Biology subjects

Shao, Y.

Publications and source records attributed to Shao, Y..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Marker gene fishing for single-cell data with complex heterogeneity

In single-cell studies, cells can be characterized with multiple sources of heterogeneity such as cell type, developmental stage, cell cycle phase, activation state, and so on. In some studies, many nuisance sources of heterogeneity (SOH) are of no interest, but may confound the identification of the SOH of interest, and thus affect the accurate annotate the corresponding cell subpopulations. In this paper, we develop B-Lightning, a novel and robust method designed to identify marker genes and cell subpopulations correponding to a SOH (e.g., cell activation status), isolating it from other sources of heterogeneity (e.g., cell type, cell cycle phase). B-Lightning uses an iterative approach to enrich a small set of trustworthy marker genes to more reliable marker genes and boost the signals of the SOH of interest. Multiple numerical and experimental studies showed that B-Lightning outperforms existing methods in terms of sensitivity and robustness in identifying marker genes. Moreover, it increases the power to differentiate cell subpopulations of interest from other heterogeneous cohorts. B-Lightning successfully identified new senescence markers in ciliated cells from human idiopathic pulmonary fibrosis (IPF) lung tissues, new T cell memory and effector markers in the context of SARS-COV-2 infections, and their synchronized patterns which were previously neglected. This paper highlights B-Lightnings potential as a powerful tool for single-cell data analysis, particularly in complex data sets where sources of heterogeneity of interest are entangled with numerous nuisance factors.

bioinformatics↗

bioRxiv2024

BC-Design: A Biochemistry-Aware Framework for High-Precision Inverse Protein Folding

Inverse protein design (IPD) extends the classical problem of inverse protein folding (IPF) by not only recovering a sequence compatible with a given backbone geometry but also generating a range of new sequences that satisfy the physicochemical constraints required for a stable fold with a specified (often designed) function. Recent progress has incorporated biochemical properties as discrete per-residue features, but such localized signals cannot represent the continuous hydrophobic and electrostatic environments that span protein surfaces and interior volumes. Here we introduce BC-DO_SCPLOWESIGNC_SCPLOW, a biochemistry-aware inverse design framework that integrates geometric structure with smoothly varying hydrophobicity and charge properties. The later are represented independent of residue coordinates, on compact point clouds sampled throughout protein surfaces and interiors. This formulation provides a natural spatial description of physicochemical environments and enriches structural cues without specifying amino-acid identities. On the CATH 4.2 benchmark, BC-DO_SCPLOWESIGNC_SCPLOW achieves 90% sequence recovery and generalizes robustly across protein lengths, contact-order regimes, and major fold classes. Masking experiments further demonstrate an interpretable fidelity-diversity control: full biochemical context yields high-fidelity reconstructions, whereas withholding information enables exploratory variant generation. Beyond diagnostic benchmarks, BC-DO_SCPLOWESIGNC_SCPLOW demonstrably improves functional design outcomes across diverse settings. It increases enzyme-substrate affinity, enhances peptide-receptor design accuracy, and achieves state-of-the-art recovery and structural fidelity in antibody loop (CDRH3) modeling. In these applications, the model not only reconstructs native-like sequences but also proposes plausible functional variants that preserve catalytic or binding geometry--such as generating CDRH3 loops that maintain antigen-contact configurations while offering new sequence solutions. These results show that integrating continuous physicochemical properties with structural geometry enables practical, function-oriented protein design, going beyond backbone-conditioned recovery.

bioinformatics↗

bioRxiv2024

Loss of Diurnal Oscillatory Rhythms in Gut Microbiota Correlates with Progression of Atherosclerosis

