Biology subjects

Cui, R.

Publications and source records attributed to Cui, R..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Spontaneous calcium transients in hair cell stereocilia

The hair bundle of auditory and vestibular hair cells converts mechanical stimuli into electrical signals through mechanoelectrical transduction (MET). The MET apparatus is built around a tip link that connects neighboring stereocilia that are aligned in the direction of mechanosensitivity of the hair bundle. Upon stimulation, the MET channel complex responds to changes in tip-link tension and allows a cation influx into the cell. Ca2+ influx in stereocilia has been used as a signature of MET activity. Using genetically encoded Ca2+ sensors (GCaMP3, GCaMP6s) and high-performance fluorescence confocal microscopy, we detect spontaneous Ca2+ transients in individual stereocilia in developing and fully formed hair bundles. We demonstrate that this activity is abolished by MET channel blockers and thus likely originates from putative MET channels. We observe Ca2+ transients in the stereocilia of mice in tissue explants as well as in vivo in zebrafish hair cells, indicating this activity is functionally conserved. Within stereocilia, the origin of Ca2+ transients is not limited to the canonical MET site at the stereocilia tip but is also present along the stereocilia length. Remarkably, we also observe these Ca2+ transients in the microvilli-like structures on the hair cell surface in the early stages of bundle development, prior to the onset of MET. Ca2+ transients are also present in the tallest rows of stereocilia in auditory hair cells, structures not traditionally thought to contain MET channels. We hypothesize that this newly described activity may reflect stochastic and spontaneous MET channel opening. Localization of these transients to other regions of the stereocilia indicates the presence of a pool of channels or channel precursors. Our work provides insights into MET channel assembly, maturation, function, and turnover.

cell biology↗

bioRxiv2024

Functional dissection of complex and molecular trait variants at single nucleotide resolution

Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types. We show that MPRA is able to discriminate between likely causal variants and controls, identifying 12,025 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% can plausibly be explained by the disruption of a known transcription factor (TF) binding motif. We dissect the mechanisms of 136 variants using saturation mutagenesis and assign impacted TFs for 91% of variants without a clear canonical mechanism. Finally, we provide evidence that epistasis is prevalent for variants in close proximity and identify multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants underlying complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.

genetics↗

bioRxiv2024

Uncovering critical transitions and molecule mechanisms in disease progressions using Gaussian graphical optimal transport

Understanding disease progression is crucial for detecting critical transitions and finding trigger molecules, facilitating early diagnosis interventions. However, the high dimensionality of data and the lack of aligned samples across disease stages have posed challenges in addressing these tasks. We present a novel framework, Gaussian Graphical Optimal Transport (GGOT), for analyzing disease progressions. The proposed GGOT uses Gaussian graphical models, incorporating protein interaction networks, to characterize the data distributions at different disease stages. Then we use population-level optimal transport to calculate the Wasserstein distances and transport maps between stages, enabling us to detect critical transitions. By analyzing the per-molecule transport distance, we quantify the importance of each molecule and identify trigger molecules. Moreover, GGOT predicts the occurrence of critical transitions in unseen samples and visualizes the disease progression process. We apply GGOT to the simulation dataset and six disease datasets with varying disease progression rates, to show its effectiveness for detecting critical transitions and identifying trigger molecules.

bioinformatics↗

bioRxiv2023

Genetically refactored Agrobacterium-mediated transformation

Members of Agrobacterium are costly plant pathogens while also essential tools for plant transformation. Though Agrobacterium-mediated transformation (AMT) has been heavily studied, its polygenic nature and its complex transcriptional regulation make identifying the genetic basis of transformational efficiency difficult through traditional genetic and bioinformatic approaches. Here we use a bottom-up synthetic approach to systematically refactor the tumor-inducing plasmid, wherein the majority of AMT machine components are encoded, into a minimal set of genes capable of plant and fungal transformation that is both controllable and orthogonal to its environment. We demonstrate that engineered vectors can be transferred to new heterologous bacteria, enabling them to transform plants. Our reductionist approach demonstrates how bottom-up engineering can be used to dissect and elucidate the genetic underpinnings of complex biological traits, and may lead to the development of strains of bacteria more capable of transforming recalcitrant plant species of societal importance.

