually require assaying many genes, e.g. 7 genes are commonly used to calculate the interferon (IFN) score. However, these gene panels fail to capture cell-type-specific host responses. Measuring gene expression of a specified single cell population, like monocytes, offers enhanced biological insight. However, it currently requires laborious cell sorting or costly single-cell sequencing techniques, limiting its clinical applicability. This study aims to develop a simple ratio-based biomarker (RBB) representing monocyte-specific host response to viral infection called DIRECT LS-TA method. A simple ratio of 2 genes (both are shortlist monocyte informative genes) quantified in peripheral blood (PB) samples correlated with gene expression in purified monocytes in the corresponding individual. These RBBs cover 3 interferon-stimulated genes (ISGs): IFI27/PSAP, IFI44L/PSAP and SIGLEC1/PSAP. They are compared to the conventional multi-gene IFN score in the differentiation of viral infection. Public gene expression datasets from NCBI GEO were used to shortlist monocyte-informative genes that can be used as the RBB in PB. The DIRECT LS-TA RBB was calculated as the ratio of the target ISG transcript abundance (TA) to that of another reference gene (PSAP or CTSS) directly quantified from bulk PB data (e.g., Log(IFI27/PSAP) in WB). The correlation (expressed by coefficient of determination, R{superscript 2}) between these DIRECT LS-TA RBBs and the gold-standard target gene TA measured in purified monocytes was assessed. The diagnostic performance of selected RBBs (IFI27/PSAP, IFI44L/PSAP, SIGLEC1/PSAP) was compared against the conventional 8-gene IFN score for differentiating viral infections from controls. Direct LS-TA RBBs measured in PB showed strong correlation with gold-standard gene expression measured in purified monocytes (R2 ranged from 0.53 for the target gene IFI27 to >0.9 for the target gene IFI44L). This high level of correlation supports that this simple RBB (DIRECT LS-TA) method can replace the tedious cell sorting approach to obtain single-cell-type gene expression data. All DIRECT LS-TA results of ISGs were raised during viral infection. The best clinical performance in triaging viral infection patients was achieved by IFI27/PSAP or IFI27/CTSS across all datasets. For example, in the GSE111368 dataset, IFI27/PSAP achieved an AUC of 0.94 (95% CI 0.90-0.97) with 88% sensitivity and 95% specificity, surpassing the IFN scores AUC of 0.90 (95% CI 0.85-0.94) with 79% sensitivity and 93% specificity. ConclusionThe DIRECT LS-TA method, utilizing the format of simple two-gene ratio-based biomarkers like IFI27/PSAP, provides a robust and accurate measure of monocyte-specific interferon pathway activation directly from peripheral blood. The superior performance of the DIRECT LS-TA method makes it a promising, readily implementable tool for clinical triage. Its ability to provide single-cell-type specific information, rapid turnaround using standard qPCR/dPCR technology, and enhanced biological specificity make it a valuable molecular host response assessment.

immunology↗

bioRxiv2025

Phenotypic and Functional Characterization of Oncohistone Mutations in Breast Cancers