Circadian rhythms in gut microbiota composition are crucial for metabolic function and disease progression, yet the diurnal oscillation patterns of gut microbiota in atherosclerotic cardiovascular disease (ASCVD) and their role in disease progression remain unknown. Here, we investigate gut bacterial dynamics in ApoE-/- mice within a day, and elucidated the dynamic changes in fecal microbiota composition and function differences among C57BL/6 and ApoE-/- mice with standard chow diet or high-fat, high-cholesterol diet under ad libitum conditions. Compared with C57BL/6 mice, ApoE-/- mice exhibit significant differences in fecal microbial composition. Rhythmic analysis showed that the dynamic changes in the composition and function of fecal microbiota in ApoE-/- mice were significantly different from those in C57BL/6 mice. We further found that the rhythmic strains (Blautia Coccoides) inhibit the progression of ASCVD by improving the intestinal and endothelial barrier function. Our findings demonstrate that diurnal oscillations in gut microbiota are closely related to the progression of ASCVD, and provide a new insight for microbial-targeted therapies for ASCVD.

microbiology↗

bioRxiv2024

Fresh Human Retinal scRNA-seq Atlas Reveals a Novel Cone Subtype and Cellular Diversity

BackgroundCurrent human retina studies predominantly utilize post-mortem tissue, and the sample accessibility constraints make the characterization of the living human retina at single-cell resolution a challenge. Although single-nucleus RNA-seq expands the utility of frozen samples, it provides a nuclear-centric view, potentially missing key cytoplasmic information and transient biological processes. Thus, it is important to generate resources directly from living human retinal tissue to complement existing datasets. MethodsWe profiled 106,829 single cells from nine unfrozen human retina samples. Living samples were collected withinLJ10LJmin of therapeutic enucleation and four postmortem samples were collected within 6LJh. After standardized dissociation, single-cell transcriptomes were generated using 10x Genomics 3 RNA-seq and applied scVI to generate batch-corrected integrated atlas. Major cell types and subtypes were annotated through iterative Leiden clustering, canonical markers. Subsequent analyses included differential expression comparisons between cell states and regulon activity profiling to further characterize cellular identities and regulatory networks. Transcriptional dynamics were assessed using RNA velocity, and cell-cell signaling pathways were inferred with CellChat. Key findings were validated in independent samples from two additional donors (four samples) using the identical workflow. ResultsWe contribute to establishing a reference for retinal cell type proportions and cellular states. Our analysis revealed ELF1-mlCone, a distinct cluster of mlCone photoreceptors identified by distinct transcriptional features. The presence and transcriptional features of this cluster were validated in independent samples. Additionally, by comparing living and post-mortem samples, our study highlights differences in transcriptional dynamics: living tissue preserved coherent RNA velocity streams, enabling clear dynamic state transitions, while post-mortem tissue exhibited disorganized patterns. These findings suggest that using living tissue can improve the capture of active cellular states and transitions. ConclusionsOur atlas provides a single-cell reference contrasting living versus early post-mortem human retina, integrating cell type composition, transcriptional diversity, and functional insights. It may serve as a useful resource for retinal research and for understanding aspects of human retinal biology, particularly given its inclusion of living tissue and diverse pathological states.

bioinformatics↗

bioRxiv2024

Enzymatic Degrading Chlorophenol Wastewater by Mixed Strains of Immobilized White Rot Fungi

To address chlorophenol wastewater pollution, immobilized mixed white rot fungi (WRF) strain microsphere was designed as a solid degradation agent, using lignin peroxidase (LiP), manganese peroxidase (MnP), and laccase (Lac) to degradating the wastewater. Considering the diverse physical and chemical properties of the fungal sphere, the immobilization agent formula is optimized and comprehensive environmental factor design response surface analysis are implemented to determine the delivery conditions. Consequently, the 2,4-DCP treatment rate and extracellular enzyme activity for a 1:1 encapsulation of T. versicolor and P. sajor-caju significantly outperform those of individual strains. Using polyvinyl alcohol (PVA), sodium alginate (SA), and biochar as carriers, with sodium dihydrogen phosphate solution as crosslinker and SiO2/zeolite as additives, immobilizing mixed bacteria yielded a high-quality solid agent. This achieved a 99.33% 2,4-DCP degradation rate over 96 hours, with optimal dosage, pH, and initial 2,4-DCP concentration at 11.5 g/L, 5.5, and 40 mg/L. The degradation of 2,4-DCP by WRF selectively removes adjacent chlorine atoms to produce 4-CP, enhancing the dechlorination efficiency. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/611973v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@1653067org.highwire.dtl.DTLVardef@4cc31dorg.highwire.dtl.DTLVardef@19daa33org.highwire.dtl.DTLVardef@1115c5_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Enhanced metagenomics-enabled transmission inference with TRACS

