Biology subjects

Zeng, A.

Publications and source records attributed to Zeng, A..

At least 19 recordsLinked to original sources

bioRxiv2026

LplA-mediated rescue of lethal myopathy and cardiomyopathy in mitochondrial lipoylation-deficient mammalian caused by Lipt1

Inherited mitochondrial metabolic disorders impair cellular energy generation and often lead to fatal metabolic crises. Mitochondrial lipoylation defects represent a severe case of such disorders that can lead to lethality but lacks effective treatment so far. In this study, we generated a viable mouse model with muscle-specific deficiency of the lipoyltransferase coded by Lipt1 to provide an in vivo preclinical model that overcomes embryonic lethality. Using this model, we examined a bacterial lipoate protein ligase A (LplA)-mediated gene therapy via adeno-associated virus (AAV) delivery. By introducing LplA alongside lipoic acid supplementation, we reconstituted a salvage pathway that bypasses the mammalian endogenous lipoylation pathway. The intervention rescued premature lethality, recovered motor function and reversed hypertrophic cardiomyopathy in the Lipt1-deficient mouse model. Mechanistically, AAV-LplA reconstitutes mitochondrial protein lipoylation and oxidative phosphorylation in situ. This energetic rescue suppresses phosphoinositide 3-kinase (PI3K)-Akt hyperactivation, thereby restoring autophagic clearance and subsequently contributing to the recovery of the pathological phenotype. This study established AAV-LplA as a promising gene-delivery strategy for rescuing lethal mitochondrial lipoylation disorders.

cell biology↗

bioRxiv2026

Surface texture guides egg-laying decisions in Aedes aegypti mosquitoes

Mosquitoes undergo development as aquatic larvae and pupae before emerging as terrestrial adults. Accordingly, blood-fed and mated female mosquitoes must select an appropriate egg-laying site to maximize the fitness of their offspring. Female yellow fever mosquitoes (Aedes aegypti) lay their eggs above the waterline of small containers or natural bodies of water, where they can remain dormant for many months until they are submerged and hatch. Here, we show that female mosquitoes use surface texture as a powerful cue to guide egg-laying decisions, selecting rougher textures over smooth when choosing among containers and when selecting specific sites within a given substrate. In addition, we identify an interaction between substrate texture and water salinity with respect to egg-laying decisions, demonstrating that female mosquitoes integrate competing cues to determine the ultimate suitability of an egg-laying site. Finally, we explore the dynamics of local egg-laying search behaviour, demonstrating that texture modulates traversal speed while mosquitoes search for appropriate egg-laying sites.

animal behavior and cognition↗

bioRxiv2026

Cell Type Architecture and Positional Gene Gradients in an Adult Animal at Subcellular Resolution

The spatial organization of cell types and gene expression underlies tissue architecture and organismal physiology. However, resolving complete cellular and molecular landscapes within a three-dimensional context remains challenging, particularly in organisms with high cellular heterogeneity and complex geometry. Here, we developed a semi-supervised workflow to reconstruct high-resolution three-dimensional spatial transcriptomic models of the planarian Schmidtea mediterranea at single-cell resolution. Planarians are basal bilaterians capable of regenerating body structures after injury. Our reconstruction maps the distribution of cell types and spatially patterned gene expression across the intact organism and identifies 119 candidate positional control genes (PCGs). These genes are expressed across muscle, neural, and epidermal populations. Functional perturbation of selected candidates, including pitx3, ptpn11, pi4ka, upf3b, and cul1, revealed roles in regeneration following injury. In addition, we identify intestinal cells as prominent components of the microenvironment surrounding adult tgs1 pluripotent stem cells (neoblasts). Together, these results demonstrate the utility of three-dimensional spatial transcriptomic reconstruction for mapping cellular architecture and positional gene regulation in complex adult organisms.

developmental biology↗

bioRxiv2026

4D Single-Cell Spatial Transcriptomics Reveals Dynamic Morphogenetic Gradients and Regenerative Domains in Planarians