Although mutations in genes encoding histones display a similar prevalence to that of some other somatic mutations in cancer, the underlying mechanisms by which histone mutations drive tumorigenesis have not been fully explored. Herein, we curated missense mutations occurring in core histone genes in breast cancers using data from MSK-IMPACT and cBioPortal to identify high frequency breast cancer-associated histone gene mutations. We characterized 17 high frequency oncohistone mutations in H2A H2B, and H3 that are enriched in breast cancer samples and occurred at glutamate (E), aspartate (D), serine (S), and arginine (R) residues. Many of these mutants co-occur with PIK3CA mutations in breast cancer samples. The oncohistone mutants were expressed in MCF-7 breast cancer cells or MCF-10A mammary epithelial cells and screened for effects on oncogenic phenotypes in a variety of cell- and tumor-based assays (i.e., proliferation, migration, invasion, competitive outgrowth, transformation). In addition, we examined the effects of selected mutants on DNA damage and gene expression. Our results indicate that the collection of oncohistone mutants that we screened have varying phenotypic and functional effects. Some can promote cancer-related phenotypes, with H2B-E76Q, H3-E97K, and H3-E105K eliciting strong oncogenic phenotypes and alterations in gene expression. All three of these mutants showed cooperativity with an activating mutation in PIK3CA (E545K), or a chemical activator of PI3K (UCL-TRO-1938), in assays of MCF-10A proliferation. H3-E105K also strongly promoted transformation of MCF-10A cells in an assay of growth on low attachment substrate independently of PIK3CA. Our results indicate that some high frequency oncohistone mutants can have oncogenic activity in breast cancers, and may act as potential cancer drivers. Collectively, these observations presented here can be used as a resource to connect biological and molecular outcomes to oncohistones in breast cancers. SignificanceIn this study, we identified and characterized 17 high frequency oncohistone mutations in H2A H2B, and H3 that are enriched in breast cancer samples and promote cancer-related phenotypes when expressed in cells. Many of these oncohistone mutations co-occur in breast cancer samples with mutations in PIK3CA, the most frequently mutated gene in breast cancer, and may act as potential cancer drivers.

cancer biology↗

bioRxiv2025

NAD+ Sensing by PARP7 Regulates the C/EBPβ-Dependent Transcription Program in Adipose Tissue In Vivo

We have identified PARP7, an NAD+-dependent mono(ADP-ribosyl) transferase, as a key regulator of the C/EBP{beta}-dependent proadipogenic transcription program. Moreover, PARP7 is required for efficient adipogenesis and downstream biological functions, including involution of the lactating mammary gland. PARP7 serves as a coregulator of C/EBP{beta}, and depletion of PARP7 causes a dramatic reduction in C/EBP{beta} binding across the genome. PARP7 functions as a sensor of nuclear NAD+ levels to control gene expression. At the relatively high nuclear NAD+ concentrations in undifferentiated preadipocytes, PARP7 is catalytically active for auto- mono(ADP-ribosyl)ation (autoMARylation). As nuclear NAD+ concentrations decline post- differentiation, autoMARylation decreases dramatically. AutoMARylation promotes instability of PARP7 through an E3 ligase-ubiquitin-proteasome pathway mediated by the ADP-ribose (ADPR)-binding ubiquitin E3 ligases DTX2 and RNF114. Genetic depletion of PARP7 in mice promotes a dramatic reduction in a wide array of lipids in the mammary gland fat pads and milk from lactating females, as well as a significant decrease in nicotinamide mononucleotide (NMN), a key nutrient in mothers milk. The latter is due to reduced expression of Nampt, the gene encoding NAMPT, the enzyme that produces NMN, which is a direct transcriptional target of PARP7 and C/EBP{beta}. Collectively, our results extend the biology of PARP7 to adipogenesis and perinatal health. Moreover, our results describe the molecular events that regulate these downstream biological functions.

cell biology↗

bioRxiv2025

Direct single cell-type gene expression analysis in Whole blood: Novel ratio-based gene expression biomarkers using 2 novel monocyte reference genes (PSAP and CTSS) for monitoring bacterial infection