microbiology↗

bioRxiv2023

Large-scale annotated dataset for cochlear hair cell detection and classification

Our sense of hearing is mediated by cochlear hair cells, localized within the sensory epithelium called the organ of Corti. There are two types of hair cells in the cochlea, which are organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains a few thousands of hair cells, and their survival is essential for our perception of sound because they are terminally differentiated and do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. However, the sheer number of cells along the cochlea makes manual quantification impractical. Machine learning can be used to overcome this challenge by automating the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, human, pig and guinea pig cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 90,000 hair cells, all of which have been manually identified and annotated as one of two cell types: inner hair cells and outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to supply other groups within the hearing research community with the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease.

neuroscience↗

bioRxiv2023

Transfer Learning Enhanced Graph Neural Network for Aldehyde Oxidase Metabolism Prediction and Its Experimental Application

Aldehyde oxidase (AOX) is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics. AOX-mediated metabolism can result in unexpected outcomes, such as the production of toxic metabolites and high metabolic clearance, which can lead to the clinical failure of novel therapeutic agents. Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability. In this study, we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism. AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction, while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks. AOMP significantly outperformed the benchmark methods in both cross-validation and external testing. Using AOMP, we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability, which were validated through in vitro experiments. Furthermore, for the convenience of the community, we established the first online service for AOX metabolism prediction based on AOMP, which is freely available at https://aomp.alphama.com.cn.

bioinformatics↗

bioRxiv2023

Rotten to the core - a neurofunctional signature of subjective core disgust generalizes to socio-moral contexts

While disgust originates in the hard-wired mammalian distaste response, the conscious experience of disgust in humans strongly depends on subjective appraisal and may even extend to sociomoral contexts. In a series of studies, we combined functional magnetic resonance imaging (fMRI) with machine-learning based predictive modeling to establish a comprehensive neurobiological model of subjective disgust. The developed neurofunctional signature accurately predicted momentary self-reported subjective disgust across discovery (n=78) and pre-registered validation (n=30) cohorts and generalized across core disgust (n=34 and n=26), gustatory distaste (n=30), and sociomoral (unfair offers; n=43) contexts. Disgust experience was encoded in distributed cortical and subcortical systems, and exhibited distinct and shared neural representations with subjective fear or negative affect in interoceptive-emotional awareness and conscious appraisal systems while the signatures most accurately predicted the respective target experience. We provide an accurate fMRI-signature for disgust with a high potential to resolve ongoing evolutionary debates.

neuroscience↗

bioRxiv2023

Nutritional composition and metabolic analysis of the newly hatched Anguilla japonica from embryo to preleptocephali obtained from artificial reproduction

The starter diet for Japanese eel (Anguilla japonica) has always been a difficult problem for the realization of total artificial reproduction. Therefore, this research analyzed the nutritional composition of artificially fertilized eggs, and transcriptome of samples from early hatchlings of fry to better understand nutrients requirements. The composition of crude lipid and crude protein in fertilized eggs was 7.24%{+/-}0.32% and 10.56%{+/-}0.41%, respectively. Seven kinds of essential amino acids (EAA) were detected but took a comparable lower content (3.19%) than other marine fish eggs. We randomly assembled 265.74 million clean reads and identified 1751 differentially expressed genes (DEGs) (P < 0.01) from pre-leptocephalus larvae. A total of 23 KEGG pathways related to the digestive and metabolic system were detected. Genes related to the secretion pathway of saliva, pancreatic juice and other digestive juices were significantly changed. The genes of carbohydrate metabolism, glycerolipid metabolism and glycerophospholipid metabolism were up-regulated significantly with the growth of the larvae (day 0 to 12). This study will facilitate future studies on the nutrition of eel larvae and other biological traits to reproductive research.