Coexisting strains of the same species within the human microbiota pose a substantial challenge to inferring the host-to-host transmission of both pathogenic and commensal microbes. Here, we present TRACS, a highly accurate algorithm for estimating genetic distances between strains at the level of individual SNPs, which is robust to intra-species diversity within the host. Analysis of well-characterised Faecal Microbiota Transplantation datasets, along with extensive simulations, demonstrates that TRACS substantially outperforms existing strain aware transmission inference methods. We use TRACS to infer transmission networks in patients colonised with multiple strains, including SARS-CoV-2 amplicon sequencing data from UK hospitals, deep population sequencing data of Streptococcus pneumoniae and single-cell genome sequencing data from malaria patients infected with Plasmodium falciparum. Applying TRACS to gut metagenomic samples from a large cohort of 176 mothers and 1,288 infants born in UK hospitals revealed species-specific transmission rates between mothers and their infants. Notably, TRACS identified increased persistence of Bifidobacterium breve in infants, a finding missed by previous analyses due to the presence of multiple strains.

bioinformatics↗

bioRxiv2024

Targeting Interferon-Driven Inflammatory Memory Prevents Epigenetic Evolution of Cancer Immunotherapy Resistance

Acquired resistance is a growing obstacle to durable responses after cancer immune checkpoint blockade (ICB). The mechanisms by which heterogeneous tumors evolve under immunotherapy pressure and strategies targeting key populations to prevent relapse are poorly understood. We show that chronic interferon (IFN) enables a subpopulation of cancer cells to acquire inflammatory memory and express memory ISGs, a subset of IFN-stimulated genes enriched for immune evasion properties, leading to subclonal epigenetic evolution of ICB-resistant states. Inflammatory memory is epigenetically encoded through chronic virus mimicry - feedforward MDA5 signaling likely activated by endogenous retroelements. While JAK inhibitors can improve ICB response, combining them with TBK1 inhibitors collapses this feedforward mechanism, erasing inflammatory memory and preventing differentiation into resistance states. Across human cancers, small subpopulations of memory ISG-expressing cells are prevalent and coupled to T cell exhaustion, suggesting inflammatory memory may be a common mechanism of acquired resistance targetable by JAK plus TBK1 inhibition.

immunology↗

bioRxiv2024

ANASFV: a workflow for ASFV whole genome sequencing, assembly, and evaluation

African Swine Fever Virus (ASFV) poses an ongoing threat with widespread outbreaks affecting both domestic and wild pig populations globally. Effective management of ASFV outbreaks necessitates a deep understanding of its genetic diversity and evolutionary dynamics. Despite the advantages of nanopore sequencing for genome analysis, its application to ASFV genomes encounters specific challenges, such as high host DNA contamination that reduces viral genome coverage and an inherently higher error rate producing small insertions and deletions (indels). Another notable issue is the lack of standardized methods for assessing the quality of ASFV genomes. Furthermore, an increasing number of recombinant isolates of genotype I and II, have been observed, further complicating the task of phylogenetic analysis. To overcome these obstacles, we developed the ANASFV (analysis of an ASFV) pipeline. The pipeline is used to solve four tasks: In the first task, the pipeline introduces an amplicon sequencing approach that significantly improves genomic coverage, enabling reliable genome assembly. The pipeline also introduce reference-aided polishing techniques to correct small indels caused by nanopore sequencing errors. Moving on to the second task, a genome quality assessment system was established to evaluate the completeness and accuracy of the assembled genomes. For the third task, a method to rapidly analyze whether an isolate is a recombinant between genotype I and II, as well as to determine the pattern of recombination, based on gene similarity. Lastly, a comprehensive phylogenetic analysis based on coding sequences (CDS) was conducted, allowing us to generate a refined phylogenetic tree that includes all known ASFV genomes. The ANASFV pipeline will facilitate ASFV full genome sequencing using the nanopore platform. The pipeline will also support robust downstream bioinformatic analyses to assess genome integrity and conduct detailed phylogenetic studies based on whole-genome data.