BackgroundTo determine single cell-type specific gene expression in peripheral blood (PB) requires either prior labour-intense cell sorting or expensive single-cell RNA sequencing. We developed and validated a novel ratio-based biomarker (RBB) called Direct Leukocyte Subpopulation-Transcript Abundance (DIRECT LS-TA) assay that allows quantification of monocyte-specific gene expression directly from peripheral blood samples without cell sorting. MethodsThe DIRECT LS-TA method leverages known cell-type proportions and differential gene expression profiles among leukocyte subpopulations (e.g. monocytes, lymphocytes and granulocytes) to identify monocyte-informative genes. We shortlisted genes that had 2.5-fold higher expression in isolated monocytes compared to PB samples, indicating >50% transcript of genes in PB are contributed by monocytes alone. Public gene expression datasets were used to generate a list of monocyte informative genes with which DIRECT LS-TA assay is applicable in PB samples. PSAP and CTSS were identified as the monocyte informative reference genes, based on low biological variation (CV <12%) and high monocyte specificity. They were used as the denominator and together with another monocyte informative target gene as the numerator, the value of this new DIRECT LS-TA can be determined which is a kind of ratio-based biomarker (RBB). The clinical utility was the differentiation of patients with bacterial infection from control subjects in a discovery dataset and 4 other replication datasets. Methods to convert DIRECT LS-TA results to multiple of control median (MoM) provided approximations to delta-delta CT values of relative quantification commonly used in qPCR or digital PCR assays. ResultsOver 50 monocyte-informative genes were identified, including key immune response genes like IFI44L, IL1B, VNN1 and NFKBIZ. DIRECT LS-TA results showed excellent correlation with the gold standard results, gene expression in isolated monocyte expression (R2=0.55-0.97). Then, DIRECT LS-TA of these 50 target genes were evaluated to identify the best RBB to detect the host response to bacterial infection. Monocyte DIRECT LS-TA VNN1 RBB showed consistent upregulation across five independent datasets (median fold change 2.7-fold, p<10-8) with strong diagnostic performance (AUC=0.84-0.99). The expected corresponding delta-delta CT value is more than 1.4 cycle which can be reliably measured by qPCR. Additional monocyte-informative genes including NLRC4, CYP1B1, PFKFB3, LILRA5, NFKBIA, and NFKBIZ also demonstrated significant diagnostic ability (AUC>0.8). ConclusionsThe DIRECT LS-TA method (as a simple RBB) provides reliable quantification of monocyte-specific gene expression directly from whole blood samples without cell separation. The robust performance in bacterial infection diagnosis demonstrates its potential clinical utility for rapid infection differentiation and informed antibiotic stewardship. DIRECT LS-TA will emerge as a new kind of in vitro diagnostics (IVD) which can convey single cell-type gene expression information from PB samples. The new kind of IVD and uniqueness of the information, together with the ease of implementation will make it very useful in clinics

immunology↗

bioRxiv2025

Avoidance of fratricide and improved efficacy of CD33-MSLN CAR-iNK cells in treating acute myeloid leukemia

Acute myeloid leukemia (AML) patients are often older, which brings challenges of endurance and persistent efficacy of autologous CAR-T cell therapies. Allogenic CAR-NK cell therapies may offer reduced toxicities and enhanced anti-leukemic potential against AML. In this study, we designed a novel CD33-mesothelin loop CAR (Loop CAR) and evaluated its anti-tumor efficacy in human umbilical cord blood-derived NK (UCB-NK) cells and human pluripotent stem cell-derived NK (hPSC-iNK) cells. The Loop CAR exhibited superior cytotoxicity against dual-antigen-positive tumor cell lines and primary AML cells. To further avoid fratricide caused by endogenous CD33 expression in NK cells, we established a hPSC-derived cell line via knockout of CD33 gene (CD33KO) and engineered Loop CAR. Rather than enforced expression of exogenous CD16, we generated abundant mature CD33KO-Loop CAR-iNK cells highly expressing endogenous CD16 via an organoid induction approach. This innovative strategy effectively mitigated NK cell fratricide and significantly enhanced CD33 and mesothelin-mediated specific cytotoxicity. Moreover, the CD33KO-Loop CAR-iNK cells demonstrated superior tumor-killing activity in AML xenograft mice and significantly prolonged survival. hPSC-derived CD33KO-Loop CAR-iNK cells possess unique advantages and translational potential for treating AML.

cancer biology↗

bioRxiv2025

Engineered CRO-CD7 CAR-NK cells derived from pluripotent stem cells avoid fratricide and efficiently suppress human T-cell malignancies