Regeneration relies on precise spatiotemporal gene expression and cellular responses to establish tissue identity and body patterning. Using high-resolution Stereo-seq (715 nm) on 353 sections from 16 whole animals at 8 regeneration timepoints, we constructed a 4D spatiotemporal transcriptomic map of planarian regeneration. Our analysis captured 36 refined cell types from 3,508,004 segmented cells, enabling genome-wide transcriptional imputation of gene expression dynamics across body axes at cellular, tissue, and organismal scales. We identified dynamic positional gradients and distinct spatially distributed cell types during regeneration, including an injury-induced Anterior Regenerative Zone (ARZ). The ARZ exhibited enriched positional signals in epidermal, muscle, and neural cells and was regulated by Mediator 8, which is crucial for polarity remodeling and blastema formation. This study provides a comprehensive spatial molecular and cellular map of regenerative processes, highlighting injury-induced spatial domains and key regulatory factors in planarian regeneration. We also provide an interactive web portal, offering a valuable resource for exploring and analyzing regeneration mechanisms in a spatiotemporal context.

developmental biology↗

bioRxiv2025

Disentangling Superpositions: Interpretable Brain Encoding Model with Sparse Concept Atoms

Encoding models using word embeddings or artificial neural network (ANN) features reliably predict brain responses to naturalistic stimuli, yet interpreting these models remains challenging. A central limitation is superposition: distinct semantic features become entangled along correlated directions in dense embeddings when latent features outnumber embedding dimensions. This entanglement renders regression weights non-identifiable--different combinations of semantic directions can produce identical predictions, precluding principled interpretation of voxel selectivity. To address this, we introduce the Sparse Concept Encoding Model, which transforms dense embeddings into a higher-dimensional, sparse, non-negative space of learned concept atoms. This transformation yields an axis-aligned semantic basis where each dimension corresponds to an interpretable concept, enabling direct readout of conceptual selectivity from voxel weights. When applied to fMRI data collected during story listening, our model matches the prediction performance of conventional dense models while substantially enhancing interpretability. It enables novel neuroscientific analyses such as disentangling overlapping cortical representations of time, space, and number, and revealing structured similarity among distributed conceptual maps. This framework offers a scalable and interpretable bridge between ANN-derived features and human conceptual representations in the brain.

neuroscience↗

bioRxiv2025

Plakophilin-2 Coordinates Energy Metabolism and Contractility in Cardiomyocytes, Revealing Its Roles beyond Desmosomes

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a familial cardiac disease associated with ventricular arrhythmias and an increased risk of sudden cardiac death. Mutations in the desmosome gene Plakophilin-2, PKP2, lead to reduction in PKP2 protein and collapse of desmosomes that is known to compromise contractility and electrical stability of cardiomyocytes. Our previous studies demonstrated the efficacy of adeno-associated virus 9 (AAV9)-mediated restoration of PKP2 expression in a cardiac specific knock-out mouse model of Pkp2 and revealed profound changes in mRNA signatures of metabolic enzymes that were reversed by the gene replacement approach. In this study, we used PKP2-deficient mouse hearts and human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to identify changes in steady-state metabolite levels associated with impaired lipid homeostasis, glycolysis, and glucose oxidation. These metabolic phenotypes align with human ARVC metabolic data and reflect an intrinsic impairment of cellular energy metabolism. Here we showed for the first time that these intracellular metabolic defects were associated specifically with poor contractility of cardiomyocytes. AAV9:PKP2 restored contractility, improved electrophysiological properties and Ca2+ transients. In contrast, we observed that treating PKP2-deficient cardiomyocytes pharmacologically with small molecule metabolic enhancers improved contractility but not electrophysiological properties and Ca2+ transients, suggesting differential sensitivity of structure-mediated functions in response to metabolic perturbance. Our study modeled and revealed a direct intracellular connection between compromised PKP2 function and metabolic impairment. We proposed that an increased risk of decoupling energy-responsive contractility from less energy-responsive electrical activities can be a new arrhythmogenic mechanism, potentially responsible for exercise-triggered cardiac adversity in ARVC disease development and progression.

cell biology↗

bioRxiv2024

Bacterial lipoate protein ligases rescue lipoylation and respiration deficiency in mammals

