Biology subjects

Tang, K.

Publications and source records attributed to Tang, K..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Bridging data gaps: predicting inadequate micronutrient intake with machine learning

Identifying populations at risk of inadequate micronutrient intake is useful for governments and humanitarian organizations in low- and middle-income countries to make informed and timely decisions on nutrition relevant policies and programmes. We propose a machine-learning methodological approach using secondary data on household dietary diversity, socioeconomic status, and climate indicators to predict the risk of inadequate micronutrient intake in Ethiopia and in Nigeria. We identify key predictive features common to both countries, and we demonstrate the models transferability from one country to another to predict risk of inadequate micronutrient intake in contexts where nationally representative primary data are unavailable.

bioinformatics↗

bioRxiv2025

A database for large-scale docking and experimental results

The rapid expansion of readily accessible compounds over the past six years has transformed molecular docking, improving hit rates and affinities. While many millions of molecules may score well in a docking campaign, the results are rarely fully shared, hindering the benchmarking of machine learning and chemical space exploration methods that seek to explore the expanding chemical spaces. To address this gap, we develop a website providing access to recent large library campaigns, including poses, scores, and in vitro results for campaigns against 11 targets, with 6.3 billion molecules docked and 3729 compounds experimentally tested. In a simple proof-of-concept study that speaks to the new librarys utility, we use the new database to train machine learning models to predict docking scores and to find the top 0.01% scoring molecules while evaluating only 1% of the library. Even in these proof-of-concept studies, some interesting trends emerge: unsurprisingly, as models train on larger sets, they perform better; less expected, models could achieve high correlations with docking scores and yet still fail to enrich the new docking-discovered ligands, or even the top 0.01% of docking-ranked molecules. It will be interesting to see how these trends develop for methods more sophisticated than the simple proof-of-concept studies undertaken here; the database is openly available at lsd.docking.org.

biophysics↗

bioRxiv2025

An integrated meta-omics approach for identifying candidate organic micropollutant degraders in complex microbial communities

Biotransformation is a significant determinant of the fate of organic micropollutants (OMPs) in natural and engineered environments; yet identifying OMP-transforming microorganisms remains challenging. Integrating metagenomics and metatranscriptomics, we searched for correlations between the biotransformation of ammonia and atenolol and the transcriptional activity of metagenome-assembled genomes (MAGs) across five nitrifier-rich cultures in batch experiments. The biotransformation of ammonia correlated with the activity of ammonia-oxidizing bacterium Nitrosomonas europaea but not with the activity of other bacteria, including several ammonia oxidizers. Additionally, the biotransformation of ammonia correlated with the transcript abundance of the ammonia monooxygenase (AMO) expressed by N. europaea but not with the transcript abundance of AMO at the community level. Atenolol biotransformation correlated with the activity of four MAGs representing three heterotrophic genera: Terrimonas, Flavobacterium, and Zeimonas. It did not correlate with the total transcript abundance of any member of a comprehensive set of amidohydrolases, which are predicted to transform this drug. By contrast, it correlated with the expression of the amidohydrolase asparagine synthase (AsnB) identified in the Terrimonas and Flavobacterium MAGs. In summary, we present a novel association-based method for elucidating biotransformation processes robust to variability in enzyme reaction kinetics with implications for OMP control. SynopsisThe fate of organic micropollutants in natural and engineered systems depends greatly on biotransformation by microbes. This study proposes an approach for identifying these microbes with implications for the study and control of organic micropollutant removal. ABSTRACT GRAPHICS O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/639455v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@17c7f1org.highwire.dtl.DTLVardef@147b9eforg.highwire.dtl.DTLVardef@1fffc9eorg.highwire.dtl.DTLVardef@121fd96_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Haplotype-based Parallel PBWT for Biobank Scale Data