zoology↗

bioRxiv2023

Attractant and repellent induce opposing changes in the chemoreceptor four-helix bundle ligand-binding domain

Motile bacteria navigate toward favorable conditions and away from unfavorable environments using chemotaxis. Mechanisms of sensing attractants are well understood, however molecular aspects of how bacteria sense repellents have not been established. Here, we identified malate as a repellent recognized by the MCP2021 chemoreceptor in a bacterium Comamonas testosteroni and showed that it binds to the same site as an attractant citrate. Binding determinants for a repellent and an attractant had only minor differences, and a single amino acid substitution in the binding site inverted the response to malate from a repellent to an attractant. We found that malate and citrate affect the oligomerization state of the ligand-binding domain in opposing way. We also observed opposing effects of repellent and attractant binding on the orientation of an alpha helix connecting the sensory domain to the transmembrane helix. We propose a model to illustrate how positive and negative signals are generated and transduced across the membrane and built chimera proteins to illustrate a universal nature of the transmembrane signaling by the repellent.

microbiology↗

bioRxiv2022

Improving fine-mapping by modeling infinitesimal effects

Fine-mapping aims to identify causal variants for phenotypes. Bayesian fine-mapping algorithms (e.g.: SuSiE, FINEMAP, ABF, and COJO-ABF) are widely used, but assessing posterior probability calibration remains challenging in real data, where model misspecification likely exists, and true causal variants are unknown. We introduce Replication Failure Rate (RFR), a metric to assess fine-mapping consistency by down-sampling. SuSiE, FINEMAP and COJO-ABF show high RFR, indicating potential under-conservative mis-calibration. Simulations reveal that non-sparse genetic architecture can lead to miscalibration, while imputation noise, non-uniform distribution of causal variants, and QC filters have minimal impact. We present SuSiE-inf and FINEMAP-inf, novel fine-mapping methods modeling infinitesimal effects alongside fewer larger causal effects. Our methods exhibit improved calibration, RFR and functional enrichment, competitive recall and computational efficiency. Notably, using our methods posterior effect sizes substantially increases PRS accuracy over SuSiE and FINEMAP. Our work improves causal variants identification for complex traits, a fundamental goal of human genetics.

bioinformatics↗

bioRxiv2022

Drug design and repurposing with a sequence-to-drug paradigm

Drug development based on target proteins has been a successful approach in recent decades. A conventional structure-based drug design pipeline is a complex, human-engineered pipeline with multiple independently optimized steps. Advances in end-to-end differentiable learning suggest the potential benefits of similarly reformulating drug design. Here, we proposed a new sequence-to-drug paradigm that discovers drug-like small-molecule modulators directly from protein sequences and validated this concept for the first time in three stages. First, we designed TransformerCPI2.0 as a core tool for the sequence-to-drug paradigm, which exhibited competitive performance with conventional structure-based drug design approaches. Second, we validated the binding knowledge that TransformerCPI2.0 has learned. Third, we applied a sequence-to-drug paradigm to discover new hits for E3 ubiquitin-protein ligases: speckle-type POZ protein (SPOP), ring finger protein 130 (RNF130) which does not have a 3D structure, and repurposed proton pump inhibitors (PPIs) for ADP-ribosylation factor 1 (ARF1). This first proof of concept shows that the sequence-to-drug paradigm is a promising direction for drug development.

molecular biology↗

bioRxiv2022

Selective binding and transport of protocadherin 15 isoforms by stereocilia unconventional myosins in a heterologous expression system

