Biology subjects

An, S.

Publications and source records attributed to An, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Scm6A: A fast and low-cost method for quantifying m6A modifications at the single-cell level

It is widely accepted that m6A exhibits significant intercellular specificity, which poses challenges for its detection using existing m6A quantitative methods. In this study, we introduce Scm6A, a machine learning-based approach for single-cell m6A quantification. Scm6A leverages input features derived from the expression levels of m6A trans regulators and cis sequence features, and found that Scm6A offers remarkable prediction efficiency and reliability. To further validate the robustness and precision of Scm6A, we applied a winscore-based m6A calculation method to conduct m6A-seq analysis on CD4+ and CD8+ T-cells isolated through magnetic-activated cell sorting (MACS). Subsequently, we employed Scm6A for analysis on the same samples. Notably, the m6A levels calculated by Scm6A exhibited a significant positive correlation with m6A quantified through m6A-seq in different cells isolated by MACS, providing compelling evidence for Scm6As reliability. We also used the scm6A-seq method to validate the reliability of our approach. Additionally, we performed single-cell level m6A analysis on lung cancer tissues as well as blood samples from COVID-19 patients, and demonstrated the landscape and regulatory mechanisms of m6A in different T-cell subtypes from these diseases. In summary, our work has yielded a novel, dependable, and accurate method for single-cell m6A detection. We are confident that Scm6A will have broad applications in the realm of m6A-related research.

bioinformatics↗

bioRxiv2023

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types

As the most abundant mRNA modification in mRNA, N6-methyladenosine (m6A) plays a crucial role in RNA fate, impacting cellular and physiological processes in various tumor types. However, our understanding of the function and role of the m6A methylome in tumor heterogeneity remains limited. Herein, we collected and analyzed m6A methylomes across nine human tissues from 97 m6A-seq and RNA-seq samples. Our findings demonstrate that m6A exhibits different heterogeneity in most tumor tissues compared to normal tissues, which contributes to the diverse clinical outcomes in different cancer types. We also found that the cancer type-specific m6A level regulated the expression of different cancer-related genes in distinct cancer types. Utilizing a novel and reliable method called "m6A-express", we predicted m6A- regulated genes and revealed that cancer type-specific m6A-regulated genes contributed to the prognosis, tumor origin and infiltration level of immune cells in diverse patient populations. Furthermore, we identified cell-specific m6A regulators that regulate cancer-specific m6A and constructed a regulatory network. Experimental validation was performed, confirming that the cell-specific m6A regulator CAPRIN1 controls the m6A level of TP53. Overall, our work reveals the clinical relevance of m6A in various tumor tissues and explains how such heterogeneity is established. These results further suggest the potential of m6A for cancer precision medicine for patients with different cancer types.

bioinformatics↗

bioRxiv2023

A neuron-specific microexon ablates the novel DNA-binding function of a histone H3K4me0 reader PHF21A

How cell-type-specific chromatin landscapes emerge and progress during metazoan ontogenesis remains an important question. Transcription factors are expressed in a cell-type-specific manner and recruit chromatin-regulatory machinery to specific genomic loci. In contrast, chromatin-regulatory proteins are expressed broadly and are assumed to exert the same intrinsic function across cell types. However, human genetics studies have revealed an unexpected vulnerability of neurodevelopment to chromatin factor mutations with unknown mechanisms. Here, we report that 14 chromatin regulators undergo evolutionary-conserved neuron-specific splicing events involving microexons. Of the 14 chromatin regulators, two are integral components of a histone H3K4 demethylase complex; the catalytic subunit LSD1 and an H3K4me0-reader protein PHF21A adopt neuron-specific forms. We found that canonical PHF21A (PHF21A-c) binds to DNA by AT-hook motif, and the neuronal counterpart PHF21A-n lacks this DNA-binding function yet maintains H3K4me0 recognition intact. In-vitro reconstitution of the canonical and neuronal PHF21A-LSD1 complexes identified the neuronal complex as a hypomorphic H3K4 demethylating machinery with reduced nucleosome engagement. Furthermore, an autism-associated PHF21A missense mutation, 1285 G>A, at the last nucleotide of the common exon immediately upstream of the neuronal microexon led to impaired splicing of PHF21A-n. Thus, ubiquitous chromatin regulatory complexes exert unique intrinsic functions in neurons via alternative splicing of their subunits and potentially contribute to faithful human brain development.