BackgroundT cell malignancies are highly aggressive hematological tumors with limited effective treatment options. CAR-NK cell therapy targeting CD7 has emerged as a promising approach for treating T-cell malignancies. However, conventional CAR-NK cell therapy faces the challenges of cell fratricide due to CD7 expression on both malignant cells and normal NK cells. Additionally, engineering CARs into human tissue-derived NK cells demonstrates heterogeneity, low transduction efficiency, and high manufacturing costs. MethodsThe human pluripotent stem cells (hPSCs) were genetically modified by knocking out the CD7 gene and introducing the CD7 CAR expression cassette to generate CD7 KO-CD7 CAR-hPSCs. These modified hPSCs were subsequently differentiated into CD7 KO-CD7 CAR-iNK cells using an efficient organoid induction method. The cytotoxicity of CD7 KO-CD7 CAR-iNK cells against CD7+ tumor cells was evaluated. Furthermore, we overexpressed the CXCR4 gene in CD7 KO-CD7 CAR-hPSCs and derived CXCR4-expressing CD7 KO-CD7 CAR-iNK (CRO-CD7 CAR-iNK) cells. The dynamics of CRO-CD7 CAR-iNK cells in vivo were tracked, and their therapeutic efficacy was assessed using human T-cell acute lymphoblastic leukemia (T-ALL) xenograft models. ResultsThe CD7 KO-CD7 CAR-iNK cells derived from CD7 KO-CD7 CAR-hPSCs effectively avoided fratricide, demonstrated normal expansion, and exhibited potent and specific anti-tumor activity against CD7+ T-cell tumor cell lines and primary T-ALL cells. CXCR4 overexpression in CRO-CD7 CAR-iNK cells improved their homing capacity and extended their persistence in vivo. The CRO-CD7 CAR iNK cells significantly suppressed tumor growth and prolonged the survival of T-ALL tumor-bearing mice. ConclusionsOur study provides a reliable strategy for the large-scale generation of fratricide-resistant CD7 CAR-iNK cells with robust anti-tumor effects from hPSCs, offering a promising cell product to treat T-cell malignancy.

cancer biology↗

bioRxiv2025

Pluripotent stem cell-derived NK progenitor cell therapy prevents tumour occurrence and eradicates minimal residual disease

The lack of persistence and short-term efficacy presents a major challenge for CAR-NK cell therapy. Here, we addressed this issue by developing pluripotent stem cell-derived NK lineage-committed progenitor (iNKP) cell therapy. For the first time, we generated abundant iNKP cells via an organoid culture system. The iNKP cells, engineered to express CXCR4 and chimeric antigen receptors (CAR), efficiently migrated to the bone marrow and generated CAR-iNK cells persisting in peripheral blood (PB) for over 80 days. Notably, CAR-iNKP cell therapy durably protected animals from tumour occurrence. Furthermore, a single low-dose infusion of CAR-iNKP cells following conventional chemotherapy eradicated minimal residual disease (MRD), leading to long-term complete remission. Our findings present a novel strategy to overcome the limitations of traditional CAR-NK cell therapy and offer dural breakthroughs for the prevention of tumour occurrence and relapse.

cancer biology↗

bioRxiv2024

BioMedGraphica: An All-in-One Platform for Biomedical Prior Knowledge and Omic Signaling Graph Generation