During hair cell development, the mechanoelectrical transduction (MET) apparatus is assembled at the stereocilia tips, where it coexists with the stereocilia actin regulatory machinery. While the myosin-based tipward transport of actin regulatory proteins is well studied, isoform complexity and built-in redundancies in the MET apparatus have limited our understanding of how MET components are transported. We used a heterologous expression system to elucidate the myosin selective transport of isoforms of protocadherin 15 (PCDH15), the protein that mechanically gates the MET apparatus. We show that MYO7A selectively transports the CD3 isoform while MYO3A and MYO3B transports the CD2 isoform. Furthermore, MYO15A showed an insignificant role in the transport of PCDH15, and none of the myosins tested transport PCDH15-CD1. Our data suggest an important role for MYO3A, MYO3B, and MYO7A in the MET apparatus formation and highlight the intricate nature of MET and actin regulation during development and functional maturation of the stereocilia bundle.

cell biology↗

bioRxiv2020

Data-informed discovery of hydrolytic nanozymes

Nanozyme is a collection of nanomaterials with enzyme-like activity but exhibits higher environmental tolerance and long-term stability than their natural counterparts. Improving the catalytic activity and expanding the category of nanozymes are prerequisites to complement or even supersede natural enzymes. Specifically, a powerful hydrolytic nanozyme is demanded to degrade the unsustainable substance which natural enzymes hardly achieve. However, the development of hydrolytic nanozymes is still hindered by diverse hydrolytic substrates and following complicated mechanisms. Here, we apply two strategies which are informed by data to screen and predict catalytic active sites of MOF (metal-organic framework) based hydrolytic nanozymes. One is to increase the intrinsic activity by finely tuned Lewis acidity of the metal clusters. The other is to adjust the volume density of the active sites by shortening the length of ligands. Finally, we construct a Ce-FMA-MOF-based hydrolytic nanozyme with robust cleavage ability towards phosphate bonds, amide bonds, glycosidic bonds whose energy ascend in order; and even their mixture, biofilms. This work provides a rational methodology to design hydrolytic nanozyme, enriches the diversity of nanozymes, and potentially sheds a light on the evolution of enzyme engineering in the future.

biophysics↗

bioRxiv2020

Leveraging supervised learning for functionally-informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs

The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experimental methods to assess variants effect on gene expressions in native chromatin context via direct perturbation are low-throughput. Existing high-throughput computational predictors thus have lacked large gold standard sets of regulatory variants for training and validation. Here, we leverage a set of 14,807 putative causal eQTLs in humans obtained through statistical fine-mapping, and we use 6,121 features to directly train a predictor of whether a variant modifies nearby gene expression. We call the resulting prediction the expression modifier score (EMS). We validate EMS by comparing its ability to prioritize functional variants with other major scores. We then use EMS as a prior for statistical fine-mapping of eQTLs to identify an additional 20,913 putatively causal eQTLs, and we incorporate EMS into co-localization analysis to identify 310 additional candidate genes across UK Biobank phenotypes.

genomics↗

bioRxiv2020

Identification of a peroxidase inhibitor that enhances kanamycin activity

BackgroundThe threat of antimicrobial resistance calls for more efforts in basic science, drug discovery, and clinical development, particularly gram-negative carbapenem-resistant pathogens. Objectives and methodsWhole-cell-based screening was performed to identify novel antibacterial agents against Acinetobacter baumannii ATCC19606. Spontaneously resistant mutant selection, whole-genome sequencing, and surface plasmon resonance were used for target identification and confirmation. Checkerboard titration assay was used for drug combination analysis. ResultsA small molecule named 6D1 with the chemical structure of 6-fluorobenzo[d]isothiazol-3(2H)-one was identified and exhibited activity against A. baumannii ATCC19606 strain (minimal inhibitory concentration, MIC = 1 mg/L). The mutation in the plasmid-derived ohrB gene that encodes a peroxidase was identified in spontaneously resistant mutants. Treatment of the bacteria with 6D1 resulted in increased sensitivity to peroxide such as tert-butyl hydroperoxide. The binding of 6D1 and OhrB was confirmed by surface plasmon resonance. Interestingly, the MIC of kanamycin against spontaneously resistant mutants decreased. Finally, we identified the effect of 6D1 on enhancing the antibacterial activity of kanamycin, including New Delhi metallo-{beta}-lactamase (NDM-1)-producing carbapenem-resistant Klebsiella pneumoniae, but not in strains carrying kanamycin resistance genes. ConclusionsIn this study, we identified a peroxidase inhibitor that suppresses the growth of A. baumannii and enhances the antibacterial activity of kanamycin. We propose that peroxidase may be potentially used as a target for kanamycin adjuvant development.

