Biology subjects

Hao, N.

Publications and source records attributed to Hao, N..

At least 19 recordsLinked to original sources

bioRxiv2026

RECON infers regions of interest from H&E images and reconstructs whole-slide molecular profiles at single-cell resolution

Spatial omics technologies resolve molecular expression and spatial architecture at single-cell resolution, but profiling whole slides remains costly. In practice, only a few regions of interest (ROIs) are profiled, leaving the rest of the tissue unmeasured. S2-omics was the first framework to unify ROI selection with out-of-ROI prediction, but it operates on superpixels rather than individual cells and predicts discrete cell types rather than continuous molecular profiles. Superpixel-based representations do not explicitly preserve cell boundaries, while categorical cell-type labels cannot quantify molecular expression within cells. Here we present RECON, a two-stage framework that performs ROI inference and whole-slide molecular reconstruction at single-cell resolution, predicting both continuous molecular profiles and discrete cell-type labels. In the first stage, RECON extracts morphological and microenvironmental features from individual cells to identify a representative ROI for spatially resolved single-cell molecular profiling. In the second stage, RECON trains deep learning models on molecular measurements acquired within the selected ROI and reconstructs transcriptomic or proteomic profiles for all remaining cells on the slide. Benchmarked against pathologist annotations, RECONs ROI selection outperforms the superpixel-based S2-omics approaches (IoU: 0.75 versus 0.64). For transcriptomics, refining the modeling unit from superpixels to single cells improves per-gene Pearson correlation by 22%. For proteomics, RECON surpasses the current state-of-the-art method, ROSIE, across all 16 markers, with a median per-cell Pearson correlation of 0.91 versus 0.84. Moreover, RECON delineates tumour boundaries and regions with distinct immune-cell densities, and highlights candidate tertiary lymphoid structures. Together, these results demonstrate that RECON enables informative ROI selection and whole-slide molecular reconstruction at single-cell resolution for both spatial transcriptomics and spatial proteomics.

bioinformatics↗

bioRxiv2026

Long-lived yeast-derived lipids promote longevity via regional and systemic metabolic remodeling

Aging is marked by a progressive breakdown of intestinal integrity and metabolic homeostasis, which together drives systemic decline in physiology and reduces lifespan. Here, we found that dietary lipids extracted from a genetically engineered long-lived yeast strain robustly extend lifespan in Drosophila and further uncovered the mechanisms using deuterium oxide-probed stimulated Raman scattering microscopy to image metabolic dynamics and single nucleus RNA sequencing (scRNA-seq) to unveil the underlying pathways. These yeast lipids are enriched in shorter, more saturated fatty acids and phospholipids as revealed by Raman spectroscopy and lipidomics, contributing to increased membrane order and reduced lipid storage. Functionally, targeted dietary supplementation with these lipid components synergistically prolongs fly lifespan. We show that these lipids reverse age-related declines in gut lipid droplet abundance, enhance membrane lipid incorporation, and increase de novo lipid synthesis, thereby improving epithelial structural integrity and barrier function. snRNA-seq identifies transcriptional remodeling in metabolically active enterocytes, including upregulation of autophagy and protein turnover genes, alongside reduction of unsaturated fatty acid biosynthesis. In the brain, dietary lipids orchestrate a dual metabolic strategy--promoting energy conservation and enhanced signaling across most neuronal and glial populations, while selectively boosting mitochondrial function in memory-critical Kenyon cells. All these leads to the enhancement of gut-to-glia communication, particularly through EGFR and FGFR pathways. Finally, analysis of our data with the Fly Metabolic Analysis Pipeline (FLY-MAP) reveals that yeast lipids restructure gut metabolic modules to coordinate energy production, redox balance, and nutrient flexibility. Our study uncovers a cross-kingdom mechanism of metabolic longevity regulation, paving the way for leveraging yeast-derived nutritional components to support tissue homeostasis and promote healthy aging.

molecular biology↗

bioRxiv2025

BudFinder: A Masked Auto-Encoder Vision Transformer Framework for Yeast Budding Detection

