Biology subjects

Guan, C.

Publications and source records attributed to Guan, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Janusein and EB Cooperate to Enhance Microtubule Plus-end Catastrophe

Microtubule (MT) plus ends are organized by end-binding (EB) proteins, yet how EB-associated factors modulate the transition from growth to catastrophe remains incompletely understood. Using spatially resolved proximity proteomics, we identified Janusein (ZC2HC1A) as a conserved, poorly characterized MT-associated protein (MAP). At low expression levels, Janusein tracked MT plus ends and reduced EB comet velocity; at higher levels, it redistributed to the MT lattice and was associated with MT bundling and widespread MT loss. Loss of Janusein resulted in spindle defects in human cells. In vitro, Janusein alone facilitated MT elongation through its C-terminal fragment, but promoted MT catastrophe through its N-terminal fragment in the presence of EB proteins. Molecular dynamics simulations and mutational analyses suggest that an N-terminal loop may perturb lateral contacts between adjacent MT protofilaments. Together, these findings identify Janusein as an unconventional MAP that functionally cooperates with EB proteins to promote MT catastrophe.

cell biology↗

bioRxiv2026

Self-centering steady-state flows emerge in confined actomyosin networks

The actin cytoskeleton drives shape changes and transport in cells and supports mechanical signal transmission. However, how cells control and use active cytoskeletal flows at the mesoscale is not well understood. We reconstituted an active cytoskeleton in water-in-oil emulsion droplets of Xenopus laevis egg extract and observed, above a critical droplet size, the emergence of a 3D radially convergent steady-state flow of polymeric actin, maintained by continuous actin turnover. The flow condensed lipid-rich cellular debris into a centered inclusion. Steady-state F-actin density and flow velocity profiles roughly collapse onto scale-invariant master curves. This behavior can be explained by a physical model representing the network as an isotropic active viscous fluid with a percolation threshold. The contracting network behaves as an active swimmer with complex internal dynamics that centers itself and the central inclusion inside the droplets without physical boundary attachment. Active contraction, crosslinking and polymerization dynamics in an actin network can thus generate cell-scale flow patterns that sense the confining geometry and external signals and exert forces that are likely sufficient to move and localize organelles in cells.

biophysics↗

bioRxiv2026

Cysteine reduction rather than methionine restriction promotes immunometabolic fitness to confer survival benefit in aging

Elevated sulfur-containing amino acids (SAA; methionine and cystine) are linked to human mortality. While methionine restriction (MR) extends lifespan in animals, it is often ignored that traditional longevity-promoting MR diets also lack cystine. When dietary cystine is eliminated, host redirects substrates from methionine cycle and generates cysteine via cystathionine {gamma}-lyase (CTH) in transsulfuration pathway, leaving it unclear which SAA controls aging. Here, we show that selective cysteine restriction in Caenorhabditis elegans enhanced lifespan and stress survival independently of methionine. Notably, cysteine-free diets (methionine-replete or restricted) in Cth-deficient mice induced pro-metabolic effects, whereas MR with normal cysteine was ineffective. Sustained 70% cysteine reduction in aged Cth-/- mice reprogrammed the immunometabolic axis, conferring healthspan benefits. Thus, lowering cysteine while keeping the methionine pool intact enhances healthy lifespan.

physiology↗

bioRxiv2025

Uncovering bacterial pseudaminylation with pan-specific antibody tools

Pseudaminic acids (Pse) are a family of carbohydrates found within bacterial lipopolysaccharides, capsular polysaccharides and glycoproteins that are critical for the virulence of human pathogens. However, a dearth of effective tools for detecting and enriching Pse has restricted study to only the most abundant Pse-containing glycoconjugates. Here, we devise a synthesis of - and {beta}-O-pseudaminylated glycopeptides to generate pan-specific monoclonal antibodies (mAbs) that recognise - and {beta}-configured Pse and its C8 epimer (8ePse) presented within glycans or directly linked to polypeptide backbones. Structural characterisation reveals the molecular basis of Pse recognition across a range of diverse chemical contexts. Using these mAbs, we establish a glycoproteomic platform to provide unprecedented depth in mapping the Pse glycome of Helicobacter pylori, Campylobacter jejuni, and Acinetobacter baumannii strains. Finally, we demonstrate that the mAbs recognise diverse capsule types in multidrug-resistant Acinetobacter baumannii and enhance phagocytosis to eliminate infections in mice.

biochemistry↗

bioRxiv2025

Hormetic elevation of taurine restrains inflammaging by deactivating the NLRP3 inflammasome.