molecular biology↗

bioRxiv2023

Cobalt-sulfur coordination chemistry drives B12 loading onto methionine synthase

Cobalt-sulfur (Co-S) coordination is labile to both oxidation and reduction chemistry and is rarely seen in Nature. Cobalamin (or vitamin B12) is an essential cobalt-containing organometallic cofactor in mammals, and is escorted via an intricate network of chaperones to a single cytoplasmic target, methionine synthase. In this study, we report that the human cobalamin trafficking protein, MMADHC, exploits the chemical lability of Co-S coordination, for cofactor off-loading onto methionine synthase. Cys-261 on MMADHC serves as the {beta}-axial ligand to cobalamin. Complex formation between MMADHC and methionine synthase is signaled by loss of the lower axial nitrogen ligand, leading to five-coordinate thiolato-cobalamin. Nucleophilic displacement by the vicinal thiolate, Cys-262, completes cofactor transfer to methionine synthase and release of a cysteine disulfide-containing MMADHC. The physiological relevance of this mechanism is supported by clinical variants of MMADHC, which impair cofactor binding and off-loading, explaining the molecular basis of the associated homocystinuria.

biochemistry↗

bioRxiv2023

Entropy-based decoy generation methods for accurate FDR estimation in large-scale metabolomics annotations.

Large-scale metabolomics research faces challenges in accurate metabolite annotation and false discovery rate (FDR) estimation. Recent progress in addressing these challenges has leveraged experience from proteomics and inspiration from other sciences. Although the target-decoy strategy has been applied to metabolomics, generating reliable decoy libraries is difficult due to the complexity of metabolites. Additionally, continuous bioinformatic efforts are necessary to increase the utilization of growing spectra resources while reducing false identifications. Here we introduce the concept of ion entropy and present two entropy-based decoy generation methods. The assessment of public spectral databases using ion entropy validated it as a good metric for ion information content in massive metabolomics data. The decoy generation method developed based on this concept outperformed current representative decoy strategies in metabolomics and achieved the best FDR estimation performance. We analyzed 47 public metabolomics datasets using the constructed workflow to provide instructive suggestions. Finally, we present MetaPhoenix, a tool equipped with a well-constructed FDR estimation workflow that facilitates the development of accurate FDR-controlled analysis in the metabolomics field.

bioinformatics↗

bioRxiv2023

Discovery of the apiosyltransferase, celery UGT94AX1 that catalyzes the biosynthesis of a flavone glycoside, apiin

Apiose is a unique branched-chain pentose found in plant glycosides and a key component of the cell wall-polysaccharide pectin and other specialized metabolites. More than 1,200 plant-specialized metabolites contain apiose residues, represented by apiin, a distinctive flavone glycoside found in celery and parsley in the family Apiaceae. The physiological functions of apiin remain obscure, partly due to our lack of knowledge on apiosyltransferase during apiin biosynthesis. Here, we identified celery UGT94AX1 (AgApiT) as a novel apiosyltransferase, responsible for catalyzing the last sugar-modification step in apiin biosynthesis. AgApiT showed strict substrate specificity for the sugar donor, UDP-apiose, and moderate specificity for acceptor substrates, thereby producing various apiose-containing flavone glycosides in celery. Homology modeling of AgApiT with UDP-apiose, followed by site-directed mutagenesis experiments, identified unique Ile139, Phe140, and Leu356 residues in AgApiT, which are seemingly crucial for the recognition of UDP-apiose in the sugar donor pocket. Sequence comparison and molecular phylogenetic analysis of celery glycosyltransferases paralogous to AgApiT suggested that AgApiT is the sole apiosyltransferase-encoding gene in the celery genome. This is the first report on the identification of a plant apiosyltransferase gene that will enhance our understanding of the physio-ecological functions of apiose and apiose-containing compounds.

biochemistry↗

bioRxiv2023

Aird-ComboComp: A combinable compressor framework with a dynamic-decider for lossy mass spectrometry data compression