Yeast replicative lifespan is a crucial part of aging research, yet its quantification remains labor-intensive and time-consuming, particularly when using time-lapse imaging and microfluidics. Manual counting methods for cell division events are prone to bias and inefficiency, while existing automated approaches often require extensive annotated datasets. These limitations hinder the adaptability of such tools across different microfluidic setups. To address these challenges, we propose a versatile image analysis approach that accurately detects yeast cell division events. To reduce the burden of requiring a large cell division annotated dataset, we pretrained a Masked Auto-Encoder on large-scale segmented yeast cell images. This substantially reduced the annotated data needed to train the transformer model for detecting cellular division events. Additionally, the model is trained directly on budding event detection, circumventing reliance on arbitrary heuristics, such as changes in cell area. By leveraging self-supervised pretraining, we reduced the training data requirement to fewer than 50 mother cells ([~]1,000 divisions), representing a >5-fold reduction compared to prior methods while maintaining comparable accuracy. Author SummaryOur work addresses a longstanding challenge in in live-cell time-lapse microscopy analysis, namely, automating cellular division tracking while minimizing the amount of training data required. Traditionally, scientists identify each division event by manually inspecting thousands of time-lapse images, a process that is both tedious and prone to bias. While automated tools exist, they often require large amounts of annotated data to work effectively, limiting their use across different experimental setups. To overcome these barriers, we developed BudFinder, which can recognize and track cell divisions with far less training data. Using yeast replicative aging data as an example, we first trained a model to understand what a yeast cell "looks like", using tens of thousands of segmented yeast cell images entrapped in our custom-built microfluidic device. Then, we taught it to detect budding events directly from time-lapse movies. This approach reduces the need for manual labeling by more than five-fold compared to previous structures in place, while maintaining accuracy comparable to existing methods. By making high-throughput analysis of cellular division more accessible, our work paves the way for faster and more scalable quantification of cellular dynamics.

systems biology↗

bioRxiv2025

Boosting Cellular Longevity Through Intracellular ATP Modulation

Mitochondrial dysfunction and declining ATP production are common features of aging, yet whether ATP availability itself directly regulates cellular lifespan. However, the causal relationship between cellular ATP homeostasis and aging has not been established. Here, we developed a synthetic system to manipulate intracellular ATP independently of endogenous energy production by expressing a plasma membrane-targeted nucleotide transporter, NTT1, from the intracellular parasite Encephalitozoon cuniculi in Saccharomyces cerevisiae. NTT1 expression depleted intracellular ATP in the absence of extracellular ATP, whereas ATP supplementation produced robust NTT1-dependent ATP uptake and increased intracellular ATP abundance. ATP availability strongly influenced replicative lifespan: ATP depletion shortened lifespan, whereas ATP supplementation restored and extended lifespan in NTT1-expressing cells. Unexpectedly, extracellular ATP also extended lifespan in wild-type cells that lack ATP import, revealing an NTT1-independent response to extracellular ATP. Transcriptomic analyses showed that NTT1- mediated ATP import suppresses glucose uptake, carbohydrate catabolism, mitochondrial respiration, and autophagy, whereas extracellular ATP elicits a distinct transcriptional response in wild-type cells involving metabolic, mitochondrial, and signaling pathways. Single-cell aging analyses further showed that ATP supplementation extends lifespan across distinct aging trajectories and shifts cells away from the mitochondrial dysfunction-associated aging state. Finally, experiments in cells lacking mitochondrial DNA separated these effects mechanistically: NTT1-associated lifespan phenotypes and high-ATP toxicity required functional mitochondria, whereas extracellular ATP extended lifespan in wild-type cells independently of mitochondrial respiration. Together, these findings demonstrate that ATP availability is a direct regulator of cellular aging and reveal distinct metabolic and extracellular ATP-responsive routes through which cellular energy state influences longevity. SignificanceCellular energy homeostasis is a crucial factor in determining the health and longevity of organisms. While intracellular ATP levels are tightly regulated, the idea that cells can directly take in extracellular ATP to influence metabolism has not been thoroughly explored. In this study, we engineered yeast cells to import external ATP and demonstrated that this approach significantly alters mitochondrial function, metabolic flow, and aging processes. Our findings show that ATP uptake inhibits catabolic pathways and modulates mitochondrial bioenergetics function, thereby extending cellular lifespan through a novel and non-traditional mechanism. This research reveals an unexpected degree of metabolic flexibility and introduces a synthetic biology-based method to reprogram energy metabolism and longevity. The principles established in this study provide a new framework for understanding the role of cellular bioenergetics in aging, highlighting how the modulation of ATP availability can impact metabolic states and lifespan regulation.