Durbins positional Burrows-Wheeler transform (PBWT) enables algorithms with the optimal time complexity of O(MN) for reporting all vs all haplotype matches in a population panel with M haplotypes and N variant sites. However, even this efficiency may still be too slow when the number of haplotypes reaches millions. To further reduce the run time, in this paper, a parallel version of the PBWT algorithms is introduced for all versus all haplotype matching, which is called HP-PBWT (haplotype-based parallel PBWT). HP-PBWT parallelly executes the PBWT by splitting a haplotype panel into blocks of haplotypes. HP-PBWT algorithms achieve parallelization for PBWT construction, reporting all versus all L-long matches, and reporting all versus all set-maximal matches while maintaining memory efficiency. HP-PBWT has an [Formula] time complexity in PBWT construction, and an [Formula] time complexity for reporting all versus all L-long matches and reporting all versus all set-maximal matches, where T is the number of threads and c* is the maximum number of matches (of length L or maximum divergence value for L-long matches and set-maximal matches, re-spectively) per haplotype per site. HP-PBWT achieves 4-fold speed-up in UK Biobank genotyping array data with 30 threads in the IO-included benchmarks. When applying HP-PBWT to a dataset of 8 million randomized haplotypes (random binary strings of equal length) in the IO-excluded benchmarks, it can achieve a 22-fold speed-up with 60 cores on the Amazon EC2 server. With further hardware optimization, HP-PBWT is expected to handle billions of haplotypes efficiently.

bioinformatics↗

bioRxiv2025

Mac/Lac-tosylceramide regulates intestinal homeostasis and secretory cell fate commitment by facilitating Notch signaling

Cell-to-cell communication via Delta-Notch signaling is widely used in various tissues and organs to regulate development and patterning; however, the mechanisms regulating Notch signaling for precise cell fate decisions remain poorly understood. Similar to mammals, the intestinal stem cells (ISCs) in the adult Drosophila midgut generate both absorptive and secretory cell progeny, guided by differential levels of Notch activation. Here we performed a forward genetic screen in Drosophila and identified glucosylceramide synthase (GlcT), a rate-limiting enzyme for glycosphingolipid (GSL) production, whose mutation causes the development of secretory cell tumors. Genetic analysis of the GSL synthesis pathway, combined with metabolite rescue experiments, revealed that the tumor formation is linked to a deficiency in Mactosylceramide/Lactosylceramide. This deficiency impaired the endocytic recycling of the Delta, subsequently reducing Notch signaling activation. Conditional knockout of UGCG, the mammalian ortholog of GlcT, in mouse small intestine caused an excessive differentiation of goblet cells, phenotypes similar to these caused by Notch inhibition. Our study suggests an evolutionarily conserved role for a specific GSL metabolite in modulating Notch signaling during stem cell fate decisions and provides a molecular connection between ceramide metabolism and Notch signaling in regulating tissue homeostasis and tumor formation.

developmental biology↗

bioRxiv2025

A SNP Foundation Model: Application in Whole-Genome Haplotype Phasing and Genotype Imputation

Millions of human genomes have been genotyped by national biobanks worldwide. Training large language models (LLM) with this data may lead to a universal model of human genome with tremendous potential. Yet the quadrillions (1015) of nucleotides-- resulting from genome length multiplied by population size--pose formidable challenges for modeling. In this study, we propose a novel AI framework designed to scale with this data and support diverse analytical tasks. To demonstrate this scheme, we developed SNPBag--a foundation model focusing on single nucleotide polymorphism (SNP). With 0.8 billion parameters, it is trained on one million synthesized human genomes, corresponding to a total of 6 trillion SNP tokens. SNPBag showed superior performance in benchmarking of multiple tasks. In genotype imputation, it achieves state-of-the-art (SOTA) accuracy. In haplotype phasing, it rivals the best method with a 72-fold speedup. By encoding 6 million SNPs per genome into a 0.75 MB embedding, SNPBag enables efficient storage, transfer and downstream applications. In particular, the genome embeddings facilitate rapid ancestry inference across global populations and detection of genetic relationships up to 12th-degree relatives. Collectively, SNPBag introduces a new paradigm for scalable, unified and multitask analysis of the ever-growing human variation data.

genomics↗

bioRxiv2024

Catestatin improves heart metabolic flexibility by promoting mitochondrial structure and function

