Biology subjects

Peng, K.

Publications and source records attributed to Peng, K..

16 recordsLinked to original sources

bioRxiv2026

AtlasOT - The Fused Unbalanced Gromov-Wasserstein for Multimodal Integration of Disease Atlases

Single-cell and spatial multiomics technologies are transforming disease atlas construction, but computational integration of unpaired modalities remains challenging, as existing methods overlook two biological constraints of data with matching samples. First, cells should only be mapped across modalities within the same donor or biospecimen, and second, cell recovery frequently differs substantially between modalities. To address these gaps, we present AtlasOT, an optimal-transport framework based on the fused unbalanced Gromov-Wasserstein (FUGW) formulation for multi-modal integration. AtlasOT jointly models a shared cross-modality feature space and modality-specific geometric structures while restricting transport to within-sample cell pairs. Moreover, AtlasOT relaxes strict mass conservation of the balanced optimal transport optimization to accommodate unbalanced cell numbers. We benchmark AtlasOT against state-of-the-art methods on scRNA-scATAC and scRNA-spatial transcriptomics mapping scenarios. Our results indicate that AtlasOT outperforms baselines and state-of-the-art methods in all considered scenarios. Moreover, we demonstrate that AtlasOT's transport plan can be used to improve several relevant tasks such as the detection of rare cell populations, spot-level cell-type deconvolution, spatial gene imputation, and reconstruction of transcription-factor-driven spatial regulatory dynamics. These results establish AtlasOT as a unified, biologically constrained framework for multimodal integration in disease atlas studies, with broad applicability to label transfer, imputation, and regulatory network analysis.

bioinformatics↗

bioRxiv2026

Development of GS-441524 Derivatives as Potent SARS-CoV-2 Mac1 Inhibitors via a Direct-to-Biology Approach

Targeting viral macrodomains (Mac) has emerged as a promising strategy for antiviral drug development, especially after the outbreak of COVID-19 that claimed millions of lives worldwide. Several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Mac1 inhibitors have been reported in the past few years. In the present work, we converted GS-441524 (IC50 of [~]10 M for SARS-CoV-2 Mac1) to KP-S54 (18c), a potent inhibitor of both SARS-CoV-2 Mac1 (IC50: 44 nM) and Middle East respiratory syndrome coronavirus (MERS-CoV) Mac1 (IC50: 91 nM) through an iterative direct-to-biology approach. This approach leverages efficient amide-coupling reaction and the mix-and-read fluorescence polarization (FP) assays where reaction mixtures could be screened directly without purification. Cocrystal structure of a selected derivative (12p) binding to SARS-CoV-2 Mac1 revealed the binding mode, which will guide future drug development against viral macrodomains.

pharmacology and toxicology↗

bioRxiv2026

Transdiagnostic Neurobiological Biotypes of Trauma Timing: Data-driven approach of Childhood and Adulthood-Onset Trauma

BackgroundThe developmental timing of trauma exposure may critically shape neurobiological outcomes, yet distinctions between childhood-onset trauma (CT) and adulthood-onset trauma (AT) remain poorly understood. AimThis study explores whether trauma onset timing is associated with distinct resting-state functional connectivity (rsFC) pattern using data-driven approach. MethodsSeventy-seven trauma-exposed individuals (Mage=36.74 years) with post-traumatic stress disorder (PTSD), PTSD with major depressive disorder (MDD), and trauma-exposed healthy controls (TEHC) underwent resting-state fMRI. Of these participants, 15 with CT only, 17 with both CT and AT, and 47 with AT only. RsFC was calculated across the amygdala, hippocampus, nucleus accumbens (NAcc), the salience (SN), default mode (DMN), and frontoparietal networks (FPN). K-means clustering identified subgroups based on rsFC, with robustness assessed via bootstrapping, cross-validation, and replication using Gaussian Mixture Modeling. The identified clusters were compared on trauma timing, type, cumulative exposure, and clinical measures. ResultsA two-cluster solution provided the most stable fit. The two generated clusters were significantly different in CT-only prevalence (p < 0.05; Cramers V = 0.26, 95% CI). The CT cluster was marked by hyperconnectivity between amygdala-FPN, DMN-SN, NAcc-SN, and hippocampus-FPN relative to the AT cluster. Individuals with both CT and AT were evenly distributed across clusters. Clusters did not differ in PTSD or comorbid diagnoses, trauma type, or cumulative exposure. ConclusionData-driven clustering revealed distinct neurobiological profiles differentiating CT and AT. CT was associated with hyperconnectivity across salience, reward, and regulatory circuits, supporting developmental timing as a determinant of brain network organization in trauma-exposed populations.