Human lipoylation pathway deficiencies caused by LIPT2/LIAS/LIPT1 gene mutations lead to inherited metabolic disorders characterized by severe defects of mitochondrial energy and amino acids metabolism. Patients with such mutations suffer from hyperlactic acidemia, encephalopathy, hypotonia and early death. So far there is no effective treatment. Here we introduced the bacteria salvage lipoylation pathway, which is absent in eukaryotes, into lipoylation defective human cells and mouse models. Both E. coli-derived LplA and B. subtilis-derived LplJ restored the phenotypes of LIPT2/LIAS/LIPT1 gene knockout cells to those of wildtype cells with lipoic acid supplementation. Biochemical and isotope tracing analysis demonstrated LplA and LplJ function through direct lipoylation of the H protein of glycine cleavage system and the E2 subunits of 2-oxoacid dehydrogenases, thereby reactivating the short-circuited TCA cycle and amino acids metabolism. This strategy is further extended to treat lipoyl precursor supply defects caused by MECR and FDX1 mutations and its efficacy and safety are validated in Lipt1-/- and LplAOE/+ mouse models. This study provides systematic characterization of lipoylation deficiency and paves the way to gene therapy for treatment of lipoylation-deficient patients.

cell biology↗

bioRxiv2024

Toward De Novo Protein Design from Natural Language

Programming biological function-designing bespoke proteins to perform specified molecular tasks-is a foundational goal of molecular engineering. However, current design paradigms remain fundamentally limited: they typically require either natural proteins as starting points for optimization or manual reformulation of functional goals as geometric and sequence-level constraints to guide candidate generation. Here we introduce Pinal, a 16-billion-parameter foundation model that designs candidate proteins from natural-language descriptions of desired function. Trained on 1.7 billion synthetically annotated protein-text pairs, Pinal links functional intent to protein sequence and structure. In computational evaluations, generated candidates combined high predicted foldability with functional-description alignment and sequence diversity, providing a basis for prioritizing experimentally testable designs. We applied Pinal to four distinct design tasks-a fluorescent protein, a polyethylene terephthalate hydrolase, an alcohol dehydrogenase and a metabolic H-protein-and experimentally observed the intended function in each case, including catalytic activity for both designed enzymes. Crucially, without iterative experimental optimization, a Pinal-designed H-protein increased product titer by 1.7-fold relative to the corresponding native E. coli H-protein in a multi-enzyme CO2 fixation pathway. These findings support natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.

bioengineering↗

bioRxiv2024

Circadian clocks in human cerebral organoids

Circadian rhythms result from cell-intrinsic timing mechanisms that impact health and disease1,2. To date, however, neural circadian research has largely focused on the hypothalamic circuitry of nocturnal rodents3. Whether circadian rhythms exist in human brain cells is unknown. Here we show bona fide circadian rhythms in human neurons, glia, cerebral organoids, and cerebral organoid slices (ALI-COs)4-8. Human neural circadian rhythms are synchronised by physiological timing cues such as glucocorticoids and daily temperature cycles, and these rhythms are temperature-compensated across the range of normal human brain temperatures9. Astrocyte rhythms are phase-advanced relative to other cultures and they modulate neuronal clock responses to temperature shift. Cerebral organoid rhythms are more robust at physiological brain temperatures; the relative amplitude of these rhythms increases over time in culture and their resetting capacity recapitulates key neurodevelopmental transitions in glucocorticoid signalling10-14. Remarkably, organoid post-transcriptional bioluminescent clock reporter rhythms are retained even when those of their putative transcriptional drivers are indiscernible15, and electrophysiology recordings confirm circadian rhythms in functional activity of monocultures, organoids, and ALI-COs. Around one third of the cerebral organoid proteome and phosphoproteome are circadian-rhythmic, with temporal consolidation of disease-relevant neural processes. Finally, we show that human brain organoid rhythms can be modulated and disrupted by commonly used brain-permeant drugs and mistimed cortisol exposure, respectively. Our results demonstrate that human brain cells and tissues develop their own circadian oscillations and that canonical mechanisms of the circadian clockwork may be inadequate to explain these rhythmic phenomena. 2D and 3D human neural cultures represent complementary and tractable models for exploring the emergence, disruption, and mechanics of the circadian neural clockwork, with important implications for chronobiology, brain function, and brain health.