Multi-omic data analysis is essential for scientific discovery in precision medicine. However, translating statistical results of omic data analysis into novel scientific hypothesis remains a significant challenge. Human experts must manually review analysis results and generate new hypothesis based on extensive and inter-connected biomedical prior knowledge, which is subjective and not scalable. While large language models (LLMs) can accelerate the discovery, their reasoning improves when grounded in structured, auditable and comprehensive biomedical prior knowledge. Biomedical knowledge, however, is scattered across heterogeneous databases that use diverse and inconsistent nomenclature systems, making it difficult to integrate resources into a unified format for scalable analysis. This fragmentation limits the ability of AI systems to fully leverage biomedical data for scientific discovery. To address these challenges, we developed BioMedGraphica, an all-in-one platform that harmonizes fragmented biomedical resources by integrating 11 entity types and 30 relation types from 43 databases into a unified knowledge graph containing 2,306,921 entities and 27,232,091 relations. In addition, to the best of our knowledge, this is the first work to propose a novel Textual-Numeric Graph (TNG) data-structure for multi-omics data analysis. In TNG, textual information captures prior biological knowledge (e.g., transcription start sites, functions, mechanisms), while numeric values represent quantitative biomedical features, and the integrated relations can help uncover mechanisms. By bridging prior knowledge with user-specific data, TNG is a novel and ideal data-structure for the development of graph foundation models, with the potential to improve prediction performance and interpretability, while also augmenting LLMs by supplying graph-structured mechanistic context to strengthen reasoning. The details for BioMedGraphica code can be accessed by github link: https://github.com/FuhaiLiAiLab/BioMedGraphica and BioMedGraphica knowledge graph data can be downloaded from huggingface dataset: https://huggingface.co/datasets/FuhaiLiAiLab/BioMedGraphica

bioinformatics↗

bioRxiv2024

Agouti and BMP signaling drive a naturally occurring fate conversion of melanophores to leucophores in zebrafish

The often-prominent pigment patterns of vertebrates are varied in form and function and depend on several types of pigment cells derived from embryonic neural crest or latent stem cells of neural crest origin. These cells and the patterns they produce have been useful for uncovering features of differentiation and morphogenesis that underlie adult phenotypes, and they offer opportunities to discover how patterns and the cell types themselves have diversified. In zebrafish, a body pattern of stripes arises by self organizing interactions among three types of pigment cells. Yet these fish also exhibit white ornamentation on their fins that depends on the transdifferentiation of black melanophores to white cells, "melanoleucophores." To identify mechanisms underlying this conversion we used ultrastructural, transcriptomic, mutational and other approaches. We show that melanophore- melanoleucophore transition depends on regional BMP signals transduced through non-canonical receptors (Rgmb-Neo1a-Lrig2) as well as BMP-dependent signaling by Agouti genes, asip1 and asip2b. These signals lead to expression of transcription factor genes including foxd3 and runx3 that are necessary to induce loss of melanin by an autophagy-like process, curtail new melanin production, and deploy a pathway for accumulating guanine crystals that, together, confer a white phenotype. These analyses uncover an important role for positional information in specifying ornamentation in zebrafish and show how tissue environmental cues and a novel gene regulatory program have allowed terminal addition of a distinct phenotype to a pre-existing cell type. SignificanceFish often have striking color patterns with important functions in behavior. In zebrafish, the familiar striped pattern forms through self-organizing interactions between pigment cells, yet the white highlights on their fins arise differently--through the transformation of black pigment cells into white ones. This study reveals how this dramatic cell transformation happens: signals from the surrounding tissue, specifically BMP and Agouti proteins, instruct black cells to change their fate. These signals trigger expression of specific genes that cause the cells to break down their black pigment while acquiring white, crystal-like structures. This work shows how local signals in tissues can drive the development of ornamental features and provides insights into how new cell types evolve.

developmental biology↗

bioRxiv2024

Nemo knows: clownfishes differentiate cryptic host species across fine and broad geographic scales and reveal a potential adaptive radiation in the clownfish-hosting sea anemones.