genetics↗

bioRxiv2024

Activation of two noncanonical R proteins by an insect effector confers plant immunity to aphid infestation

Molecular characterization of resistance genes is crucial for efficiently understanding and fortifying plant immunity against insect herbivores. Here we report that RMES1A and RMES1B proteins confer resistance to the sorghum aphid Melanaphis sorghi when activated by an insect effector MsEF1. Map-based cloning plus genetic analysis of knockout mutants confirm that RMES1A and RMES1B are both required for aphid resistance. Upon aphid attack, RMES1A and RMES1B expression is elevated in the sclerenchyma cells and vascular bundles of leaves; the two proteins interact with MsEF1 in the exocysts, thus upregulating key defense processes such as reactive oxygen species burst. Structural modeling predicts that RMES1A and RMES1B each carry an ATP binding site and two leucine-rich-repeat domains but lack coiled-coil or Toll/Interleukin-1 receptor/resistance domain, thus likely representing a new type of resistance controlling proteins in plants. Our work reveals new genes and mechanisms for further deciphering and improving plant immunity to insect pests.

genetics↗

bioRxiv2024

GeneBag: training a cell foundation model for broad-spectrum cancer diagnosis and prognosis with bulk RNA-seq data

Numerous Pre-trained cell foundation models (CFM) have been crafted to encapsulate the comprehensive gene-gene interaction network within cells, leveraging extensive single-cell sequencing data. These models have shown promise in various cell biology applications, including cell type annotation, perturbation inference, and cell state embedding, etc. However, their clinical utility, particularly in cancer diagnosis and prognosis, remains an open question. We introduce the GeneBag model, a novel CFM that represents a cell as "a bag of unordered genes" with continuous expression values and a full-length gene list. Pre-trained on single-cell data and fine-tuned on bulk RNA-seq datasets, GeneBag achieves superior performance across cancer diagnosis and prognosis scenarios. In a zero-shot learning setting, GeneBag can classify cancer and non-cancer tissues with approximately 96.2% accuracy. With fine-tuning, it can annotate 40 different types of cancers and corresponding normal biopsies with an overall accuracy of [~]97.2%. It notably excels in classifying challenging cancers such as bladder (93%) and stomach (90%). Furthermore, GeneBag is capable of cancer staging with 68.5% accuracy and 5-year survival prediction with an AUC of [~]80.4%. This study marks the first to demonstrate the potential of CFMs in RNA-based cancer diagnostics and prognostics, indicating a promising avenue for AI-assisted molecular diagnosis.

bioinformatics↗

bioRxiv2024

Giraffe: a tool for comprehensive processing andvisualization of multiple long-read sequencing data

Third-generation sequencing techniques have become increasingly popular due to their ability to generate long, high-quality reads. Utilizing datasets from various samples and multiple sequencing platforms for comparative and comprehensive analysis is essential for exploring biological mechanisms and establishing benchmark baselines. However, current tools for long reads primarily focus on quality control (QC) and read processing for individual samples, complicating the profiling and comparison of multiple datasets. The lack of tools for data comparison and visualization presents challenges for researchers with limited bioinformatics experience. Furthermore, developing a comprehensive long-read QC method that facilitates comparative analysis and visualization across multiple samples and platforms is necessary to establish benchmark baselines for selecting appropriate sequencing platforms. We introduce Giraffe, a Python3-based command line tool designed for comparative analysis and visualization across multiple samples and platforms. Giraffe enables the assessment of read quality, sequencing bias, and genomic regional methylation proportions for both DNA and direct RNA sequencing reads. Its usability has been demonstrated in various scenarios, including comparisons of different biological processing methods (whole genome amplification vs. shotgun), sequencing platforms (Oxford Nanopore Technology vs. Pacific Biosciences), tissues (kidney marrow with and without blood), and biological replicates (kidney marrows). Additionally, our findings indicate that Oxford Nanopore duplex reads outperform PacBio HiFi reads in homopolymer identification and GC evenness while maintaining comparable overall read quality.