Taurine, the most abundant sulfonic amino acid in humans is largely obtained from diets rich in animal proteins. However, taurine is dietary non-essential because it can be synthesized from cysteine by activation of transsulfuration pathway (TSP) when food consumption is low or if the diet is predominantly plant based. The decline of taurine was proposed as the driver of aging through an undefined mechanism. Here, we found that mild food restriction in humans for one year that resulted in 14% reduction of calorie intake elevated the hypotaurine and taurine concentration in adipose tissue. Therefore, we investigated whether elevated taurine mimics caloric-restrictions beneficial effects on inflammation, a key mechanism of aging. Interestingly, aging increased the circulating and tissue concentrations of taurine suggesting that elevated taurine may serve as a hormetic stress response metabolite that regulates mechanism of age-related inflammation. The elevated taurine protected mice against mortality from sepsis and inhibited inflammasome-driven inflammation and gasdermin-D (GSDMD) mediated pyroptosis. Mechanistically, danger signals including hypotonicity that activate NLRP3-inflammasome, caused upstream taurine efflux from macrophages, which triggered potassium (K+) release and downstream canonical NLRP3 inflammasome assembly, caspase-1 activation, GSDMD cleavage and IL-1{beta} and IL-18 secretion that was reversed by taurine restoration. Notably, taurine does not efflux from GSDMD pore and inhibited IL-1{beta} from macrophages independently of known transporters SLC6A6 and SLC36A1. Increased taurine in old mice promotes healthspan by inducing anti-inflammatory pathways previously linked to youthfulness. These findings demonstrate that taurine is an upstream metabolic sensor of cellular perturbations that control NLRP3 inflammasome and lowers age-related inflammation.

immunology↗

bioRxiv2025

Block-Champagne: A novel Bayesian framework for Imaging E/MEG Source

Estimating the extents of E/MEG source activities is vital for exploring brain dynamics at high spatiotemporal resolution. However, conventional ESI models exclusively overemphasize on the accurate estimation of the source locations and struggle to reconstruct the extents due to the ill-posed nature of the problem, which requires effective integration of biophysical constraints and proficiency in signal processing methods. In this study, a novel Bayesian framework - Block-Champagne is introduced to provide accurate estimation of extended sources (i.e., both locations and extents). Specifically, a blocksparsity constraint is employed to model the local homogeneity of sources, which can be updated automatically to reconstruct source with arbitrary extents. Furthermore, prior constraints from other modalities, such as fMRI maps, can be incorporated to model interactions between remote sources to further enhance source reconstruction. The performance of Block-Champagne was quantitatively evaluated through simulation experiments, demonstrating its overall superiority under various complex scenarios (i.e., SNR, extent size, & number of extents) compared to benchmark algorithms (including LORETA, EBI-Convex, tsCham, L21-Sissy, & SI-STBF). Moreover, validation results obtained from deep-brain stimulation EEG, epilepsy data, and face-processing multi-modal data further proved the practical feasibility of Block-Champagne. In conclusion, our study reveals the superiority of the proposed BlockChampagne in accurate reconstruction of extended source, positioning Block-Champagne as a highly promising tool for realistic applications where source locations and extents are of equivalent importance.

neuroscience↗

bioRxiv2025

Improving functional protein generation via foundation model-derived latent space likelihood optimization

