Biology subjects

Shi, C.

Publications and source records attributed to Shi, C..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Gas Vesicle-Expressing Human Pluripotent Stem Cells Enable Multimodal Ultrasound and Optical Coherence Tomographic Imaging

Genetically encoded imaging reporters are critical tools for tracking cell fate and function in regenerative medicine. Gas vesicles (GVs), air-filled protein nanostructures derived from bacteria, offer unique advantages for noninvasive imaging due to their acoustic and optical properties. In this study, we engineered human pluripotent stem cells (hPSCs) to express GVs using a doxycycline-inducible system. Upon doxycycline (Dox) treatment, GVs formed intracellularly and enabled enhanced contrast in both ultrasound and optical coherence tomography (OCT) imaging. Dynamic ultrasound imaging revealed pressure-dependent GV buckling and harmonic signal generation, while OCT imaging confirmed high sensitivity and depth-resolved detection in both in vitro and ex vivo retinal models. Our work establishes a multimodal GV-based reporter platform compatible with human stem cells and clinically relevant imaging modalities. This approach offers a powerful and versatile tool for noninvasively visualizing and tracking therapeutic cells in real time, advancing the development and monitoring of cell-based therapies.

synthetic biology↗

bioRxiv2025

De novo design of inducibly assembling multi-component filaments

The design of multi-component nanomaterials is an outstanding challenge. Here, we describe the computational design of protein filaments with two or three distinct structural components that assemble into micron-scale, well-ordered fibers when mixed. CryoEM structure determination of four fiber designs was close to the computational design models. Filament assembly can be initiated by mixing the components, and modulated by addition and/or phosphorylation of designed regulatory subunits. This work demonstrates that regulatable multi-component protein filament systems can now be designed, opening the door to a wide range of engineered materials.

bioengineering↗

bioRxiv2025

In vivo single-cell CRISPR screening for microproteins identifies a critical ribosomal component

The dark proteome includes a rapidly expanding catalog of microproteins with unknown functions that have been historically ignored in genome annotations. Here, we exploit an in vivo single-cell CRISPR screening strategy in the mouse epidermis to systematically investigate the tissue-wide function of microproteins. We document the global and cell-type-specific roles of microproteins during epidermal development and homeostasis at single-cell transcriptomic resolution. Focusing on select candidates, we identify a novel microprotein on Gm10076, identical to the ribosomal intersubunit bridge protein RPL41, whose perturbation strongly impairs proliferation and protein synthesis. Employing ribosome profiling and RNA sequencing, we show that Gm10076 perturbation profoundly reshapes the translational landscape. Contrary to its prior classification as nonessential, we find that the ribosomal protein RPL41 is essential for cellular proliferation, warranting further investigation into its role as an intersubunit bridge in the translational machinery. Together, our study comprehensively charts the tissue-wide functional landscape of the dark proteome, uncovers a second Rpl41 gene critical for ribosome function and establishes a basis for exploring the impact of microproteins on disease pathogenesis.

genetics↗

bioRxiv2025

Coaxial line-scanning Brillouin microscopy

Confocal Brillouin microscopy (CBM) enables high-resolution mechanical imaging but has slow acquisition speeds due to its point-by-point scanning strategy. Line-scanning Brillouin microscopy (LSBM) offers imaging acquisition speed improvements but faces challenges such as beam distortion in biaxial configurations and insufficient extinction ratio due to the single-stage VIPA spectrometer. To overcome these limitations, we developed a coaxial line-scanning Brillouin microscopy (cLSBM) system by using a two-stage parallel VIPA spectrometer. The coaxial design minimizes image distortion, and the two-stage parallel VIPA spectrometer significantly enhances the rejection of non-Brillouin noises. Experiment results showed that the first VIPA, served as a filter for noise rejection, has a rejection ability of 18 dB. The system was characterized by standard materials including ethanol and water, achieving a precision of 7.5 MHz and 12.6 MHz respectively. In the next step, we will optimize the system to further enhance noise rejection and utilize this setup to investigate the evolution of tissue mechanics during embryonic development.