neuroscience↗

bioRxiv2023

xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein

Protein language models have shown remarkable success in learning biological information from protein sequences. However, most existing models are limited by either autoencoding or autoregressive pre-training objectives, which makes them struggle to handle protein understanding and generation tasks concurrently. We propose a unified protein language model, xTrimoPGLM, to address these two types of tasks simultaneously through an innovative pre-training framework. Our key technical contribution is an exploration of the compatibility and the potential for joint optimization of the two types of objectives, which has led to a strategy for training xTrimoPGLM at an unprecedented scale of 100 billion parameters and 1 trillion training tokens. Our extensive experiments reveal that 1) xTrimoPGLM significantly outperforms other advanced baselines in 18 protein understanding benchmarks across four categories. The model also facilitates an atomic-resolution view of protein structures, leading to an advanced 3D structural prediction model that surpasses existing language model-based tools. 2) xTrimoPGLM not only can generate de novo protein sequences following the principles of natural ones, but also can perform programmable generation after supervised fine-tuning (SFT) on curated sequences. These results highlight the substantial capability and versatility of xTrimoPGLM in understanding and generating protein sequences, contributing to the evolving landscape of foundation models in protein science. Trained weight for the xTrimoPGLM model, and downstream datasets are available at https://huggingface.co/proteinglm.

synthetic biology↗

bioRxiv2023

Thermosensitivity of translation underlies the mammalian nocturnal-diurnal switch

Early mammals were nocturnal until the Cretaceous-Paleogene extinction enabled diurnal niche expansion. Diurnality evolved multiple times independently, but the mechanisms driving this shift remain unclear. We identify a conserved cell-intrinsic signal inversion that facilitates the transition from nocturnality to diurnality. Diurnal and nocturnal mammalian cells respond oppositely to temperature and osmotic cycles, mirroring species activity patterns. Cells exhibit differential global responses to temperature changes, including the phosphoproteome and protein synthesis. mTOR signaling is identified as a central mediator of this inversion, with diurnal mammals converging on modifications to mTOR and WNK pathways during evolution. Reducing mTOR activity induces nocturnal-to-diurnal shifting at cellular, tissue, and organismal levels. Therefore, the mTOR pathway is a cellular nexus that integrates energetic state and environmental signals to determine activity niche.

cell biology↗

bioRxiv2022

Linking Choroid Plexus Enlargement with Plasma Analyte and Structural Phenotypes in Clinical High Risk for Psychosis: A Multisite Neuroimaging Study

BackgroundChoroid plexus (ChP) enlargement exists in first-episode and chronic psychosis, but whether enlargement occurs before psychosis onset is unknown. This study investigated whether ChP volume is enlarged in individuals with clinical high-risk (CHR) for psychosis and whether these changes are related to clinical, neuroanatomical, and plasma analytes. MethodsClinical and neuroimaging data from the North American Prodrome Longitudinal Study 2 (NAPLS2) was used for analysis. 509 participants (169 controls, 340 CHR) were recruited. Conversion status was determined after 2-years of follow-up, with 36 psychosis converters. The lateral ventricle ChP was manually segmented from baseline scans. A subsample of 31 controls and 53 CHR had plasma analyte and neuroimaging data. ResultsCompared to controls, CHR (d=0.23, p=0.017) and non-converters (d=0.22, p=0.03) demonstrated higher ChP volumes, but not in converters. In CHR, greater ChP volume correlated with lower cortical (r=-0.22, p<0.001), subcortical gray matter (r=-0.21, p<0.001), and total white matter volume (r=-0.28,p<0.001), as well as larger lateral ventricle volume (r=0.63,p<0.001). Greater ChP volume correlated with makers functionally associated with the lateral ventricle ChP in CHR [CCL1 (r=-0.30, p=0.035), ICAM1 (r=0.33, p=0.02)], converters [IL1{beta} (r=0.66, p=0.004)], and non-converters [BMP6 (r=-0.96, p<0.001), CALB1 (r=-0.98, p<0.001), ICAM1 (r=0.80, p=0.003), SELE (r=0.59, p=0.026), SHBG (r=0.99, p<0.001), TNFRSF10C (r=0.78, p=0.001)]. ConclusionsCHR and non-converters demonstrated significantly larger ChP volumes compared to controls. Enlarged ChP was associated with neuroanatomical alterations and analyte markers functionally associated with the ChP. These findings suggest that the ChP may be a key explanatory biomarker in CHR for psychosis.