Hypertension, a major cause of cardiomyopathy, is one of the most critical risk factors for heart failure and mortality worldwide. Loss of metabolic flexibility of cardiomyocytes is one of the major causes of heart failure. Although Catestatin (CST) treatment is known to be both hypotensive and cardioprotective, its effect on cardiac metabolism is unknown. In this study, we undertook a transcriptomic approach to identify differentially expressed genes that were filtered using Boolean implication relationships to develop a model of gene regulation in saline or CST-supplemented CST knockout (CST-KO) mice. The analysis revealed a set of gene signatures (fibroblast, cardiomyocyte, and macrophage) rescued after CST supplemented CST-KO mice compared to wild-type. Furthermore, we independently validated these gene signature models using publicly available patient datasets. Since the gene signature includes genes related to glucose, fatty acid metabolism, and mitochondrial function, we assessed the glucose and fatty acid uptake after CST treatment. We found that CST treatment can restore the cardiac metabolic inflexibility in CST-KO heart due to the metabolic shift of glucose utilization to fatty acid as energy source. Binding studies after immunoprecipitation and mass spectrometry revealed CST binding with ATP synthase, supported by molecular simulation and computational modeling that predicted CST binding to /{beta} subunit of ATP synthase. Colocalization of CST with mitochondria and increased mitochondrial membrane potential and ATP production upon CST treatment in neonatal cardiomyocytes further exhibit CST as a key regulator of cardiac metabolism and mitochondrial function.

physiology↗

bioRxiv2024

TCPGdb: A comprehensive T cell perturbation genomics database for identification of critical T cell regulators

CAR-T therapies utilizing T cells engineered with chimeric antigen receptors (CARs) have revolutionized the treatment of hematologic and immune-related malignancies. However, the anti-tumor capability of engineered CAR-T cells are often not persistent, which greatly dampen its clinical efficacy. To address this limitation, massive parallel genetic screens were widely used to identified novel targets and regulators that enhance T cell anti-tumor capability and persistence in tumor microenvironment. We hypothesized that by combining the pooled screen data from multiple independent genetic screens we could provide a systematic, comprehensive, and robust analysis of the effect of gene perturbation on T-cell based immunotherapies. After collecting data from previously published T cell screens, including CRISPR-based and ORF-based screens, through Gene Expression Omnibus (GEO), we reprocessed the gene hits summary and conducting a pathway enrichment analysis. A T cell screen perturbation score (TPS) was employed to quantifies the impact of the gene on T cell function. Additionally, gene expression data (both bulk RNA level and single-cell RNA level) from autoimmune disease and T cell-derived cancers were analyzed to pick up gene perturbations that potentially augment T cell proliferation. We integrated all data and analysis on 27 T-cells screens into our state-of-the-art T cell perturbation genomics database (TCPGdb), which is made easily accessible through our webserver and allows users to interactively explore the impact of query genes on T cell function based on prior screen data and our TPS scoring module. TCPGdb is publicly accessible at http://tcpgdb.sidichenlab.org/.

bioinformatics↗

bioRxiv2024

Heat Acclimation in Mice Requires Preoptic BDNF Neurons and Postsynaptic Potentiation

Heat acclimation (HA) is a key adaptive response in mammals to repeated heat exposure, essential for fitness and survival1-3. HA improves cardiovascular function, thermal comfort, and exercise capacity4, 5. However, the lack of a genetically tractable model has hindered understanding of the molecular and neural mechanisms underlying HA. Here, we show that 10 days of daily 38{degrees}C exposure lowers core body temperature (Tcore) and reduces anxiety during subsequent heat exposures in mice. HA increases brain-derived neurotrophic factor (BDNF) expression in the medial preoptic area (MPO). BDNF-expressing MPO neurons (MPOBDNF) show increased intrinsic heat sensitivity after HA. These neurons orchestrate downstream targets in the dorsomedial hypothalamus (DMH) and rostral raphe pallidus (rRPa) to mediate HA effects. BDNF, acting through its receptor tropomyosin-related kinase B (TrkB) in the DMH, facilitates the anxiolytic effect of HA by enhancing excitatory synaptic connections between MPOBDNF and DMH neurons. This study provides new insights into HA mechanisms, setting the stage for future research on heat stress reduction and exercise optimization.

neuroscience↗

bioRxiv2024

Targeting long non-coding RNA RP11-502I4.3 delays the trend of angiogenesis in diabetic retinopathy