molecular biology↗

bioRxiv2025

Evolved microbial diversity enables combinatoric biosensing in complex environments

Whole-cell biosensors (WCBs) offer rapid, cost-effective monitoring of environmental contamination and human disease. Current WCB efforts to optimize detection of single target analytes under laboratory conditions have achieved vastly improved performance, setting the stage for WCB deployment in complex environments. We propose a framework that leverages the cross-specificity of single-target WCBs to quantify multiple targets using supervised machine learning. Specifically, we engineer six sensors for heavy metal contaminants in laboratory E. coli. We then evolve the strain to generate five chassis with improved growth in seawater conditions. We transform the chassis with the sensors, creating a set of 30 variants. The variant dynamic responses are characterized with microfluidics, revealing significant diversity. Leveraging this diversity, we construct a consortium to combinatorically quantify multiple analytes with machine learning, outperforming single-target biosensors in over 90% of our test samples. These results form a generalizable framework that facilitates WCB translation toward settings beyond the laboratory.

bioengineering↗

bioRxiv2024

Tardigrade Dsup: Interactions with DNA and protection of cells from oxidative stress

The remarkable capability of Tardigrade to survive under extreme conditions has been partially attributed to Dsup, an intrinsically disordered, highly positively charged protein. Dsup has been shown to bind to DNA in vitro, a property that has been associated with the capability of Dsup to exhibit stress-protective effects when expressed in mammalian cells. However, DNA binding of Dsup has not been visualized in living cells and expression of Dsup in different cell types was associated with either protective or detrimental effects. In addition, the effect of Dsup expression has not been clearly demonstrated at the organism level. Here we combined molecular dynamics (MD) simulations and fluorescence lifetime imaging microscopy (FLIM)-Forster resonance energy transfer (FRET) to interrogate Dsup-DNA interactions and demonstrated Dsup binding to DNA in living mammalian cells. Furthermore, Dsup expression in both HEK293T cells and yeast enhanced cell survival in the presence of hydrogen peroxide, suggesting that the presence of Dsup allows both mammalian and yeast cells to better cope with oxidative stress conditions. This study provides a better understanding of the property and functional role of Dsup and lays a foundation to explore new approaches to enhance stress resistance.

biophysics↗

bioRxiv2024

An Iterative Approach to Polish the Nanopore Sequencing Basecalling for Therapeutic RNA Quality Control

Nucleotide modifications deviate nanopore sequencing readouts, therefore generating artifacts during the basecalling of sequence backbones. Here, we present an iterative approach to polish modification-disturbed basecalling results. We show such an approach is able to promote the basecalling accuracy of both artificially-synthesized and real-world molecules. With demonstrated efficacy and reliability, we exploit the approach to precisely basecall therapeutic RNAs consisting of artificial or natural modifications, as the basis for quantifying the purity and integrity of vaccine mRNAs which are transcribed in vitro, and for determining modification hotspots of novel therapeutic RNA interference (RNAi) molecules which are bioengineered (BioRNA) in vivo.

bioinformatics↗

bioRxiv2024

Training Data Diversity Enhances the Basecalling of Novel RNA Modification-Induced Nanopore Sequencing Readouts

Accurately basecalling sequence backbones in the presence of nucleotide modifications remains a substantial challenge in nanopore sequencing bioinformatics. It has been extensively demonstrated that state-of-the-art basecallers are less compatible with modification-induced sequencing signals. A precise basecalling, on the other hand, serves as the prerequisite for virtually all the downstream analyses. Here, we report that basecallers exposed to diverse training modifications gain the generalizability to analyze novel modifications. With synthesized oligos as the model system, we precisely basecall various out-of-sample RNA modifications. From the representation learning perspective, we attribute this generalizability to basecaller representation space expanded by diverse training modifications. Taken together, we conclude increasing the training data diversity as a novel paradigm for building modification-tolerant nanopore sequencing basecallers.