neuroscience↗

bioRxiv2022

Optical Metabolic Imaging Uncovers Sex- and Diet-dependent Lipid Changes in Aging Drosophila Brain

Aging is associated with progressive declines in physiological integrity and functions alongside increases in vulnerability to develop a number of diseases. The brain regulates sensory and motor functions as well as endocrine functions, and age-associated changes in brain are likely prerequisite for the organismal aging. Lipid metabolism has been associated with brain aging, which could be easily intervened by diets and lifestyles. However, the underlying mechanism through which brain lipid metabolism is regulated by diet during aging is elusive. Using stimulated Raman scattering (SRS) imaging combined with deuterium water (D2O) labeling, we visualized that lipid metabolic activities were changed by diet manipulation in aging Drosophila brain. Furthermore, we illuminated that insulin/IGF-1 signaling (IIS) pathway mediates the transformation of brain lipid metabolic changes in both an aging- and a diet-dependent manner. The lipid droplets (LDs) in the brain gradually became inert in both activities of lipid synthesis and mobilization with aging. High sugar diets enhanced the metabolic activity through promoting lipogenesis while dietary restriction increased the metabolic activity in both lipogenesis and lipolysis in brain LDs. However, these effects were impaired in both chico1/+ and dfoxo Drosophila mutants. We also observed that old chico1/+ brains maintained high metabolic activities, whilst the aged dfoxo brains acted exactly the opposite. More interestingly, the sexual dimorphism in brain lipid metabolism was impaired under diet regulation in both chico1/+ and dfoxo mutants. Locally reduced IIS activity in glial cells can mimic the systemic changes in systematic IIS mutants to maintain lipogenesis and lipolysis in aged brains, providing mechanistic insight into the anti-aging effects of IIS pathway. Our results highlight the manipulation of glia-specific IIS activity as a promising strategy in anti-aging treatments.

bioengineering↗

bioRxiv2022

Circadian regulation of protein turnover and proteome renewal

Although costly to maintain, protein homeostasis is indispensable for normal cellular function and long-term health. In mammalian cells and tissues, daily variation in global protein synthesis has been observed, but its utility and consequences for proteome integrity are not fully understood. Using several different pulse-labelling strategies, here we gain direct insight into the relationship between protein synthesis and abundance proteome-wide. We show that protein degradation varies in-phase with protein synthesis, facilitating rhythms in turnover rather than abundance. This results in daily consolidation of proteome renewal whilst minimising changes in composition. Coupled rhythms in synthesis and turnover are especially salient to the assembly of macromolecular protein complexes, particularly the ribosome, the most abundant species of complex in the cell. Daily turnover and proteasomal degradation rhythms render cells and mice more sensitive to proteotoxic stress at specific times of day, potentially contributing to daily rhythms in the efficacy of proteasomal inhibitors against cancer. Our findings suggest that circadian rhythms function to minimise the bioenergetic cost of protein homeostasis through temporal consolidation of protein turnover.

cell biology↗

bioRxiv2021

SC2MeNetDrug: A computational tool to uncover inter-cell signaling targets and identify relevant drugs based on single cell RNA-seq data

Single-cell RNA sequencing (scRNA-seq) is a powerful technology to investigate the transcriptional programs in stromal, immune, and disease cells, like tumor cells or neurons within the Alzheimers Disease (AD) brain or tumor microenvironment (ME) or niche. Cell-cell communications within ME play important roles in disease progression and immunotherapy response and are novel and critical therapeutic targets. Though many tools of scRNA-seq analysis have been developed to investigate the heterogeneity and sub-populations of cells, few were designed for uncovering cell-cell communications of ME and predicting the potentially effective drugs to inhibit the communications. Moreover, the data analysis processes of discovering signaling communication networks and effective drugs using scRNA-seq data are complex and involve a set of critical analysis processes and external supportive data resources, which are difficult for researchers who have no strong computational background and training in scRNA-seq data analysis. To address these challenges, in this study, we developed a novel open-source computational tool, sc2MeNetDrug (https://fuhaililab.github.io/sc2MeNetDrug/). It was specifically designed using scRNA-seq data to identify cell types within disease MEs, uncover the dysfunctional signaling pathways within individual cell types and interactions among different cell types, and predict effective drugs that can potentially disrupt cell-cell signaling communications. sc2MeNetDrug provided a user-friendly graphical user interface to encapsulate the data analysis modules, which can facilitate the scRNA-seq data-based discovery of novel inter-cell signaling communications and novel therapeutic regimens.