Based on our previous findings, we hypothesized that the long non-coding RNA RP11-502I4.3 may be involved in angiogenesis associated with Diabetic retinopathy (DR). We investigated the role of RP11-502I4.3 in DR by examining its regulation of vascular endothelial growth factor (VEGF). We assessed differences in RP11-502I4.3 expression between the normal control group and streptozotocin-induced diabetic rats or high glucose (HG)-stimulated human retinal microvascular endothelial cells (HRMECs). VEGF expression was measured with and without lentiviral vectors overexpressing RP11-502I4.3. We analyzed the structural and functional alterations related to DR. Our analysis revealed that RP11-502I4.3 expression was lower in the retinas of diabetic rats and in HG-stimulated HRMECs compared with normal glucose conditions. Overexpressing of RP11-502I4.3 resulted in decreased VEGF levels. Diabetic rats exhibited retinopathy characterized by thinning of the retinal layer thickness, structural changes in the inner and outer nuclear layers, a reduced count of retinal ganglion cells, and the presence of acellular capillaries. The proliferative activity, migration count, and tube formation ability of HG-treated HRMECs were significantly higher than those of the normal control group; however, these changes were delayed by RP11-502I4.3 overexpression. RP11-502I4.3 downregulation in DR appears to promote angiogenesis.

zoology↗

bioRxiv2024

Spatially organized striatum-wide acetylcholine dynamics for the learning and extinction of Pavlovian cues and actions

Striatal acetylcholine (ACh) signaling has been proposed to counteract reinforcement signals to promote extinction and behavioral flexibility. ACh dips to cues and rewards may open a temporal window for associative plasticity to occur, while elevations may promote extinction. Changes in multi-phasic striatal ACh signals have been widely reported during learning, but how and where signals are distributed to enable region-specific plasticity for the learning and degradation of cue-reward associations is poorly understood. We used array fiber photometry in mice to investigate how ACh release across the striatum evolves during learning and extinction of Pavlovian associations. We report a topographic organization of opposing changes in ACh release to cues, rewards, and consummatory actions across distinct striatum regions. We localized reward prediction error encoding in particular phases of the ACh dynamics to a specific region of the anterior dorsal striatum (aDS). Positive prediction errors in the aDS were expressed in ACh dips, and negative prediction errors in long latency ACh elevations. Silencing aDS ACh release impaired behavioral extinction, suggesting a role for ACh elevations in down-regulating cue-reward associations. Dopamine release in aDS dipped for cues during extinction, but glutamate input onto cholinergic interneurons did not change, suggesting an intrastriatal mechanism for the emergence of ACh elevations. Our large scale measurements indicate how and where ACh dynamics can shape region-specific plasticity to gate learning and promote extinction of Pavlovian associations.

neuroscience↗

bioRxiv2024

GeneBag: training a cell foundation model for broad-spectrum cancer diagnosis and prognosis with bulk RNA-seq data

Numerous Pre-trained cell foundation models (CFM) have been crafted to encapsulate the comprehensive gene-gene interaction network within cells, leveraging extensive single-cell sequencing data. These models have shown promise in various cell biology applications, including cell type annotation, perturbation inference, and cell state embedding, etc. However, their clinical utility, particularly in cancer diagnosis and prognosis, remains an open question. We introduce the GeneBag model, a novel CFM that represents a cell as "a bag of unordered genes" with continuous expression values and a full-length gene list. Pre-trained on single-cell data and fine-tuned on bulk RNA-seq datasets, GeneBag achieves superior performance across cancer diagnosis and prognosis scenarios. In a zero-shot learning setting, GeneBag can classify cancer and non-cancer tissues with approximately 96.2% accuracy. With fine-tuning, it can annotate 40 different types of cancers and corresponding normal biopsies with an overall accuracy of [~]97.2%. It notably excels in classifying challenging cancers such as bladder (93%) and stomach (90%). Furthermore, GeneBag is capable of cancer staging with 68.5% accuracy and 5-year survival prediction with an AUC of [~]80.4%. This study marks the first to demonstrate the potential of CFMs in RNA-based cancer diagnostics and prognostics, indicating a promising avenue for AI-assisted molecular diagnosis.