bioengineering↗

bioRxiv2025

Investigating Facial Expression Processing during Fast Periodic Visual Stimulation using Highly Variable Stimuli

Facial expression recognition is a fundamental aspect of human social interaction, enabling effective communication and emotional understanding. Fast Periodic Visual Stimulation (FPVS) paradigms have recently emerged as a powerful approach for studying facial expression processing. However, previous studies often utilized identical base stimuli, making it difficult to disentangle neural responses to low-level perceptual differences from those reflecting conceptual discrimination of emotion. By introducing variability in our stimuli, we aimed to overcome these limitations and investigate neural responses to facial expressions of anger, fear, happiness, and sadness. Using EEG, robust oddball responses were observed across participants at both individual and group levels, demonstrating the paradigms sensitivity even with brief recordings and limited post-processing. Significant neural responses were detected across key regions of interest, with the right occipito-temporal region showing the strongest activity, consistent with its role in high-level facial expression processing. This study highlights the effectiveness of the FPVS paradigm for examining emotional processing using naturalistic stimuli and provides a framework for future research into neural mechanisms underlying facial emotion recognition in diverse and pathological populations.

neuroscience↗

bioRxiv2025

Reduced Fast Periodic Visual Stimulation Oddball Responses to Threatening Faces Associated with Anxiety

Facial expression processing is crucial for social communication and survival, with anxiety disorders often linked to alterations in attentional biases toward threat-related stimuli. While previous studies using event-related potentials (ERPs) have yielded conflicting findings regarding threat sensitivity in anxiety, Fast Periodic Visual Stimulation (FPVS) offers a high signal-to-noise, implicit alternative for assessing emotion processing. This study utilized FPVS to investigate neural responses to facial expressions in individuals with elevated anxiety-related characteristics (e.g., prior diagnosis or elevated symptom scores) and those without. EEG responses were recorded while participants viewed sequences of neutral faces interspersed with emotional oddball expressions (angry, fearful, happy, and sad). Results revealed robust neural discrimination responses to all facial expressions. Participants with anxiety-related characteristics showed significantly greater summed baseline-corrected amplitudes (BCA) at occipital electrodes in response to angry and sad oddball faces compared to the low-anxiety group. This was accompanied by reduced top-down interactions. Although, dimensional anxiety scores were generally low, suggesting results may reflect residual or trait-level differences rather than acute symptomatology, these findings provide preliminary evidence that FPVS may be sensitive to enduring differences in emotion processing associated with anxiety vulnerability.

neuroscience↗

bioRxiv2025

Implicit Emotional Biases in Anxiety and Depression: A Fast Periodic Visual Stimulation Study

Anxiety and depression are among the leading global causes of disability, yet their underlying neural mechanisms remain poorly understood. Traditional event-related potential (ERP) studies have shown attentional biases in anxiety and blunted responses to positive stimuli in depression, but limitations in sensitivity and interpretability hinder their clinical application. Fast Periodic Visual Stimulation (FPVS) offers an objective, high signal-to-noise ratio (SNR) approach to measuring neural responses to emotional stimuli. In this study, we applied FPVS with affective images to assess differences in emotional processing between individuals with anxiety and healthy controls across two experimental phases, optimizing stimulus presentation parameters. The results revealed that individuals with anxiety exhibited increased neural responses to negative stimuli compared to positive stimuli, as well as reduced responses to high-arousal stimuli, particularly in occipito-temporal and central-parietal regions. Additionally, individuals with comorbid depression showed blunted responses to high-arousal stimuli across multiple brain regions, consistent with reduced emotional reactivity. These findings support the feasibility of FPVS as a rapid and reliable tool for assessing emotional processing differences in clinical populations, with potential applications in translational research and psychiatric screening

neuroscience↗

bioRxiv2025

Multiomics analysis revealed anti-freezing mechanism of Staphylococcus aureus in its anti-freezing strain