bioinformatics↗

bioRxiv2024

Enhanced Recognition of a Herbal Compound Epiberberine by a DNA Quadruplex-Duplex Structure

The small molecule epiberberine (EPI) is a natural alkaloid with versatile bioactivities against several diseases, including cancer and bacterial infection. EPI can induce the formation of a unique binding pocket at the 5' side of a human telomeric G-quadruplex (HTG) sequence Q4, resulting in a nanomolar binding affinity (KD approximately 26 nM) with significant fluorescence enhancement upon binding. It is important to understand (1) how EPI binding affects HTG structural stability and (2) how enhanced EPI binding may be achieved through the engineering of the DNA binding pocket. In this work, the EPI binding-induced HTG structure stabilization effect was probed by a peptide nucleic acid (PNA) invasion assay in combination with a series of biophysical techniques. We show that the PNA invasion-based method may be useful for the characterization of compounds binding to DNA (and RNA) structures in physiological conditions without the need to vary the solution temperature or buffer components, which are typically needed for structural stability characterization. Importantly, the combination of theoretical modeling and experimental quantification allows us to successfully engineer the Q4 derivative Q4-ds-A by a simple extension of a duplex structure to Q4 at the 5' end. Q4-ds-A is a superb EPI binder with a KD of 8 nM, with the binding enhancement achieved through the preformation of a binding pocket and a reduced dissociation rate. The tight binding of Q4 and Q4-ds-A with EPI allows us to develop a novel magnetic bead-based affinity purification system to effectively extract EPI from Rhizoma coptidis (Huang Lian) extracts.

biochemistry↗

bioRxiv2024

Corticospinal and corticoreticulospinal projections benefit motor behaviors in chronic stroke

After corticospinal tract (CST) stroke, several motor deficits in the upper extremity (UE) emerge, including diminished muscle strength, motor control, and muscle individuation. Both the ipsilesional CST and contralesional corticoreticulospinal tract (CReST) innervate the paretic UE and may have different innervation patterns for the proximal and distal UE segments. These patterns may underpin distinct pathway relationships to separable motor behaviors. In this cross-sectional study of 15 chronic stroke patients and 28 healthy subjects, we examined two key questions: (1) whether segmental motor behaviors differentially relate to ipsilesional CST and contralesional CReST projection strengths, and (2) whether motor behaviors segmentally differ in the paretic UE. We measured strength, motor control, and muscle individuation in a proximal (biceps, BIC) and distal muscle (first dorsal interosseous, FDI) of the paretic UE. We measured the projection strengths of the ipsilesional CST and contralesional CReST to these muscles using transcranial magnetic stimulation (TMS). Stroke subjects had abnormal motor control and muscle individuation despite strength comparable to healthy subjects. In stroke subjects, stronger ipsilesional CST projections were linked to superior motor control in both UE segments, whereas stronger contralesional CReST projections were linked to superior muscle strength and individuation in both UE segments. Notably, both pathways also shared associations with behaviors in the proximal segment. Motor control deficits were segmentally comparable, but muscle individuation was worse for distal motor performance. These results suggest that each pathway has specialized contributions to chronic motor behaviors but also work together, with varying levels of success in supporting chronic deficits. Key points summaryO_LIIndividuals with chronic stroke typically have deficits in strength, motor control, and muscle individuation in their paretic upper extremity (UE). It remains unclear how these altered behaviors relate to descending motor pathways and whether they differ by proximal and distal UE segment. C_LIO_LIIn this study, we used transcranial magnetic stimulation (TMS) to examine projection strengths of the ipsilesional corticospinal tract (CST) and contralesional corticoreticulospinal tract (CReST) with respect to quantitated motor behaviors in chronic stroke. C_LIO_LIWe found that stronger ipsilesional CST projections were associated with better motor control in both UE segments, whereas stronger contralesional CReST projections were associated with better strength and individuation in both UE segments. In addition, projections of both pathways shared associations with motor behaviors in the proximal UE segment. C_LIO_LIWe also found that deficits in strength and motor control were comparable across UE segments, but muscle individuation was worse with controlled movement in the distal UE segment. C_LIO_LIThese results suggest that the CST and CReST have specialized contributions to chronic motor behaviors and also work together, although with different degrees of efficacy. C_LI

neuroscience↗

bioRxiv2024

A novel classification framework for genome-wide association study of whole brain MRI images using deep learning