bioinformatics↗

bioRxiv2024

Study of Impacts of Two Types of Cellular Aging on the Yeast Bud Morphogenesis

Understanding the mechanisms of cellular aging processes is crucial for attempting to extend organismal lifespan and for studying age-related degenerative diseases. Yeast cells divide through budding, providing a classical biological model for studying cellular aging. With their powerful genetics, relatively short lifespan and well-established signaling pathways also found in animals, yeast cells offer valuable insights into the aging process. Recent experiments suggested the existence of two aging modes in yeast characterized by nucleolar and mitochondrial declines, respectively. In this study, by analyzing experimental data it was shown that cells evolving into those two aging modes behave differently when they are young. While buds grow linearly in both modes, cells that consistently generate spherical buds throughout their lifespan demonstrate greater efficacy in controlling bud size and growth rate at young ages. A three-dimensional chemical-mechanical model was developed and used to suggest and test hypothesized mechanisms of bud morphogenesis during aging. Experimentally calibrated simulations showed that tubular bud shape in one aging mode could be generated by locally inserting new materials at the bud tip guided by the polarized Cdc42 signal during the early stage of budding. Furthermore, the aspect ratio of the tubular bud could be stabilized during the late stage, as observed in experiments, through a reduction on the new cell surface material insertion or an expansion of the polarization site. Thus model simulations suggest the maintenance of new cell surface material insertion or chemical signal polarization could be weakened due to cellular aging in yeast and other cell types. Significance StatementAging yeast exhibits two modes with different bud shapes. Experimental data analysis reveals that control of growth rate and bud size is more robust in cells aging in a spherical budding mode than in cells aging in a tubular budding mode. A computational model was developed and used in combination with experiments to test the hypothesized mechanisms underlying different types of budding in aging cells. Model simulations suggest that localized growth is sufficient to generate tubular budding and its aspect ratio can be stabilized through the regulation of chemical signals with an expanding polarization site or a decline on the new cell surface material insertion. Proposed mechanisms of morphological changes in aging yeast can be present in other cell types.

biophysics↗

bioRxiv2023

Adapting Nanopore Sequencing Basecalling Models for Modification Detection via Incremental Learning and Anomaly Detection

We leverage machine learning approaches to adapt nanopore sequencing basecallers for nucleotide modification detection. We first apply the incremental learning technique to improve the basecalling of modification-rich sequences, which are usually of high biological interests. With sequence backbones resolved, we further run anomaly detection on individual nucleotides to determine their modification status. By this means, our pipeline promises the single-molecule, single-nucleotide and sequence context-free detection of modifications. We benchmark the pipeline using control oligos, further apply it in the basecalling of densely-modified yeast tRNAs and E.coli genomic DNAs, the cross-species detection of N6-methyladenosine (m6A) in mammalian mRNAs, and the simultaneous detection of N1-methyladenosine (m1A) and m6A in human mRNAs. Our IL-AD workflow is available at: https://github.com/wangziyuan66/IL-AD.

bioinformatics↗

bioRxiv2023

Using Deep Learning to Decipher the Impact of Telomerase Promoter Mutations on the Morpholome

Melanoma showcases a complex interplay of genetic alterations and cellular morphological changes during metastatic transformation. While pivotal, the role of specific mutations in dictating these changes still needs to be fully elucidated. Telomerase promoter mutations (TPMs) significantly influence melanomas progression, invasiveness, and resistance to various emerging treatments, including chemical inhibitors, telomerase inhibitors, targeted therapy, and immunotherapies. We aim to understand the morphological and phenotypic implications of the two dominant monoallelic TPMs, C228T and C250T, enriched in melanoma metastasis. We developed isogenic clonal cell lines containing the TPMs and utilized dual-color expression reporters steered by the endogenous Telomerase promoter, giving us allelic resolution. This approach allowed us to monitor morpholomic variations induced by these mutations. TPM-bearing cells exhibited significant morpholome differences from their wild-type counterparts, with increased allele expression patterns, augmented wound-healing rates, and unique spatiotemporal dynamics. Notably, the C250T mutation exerted more pronounced changes in the morpholome than C228T, suggesting a differential role in metastatic potential. Our findings underscore the distinct influence of TPMs on melanomas cellular architecture and behavior. The C250T mutation may offer a unique morpholomic and systems-driven advantage for metastasis. These insights provide a foundational understanding of how a non-coding mutation in melanoma metastasis affects the system, manifesting in cellular morpholome.