The symbiosis between clownfishes (or anemonefishes) and their host sea anemones ranks among the most recognizable animal interactions on the planet. Found on coral reef habitats across the Indian and Pacific Oceans, 28 recognized species of clownfishes adaptively radiated from a common ancestor to live obligately with only 10 nominal species of host sea anemones. Are the host sea anemones truly less diverse than clownfishes? Did the symbiosis with clownfishes trigger a reciprocal adaptive radiation in sea anemones, or minimally, a co-evolutionary response to the mutualism? To address these questions, we combined fine- and broad-scale biogeographic sampling with multiple independent genomic datasets for the bubble-tip sea anemone, Entacmaea quadricolor--the most common clownfish host anemone throughout the Indo-West Pacific. Fine-scale sampling and restriction site associated DNA sequencing (RADseq) throughout the Japanese Archipelago revealed three highly divergent cryptic species: two of which co-occur throughout the Ryukyu Islands and can be differentiated by the clownfish species they host. Remarkably, broader biogeographic sampling and bait-capture sequencing reveals that this pattern is not simply the result of local ecological processes unique to Japan, but part of a deeper evolutionary signal where some species of E. quadricolor serve as host to the generalist clownfish species Amphiprion clarkii and others serve as host to the specialist clownfish A. frenatus. In total, we delimit at least five cryptic species in E. quadricolor that have diversified within the last five million years. The rapid diversification of E. quadricolor combined with functional ecological and phenotypic differentiation supports the hypothesis that this may represent an adaptive radiation in response to mutualism with clownfishes. Our data indicate that clownfishes are not merely settling in locally available hosts but recruiting to specialized host lineages with which they have co-evolved. These findings have important implications for understanding how the clownfish-sea anemone symbiosis has evolved and will shape future research agendas on this iconic model system.

evolutionary biology↗

bioRxiv2024

Automatic diagnostics of electroencephalography pathology based on multi-domain feature fusion

Electroencephalography (EEG) serves as a practical auxiliary tool deployed to diagnose diverse brain-related disorders owing to its exceptional temporal resolution, non-invasive characteristics, and cost-effectiveness. In recent years, with the advancement of machine learning, automated EEG pathology diagnostics methods have flourished. However, most existing methods usually neglect the crucial spatial correlations in multi-channel EEG signals and the potential complementary information among different domain features, both of which are keys to improving discrimination performance. In addition, latent redundant and irrelevant features may cause overfitting, increased model complexity, and other issues. In response, we propose a novel feature-based framework designed to improve the diagnostic accuracy of multi-channel EEG pathology. This framework first applies a multi-resolution decomposition technique and a statistical feature extractor to construct a salient time-frequency feature space. Then, spatial distribution information is channel-wise extracted from this space to fuse with time-frequency features, thereby leveraging their complementarity to the fullest extent. Furthermore, to eliminate the redundancy and irrelevancy, a two-step dimension reduction strategy, including a lightweight multi-view time-frequency feature aggregation and a non-parametric statistical significance analysis, is devised to pick out the features with stronger discriminative ability. Comprehensive examinations of the Temple University Hospital Abnormal EEG Corpus V. 2.0.0 demonstrate that our proposal outperforms state-of-the-art methods, highlighting its significant potential in clinically automated EEG abnormality detection.

bioengineering↗

bioRxiv2024

Multimodal Protein-Ligand Contrastive Pretraining for Effective and Efficient Drug Discovery

Recent advancements in genomics and proteomics have identified numerous clinically significant protein targets, with notably 85% categorized as undruggable. These targets present widespread challenges due to their complex structures and dynamics, rendering conventional drug design strategies not always effective. In this study, we introduce Uni-Clip, a contrastive learning framework that incorporates multi-modal features of proteins (structure and residue) and ligands (conformation and graph). Optimized with a specifically designed CF-InfoNCE loss, Uni-Clip enhances the modeling of protein-ligand interactions for both undruggable and druggable proteins. Uni-Clip demonstrates superior performance in benchmark evaluations on widely acknowledged datasets, LIT-PCBA and DUD-E, achieving a 147% and 218% improvements in enrichment factors at 1% compared to baselines. Furthermore, Uni-Clip proves to be a practical tool for various drug discovery applications. In virtual screening for the challenging protein target GPX4 with flat surface, it identified non-covalent inhibitors with an IC50 of 4.17 M, in contrast to the predominantly covalent inhibitors currently known. Through target fishing for benzbromarone, Uni-Clip identified the intrinsically disordered protein c-Myc as a potential target, highlighting benzbromarones potential for repurposing in cancer therapy. Explainable analyses effectively identified binding sites consistent with molecular dynamics and experimental results, even for challenging undruggable targets.