Frozen food is currently a common food type. However, the presence of Staphylococcus aureus contamination caused serious challenge to frozen food safety. In this study, we explored the differences between sensitive strains and anti-freeze strains through multiomics analysis such as proteomics, phosphorylated proteomics, and metabolomics studies to understand the anti-freezing mechanism of S. aureus. This study compared the proteomics, phosphorylated proteomics and metabolomic differences between anti-freeze strains and sensitive strains before and after freezing. pre- and post-freezing, antifreeze strains mainly responded to low temperatures by enhancing antioxidant capacity, energy metabolism and antibiotic synthesis before freezing, while after freezing, bacteria depended more on biofilm formation, nitrogen metabolism and amino acid metabolism to improve frost resistance and adaptability. The ket gene such as sucD and coaD in the energy metabolism and metabolic pathways, gapA1 and tpiA in glucose metabolism and energy balance, asd and gnd in the metabolic pathways of amino acid synthesis and protein synthesis, crtN in the context of protective mechanisms and stress response should be explored furthermore. In metabolomic research, the arginine synthesis pathway, biofilm formation pathway, Adenosine triphosphate-binding cassette transporters and other metabolic pathways deserve special attention and research. IMPORTANCEThis study highlights the importance of understanding the anti-freezing mechanisms of *Staphylococcus aureus* in frozen food safety. By analyzing proteomics, phosphorylated proteomics, and metabolomics, it identifies key pathways like energy metabolism, biofilm formation, and amino acid synthesis that enhance bacterial frost resistance, offering insights for improving food preservation and safety.

microbiology↗

bioRxiv2024

Development of a novel peripherally acting alpha2A-adrenergic receptor antagonist for anti-diabetic

Yohimbine, a potent alpha2A-adrenergic receptor (2AAR) antagonist, was found therapeutic potential for type 2 diabetes through improving insulin release. However, the adverse side effects mediated by its actions in the brain hampered its use. Here, based on molecular docking analysis and structural modification, we have developed a novel peripherally acting yohimbine derivative (CDS479-2). CryoEM data found that yohimbine and CDS479-2 have similar interactions with the structure of 2AAR. Importantly, CDS479-2 shows similar 2AAR antagonist activity as yohimbine, but with very limited access to the brain, and thus avoiding the unwanted central effects such as hypertension and anxiety. Acute administration of CDS479-2 by injection or gavage lowered blood glucose levels and improved glucose tolerance in the high-fat diet-induced obesity (DIO) mice, an animal model for human type 2 diabetes. Remarkably, DIO mice received 2 weeks of daily administration of CDS479-2, but not yohimbine, exhibited sustained normoglycaemia, and increased density of the insulin-producing beta cells, in which important proliferation genes were found upregulated. Moreover, the overall protein expression levels of their pancreas were more similar to that of the healthy chow-fed mice. Thus, CDS479-2 may indicate a new direction for type 2 diabetes treatment. Importantly, the strategy we employed in this study will inspire the optimization for drugs that with both peripheral and central targets. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=166 HEIGHT=200 SRC="FIGDIR/small/628818v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1d3d7corg.highwire.dtl.DTLVardef@1afbad3org.highwire.dtl.DTLVardef@12a1aborg.highwire.dtl.DTLVardef@1341a02_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2024

CellBinDB: A Large-Scale Multimodal Annotated Dataset for Cell Segmentation with Benchmarking of Universal Models

In recent years, cell segmentation techniques have played a critical role in the analysis of biological images, especially for quantitative studies. Deep learning-based cell segmentation models have demonstrated remarkable performance in segmenting cell and nucleus boundaries, however, they are typically tailored to specific modalities or require manual tuning of hyperparameters, limiting their generalizability to unseen data. Comprehensive datasets that support both the training of universal models and the evaluation of various segmentation techniques are essential for overcoming these limitations and promoting the development of more versatile cell segmentation solutions. Here, we present CellBinDB, a large-scale multimodal annotated dataset established for these purposes. CellBinDB contains more than 1,000 annotated images, each labeled to identify the boundaries of cells or nuclei, including 4,6-Diamidino-2-Phenylindole (DAPI), Single-stranded DNA (ssDNA), Hematoxylin and Eosin (H&E), and Multiplex Immunofluorescence (mIF) staining, covering over 30 normal and diseased tissue types from human and mouse samples. Based on CellBinDB, we benchmarked seven state-of-the-art and widely used cell segmentation technologies/methods, and further analyzed the effects of four cell morphology indicators and image gradient on the segmentation results.