systems biology↗

bioRxiv2023

Elf1 promotes Rad26 interaction with lesion-arrested Pol II for transcription-coupled repair

Transcription-coupled nucleotide excision repair (TC-NER) is a highly conserved DNA repair pathway that removes bulky lesions in the transcribed genome. Cockayne syndrome B protein (CSB), or its yeast ortholog Rad26, has been known for decades to play important roles in the lesion-recognition steps of TC-NER. Another conserved protein ELOF1, or its yeast ortholog Elf1, was recently identified as a core transcription-coupled repair factor. How Rad26 distinguishes between RNA polymerase II (Pol II) stalled at a DNA lesion or other obstacles and what role Elf1 plays in this process remains unknown. Here, we present cryo-EM structures of Pol II-Rad26 complexes stalled at different obstacles that show that Rad26 uses a universal mechanism to recognize a stalled Pol II but interacts more strongly with a lesion-arrested Pol II. A cryo-EM structure of lesion-arrested Pol II-Rad26 bound to Elf1 revealed that Elf1 induces new interactions between Rad26 and Pol II when the complex is stalled at a lesion. Biochemical and genetic data support the importance of the interplay between Elf1 and Rad26 in TC-NER initiation.

biophysics↗

bioRxiv2023

Enhanced cellular longevity arising from environmental fluctuations

Cellular longevity is regulated by both genetic and environmental factors. However, the interactions of these factors in the context of aging remain largely unclear. Here, we formulate a mathematical model for dynamic glucose modulation of a core gene circuit in yeast aging, which not only guided the design of pro-longevity interventions, but also revealed the theoretical principles underlying these interventions. We introduce the dynamical systems theory to capture two general means for promoting longevity - the creation of a stable fixed point in the "healthy" state of the cell and the dynamic stabilization of the system around this healthy state through environmental oscillations. Guided by the model, we investigate how both of these can be experimentally realized by dynamically modulating environmental glucose levels. The results establish a paradigm for theoretically analyzing the trajectories and perturbations of aging that can be generalized to aging processes in diverse cell types and organisms.

systems biology↗

bioRxiv2023

Quantifying dynamic pro-inflammatory gene expression and heterogeneity in single macrophage cells

Macrophages must respond appropriately to pathogens and other pro-inflammatory stimuli in order to perform their roles in fighting infection. One way in which inflammatory stimuli can vary is in their dynamics - that is, the amplitude and duration of stimulus experienced by the cell. In this study, we performed long-term live cell imaging in a microfluidic device to investigate how the pro-inflammatory genes IRF1, CXCL10, and CXCL9 respond to dynamic interferon-gamma (IFN{gamma}) stimulation. We found that IRF1 responds to low concentration or short duration IFN{gamma} stimulation, whereas CXCL10 and CXCL9 require longer or higher-concentration stimulation to be expressed. We also investigated the heterogeneity in the expression of each gene and found that CXCL10 and CXCL9 have substantial cell-to-cell variability. In particular, the expression of CXCL10 appears to be largely stochastic with a subpopulation of non-responding cells across all the stimulation conditions tested. We developed both deterministic and stochastic models for the expression of each gene. Our modeling analysis revealed that the heterogeneity in CXCL10 can be attributed to a slow chromatin-opening step that is on a similar timescale to that of adaptation of the upstream signal. In this way, CXCL10 expression in individual cells can remain stochastic in response to each pulse of repeated simulations, as validated by experiments. Together, we conclude that pro-inflammatory genes in the same signaling pathway can respond to dynamic IFN{gamma} stimulus with very different response features and that upstream signal adaptation can contribute to shaping the features of heterogeneous gene expression.

systems biology↗

bioRxiv2021

Age-dependent aggregation of ribosomal RNA-binding proteins links deterioration in chromatin stability with loss of proteostasis