microbiology↗

bioRxiv2020

Large-scale characterization of sex pheromone communication systems in Drosophila

Insects use sex pheromones as a reproductive isolating mechanism to attract conspecifics and repel heterospecifics. Despite the profound knowledge of sex pheromones, little is known about the coevolutionary mechanisms and constraints on their production and detection. Using whole-genome sequences to infer the kinship among 99 drosophilids, we investigate how phylogenetic and chemical traits have interacted at a wide evolutionary timescale. Through a series of chemical syntheses and electrophysiological recordings, we identify 51 sex-specific compounds, many of which are detected via olfaction. Behavioral analyses reveal that many of the 42 male-specific compounds are transferred to the female during copulation and mediate female receptivity and/or male courtship inhibition. Measurement of phylogenetic signals demonstrates that sex pheromones and their cognate olfactory channels evolve rapidly and independently over evolutionary time to guarantee efficient intra- and inter-specific communication systems. Our results show how sexual isolation barriers between species can be reinforced by species-specific olfactory signals.

evolutionary biology↗

bioRxiv2020

CREB is Required in Excitatory Neurons in the Forebrain to Sustain Wakefulness

The molecular and intracellular signaling processes that control sleep and wake states remain largely unknown. A consistent observation is that the cyclic-AMP response element binding protein (CREB), an activity-dependent transcription factor, is differentially activated during sleep and wakefulness. CREB is phosphorylated by the cyclic AMP/protein kinase A (cAMP/PKA) signaling pathway as well as other kinases, and phosphorylated CREB (pCREB) promotes transcription of target genes. Genetic studies in flies and mice suggest that CREB signaling influences sleep/wake states by promoting and stabilizing wakefulness. However, it remains unclear where in the brain CREB is required to drive wakefulness. In rats, CREB phosphorylation increases in the cerebral cortex during wakefulness and decreases during sleep, but it is not known if this change is functionally relevant to the maintenance of wakefulness. Here, we used the cre/lox system to conditionally delete CREB in the forebrain and in the locus coereleus (LC), two regions known to be important for the production of arousal and wakefulness. We used polysomnography to measure sleep/wake levels and sleep architecture in conditional CREB mutant mice and control littermates. We found that forebrain-specific deletion of CREB decreased wakefulness and increased non-rapid eye movement (NREM) sleep. Mice lacking CREB in the forebrain were unable sustain normal periods of wakefulness. On the other hand, deletion of CREB from LC neurons did not change sleep/wake levels or sleep/wake architecture. Taken together, these results suggest that CREB is required in neurons within the forebrain but not in the LC to promote and stabilize wakefulness.

neuroscience↗

bioRxiv2020

Genomics of a killifish from the Seychelles islands supports transoceanic island colonization and reveals relaxed selection of developmental genes

How freshwater fish colonize remote islands remains an evolutionary puzzle. Tectonic drift and trans-oceanic dispersal models have been proposed as possible alternative mechanisms. Integrating dating of known tectonic events with population genetics and experimental test of salinity tolerance in the Seychelles islands golden panchax (Pachypanchax playfairii), we found support for trans-oceanic dispersal being the most likely scenario. At the macroevolutionary scale, the non-annual killifish golden panchax shows stronger genome-wide purifying selection compared to annual killifishes from continental Africa. Reconstructing past demographies in isolated golden panchax populations provides support for decline in effective population size, which could have allowed slightly deleterious mutations to segregate in the population. Unlike annual killifishes, where relaxed selection preferentially targets aging-related genes, relaxation of purifying selection in golden panchax affects genes involved in developmental processes, including fgf10.

evolutionary biology↗