neuroscience↗

bioRxiv2026

A High-throughput Fluorescence Polarization Assay for Screening Sirtuin Inhibitors

Sirtuins (SIRTs), which remove protein lysine acyl modifications, play crucial roles in diverse cellular processes, including metabolism, gene transcription, DNA damage repair, cell survival, and stress response. Several sirtuins are considered non-oncogene addiction of cancer cells and promising targets for anticancer drug development. High-throughput screening (HTS) methods for sirtuins are critical for the development of potent and isoform-selective sirtuin inhibitors, which are needed to validate the therapeutic potential. Herein, we designed and synthesized a fluorescent polarization (FP) tracer, KP-SC-1. Using this high-affinity tracer, we developed a robust, high-throughput FP competition assay for screening SIRT1-3 inhibitors. The assay was validated by testing known SIRT1-3 inhibitors. The assay can detect NAD+-independent SIRT1-3 inhibitors, as well as NAD+-dependent inhibitors, such as Ex-527 and TM. Finally, our assay showed satisfactory stability and outstanding performance in a pilot library screening. Compared to previous assays, the FP assay uses much less SIRT1-3 enzymes, a feature important for high-throughput library screening. We believe that the FP assay developed here will accelerate the discovery and development of SIRT1-3 inhibitors.

biochemistry↗

bioRxiv2026

Polyploid cardiomyocytes define disease-specific transcriptional states in the mammalian heart

The adult mammalian heart has a limited regenerative capacity. Following injury, cardiomyocytes undergo a hypertrophic response accompanied by polyploidization, which has been described as a barrier to proliferation and regeneration of the heart1,2. However, the unique molecular programs of polyploidy, or genome multiplied cardiomyocytes, and their influence on the disease-related myocardial remodelling process remains unclear. Here, we integrate single-nuclei and high-resolution spatial multi-omics across human, rat, and mouse hearts to define novel cardiac cell states and their tissue niches in ischemic and non-ischemic heart disease. Computational analysis across scales allowed us to generate detailed networks of the cardiac tissue remodelling process as well as tissue and sub-cellular environments uniquely enriched in polyploid cardiomyocytes or their diploid origins. We identify a conserved, dichotomous transcriptional program distinguishing diploid from polyploid cardiomyocytes. Polyploid cardiomyocytes demonstrated rewired metabolic and chromatin-remodeling transcriptional programs and recapitulate the gene signature of immature human fetal cardiomyocytes. Notably, we observe that polyploid cardiomyocytes--rather than the general myocyte population--are the primary sites of enrichment for major heart-failure drug targets, including the mineralocorticoid, {beta}1-adrenergic, and glucagon-like peptide-1 receptors. Based on our cross-species dataset we further identified TNIK, a Wnt-pathway regulator expressed in polyploid cardiomyocytes across species, as a potential therapeutic target and demonstrate that pharmacological TNIK inhibition improves cardiac function after myocardial infarction in rats. Together, this species-spanning, disease-resolved study redefines cardiomyocyte heterogeneity in heart disease and suggests a therapeutic path to heart failure treatment by targeting polyploid cardiomyocytes.