Chromatin instability and loss of protein homeostasis (proteostasis) are two well-established hallmarks of aging, which have been considered largely independent of each other. Using microfluidics and single-cell imaging approaches, we observed that, during the replicative aging of S.cerevisiae, proteostasis decline occurred specifically in the fraction of cells with decreased stability at the ribosomal DNA (rDNA) region. A screen of 170 yeast RNA-binding proteins identified ribosomal RNA (rRNA)- binding proteins as the most enriched group that aggregate upon a decrease in rDNA stability. We further found that loss of rDNA stability contributes to age-dependent aggregation of rRNA-binding proteins through aberrant overproduction of rRNAs. These aggregates negatively impact nucleolar integrity and global proteostasis and hence limit cellular lifespan. Our findings reveal a mechanism underlying the interconnection between chromatin instability and proteostasis decline and highlight the importance of cell-to-cell variability in aging processes.

cell biology↗

bioRxiv2021

Age-induced P-bodies become detrimental and shorten the lifespan of yeast

Aging is an irreversible process characterized by a progressive loss of homeostasis in cells, which often manifests as protein aggregates. Recently, it has been speculated that aggregates of RNA-binding proteins (RBPs) may go through pathological transitions during aging and drive the progression of ageassociated neurodegenerative diseases. Using Saccharomyces cerevisiae as a model system of aging, we find that P-bodies --an RBP granule that is formed and can be beneficial for cell growth during stress conditions -- naturally form during aging without any external stresses and an increase in P-body intensity is negatively correlated with the future lifespan of yeast cells. When mother cells transfer age-induced P-bodies to daughter cells, the mother cells extend lifespan, while the daughter cells grow poorly, suggesting that these age-induced P-bodies may be directly pathological. Furthermore, we find that suppressing acidification of the cytosol during aging slows down the increase in the intensity of P-body foci and extends lifespan. Our data suggest that acidification of the cytosol may facilitate the pathological transition of RBP granules during aging.

cell biology↗

bioRxiv2020

Cell cycle-gated feedback control mediates desensitization to interferon stimulation

Cells use sophisticated molecular circuits to interpret and respond to extracellular signal factors, such as hormones and cytokines, which are often released in a temporally varying fashion. In this study, we focus on type I interferon (IFN) signaling in human epithelial cells and combine microfluidics, time-lapse microscopy, and computational modeling to investigate how the IFN-responsive regulatory network operates in single cells to process repetitive IFN stimulation. We found that IFN- pretreatments lead to opposite effects, priming versus desensitization, depending on the input durations. These effects are governed by a regulatory network composed of a fast-acting positive feedback loop and a delayed negative feedback loop, mediated by upregulation of ubiquitin-specific peptidase 18 (USP18). We further revealed that USP18 upregulation can only be initiated at the G1 and early S phases of cell cycle upon the treatment onset, resulting in heterogeneous and delayed induction kinetics in single cells. This cell cycle gating provides a temporal compartmentalization of feedback control processes, enabling duration-dependent desensitization to repetitive stimulations. Moreover, our results, highlighting the importance of IFN dynamics, may suggest time-based strategies for enhancing the effectiveness of IFN pretreatment in clinical applications against viruses, such as SARS-CoV-2.

systems biology↗

bioRxiv2019

A Protein Kinase A-Regulated Network Encodes Short- and Long-Lived Cellular Memory

Cells can store memories of prior experiences to modulate their responses to subsequent stresses, as seen for the protein kinase A (PKA)-mediated general stress response in yeast, which is required for resistance against future stressful conditions. Using microfluidics and time-lapse microscopy, we quantitatively analyzed how cellular memory of stress adaptation is encoded in single yeast cells. We found that cellular memory is biphasic. Short-lived memory was mediated by trehalose synthase and trehalose metabolism. Long-lived memory was mediated by PKA-regulated stress-responsive transcription factors and cytoplasmic messenger ribonucleoprotein (mRNP) granules. Strikingly, short- and long-lived memory could be selectively induced by different priming input dynamics. Computational modeling revealed how the PKA-mediated regulatory network could encode previous stimuli into memories with distinct dynamics. This biphasic memory-encoding scheme, analogous to innate and adaptive immune responses in mammals, might represent a general strategy to prepare for future challenges in rapidly changing environments.

systems biology↗