bioinformatics↗

bioRxiv2024

Protein overabundance is driven by growth robustness

Protein expression levels optimize cell fitness: Too low an expression level of essential proteins will slow growth by compromising essential processes; whereas overexpression slows growth by increasing the metabolic load. This trade-off naively predicts that cells maximize their fitness by sufficiency, expressing just enough of each essential protein for function. We test this prediction in the naturally-competent bacterium Acinetobacter baylyi by characterizing the proliferation dynamics of essential-gene knockouts at a single-cell scale (by imaging) as well as at a genome-wide scale. In these experiments, cells proliferate for multiple generations as target protein levels are diluted from their endogenous levels. This approach facilitates a proteome-scale analysis of the fitness landscape with respect to protein abundance. We find that most essential proteins are subject to a threshold-like fitness landscape: growth is independent of protein abundance above a critical threshold and arrests below that threshold. We have recently analyzed the implications of this landscape for growth robustness. Confirming signature predictions of this model, we find that (i) roughly 70% of essential proteins are overabundant, (ii) overabundance increases as the expression level decreases and (iii) the lowest abundance proteins are in vast excess (>10x) of what is required for growth in the typical cell. These results reveal that robustness plays a fundamental role in determining the expression levels of essential genes and that overabundance is a key mechanism for ensuring robust growth.

systems biology↗

bioRxiv2024

mosGraphGPT: a foundation model for multi-omic signaling graphs using generative AI

Generative pretrained models represent a significant advancement in natural language processing and computer vision, which can generate coherent and contextually relevant content based on the pre-training on large general datasets and fine-tune for specific tasks. Building foundation models using large scale omic data is promising to decode and understand the complex signaling language patterns within cells. Different from existing foundation models of omic data, we build a foundation model, mosGraphGPT, for multi-omic signaling (mos) graphs, in which the multi-omic data was integrated and interpreted using a multi-level signaling graph. The model was pretrained using multi-omic data of cancers in The Cancer Genome Atlas (TCGA), and fine-turned for multi-omic data of Alzheimers Disease (AD). The experimental evaluation results showed that the model can not only improve the disease classification accuracy, but also is interpretable by uncovering disease targets and signaling interactions. And the model code are uploaded via GitHub with link: https://github.com/mosGraph/mosGraphGPT

bioinformatics↗

bioRxiv2024

Differential regulation of BAX and BAK apoptotic activity revealed by a novel small molecule

Defective apoptosis mediated by BAK or BAX underlies various human pathologies including autoimmune and degenerative conditions. The mitochondrial channel protein VDAC2 interacts with BAK and BAX through a common interface to either inhibit BAK or to facilitate BAX apoptotic activity. Using a newly developed small molecule (WEHI-3773) that inhibits the interaction between VDAC2 and BAK or BAX, we reveal contrasting effects on BAX and BAK apoptotic activity. WEHI-3773 inhibits apoptosis mediated by BAX by blocking VDAC2-mediated BAX recruitment to mitochondria. Conversely, WEHI-3773 primes BAK for apoptosis by impairing its inhibitory sequestration by VDAC2 on the mitochondrial membrane. In cells expressing both BAX and BAK, repressing their association with VDAC2 promotes apoptosis, because once BAK is activated, it further activates BAX through a feed-forward mechanism. In some leukemias, mutation or loss of BAX is a key driver of resistance to the BH3-mimetic anti-cancer drug venetoclax. Strikingly, promoting BAK-mediated killing by small molecule dissociation of the VDAC2 interaction can overcome this resistance in different leukemia models. These data reveal a hitherto unappreciated level of coordination of BAX and BAK apoptotic activity through their interaction with VDAC2 that may be targeted therapeutically.

cell biology↗

bioRxiv2024

Efficient generation of CAR NK cells from human umbilical cord blood CD34+ stem and progenitors for democratizing affordable immunotherapy