genomics↗

bioRxiv2025

Synthesizing images to map neural networks to the human brain

Computational models can be used to generate hypotheses about the brain. In the visual system, this approach has revealed similarities between how natural images are represented in convolutional neural networks and in cortical regions. However, natural images generate highly correlated representations across the hierarchy of model layers, meaning that each brain region will not correspond selectively to a single layer. Because each model layer performs additional image transformations, gaining a more selective mapping between individual layers and regions could reveal how specific algorithmic stages of processing are instantiated in the brain. To enable this mapping, we developed a generative framework for image synthesis that minimizes the similarity of image representational similarity matrices across model layers, aiming to orthogonalize the distances between the patterns of unit activations evoked by the same set of images. With the patterns orthogonalized, the resulting similarity matrix for each layer provides a fingerprint of the unique computational role of that layer. To test this approach, we synthesized 16 artificial images from the Inception-V1/GoogLeNet model and scanned participants with fMRI while they viewed these images repeatedly in random order. Image-specific patterns of voxel activity were used to compute image-by-image similarity matrices across the whole brain with searchlights. Most layers could be mapped to circumscribed cortical regions, and these mappings overlapped less than the mappings obtained with natural images. Given the prevalence of existing fMRI datasets with natural images, we used the synthesis method as a benchmark to develop an alternative residual method that can achieve comparable performance for natural image datasets. These approaches could be extended to other neural network architectures and stimulus modalities for targeted mappings of model computations to the brain and behavior.

neuroscience↗

bioRxiv2025

Multi-Dimensional Spatiotemporal Attention Neural Network for Next Generation Sequencing Basecalling

Next-generation sequencing (NGS) remains the most used sequencing technique in the field of genomics. Traditional basecall methods face significant challenges in decoding high density sequencing data due to inherent noise in biochemical reactions and limitations of instruments. Here, we present a multi-dimensional deep learning neural network based on spatiotemporal attention mechanism named AICall. The network skips computationally heavy but less effective steps of peak finding and brightness extraction/correction, and directly basecalls from the time sequence of multi-dimensional image stacks obtained in real time. By introducing attention mechanism, it effectively extracts spatial and time-related key information including spatial crosstalk, spectral crosstalk, phasing, base-quenching, and intensity decay, and significantly improves basecall accuracy. We demonstrate that AICall achieves an average error rate less than 0.01% and provides more reliable sequencing results for downstream analysis.

bioinformatics↗

bioRxiv2024

Apoptotic caspases cleave DRP1 to promote mitochondrial fusion and anti-viral immune responses

Apoptosis has been recognized as a suicidal host-defense programmed cell death pathway against invading pathogens. However, recent evidences showed that viruses can employ caspases to cleave and inactivate immune signaling molecules to facilitate infection. Whether caspases can instead promote anti-viral immune responses is currently unknown. Here, we demonstrated that the NSs protein of RVFV triggers activation of apoptotic caspases, which cleave the mitochondrial fission factor DRP1 resulting in mitochondrial elongation. Elongated mitochondria promote MAVS aggregation leading to enhanced anti-viral immunity. Apoptotic caspases, including caspase-3, -6, -7 and -8, cleave DRP1 at the motifs of D500FAD503 and/or AEAD556, suggesting that this cleavage event may occur during infection of different viruses. Indeed, infection of H1N1, SeV and HSV-1 all triggered apoptotic caspases activation to cleave DRP1 promoting anti-viral immune responses. Compared with wild-type DRP1, introduction of caspase-resistant DRP1 strongly attenuated immune responses triggered by virus infection. These results revealed a mechanism through which apoptotic caspases promote anti-viral immunity by regulating mitochondrial morphodynamics.

microbiology↗

bioRxiv2023

Inducing representational change in the hippocampus through real-time neurofeedback

AO_SCPLOWBSTRACTC_SCPLOWWhen you perceive or remember one thing, other related things come to mind. This competition has consequences for how these items are later perceived, attended, or remembered. Such behavioral consequences result from changes in how much the neural representations of the items overlap, especially in the hippocampus. These changes can reflect increased (integration) or decreased (differentiation) overlap; previous studies have posited that the amount of coactivation between competing representations in cortex determines which will occur: high coactivation leads to hippocampal integration, medium coactivation leads to differentiation, and low coactivation is inert. However, those studies used indirect proxies for coactivation, by manipulating stimulus similarity or task demands. Here we induce coactivation of competing memories in visual cortex more directly using closed-loop neurofeedback from real-time fMRI. While viewing one object, participants were rewarded for implicitly activating the representation of another object as strongly as possible. Across multiple real-time fMRI training sessions, they succeeded in using the neurofeedback to induce coactivation. Compared with untrained objects, this coactivation led to behavioral and neural integration: The trained objects became harder for participants to discriminate in a categorical perception task and harder to decode from patterns of fMRI activity in the hippocampus.