bioinformatics↗

bioRxiv2021

m6A-mediated Cell-cell Communication Controls Planarian Regeneration

Regeneration is the regrowth of damaged tissues or organs, a vital mechanism responding to damages from primitive organisms to higher mammals. Planarian possesses active whole-body regenerative capability owning to its vast reservoir of adult stem cells, neoblasts, thus provides an ideal model to delineate the underlying mechanisms for regeneration. N6-methyladenosine (m6A) regulates stem cell renewal and differentiation. However, how m6A controls regeneration at whole-organism level remains largely unknown. Here, we demonstrate that the depletion of m6A methyltransferase regulatory subunit wtap abolishes planarian regeneration, through regulating cell-cell communication and cell cycle. scRNA-Seq analysis unveils that the wtap knockdown induces a unique type of neural progenitor-like cells (NP-like cells), characterized by specific expression of the cell-cell communication ligand grn. Intriguingly, the depletion of m6A-modified transcripts grn/cdk9 (or cdk7) axis rescues the defective regeneration of planarian without wtap. Overall, our study reveals an indispensable role of m6A-dependent cell-cell communication essential for whole-organism regeneration.

molecular biology↗

bioRxiv2020

Signaling interaction link prediction using deep graph neural networks integrating protein-protein interactions and omics data

Uncovering signaling links or cascades among proteins that potentially regulate tumor development and drug response is one of the most critical and challenging tasks in cancer molecular biology. Inhibition of the targets on the core signaling cascades can be effective as novel cancer treatment regimens. However, signaling cascades inference remains an open problem, and there is a lack of effective computational models. The widely used gene co-expression network (no-direct signaling cascades) and shortest-path based protein-protein interaction (PPI) network analysis (with too many interactions, and did not consider the sparsity of signaling cascades) were not specifically designed to predict the direct and sparse signaling cascades. To resolve the challenges, we proposed a novel deep learning model, deepSignalingLinkNet, to predict signaling cascades by integrating transcriptomics data and copy number data of a large set of cancer samples with the protein-protein interactions (PPIs) via a novel deep graph neural network model. Different from the existing models, the proposed deep learning model was trained using the curated KEGG signaling pathways to identify the informative omics and PPI topology features in the data-driven manner to predict the potential signaling cascades. The validation results indicated the feasibility of signaling cascade prediction using the proposed deep learning models. Moreover, the trained model can potentially predict the signaling cascades among the new proteins by transferring the learned patterns on the curated signaling pathways. The code was available at: https://github.com/fuhaililab/deepSignalingPathwayPrediction.

bioinformatics↗

bioRxiv2020

Compensatory ion transport buffers daily protein rhythms to regulate osmotic balance and cellular physiology

Between 6-20% of the cellular proteome is under circadian control to tune cell function with cycles of environmental change. For cell viability, and to maintain volume within narrow limits, the osmotic pressure exerted by changes in the soluble proteome must be compensated. The mechanisms and consequences underlying compensation are not known. Here, we show in cultured mammalian cells and in vivo that compensation requires electroneutral active transport of Na+, K+, and Cl- through differential activity of SLC12A family cotransporters. In cardiomyocytes ex vivo and in vivo, compensatory ion fluxes alter their electrical activity at different times of the day. Perturbation of soluble protein abundance has commensurate effects on ion composition and cellular function across the circadian cycle. Thus, circadian regulation of the proteome impacts ion homeostasis with substantial consequences for the physiology of electrically active cells such as cardiomyocytes.

cell biology↗