Chimeric antigen receptor (CAR) natural killer cells (CAR NK) cells, leveraging safety and not requiring HLA match in adoptive infusion, have emerged as promising alternative cells to CAR-T cells for immunotherapies. High and multiple doses of CAR NK cell infusions are essential to maintain therapeutic efficacy in clinical trials. This requires efficient methods for generating large-scale CAR NK cells and significantly reducing CAR engineering costs. In this study, we develop a three-step strategy to generate highly high yields of induced NK (iNK) and CAR iNK cells from human umbilical cord blood CD34+ hematopoietic stem and progenitor cells (CD34+ HSPCs). Starting from a single umbilical cord blood CD34+ HSPC, our reliable method efficiently produces 14-83 million mature iNK cells or 7-32 million CAR iNK cells with high expression levels of CD16 and zero T cell contaminations. Introducing CAR expression elements at the HSPC level reduces the quantities of CAR pseudoviruses to 1 / 140.000 - 1 / 600,000 compared to engineering CARs in mature NK cells. The iNK and CAR iNK cells, including fresh cells and thawed cells from cryopreserved conditions, demonstrate remarkable tumoricidal activities against various human cancer cells and significantly prolong the survival of human tumor-bearing animals. The high yields of CAR NK cells and negligible costs of CAR engineering of our method support the broad applications of CAR NK cells for treating cancer patients.

cell biology↗

bioRxiv2024

Stratifying variant deleteriousness and trait-modulating effect under human recent adaptation

Despite advances in annotating and interpreting human genetic variants, existing methods to distinguish deleterious/pathogenic from neutral variants still inadequately capture the nuanced impact of genetic variants on fitness and disease susceptibility. In this study, we introduced a new deep learning framework, the FIND model, by stratifying genetic variants into refined categories based on selection pressures and derived allele frequency. FIND demonstrated superior performance over existing genome-wide methods, delivering enhanced resolution in differentiating trait-modulating alleles from those that are pathogenic or neutral. Access to base-wise informative annotations has unveiled novel features that significantly enhance the model interpretability, and FIND has adeptly delineated evolutionary trends in human accelerated regions. Furthermore, applying FIND to the interpretation of clinical variants demonstrates its substantial potential in reclassifying variants of unknown significance. This work advances our understanding of the genetic underpinnings of human adaptation and disease, providing a new tool to explore the complexities of genetic contributions to health.

genetics↗

bioRxiv2024

SlNAP2 promoted fruit ripening by directly binding the ACS2 promoter and interacting with EIL3

The ripening process of tomato fruit is affected by a variety of environmental factors and genetic regulators. NAC transcription factors (TFs) function in a multitude of biological processes, while the current knowledge on the participation of NAC TFs in the regulatory network of fruit ripening is relatively limited. In this study, we isolated a NAC TFs, NAP2, which acts as a positive transcription activator in tomato fruit ripening. We also observed a notable delay in the ripening process of SlNAP2 silenced and knockout mutant fruit. In particular, ethylene production was obviously inhibited in SlNAP2 mutant fruit. Y1H and DLR assays showed that SlNAP2 directly binds to the promoter of SlACS2 and activates its transcriptional activity. Furthermore, SlNAP2 and SlEIL3 physically interaction was demonstrated by yeast two-hybrid (Y2H), luciferase complementation (LUC), bimolecular fluorescence complementation (BiFC) and coimmunoprecipitation analysis (CoIP) assays. Meanwhile, the pigment content, firmness and the transcript levels of genes associated with carotenoid and chlorophyll metabolism and cell wall metabolism were also potentially affected by the SlNAP2 deletion; however, it has remained unclear whether these genes are also directly regulated by SlNAP2. Therefore, our findings indicate that SlNAP2 directly binds to SlACS2 promoter to activate its expression and promote ethylene generation, which in turn interacts with EIL3 to enhance the function of ethylene in tomato fruit ripening. Collectively, our data contribute to understanding the interaction of NAC TFs and ethylene in tomato fruit ripening, thereby enhancing our knowledge of the ripening regulatory network that governs tomato fruit maturation.

biochemistry↗