Genome-wide association studies (GWASs) have been widely applied in the neuroimaging field to discover genetic variants associated with brain-related traits. So far, almost all GWASs conducted in neuroimaging genetics are performed on univariate quantitative features summarized from brain images. On the other hand, powerful deep learning technologies have dramatically improved our ability to classify images. In this study, we proposed and implemented a novel machine learning strategy for systematically identifying genetic variants that lead to detectable nuances on Magnetic Resonance Images (MRI). For a specific single nucleotide polymorphism (SNP), if MRI images labeled by genotypes of this SNP can be reliably distinguished using machine learning, we then hypothesized that this SNP is likely to be associated with brain anatomy or function which is manifested in MRI brain images. We applied this strategy to a catalog of MRI image and genotype data collected by the Alzheimers Disease Neuroimaging Initiative (ADNI) consortium. From the results, we identified novel variants that show strong association to brain phenotypes.

bioinformatics↗

bioRxiv2023

Integrated Hfq-interacting RNAome and transcriptomic analysis reveals complex regulatory networks of nitrogen fixation in root-associated Pseudomonas stutzeri A1501

The RNA chaperone Hfq acts as a global regulator of numerous biological processes, such as carbon/nitrogen metabolism and environmental adaptation in plant-associated diazotrophs; however, its target RNAs and the mechanisms underlying nitrogen fixation remain largely unknown. Here, we used enhanced UV cross-linking immunoprecipitation coupled with high-throughput sequencing (eCLIP-seq) to identify hundreds of Hfq-binding RNAs probably involved in nitrogen fixation, carbon substrate utilization, biofilm formation, and other functions. Collectively, these processes endow strain A1501 with the requisite capabilities to thrive in the highly competitive rhizosphere. Our findings revealed a previously uncharted landscape of Hfq target genes. Notable among these is nifM, encoding an isomerase necessary for nitrogenase reductase solubility; amtB, encoding an ammonium transporter; oprB, encoding a carbohydrate porin; and cheZ, encoding a chemotaxis protein. Furthermore, we identified more than one hundred genes of unknown function, which expands the potential direct regulatory targets of Hfq in diazotrophs. Our data showed that Hfq directly interacts with regulatory proteins (RsmA, AlgU, NifA), regulatory ncRNA RsmY, and other potential targets, thus revealing the mechanistic links in nitrogen fixation and other metabolic pathways. IMPORTANCENumerous experimental approaches often face challenges in distinguishing between direct and indirect effects of Hfq-mediated regulation. New technologies based on high-throughput sequencing are increasingly providing insight into the global regulation of Hfq in gene expression. Here, enhanced UV cross-linking immunoprecipitation coupled with high-throughput sequencing (eCLIP-seq) was employed to identify the Hfq-binding sites and potential targets in the root-associated P. stutzeri A1501, and identify hundreds of novel Hfq-binding RNAs that are predicted to be involved in metabolism, environmental adaptation, and nitrogen fixation. In particular, we have shown that Hfq interactions with various regulatory proteins and their potential targets at both the protein and RNA levels. This study not only enhances our understanding of Hfq regulation but, importantly, also provides a framework for addressing integrated regulatory network underlying root-associated nitrogen fixation.