A variety of deep generative models have been adopted to perform de novo functional protein generation. Compared to 3D protein design, sequence-based generation methods, which aim to generate amino acid sequences with desired functions, remain a major approach for functional protein generation due to the abundance and quality of protein sequence data, as well as the relatively low modeling complexity for training. Although these models are typically trained to match protein sequences from the training data, exact matching of every amino acid is not always essential. Certain amino acid changes (e.g., mismatches, insertions, and deletions) may not necessarily lead to functional changes. This suggests that maximizing the training data likelihood beyond the amino acid sequence space could yield better generative models. Pre-trained protein large language models (PLMs) like ESM2 can encode protein sequences into a latent space, potentially serving as functional validators. We propose training functional protein sequence generative models by simultaneously optimizing the likelihood of training data in both the amino acid sequence space and the latent space derived from a PLM. This training scheme can also be viewed as a knowledge distillation approach that dynamically re-weights samples during training. We applied our method to train GPT- like models (i.e., autoregressive transformers) for antimicrobial peptide (AMP) and malate dehydrogenase (MDH) generation tasks. Computational experiments confirmed that our method outperformed various deep generative models (e.g., generative adversarial net, variational autoencoder, and GPT model without the proposed training strategy) on these tasks, demonstrating the effectiveness of our multi-likelihood optimization strategy.

bioinformatics↗

bioRxiv2024

Venomics AI: a computational exploration of global venoms for antibiotic discovery

The relentless emergence of antibiotic-resistant pathogens, particularly Gram-negative bacteria, highlights the urgent need for novel therapeutic interventions. Drug-resistant infections account for approximately 5 million deaths annually, yet the antibiotic development pipeline has largely stagnated. Venoms, representing a remarkably diverse reservoir of bioactive molecules, remain an underexploited source of potential antimicrobials. Venom-derived peptides, in particular, hold promise for antibiotic discovery due to their evolutionary diversity and unique pharmacological profiles. In this study, we mined comprehensive global venomics datasets to identify new antimicrobial candidates. Using machine learning, we explored 16,123 venom proteins, generating 40,626,260 venom-encrypted peptides (VEPs). Using APEX, a deep learning model combining a peptide-sequence encoder with neural networks for antimicrobial activity prediction, we identified 386 VEPs structurally and functionally distinct from known antimicrobial peptides. Our analyses showed that these VEPs possess high net charge and elevated hydrophobicity, characteristics conducive to bacterial membrane disruption. Structural studies revealed considerable conformational flexibility, with many VEPs transitioning to -helical conformations in membrane-mimicking environments, indicative of their antimicrobial potential. Of the 58 VEPs selected for experimental validation, 53 displayed potent antimicrobial activity. Mechanistic assays indicated that VEPs primarily exert their effects through bacterial membrane depolarization, mirroring AMP-like mechanisms. In vivo studies using a mouse model of Acinetobacter baumannii infection demonstrated that lead VEPs significantly reduced bacterial burdens without notable toxicity. This study highlights the value of venoms as a resource for new antibiotics. By integrating computational approaches and experimental validation, venom-derived peptides emerge as promising candidates to combat the global challenge of antibiotic resistance.

bioengineering↗

bioRxiv2024

STARTS: A self-adapted spatio-temporal framework for automatic E/MEG source imaging

To obtain accurate brain source activities, the highly ill-posed source imaging of electro- and magneto-encephalography (E/MEG) requires proficiency in incorporation of biophysiological constraints and signal-processing techniques. Here, we propose a spatio-temporal-constrainted E/MEG source imaging framework-STARTS that can reconstruct the source in a fully automatic way. Specifically, a block-diagonal covariance was adopted to reconstruct the source extents while maintain spatial homogeneity. Temporal basis functions (TBFs) of both sources and noises were estimated and updated in a data-driven fashion to alleviate the influence of noises and further improve source localization accuracy. The performance of the proposed STARTS was quantitatively assessed through a series of simulation experiments, wherein superior results were obtained in comparison with the benchmark ESI algorithms (including LORETA, EBI-Convex, & SI-STBF). Additional validations on epileptic and resting-state EEG data further indicate that the STARTS can produce neurophysiologically plausible results. Moreover, a computationally efficient version of STARTS-smooth STARTS was also introduced with an elementary spatial constraint, which exhibited comparable performance and reduced execution cost. In sum, the proposed STARTS, with its advanced spatio-temporal constraints and self-adapted update operation, provides an effective and efficient approach for E/MEG source imaging.