Mass spectrum (MS) data volumes increase with an improved ion acquisition ratio and a highly accurate mass spectrometer. However, the most widely used data format, mzML, does not take advantage of compression methods and improved read performances. Several compression algorithms have been proposed in recent years, and they consider a number of factors, including, numerical precision, metadata read strategies and the compression performance. Due to limited compression ratio, the high-throughput MS data format is still quite large. High bandwidth and memory requirements severely limit the applicability of MS data analysis in cloud and mobile computing. ComboComp is a comprehensive improvement to the Aird data format. Instead of using the general-purpose compressor directly, ComboComp uses two integer-purpose compressors and four general-purpose compressors, and obtains the best compression combination with a dynamic decider, achieving the most balanced compression ratio among all the numerous varieties of compressors. ComboComp supports a seamless extension of the new integer and generic compressors, making it an evolving compression framework. The improvement of compression rate and decoding speed greatly reduces the cost of data exchange and real-time decompression, and effectively reduces the hardware requirements of MS data analysis. Analyzing mass spectrum data on IoT devices can be useful in real-time quality control, decentralized analysis, collaborative auditing, and other scenarios. We tested ComboComp on 11 datasets generated by commonly used MS instruments. Compared with Aird-ZDPD, the compression size can be reduced by an average of 12.9%. The decompression speed is increased by an average of 27.1%. The average compression time is almost the same as that of ZDPD. The high compression rate and decoding speed make the Aird format effective for data analysis on small memory devices. This will enable MS data to be processed normally even on IoT devices in the future. We provide SDKs in three languages, Java, C# and Python, which offer optimized interfaces for the various acquisition modes. All the SDKs can be found on Github: https://github.com/CSi-Studio/Aird-SDK.

bioinformatics↗

bioRxiv2023

How much storage precision can be lost: Guidance for near-lossless compression of untargeted metabolomics mass spectrometry data

The size of high-resolution mass spectrometry (HRMS) data has been increasing significantly. Several lossy compressors have been developed for higher compression rates. Currently, a comprehensive evaluation of what and how MS data (m/z and intensities) with precision losses would affect data processing (i.e., feature detection and compound identification) is absent. Here, we set an error threshold at 1% to assess the significance of the difference between two files in feature and compound detection results obtained from MZmine3. First, we examined that mzML files with both m/z and intensity encoded in 32-bit precision appear to be a preferred combination via msConvert, which has smaller file size and minor variation with other combinations of storage precision (<0.13%). We then identified that the absolute error of 10-4 for m/z had a feature detection error of 0.57% and compound detection error of 1.1%. For intensities, the relative error group of 2x10-2 had an error of 4.65% for features and 0.98% for compounds, compared with precision-lossless files. Taken together, we provided a reasonable scene-accuracy proposal, with a maximum absolute error of 10-4 for m/z and a maximum relative error of 2x10-2 for intensity. This guidance aimed to help researchers in improving lossy compression algorithms and minimizing the negative effects of precision losses on downstream data processing.

bioinformatics↗

bioRxiv2023

Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies

Growth factors and cytokines signal by binding to the extracellular domains of their receptors and drive association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affects signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo designed fibroblast growth-factor receptor (FGFR) binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and MAPK pathway activation. The high specificity of the designed agonists reveal distinct roles for two FGFR splice variants in driving endothelial and mesenchymal cell fates during early vascular development. The ability to incorporate receptor binding domains and repeat extensions in a modular fashion makes our designed scaffolds broadly useful for probing and manipulating cellular signaling pathways. HighlightsO_LIDe novo designed cyclic oligomers with tunable geometric properties C_LIO_LICyclic, homo-oligomeric FGFR binding modules induce geometry- and valency-dependent activity of isoform-specific FGF signaling C_LIO_LIModulation of FGFR isoform activity controls bifurcation of endothelial and mesenchymal fate during vascular development C_LIO_LIC-isoform activation favors arterial endothelial cell formation while B-isoform induces pericyte differentiation C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/532666v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@151f6eforg.highwire.dtl.DTLVardef@2ae877org.highwire.dtl.DTLVardef@103e0d1org.highwire.dtl.DTLVardef@19cd695_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2023

InjectionDesign: Plate Design with Optimized Stratified Block Randomization for Modern LC/GC-MS-Based Sample Preparation

Plate Design is a necessary and time-consuming operation for GC/LC-MS based sample preparation. The implementation of the inter-batch balancing algorithm and the intra-batch randomization algorithm can have a significant impact on the final analysis results. For researchers without programming skills, a stable and efficient online service for plate design is necessary. However, most exist products do not currently have online services, and are not optimized for GC/LC-MS instruments with custom injection capabilities. Here we describe InjectionDesign, a free online plate design service focus on GC/LC-MS-based multi-omics experiment design. It offers the ability to separate the position design from the sequence design, making the output more compatible with the requirements of a modern mass spectrometer-based laboratory. In addition, it has implemented an optimized block randomization algorithm, which can be better applied to sample stratification with block randomization for unbalanced distribution. It is easy to use, with built-in support for common instrument models and quick export to worksheet. InjectionDesign is an open-source project based on Java. Researchers can get the source code of the project from Github: https://github.com/CSi-Studio/InjectionDesign. A free web service is also provided: http://www.injection.design. Demo Projecthttp://www.injection.design/#/project/detail?projectId=Test