cell biology↗

bioRxiv2024

Glycophagy is an ancient bilaterian pathway supporting metabolic adaptation through STBD1 structural evolution

The selective autophagy of glycogen (glycophagy) has recently emerged as being crucial to glucose homeostasis in vertebrates, yet its origins remain elusive. Here, we provide evidence that starch-binding domain-containing protein 1 (STBD1), the key glycophagy receptor in vertebrates, is functionally conserved in the Pacific oyster, revealing its conserved position within ancient autophagy networks. We show that STBD1 in oysters - as seen in other invertebrate groups - possesses an N-terminal carbohydrate binding module family 20 (CBM20) domain, representing the ancestral state for this protein, while a shuffling of CBM20 to the C- terminus occurred during early chordate evolution. Structural modelling and functional studies reveal that the N-terminal CBM20 organization of STBD1 enhances glycogen binding. Functional experiments demonstrate that an STBD1-glycogen complex, anchored by GABARAPL2, facilitates an increased glycogen flux into autophagosomes for lysosomal degradation. We conclude that glycophagy is deeply conserved in bilaterians and that STBD1 structural evolution underlies potentially adaptive variation in metabolic strategies across distinct animal clades.

evolutionary biology↗

bioRxiv2024

Spatial Transcriptomics of IPMN Reveals Divergent Indolent and Malignant Lineages

PurposeIntraductal papillary mucinous neoplasms (IPMN) occur in 5-10% of the population, but only a small minority progress to pancreatic ductal adenocarcinoma (PDAC). The lack of accurate predictors of high-risk disease leads both to unnecessary operations for indolent neoplasms as well as missed diagnoses of PDAC. Digital spatial RNA profiling (DSP-RNA) provides an opportunity to define and associate transcriptomic states with cancer risk. Experimental DesignWhole-transcriptome DSP-RNA profiling was performed on 10 IPMN specimens encompassing the spectrum of dysplastic changes from normal duct to cancer. Ductal epithelial regions within each tissue were annotated as normal duct (NL), low-grade dysplasia (LGD), high-grade dysplasia (HGD), or invasive carcinoma (INV). Gene expression count data was generated by Illumina sequencing and analyzed with R/Bioconductor. ResultsDimension reduction analysis exposed three clusters reflecting IPMN transcriptomic states denoted "normal-like" (cNL), "low-risk" (cLR) and "high-risk" (cHR). In addition to specific marker genes, the three states exhibited significant enrichment for the exocrine, classical, and basal-like programs in PDAC. Specifically, exocrine function diminished in cHR, classical activation distinguished neoplasia from cNL, and basal-like genes were specifically upregulated in cHR. Intriguingly, markers of cHR were detected in NL and LGD regions from specimens with PDAC but not low-grade IPMN. ConclusionsDSP-RNA of IPMN revealed low-risk (indolent) and high-risk (malignant) expression programs that correlated with the activity of exocrine and basal-like PDAC signatures, respectively, and distinguished pathologically low-grade from malignant specimens. These findings contextualize IPMN pathogenesis and have the potential to transform existing risk stratification models. Statement of translational relevanceCurrent consensus guidelines for management of intraductal papillary mucinous neoplasms (IPMN) of the pancreas utilize clinical and radiographic criteria for risk stratification. Unfortunately, the estimated positive predictive value of these criteria for IPMN-associated pancreatic ductal adenocarcinoma (PDAC) is under 50%, indicating that over half of pancreatectomies are performed for benign disease. Moreover, nearly 15% of patients who were deemed "low risk" by the same criteria harbored PDAC. Surgical resection of IPMN has maximal benefit when performed prior to the development of PDAC, as evidence of carcinoma has been associated with a high rate of recurrence and poor overall survival. Thus, the development of molecular diagnostics that improve the accuracy of IPMN risk classification would have immediate relevance for patient care, both in terms of better selecting patients for potentially curative operations, as well as sparing patients with low-risk lesions from invasive procedures.