bioinformatics↗

bioRxiv2024

Chromogranin A Deficiency Attenuates Tauopathy by Altering Epinephrine Alpha-Adrenergic Receptor Signaling

Our previous studies have indicated that insulin resistance, hyperglycemia, and hypertension in aged wild-type (WT) mice can be reversed in mice lacking chromogranin-A (CgA-KO mice). These health conditions are associated with a higher risk of Alzheimers disease (AD). CgA, a neuroendocrine secretory protein has been detected in protein aggregates in the brains of AD patients. Here, we determined the role of CgA in tauopathies, including AD (secondary tauopathy) and corticobasal degeneration (CBD, primary tauopathy). We found elevated levels of CgA in both AD and CBD brains, which were positively correlated with increased phosphorylated tau in the frontal cortex. Furthermore, CgA ablation in a human P301S tau (hTau) transgenic mice (CgA-KO/hTau) exhibited reduced tau aggregation, resistance to tau spreading, and an extended lifespan, coupled with improved cognitive function. Transcriptomic analysis of mice cortices highlighted altered levels of alpha-adrenergic receptors (Adra) in hTau mice compared to WT mice, akin to AD patients. Since CgA regulates the release of the Adra ligands epinephrine (EPI) and norepinephrine (NE), we determined their levels and found elevated EPI levels in the cortices of hTau mice, AD and CBD patients. CgA-KO/hTau mice exhibited reversal of EPI levels in the cortex and the expression of several affected genes, including Adra1 and 2, nearly returning them to WT levels. Treatment of hippocampal slice cultures with EPI or an Adra1 agonist intensified, while an Adra1 antagonist inhibited, tau hyperphosphorylation and aggregation. These findings reveal a critical role of CgA in regulation of tau pathogenesis via the EPI-Adra signaling axis.

neuroscience↗

bioRxiv2024

SARS-CoV-2 infection activates inflammatory macrophages in vascular immune organoids

SARS-CoV-2 provokes devastating tissue damage by cytokine release syndrome and leads to multi-organ failure. Modeling the process of immune cell activation and subsequent tissue damage is a significant task. Organoids from human tissues advanced our understanding of SARS-CoV-2 infection mechanisms though, they are missing crucial components: immune cells and endothelial cells. This study aims to generate organoids with these components. We established vascular immune organoids from human pluripotent stem cells and examined the effect of SARS-CoV-2 infection. We demonstrated that infections activated inflammatory macrophages. Notably, the upregulation of interferon signaling supports macrophages role in cytokine release syndrome. We propose vascular immune organoids are a useful platform to model and discover factors that ameliorate SARS-CoV-2-mediated cytokine release syndrome.

immunology↗

bioRxiv2024

High-fidelity enhanced AsCas12a knock-in mice for efficient multiplexed gene editing, disease modeling and orthogonal immunogenetics

The advancement of CRISPR gene editing technology, especially the development of Cas9 knock-in mice, has significantly boosted the functional discovery of various genetics factors in diverse fields including genetics, genomics, immunology, and the biology of cancer. However, the pleiotropic effects on human disease and the complex nature of gene interaction networks require a knock-in mouse model capable of simultaneous multiplexed gene perturbation. Here, we present the generation and applications of Cre-dependent conditional and constitutive high-fidelity, enhanced AsCas12a (enAsCas12a-HF1) Rosa26-knock-in mice in the C57BL/6 background. With these mouse strains, we demonstrate highly efficient and multiplexed in vivo and ex vivo genome engineering as applied to lipid nanoparticle (LNP)-RNA-based liver protein targeting, AAV-based tumor modeling, and retrovirus-based immune cell engineering. By integrating with a dCas9-SPH CRISPR activation transgenic strain, we establish a simultaneous dual gene activation and knockout (DAKO) system that showcases the modular potential of these enAsCas12a-HF1 mice. Importantly, constitutive expression of enAsCas12a-HF1 does not lead to any discernable pathological differences as compared to the C57BL/6 background strain. These knock-in mice and the accompanying delivery methods would empower the deconvolution of complex gene interaction networks in broad areas of research.