neuroscience↗

bioRxiv2024

S-RNase Evolution in Self-Incompatibility: Phylogenomic Insights into Synteny with S-Like Genes

S-RNases are essential in the gametophytic self-incompatibility (GSI) system of many flowering plants, where they act as stylar-S determinants. Despite their significance, the syntenic genomic origin and evolutionary trajectory of S-RNase genes in eudicots have remained largely unclear. Here, we performed large-scale phylogenetic and microsynteny network analyses of RNase T2 genes across 130 angiosperm genomes, encompassing 35 orders and 56 families. Based on the connections observed in the synteny network, particularly the persisting synteny block in none-SI Cucurbitaceae species, we infer that well-characterized S-RNase genes (Class III-A RNase genes) were duplicated and evolved from Class I S-like RNase genes, possibly as a result of the gamma triplication event shared by core eudicots. Additionally, we identified frequent lineage-specific gene transpositions of S-RNase genes across diverse angiosperm lineages, including Rosaceae, Solanaceae, and Rutaceae families, accompanied by a significant increase in transposable element (TE) activity near these genes. Our findings delineate the precise genomic origin and evolutionary path of eudicot S-RNase genes, enhancing our understanding of the evolution of the S-RNase-based GSI system.

evolutionary biology↗

bioRxiv2024

Myosin II actively regulates Drosophila proprioceptors

Auditory receptors can be motile to actively amplify their mechanical input. Here we describe a novel and different type of motility that, residing in supporting cells, shapes physiological responses of mechanoreceptor cells. In Drosophila larvae, supporting cap cells transmit mechanical stimuli to proprioceptive chordotonal neurons. We found that the cap cells are strongly pre-stretched at rest to twice their relaxed length. The tension in these cells is modulated by non-muscle myosin-II motors. Activating the motors optogenetically causes contractions of the cap cells. Cap-cell-specific knockdown of the regulatory light chain of myosin-II alters mechanically evoked receptor neuron responses, converting them from phasic to more tonic, impairing sensory adaptation. Hence, two motile mechanisms seem to operate in concert in insect chordotonal organs, one in the sensory receptor neurons, based on dynein, and the other in supporting cells, based on myosin. One Sentence SummaryMyosin II motors in contractile cells pre-stretch Drosophila stretch receptors.

cell biology↗

bioRxiv2023

A functional perspective on the conditional covariance comparison problem in dementia analysis

Although there are many methods available in the literature to compare the covariance structures of two populations, few are suitable for clinical application due to the inability to account for covariate(s) that affect the dependence structure of the variables being investigated. A common method is to adjust the effect of the covariates via a linear model and work with the resulting residuals. However, removing the effects of the covariates could potentially eliminate valuable information from the analysis. We propose a functional nonparametric covariance matrix estimator to account for any given value in the covariate(s), which allows a comparison of the functional covariance structures of the multivariate data. This comparison is facilitated via a test statistic involving the first eigenvalue of the combined form of covariance matrices of the two groups. Three different approaches, namely, the parametric Tracy-Widom, the semi-parametric Forkmans test, and the nonparametric Permutation method, are used to compute the approximate p-values of the test statistic. We have conducted extensive simulation studies to determine the type I error and power of the proposed hypothesis testing methods and developed practical recommendations for implementing this novel approach. Finally, we apply our methods to the Alzheimers Disease Neuroimaging Initiative (ADNI) study to compare cerebrospinal fluid (CSF) biomarkers between dementia and non-dementia cohorts, which offers a fascinating insight into the differences between covariance structures of biomarkers amyloid {beta}(1-42) (A{beta}42), total tau (tau), and phosphorylated tau (ptau) for given values of age, sex, and years of education.

neuroscience↗

bioRxiv2023

An insect's view of a numerosity illusion: a simple strategy may explain complex numerical performance in bumblebees