cancer biology↗

bioRxiv2024

BEGAN: Boltzmann-Reweighted Data Augmentation for Enhanced GAN-Based Molecule Design in Insect Pheromone Receptors

Identifying molecules that bind strongly to target proteins in rational drug design is crucial. Machine learning techniques, such as generative adversarial networks (GAN), are now essential tools for generating such molecules. In this study, we present an enhanced method for molecule generation using objective-reinforced GANs. Specifically, we introduce BEGAN (Boltzmann-Enhanced GAN), a novel approach that adjusts molecule occurrence frequencies during training based on the Boltzmann distribution exp(-{Delta}U/{tau}), where {Delta}U represents the estimated binding free energy derived from docking algorithms and{tau} is a temperature-related scaling hyperparameter. This Boltzmann reweighting process shifts the generation process towards molecules with higher binding affinities, allowing the GAN to explore molecular spaces with superior binding properties. The reweighting process can also be refined through multiple iterations without altering the overall distribution shape. To validate our approach, we apply it to the design of sex pheromone analogs targeting Spodoptera frugiperda pheromone receptor SfruOR16, illustrating that the Boltzmann reweighting significantly increases the likelihood of generating promising sex pheromone analogs with improved binding affinities to SfruOR16, further supported by atomistic molecular dynamics simulations. Furthermore, we conduct a comprehensive investigation into parameter dependencies and propose a reasonable range for the hyperparameter{tau} . Our method offers a promising approach for optimizing molecular generation for enhanced protein binding, potentially increasing the efficiency of drug discovery pipelines. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=186 SRC="FIGDIR/small/611826v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@120c4d3org.highwire.dtl.DTLVardef@5a2034org.highwire.dtl.DTLVardef@f8478aorg.highwire.dtl.DTLVardef@20db79_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Haplotype-resolved genomes provide insights into the origin and function of genome diversity in bivalves

Bivalves are famed for exhibiting vast genetic diversity of poorly understood origins and functional significance. Within bivalves, oysters are an ancient group showing remarkable genetic and phenotypic variability alongside extensive adaptability, serving as an ideal system to understand the origins and functional significance of genomic diversity. Here, we reveal the divergent genomic landscape of Crassostrea oysters, characterized by a history of genome size reduction associated with transposable elements (TEs). By constructing a haplotype-resolved genome for Kumamoto oyster C. sikamea, we demonstrate the widespread presence of haplotype divergent sequences (HDS); genomic regions present in just one haplotype. Combined with population resequencing, we define the role of genomic divergence driven by TEs in shaping oyster genetic diversity. Comparisons of haplotype-resolved genomes across four bivalve orders reveal that while extensive HDS is common, its origins may differ markedly. We show that HDS are a hotspot of genetic innovation, harboring rapidly evolving genes of various evolutionary ages, while also strongly influencing gene expression phenotypes. A widespread lack of allele-specific expression shared among oyster individuals indicates that haplotype polymorphism provides a key source of expression variation, promoting phenotypic plasticity and adaptation. These findings advance understanding on the origins of genomic diversity and its role in adaptive evolution.

genomics↗

bioRxiv2024

Multiplexed Glycan Immunofluorescence Identification of Pancreatic Cancer Cell Subpopulations in Both Tumor and Blood Samples

Pancreatic ductal adenocarcinoma (PDAC) tumor heterogeneity impedes the development of biomarker assays suitable for early disease detection that would improve patient outcomes. The CA19-9 glycan is currently used as a standalone biomarker for PDAC. Furthermore, previous studies have shown that cancer cells may display aberrant membrane-associated glycans. We therefore hypothesized that PDAC cancer cell subpopulations could be distinguished by aberrant glycan signatures. We used multiplexed glycan immunofluorescence combined with pathologist annotation and automated image processing to distinguish between PDAC cancer cell subpopulations within tumor tissue. Using a training-set/test-set approach, we found that PDAC cancer cells may be identified by signatures comprising 4 aberrant glycans (VVL, CA19-9, sTRA, and GM2) and that there are three glycan-defined PDAC tumor types: sTRA type, CA19-9 type, and intermixed. To determine whether the aberrant glycan signatures could be detected in blood samples, we developed hybrid glycan sandwich assays for membrane-associated glycans. In both patient-matched tumor and blood samples, the proportion of aberrant glycans detected was consistent. Furthermore, our multiplexed glycan immunofluorescent approach proved to be more sensitive and more specific than CA19-9 alone. Our results provide proof of concept for a novel methodology to improve early PDAC detection and patient outcomes.