bioinformatics↗

bioRxiv2023

Quantitative model of aging-related muscle degeneration: a Drosophila study

Changes in the composition and functionality of somatic muscles is a universal hallmark of aging that is displayed by a wide range of species. In humans, complications arising from muscle decline due to sarcopenia aggravate morbidity and mortality rates. The genetics of aging-related deterioration of muscle tissue is not well understood, which prompted us to characterize aging-related muscle degeneration in Drosophila melanogaster (fruit fly), a leading model organism in experimental genetics. Adult flies demonstrate spontaneous degeneration of muscle fibers in all types of somatic muscles, which correlates with functional, chronological, and populational aging. Morphological data imply that individual muscle fibers die by necrosis. Using quantitative analysis, we demonstrate that muscle degeneration in aging flies has a genetic component. Chronic neuronal overstimulation of muscles promotes fiber degeneration rates, suggesting a role for the nervous system in muscle aging. From the other hand, muscles decoupled from neuronal stimulation retain a basal level of spontaneous degeneration, suggesting the presence of intrinsic factors. Based on our characterization, Drosophila can be adopted for systematic screening and validation of genetic factors linked to aging-related muscle loss.

pathology↗

bioRxiv2023

A novel HERC4-dependent glue degrader targeting STING

Stimulator of interferon genes (STING) is a central component of the pathway sensing the presence of cytosolic nucleic acids, having a key role in type I interferon innate immune response. Localized at the endoplasmic reticulum (ER), STING becomes activated by cGAMP, which is generated by the intracellular DNA sensor cyclic GMP-AMP synthase (cGAS). Due to its critical role in physiological function and its involvement in a variety of diseases, STING has been a notable focus for drug discovery. Recent advances in drug discovery allow the targeting of proteins previously considered "un-druggable" by novel mechanism of actions. Molecular glue degraders are defined as the compounds leading targeted protein degradation (TPD) by creating novel ligase-substrate interactions. Here, we identified AK59 as a novel molecular glue degrader for STING. A genome-wide, CRISPR/Cas9 knockout screen showed that the compound-mediated degradation of STING by AK59 is compromised by the loss of HECT and RLD domain containing E3 ubiquitin protein ligase 4 (HERC4), ubiquitin-like modifier activating enzyme 5 (UBA5) and ubiquitin like modifier activating enzyme 6 (UBA6). While UBA5 and UBA6 could be the auxiliary factors for AK59 activity, our results indicate that HERC4 is the main E3 ligase for the observed degradation mechanism. Validation by individual CRISPR knockouts, co-immunoprecipitations, as well as proximity mediated reporter assays suggested that AK59 functions as a glue degrader by forming a novel interaction between STING and HERC4. Furthermore, our data reveals that AK59 was effective on the most common pathological STING mutations that cause STING-associated vasculopathy with onset in infancy (SAVI), suggesting a potential clinical application of this mechanism. Thus, these findings not only reveal a novel mechanism for compound-induced degradation of STING but also utilize HERC4 as potential E3 ligase that for TPD, enabling novel therapeutic applications.

molecular biology↗

bioRxiv2022

MIDAS: a deep generative model for mosaic integration and knowledge transfer of single-cell multimodal data

AO_SCPLOWBSTRACTC_SCPLOWRapidly developing single-cell multi-omics sequencing technologies generate increasingly large bodies of multimodal data. Integrating multimodal data from different sequencing technologies, i.e. mosaic data, permits larger-scale investigation with more modalities and can help to better reveal cellular heterogeneity. However, mosaic integration involves major challenges, particularly regarding modality alignment and batch effect removal. Here we present a deep probabilistic framework for the mosaic integration and knowledge transfer (MIDAS) of single-cell multimodal data. MIDAS simultaneously achieves dimensionality reduction, imputation, and batch correction of mosaic data by employing self-supervised modality alignment and information-theoretic latent disentanglement. We demonstrate its superiority to other methods and reliability by evaluating its performance in full trimodal integration and various mosaic tasks. We also constructed a single-cell trimodal atlas of human peripheral blood mononuclear cells (PBMCs), and tailored transfer learning and reciprocal reference mapping schemes to enable flexible and accurate knowledge transfer from the atlas to new data. Applications in mosaic integration, pseudotime analysis, and cross-tissue knowledge transfer on bone marrow mosaic datasets demonstrate the versatility and superiority of MIDAS.