Despite some similarities in numerical abilities among vertebrates, animals seem to differ with respect to the perceptual factors underlying numerical estimation. This is particularly evident in the case of numerosity illusions, a type of illusory phenomena elicited by the spatial arrangement of the elements that compose it. We investigated whether an insect experiences the most famous numerosity illusion, the Solitaire Illusion. Bumblebees (Bombus terrestris audax) presented with two mixed arrays containing magenta and yellow dots were trained to select the array containing the larger number of a target colour (either magenta or yellow). In the test phases, bumblebees were presented with sets of stimuli differing in the numerical ratio, including the illusory arrays: in one array, magenta dots were centrally located (yellow dots in the perimeter), whereas in the other one, magenta dots were located in the perimeter (yellow dots in the centre). Bees discriminated up to a ratio of 0.78 (14 vs. 18). Video analyses showed that bumblebees sequentially scanned the stimuli before making a choice. Bumblebees required longer scanning time for patterns with smaller numbers of reinforced colour dots, suggesting that bumblebees spent longer time on searching for more information or finding a reinforced arrangement of spatial dots before making an accurate decision. In the presence of the "illusion arrangement", bees behaved in a manner consistent with misperception of numerosity, overestimating the number of centrally located dots. The spatial configuration of the stimuli influenced how the patterns were assessed: bees examined the clustered reinforced colour dots longer. Flying paths analysis suggested that bumblebees followed the paths formed by similar colour dots rather than counting each dot to make a numerical discrimination. These results challenge the notion that visual illusions can be inferred simply from evaluating choices of different visual patterns and reinforce the idea that multiple strategies can potentially be used to achieve seemingly similar cognitive outcomes. Detailed analyses of decision-making processes are essential to deduce the cognitive strategies underpinning discrimination tasks, whether they are numerical or other visual tasks.

animal behavior and cognition↗

bioRxiv2023

Modification of DNA by a viral enzyme and charged tRNA

Bacteriophage enzymes synthesize varied and complex DNA hypermodifications. The enzyme encoded by the phage Mu gene mom is necessary for post-replicative carbamoylmethyl addition to the exocyclic amine of deoxyadenosine in DNA during the lytic phase of the viral life-cycle. The molecular details of this modification reaction, including the molecular origins of the modification itself, have long eluded understanding. Here, we demonstrate that Mom co-opts the translational machinery of the host by harvesting activated glycine from charged tRNAGly to hypermodify adenine. Based on this insight, we report the first in vitro reconstitution of the Mu hypermodification from purified components. Using isotope labeling, we demonstrate that the carbamoyl nitrogen of the Mom modification is derived from the N6 of adenine, indicating an on-base rearrangement of the N6 aminoacylation product, possibly via a cyclic intermediate. Informed by the X-ray crystal structure of Mom, we have probed the location of the active site, identified a novel insertion, and established substrate specificities of the Mom enzyme.

biochemistry↗

bioRxiv2022

Analyzing the covariance structure of plasma signaling proteins in relation to the diagnosis of dementia

Numerous studies have shown that individuals with dementia have exhibited activation of inflammatory pathways in their brains. Typically, these studies use traditional and well-established regression methods for data analysis. In this paper, a new approach is introduced that utilizes the analysis of the covariance structure using methods related to the principal component analysis (PCA) theory. Eleven biomarkers related to neuroinflammation were used to determine the association with the onset of dementia. Various demographic covariates were adjusted to account for possible confounding effects of the covariance structure. Three hypothesis testing methods were considered to discern differences between partial covariance matrices for comparing power and Type I errors through simulation studies. Application of hypothesis testing methods using data from Framingham Heart Study (FHS) found significant differences in covariance matrices between the non-dementia and dementia groups.

neuroscience↗

bioRxiv2022

A novel attention-based peptide language model for dipeptidyl peptidase-IV inhibitory peptides mining