microbiology↗

bioRxiv2023

Differential developmental blueprints of organ-intrinsic nervous systems

The organ-intrinsic nervous system is a major interface between visceral organs and the brain, mediating important sensory and regulatory functions in the body-brain axis and serving as critical local processors for organ homeostasis. Molecularly, anatomically, and functionally, organ-intrinsic neurons are highly specialized for their host organs. However, the underlying mechanism that drives this specialization is largely unknown. Here, we describe the differential strategies utilized to achieve organ-specific organization between the enteric nervous system (ENS)1 and the intrinsic cardiac nervous system (ICNS)2, a neuronal network essential for heart performance but poorly characterized. Integrating high-resolution whole-embryo imaging, single-cell genomics, spatial transcriptomics, proteomics, and bioinformatics, we uncover that unlike the ENS which is highly mobile and colonizes the entire gastrointestinal (GI) tract, the ICNS uses a rich set of extracellular matrix (ECM) genes that match with surrounding heart cells and an intermediate dedicated neuronal progenitor state to stabilize itself for a beads-on-the-necklace organization on heart atria. While ICNS- and ENS-precursors are genetically similar, their differentiation paths are influenced by their host-organs, leading to distinct mature neuron types. Co-culturing ENS-precursors with heart cells shifts their identity towards the ICNS and induces the expression of heart-matching ECM genes. Our cross-organ study thus reveals fundamental principles for the maturation and specialization of organ-intrinsic neurons.

neuroscience↗

bioRxiv2023

An enclosed live-imaging platform to reveal ultrasound-inflicted mechanolysis and wound healing response

Focused ultrasound (FUS) has been widely adopted in medical and life science researches. Although various physical and biological effects of FUS have been well-documented, there is still a lack of understanding and direct evidence on the biological mechanism of therapeutic cell ablation caused by high-intensity ultrasound (HIFU) and the subsequent wound healing responses. This study develops an enclosed cell culture device that synergistically combines non-invasive FUS stimulation and real-time, on-the-fly live-cell imaging, providing an in vitro platform to explore short and long-term biological effects of ultrasound. The process, mechanism, and wound healing response of cell ablation induced by HIFU are elucidated, revealing a unique mechanism, termed ultrasound-inflicted cellular mechanolysis, that is mediated by growing subcellular cavitation air bubbles under confined contact with cells. This provides a previously unappreciated mechanism for understanding the biomechanical principles of ultrasound-based ablative therapy. We also reveal a post-ablation phantom layer that serves as a guiding cue for collective cell migration during wound healing, thereby providing a biomimetic model for studying wound healing after HIFU-inflicted damage. Together, this study provides theoretical and technological basis for advancing our understanding of the biological effects of ultrasound-based ablative therapy and inspiring clinically relevant applications in the future. Key Points1) Development of an integrated platform for real-time, on-the-fly imaging of FUS-induced cell ablation and response processes at cellular and subcellular levels 2) Focused ultrasound induces cellular mechanolysis through previously unappreciated subcellular cavitation bubbles that grow under confined contact with cells 3) Post-ablation phantom cell layer could serve as a guiding cue for collective wound healing after ultrasound-inflicted ablation

bioengineering↗

bioRxiv2023

Pre-neuronal biomechanical filtering modulates and diversifies whole-hand tactile encoding

Touching an object elicits skin oscillations that are biomechanically transmitted throughout the hand, driving responses in thousands of tactile receptors, including numerous exquisitely sensitive Pacinian corpuscles (PCs). Accepted descriptions of PC functionality characterize their response properties as highly stereotyped, based on experimental data gathered when stimuli are applied near the receptor. However, during natural touch, spiking activity in the majority of PCs is evoked by transmitted skin oscillations that are modified by biomechanical filtering. This filtering mechanism, stemming from dispersive wave dynamics in the skin, bears some similarity to the pre-neuronal filtering of auditory signals by the basilar membrane, a mechanical process that is instrumental to perception. Thus, we sought to clarify how skin biomechanics might influence tactile information encoding in the periphery. We used vibrometry imaging and computational neural experiments to examine the influence of biomechanical filtering on neural activity in whole-hand PC populations. We observed complex, location- and frequency-dependent patterns of filtering that were shaped by tissue mechanics and hand morphology. This source of biomechanical modulation diversified PC population spiking activity and enhanced tactile information encoding efficiency. These findings indicate that biomechanics furnishes a pre-neuronal mechanism that facilitates efficient tactile encoding and processing.

neuroscience↗