cancer biology↗

bioRxiv2024

The molecular mechanism of temperature-dependent phase separation of Heat shock factor 1

Heat shock factor 1 (HSF1) is the critical orchestrator for a cell responding to heat shock, and its dysfunction is linked to cancers and neurodegenerative diseases. HSF1 undergoes phase separation upon heat shock, and its activity is regulated by various post-translational modifications (PTMs). Despite its importance, the molecular details underlying HSF1 phase separation, temperature sensing, and post-translational modifications (PTMs) regulation remain poorly understood. Here, we discovered that HSF1 exhibits temperature-dependent phase separation with a lower critical solution temperature (LCST) behavior due to entropy contribution from solvent molecules, providing a new conceptual mechanism accounting for HSF1 activation. We employed a synergistic approach combining coarse-grain simulation and nuclear magnetic resonance spectroscopy to reveal the residue-level molecular details of the interactions driving the phase separation of wild-type HSF1 and its distinct PTM patterns at various temperatures. The identified interaction sites were further validated with biochemistry assays and mapped interface accounts for HSF1 functions reported. Importantly, the amino acid substitution experiment reveals the molecular grammar for temperature-dependent HSF1 phase separation is species-specific and physiologically relevant. These findings delineate chemical code that integrates protein PTM patterns with accurate phase separation for body physiological temperature control in animals.

biochemistry↗

bioRxiv2024

Three-dimension transcriptomics maps of whole mouse embryo during organogenesis

Understanding mammalian development heavily relies on classical animal models like the house mouse (Mus musculus). Advanced spatial transcriptomics has enabled biologists to break new ground in studies of molecular dynamics and cellular patterning during embryonic development with spatiotemporal resolution. To construct a comprehensive developmental trajectory, current three-dimensional (3D) spatial transcriptomic profiling leverages mouse embryos from gastrulation (E5.5) to organogenesis (E13.5) in continuity. However, a crucial phase for early organogenesis between E9.5 and E11.5 was deficient. To unveil the mystery of this stage, we present the 3D transcriptomics of mouse embryos at E9.5 and E11.5, with a widely applicable reconstruction workflow that bypasses sophisticated bioinformatic calculations. As our 3D atlas is generated at single-cell resolution, we demonstrate how organogenetic processes can be interpreted at different levels of granularity, from local cellular interactions to whole embryonic regionalization. We release the open-access database MOSTA3D (Mouse Organogenesis Spatiotemporal Transcriptomic Atlas in Three-dimensional) and hope a broader community will contribute to extending this framework from conception to senility in the near future.

developmental biology↗

bioRxiv2024

Mechanical evolution of metastatic cancer cells in three-dimensional microenvironment

Cellular biomechanics plays critical roles in cancer metastasis and tumor progression. Existing studies on cancer cell biomechanics are mostly conducted in flat 2D conditions, where cells behavior can differ considerably from those in 3D physiological environments. Despite great advances in developing 3D in vitro models, probing cellular elasticity in 3D conditions remains a major challenge for existing technologies. In this work, we utilize optical Brillouin microscopy to longitudinally acquire mechanical images of growing cancerous spheroids over the period of eight days. The dense mechanical mapping from Brillouin microscopy enables us to extract spatially resolved and temporally evolving mechanical features that were previously inaccessible. Using an established machine learning algorithm, we demonstrate that incorporating these extracted mechanical features significantly improves the classification accuracy of cancer cells, from 74% to 95%. Building on this finding, we have developed a deep learning pipeline capable of accurately differentiating cancerous spheroids from normal ones solely using Brillouin images, suggesting the mechanical features of cancer cells could potentially serve as a new biomarker in cancer classification and detection.

biophysics↗