Mining of anti-diabetic dipeptidyl peptidase IV (DPP-IV) inhibitory peptides (DPP-IV-IPs) is currently a costly and laborious process. Due to the absence of rational peptide design rules, it relies on cumbersome screening of unknown enzyme hydrolysates. Here, we present an enhanced deep learning (DL) model called BERT-DPPIV, specifically designed to classify DPP-IV-IPs and exploring their design rules to discover potent candidates. The end-to-end model utilizes a fine-tuned bidirectional encoder representations (BERT) architecture to extract structural/functional information from input peptides and accurately identify DPP-IV-Ips from input peptides. Experimental results in benchmark dataset showed BERT-DPPIV yielded state-of-the-art accuracy of 0.894, surpassing the 0.797 obtained by sequence-feature model. Furthermore, we leverage the attention mechanism to uncover that our model could recognize restriction enzyme cutting site and specific residues that contribute to the inhibition of DPP-IV. Moreover, guided by BERT-DPPIV, proposed design rules of DPP-IV inhibitory tripeptides and pentapeptides were validated and they can be used to screen potent DPP-IV-IPs.

bioinformatics↗

bioRxiv2021

Preserved motor representations after paralysis

AO_SCPLOWBSTRACTC_SCPLOWNeural plasticity allows us to learn skills and incorporate new experiences. What happens when our lived experiences fundamentally change, such as after a severe injury? To address this question, we analyzed intracortical population activity in a tetraplegic adult as she controlled a virtual hand through a brain-computer interface (BCI). By attempting to move her fingers, she could accurately drive the corresponding virtual fingers. Neural activity during finger movements exhibited robust representational structure and dynamics that matched the representational structure, previously identified in able-bodied individuals. The finger representational structure was consistent during extended use, even though the structure contributed to BCI decoding errors. Our results suggest that motor representations are remarkably stable, even after complete paralysis. BCIs re-engage these preserved representations to restore lost motor functions.

neuroscience↗

bioRxiv2021

Large-scale CRISPRi and transcriptomics of Staphylococcus epidermidis identify genetic factors implicated in commensal-pathogen lifestyle versatility

Staphylococcus (S.) epidermidis is a ubiquitous human commensal skin bacterium that is also one of the most prevalent nosocomial pathogens. The genetic factors underlying this remarkable lifestyle plasticity are incompletely understood, much due to the difficulties of genetic manipulation, precluding high-throughput functional profiling of this species. To probe S. epidermdis versatility to survive across a diversity of skin sites and infection niches, we developed a large-scale CRISPR interference (CRISPRi) screen complemented by transcriptional profiling (RNA-seq) across 24 diverse environmental conditions and piloted a droplet-based CRISPRi approach to enhance throughput and sensitivity. We identified putative essential genes, importantly, revealing amino acid metabolism as crucial to survival across diverse environments and demonstrated the importance of trace metal uptake for survival under multiple stress conditions. We identified pathways significantly enriched and repressed across our range of stress and nutrient limited conditions, demonstrating the considerable plasticity of S. epidermidis in responding to environmental stressors. We postulate a mechanism by which nitrogen metabolism is linked to lifestyle versatility in response to hyperosmotic challenges, such as those encountered on human skin. Finally, we examined S. epidermidis survival under acid stress and hypothesize a role for cell wall modification as a vital component of the survival response in acidic conditions. Taken together, this study integrates large scale CRISPRi and transcriptomics data across multiple environments to provide insights into a keystone member of the human skin microbiome. Our results additionally provide a valuable benchmarking analysis for CRISPRi screens and are rich resource for other staphylococcal researchers. Author summaryStaphylococcus epidermidis is an important bacteria of the skin microbiome. While it has an important role in skin health, it can also be a major infectious agent, especially in bloodstream and catheter infections. Understanding the underlying genes and pathways that contribute to S. epidermidis ability to have both health and disease-associated abilities will be important to promoting the former and targeting the latter. Yet the function of many S. epidermidis genes, particularly in skin and infection environments, remains unknown. We developed a CRISPRi platform to knock down the function of S. epidermidis genes to better understand to what degree they are essential for growth in these environments. We complemented this gene essentiality data with gene expression data in the same environments to understand how regulation of these genes contribute to S. epidermidis survival. These large-scale data generated numerous hypotheses for new genetic links to S. epidermidis growth versatility.

microbiology↗