neuroscience↗

bioRxiv2023

Mime: A flexible machine-learning framework to construct and visualize models for clinical characteristics prediction and feature selection

With the widespread use of high-throughput sequencing technologies, understanding biology and cancer heterogeneity has been revolutionized. Recently, several machine-learning models based on transcriptional data have been developed to accurately predict patients outcome and clinical response. However, an open-source R package covering state-of-the-art machine learning algorithms for user-friendly access has yet to be developed. Thus, we proposed a flexible computational framework to construct machine learning-based integration model with elegant performance (Mime). Mime streamlined the process of developing predictive models with high accuracy, leveraging complex datasets to identify critical genes associated with prognosis. An in silico combined model based on de novo PIEZO1-associated signatures constructed by Mime demonstrated high accuracy in predicting outcomes of patients compared with other published models. In addition, PIEZO1-associated signatures could also precisely infer immunotherapy response by applying different algorithms in Mime. Finally, SDC1 selected from PIEZO1-associated signatures presented high-potential role in glioma with targeted prospect. Taken together, our package provides a user-friendly solution for constructing machine learning-based integration models and will be greatly expanded to provide valuable insights into current fields.

bioinformatics↗

bioRxiv2022

SP1 affects the migration and invasion of laryngeal cancer cells by regulating methylation of claudin 4 promoter region through the p-JNK pathway

Claudin 4 (CLDN4) is abnormally expressed in various tumors, but the mechanisms controlling CLDN4 expression in laryngeal cancer are poorly understood. Here, we describe hypermethylation of the promoter region of the CLDN4 gene and a positive correlation between the expression of CLDN4 and transcription factor Sp1 in laryngeal carcinoma. Specifically, CLDN4 expression was downregulated when laryngeal cancer cells were treated with Sp1 transcription factor inhibitor MTM. Immunohistochemical staining showed that while the expression of CLDN4 and p-JNK was negatively correlated, p-JNK positively correlated with MMP-2 and MMP-9 expression. The expressions of p-JNK, MMP-2, and MMP-9 were significantly downregulated in HEp-2 cells transfected with CLDN4, decreasing migration and invasiveness of HEp-2 cells. Thus, we show that SP1-mediated hypermethylation of the CLDN4 promoter region may activate the JNK signaling pathway and increase MMP-2/MMP-9 expression, which can then affect the migration and invasiveness of laryngeal cancer cells. These results contribute to our understanding of the regulatory mechanisms of CLDN4 in laryngeal cancer and identify the Sp1-CLDN4-jnk signaling pathway-MMP-2/MMP-9 axis as a potential target for the treatment of laryngeal cancer.

cancer biology↗

bioRxiv2021

Virtual meetings promise to eliminate the geographical and administrative barriers and increase accessibility, diversity, and inclusivity

The COVID-19 pandemic brought a new set of unprecedented challenges not only for healthcare, education, and everyday jobs but also in terms of academic conferences. In this study, we investigate the effect of the broad adoption of virtual platforms for academic conferences as a response to COVID-19 restrictions. We show that virtual platforms enable higher participation from underrepresented minority groups, increased inclusion, and broader geographic distribution. We also discuss emerging challenges associated with the virtual conference format resulting in a decreased engagement of social activities, limited possibilities of cross-fertilization between participants, and reduced peer-to-peer interactions. Lastly, we conclude that a novel comprehensive approach needs to be adopted by the conference organizers to ensure increased accessibility, diversity, and inclusivity of post-pandemic conferences. Our findings provide evidence favoring a hybrid format for future conferences, marrying the strength of both in-person and virtual platforms.

scientific communication and education↗

bioRxiv2021

The genetic architecture of phenotypic diversity in the betta fish (Betta splendens)

The Betta fish displays a remarkable variety of phenotypes selected during domestication. However, the genetic basis underlying these traits remain largely unexplored. Here, we report a high-quality genome assembly and re-sequencing of 727 individuals representing diverse morphologies of the betta fish. We show that current breeds have a complex domestication history with extensive introgression with wild species. Using GWAS, we identify the genetic basis of multiple traits, including several coloration phenotypes, sex-determination which we map to DMRT1, and the long-fin phenotype which maps to KCNJ15. We identify a polygenic signal related to aggression with many similarities to human psychiatric traits, involving genes such as CACNB2 and DISC1. Our study provides a resource for developing the Betta fish as a genetic model for morphology and behavior in vertebrates.