bioengineering↗

bioRxiv2024

Addressing Artemisinin Resistance in Malaria Treatment: A Novel Ferrous ACT (FACT) Formulation

Malaria is the worldwide infectious disease causing significant losses of human lives every year. The deployment of artemisinin-based combination therapies (ACTs) has helped to reduce the losses caused by malaria. However, resistance to ACTs evolved especially by Plasmodium falciparum occurs and becomes more and more threats for human lives. Up to now, there is no effective way to solve this drug-resistance problem. Here we propose a new ACT, which contains traditional ACT plus iron supplement, so-called ferrous ACT (FACT). The FACT is promising to become a safe and effective new formulation to combat ACT resistance malaria, helping WHO reach its 2030s Malaria Control Goal.

cell biology↗

bioRxiv2023

CSTA: A Biomarker Regulating Esophageal Stricture Epithelial Barrier, Potential Medication Target

Esophageal strictures resulting from ESD/EMR in the esophagus are distressing, with uncertain causes and treatments due to epithelial barrier dysfunction. We explored cystatin A (CSTA) as a novel biomarker for the esophageal epithelial barrier. CSTA regulates the barrier and is influenced by tacrolimus (FK506). Analyzing biopsy samples by proteomics, we identified CSTA as an esophageal epithelial biomarker. Knocking down CSTA reduced responsiveness to triamcinolone acetonide (TA) and lowered expression of proteins related to cell-cell junctions and barrier function during inflammation. These findings suggest that down-regulate CSTA weakens tight junctions and the esophageal barrier, leading to strictures. Notably, FK506 showed promise in rescuing CSTA-knockdown cells by increasing the expression of proteins related to cell-cell junctions and barrier function. This highlights FK506 as a potential therapy for esophageal strictures in patients with CSTA mutations.

cell biology↗

bioRxiv2023

Cladosporium species detoxify multiple water micropollutants of emerging concern using diverse strategies

The accumulation of micropollutants of emerging concern in aqueous systems raises safety concerns regarding biological systems and human health. Mycoremediation is a promising and green strategy to mitigate the micropollutant challenge. Hitherto, focus has mainly been on white-rot Basidiomycota and micropollutant transformation by ascomycetes remains underexplored. Here, we assayed 53 Ascomycota isolates from 10 genera for the removal of 22 micropollutants. Notably, 9 out of 22 micropollutants were removed from fungal culture supernatant at efficacies >45%. Temporal analysis of the nine top- performing strains, highlighted remarkable potency of Cladosporium isolates in removal of multiple micropollutants. Importantly, Cladosporium considerably reduced the toxicity of a micropollutant cocktail based on growth assays. Metabolomics analyses identified oxidation for 5-methyl-1H-benzotriazole and citalopram, whereas methylation and carboxylation were observed for 5-chlorobenzotriazole. No transformation products were detected for ciprofloxacin, sulfamethoxazole, and sertraline, hinting their extensive degradation. These findings suggest micropollutant transformation via diverse catalytic routes by Cladosporium. Genome sequencing and proteomic analyses of the top-performing isolates were consistent with the observed transformations and tentatively identified the molecular apparatus, conferring micropollutant transformation. This unprecedented study brings novel insight into the micropollutant transformation and detoxification capabilities of the prevalent Cladosporium species, thereby revealing a considerable and hitherto underappreciated potential of this genus and potentially other ascomycetes in micropollutant transformation. ImportanceAt present, conventional wastewater treatment plants (WWTPs) are not designed for removing micropollutants, which are released into aqueous systems. This raises concerns due to the poor insight into micropollutant long-term interplay with biological systems. Innovating biotechnological solutions to tackle micropollutant require addressing the paucity of knowledge on microbial groups and molecular pathways, which mediate micropollutant transformation. Our study highlights the considerable potential of the Cladosporium genus that remains underexplored in the arena of micropollutant transformation. We report the first genomes sequences for three Cladosporium species: C. allicinum, C. inversicolor, and C. fusiforme, which sets the stage for further analyses of micropollutant transformation, but also offers an important resource on this ecologically significant, albeit under-studied genus and related Ascomycota.

microbiology↗