genetics↗

bioRxiv2020

Yeast synthetic minimal biosensors for evaluating protein production

The unfolded protein response (UPR) is a highly conserved cellular response in eukaryotic cells to counteract endoplasmic reticulum (ER) stress, typically triggered by unfolded protein accumulation. In addition to its relevance to human diseases like cancer cell development, the induction of the UPR has a significant impact on recombinant protein production yields in microbial cell factories, including the industrial workhorse Saccharomyces cerevisiae. Being able to accurately detect and measure this ER stress response in single cells, enables the rapid optimisation of protein production conditions and high-throughput strain selection strategies. Current methodologies to monitor the UPR in S. cerevisiae are often temporally and spatially removed from the cultivation stage, or lack updated systematic evaluation. To this end we constructed and systematically evaluated a series of high-throughput UPR sensors by different designs, incorporating either yeast native UPR promoters or novel synthetic minimal UPR promoters. The native promoters of DER1 and ERO1 were identified to have suitable UPR biosensor properties and served as an expression level guide for orthogonal sensor benchmarking. Our best synthetic minimal sensor, SM1, was only 98 bp in length, had minimal homology to other native yeast sequences and displayed superior sensor characteristics. Using this synthetic minimal UPR sensor, we demonstrate its ability to accurately discriminate between cells expressing different heterologous proteins and at varying production levels. Our sensor is thus a novel high-throughput tool for determining expression/engineering strategies for optimal heterologous protein production.

synthetic biology↗

bioRxiv2019

Pain Stickiness in Complex Regional Pain Syndrome: A role for the Nucleus Accumbens

Some individuals with chronic pain experience improvement in their pain with treatment, whereas others do not. The neurobiological reason is unclear, but an understanding of brain structure and functional patterns may provide insights into pains responsivity to treatment. In this investigation, we used magnetic resonance imaging (MRI) techniques to determine grey matter density alterations on resting functional connectivity (RFC) strengths between pain responders and nonresponders. Brain metrics of pediatric patients at admission to an intensive pain rehabilitative treatment program were evaluated. Pain responders reported significant pain improvement at discharge and/or follow-up whereas nonresponders reported no improvements, increases in pain, or emergence of new pain symptoms. The pain (responder/nonresponder) groups were compared with pain-free healthy controls to examine predictors of pain responder status via brain metrics. Our results show: (1) on admission, pain nonresponders had decreased grey matter density (GMD) within the nucleus accumbens (NAc) and reduced RFC strength between the NAc and the dorsolateral prefrontal cortex vs. responders; (2) Connectivity strength was positively correlated with change in pain intensity from admission to discharge; (3) Compared with pain-free controls, grey matter and RFC differences emerged only among pain nonresponders; and (4) Using a discriminative model, combining GMD and RFC strengths assessed at admission showed the highest prediction estimate (87%) on potential for pain improvement, warranting testing in a de novo sample. Taken together, these results support the idea that treatment responsiveness on pain is underpinned by concurrent brain structure and resting brain activity.

neuroscience↗

bioRxiv2016

Shared neural basis for experiencing the beauty of human faces and visual art: Evidence from a meta-analyses of fMRI studies

The existence of a common beauty is a long-standing debate in philosophy and related disciplines. In the last two decades, cognitive neuroscientists have sought to elucidate this issue by exploring the common neural basis of the experience of beauty. Still, empirical evidence for such common neural basis of different forms of beauty is not conclusive. To address this question, we performed an activation likelihood estimation (ALE) meta-analysis on the existing neuroimaging studies of beauty appreciation of faces and visual art by non-expert adults (49 studies, 982 participants, meta-data are available at https://osf.io/s9xds/). We observed that perceiving these two forms of beauty activated distinct brain regions: while the beauty of faces convergently activated the left ventral striatum, the beauty of visual art convergently activated the anterior medial prefrontal cortex (aMPFC). However, a conjunction analysis failed to reveal any common brain regions for the beauty of visual art and faces. The implications of these results are discussed.

neuroscience↗