bioinformatics↗

bioRxiv2022

A highly expressed odorant receptor from the yellow fever mosquito, AaegOR11, responds to (+)- and (-)-fenchone and a phenolic repellent

The cornerstone of the reverse chemical ecology approach is the identification of odorant receptors (OR) sensitive to compounds in a large panel of odorants. In this approach, we de-orphanize ORs and, subsequently, measure behaviors elicited by these semiochemicals. After that, we evaluate behaviorally active compounds for applications in insect vector management. Intriguingly, multiple ORs encoded by genes highly expressed in mosquito antennae do not respond to any test odorant. One such case is CquiOR125 from the southern house mosquito, Culex quinquefasciatus Say. To better understand CquiOR125s role in Culex mosquito olfaction, we have cloned a CquiOR125 orthologue in the genome of the yellow fever mosquito, Aedes aegypti (L.), AaegOR11. Unlike the unresponsive nature of the orthologue in Cx. quinquefasciatus, oocytes co-expressing AaegOR11 and AaegOrco elicited robust responses when challenged with fenchone, 2,3-dimethylphenol, 3,4-dimethylphenol, 4-methycyclohexanol, and acetophenone. AlphaFold models showed that AaegOR11 and CquiOR125 share structural homolog cores with MhraOR5, the only insect OR structure (PDB: 7LID) elucidated to date. Interestingly, AaegOR11 responded strongly and equally to (+)- and (-)-fenchone, with no chiral discrimination. Contrary to reports in the literature, fenchone did not show any repellency activity against Ae. aegypti or Cx. quinquefasciatus. Laboratory and field tests did not show significant increases in egg captures in cups filled with fenchone solutions compared to control cups. The second most potent ligand, 2,3-dimethylphenol, showed repellency activity stronger than that elicited by DEET at the same dose. We, therefore, concluded that AaegOR11 is a mosquito repellent sensor. It is feasible that CquiOR125 responds to repellents that remain elusive.

neuroscience↗

bioRxiv2022

Talaromyces marneffei suppresses human macrophages inflammatory by producing the truncated protein NCOR2-013 via TUT1-regulated alternative splicing

Talaromyces marneffei (T. marneffei) immune-escaping is an important factor for high mortality of talaromycosis. It is currently known that T. marneffei performs these functions through a variety of strategies, however, the role of alternative splicing (AS) in this process is poorly understood. Here we depicted the AS landscape in the macrophage upon T. marneffei infection via high-throughput RNA sequencing. Moreover, we identified a truncated protein of NCOR2/SMRT, namedly NCOR2-013, was significantly upregulated upon T. marneffei infection. Mechanistic analysis indicates that NCOR2-013 forms a co-repression complex with TBL1XR1/TBLR1 and HDAC3, thereby inhibiting JunB-mediated transcriptional activation of pro-inflammatory cytokines via the inhibition of histone acetylation. Also, we identified TUT1 as the AS regulator that involved in facilitating T. marneffei immune evasion via regulation of NCOR2-013 production. Collectively, the findings indicate that T. marneffei escapes macrophages killing through the TUT1-mediated the alternative splicing of NCOR2-013, which providing a new insight into the molecular mechanisms of T. marneffei immune evasion, and a potential targets for talaromycosis therapy.

microbiology↗

bioRxiv2022

Mechanistic insights of glucosome condensate formation by stochastic modeling approaches

Human liver-type phosphofructokinase 1 (PFKL) has been shown to play a scaffolder role to recruit and organize glycolytic and gluconeogenic enzymes into a multienzyme metabolic condensate, the glucosome, that regulates glucose flux in living human cells. However, it has been challenging to characterize which factors control phase separation of PFKL and so glucosome condensates in a living cell, thus hampering to understand a mechanism of reversible glucosome formation and its functional contribution to human cells. In this work, we developed a stochastic model in silico using the principal of Langevin dynamics to investigate how biological properties of PFKL contribute to the formation of glucosome condensates. Molecular dynamics simulation using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) revealed the importance of an intermolecular interaction between PFKLs, an effective concentration of PFKL at a region of interest, and a pre-organization of its own self-assembly in formation of PFKL condensates and control of their sizes. Such biological properties that define intracellular dynamics of PFKL appear to be essential for phase separation of PFKL and thus formation of glucosome condensates. Collectively, our computational study provides mechanistic insights of glucosome formation, particularly an initiation step through the formation of PFKL condensates in living human cells.

biochemistry↗

bioRxiv2022

High-content quantitative high-throughput screening identifies a cell cycle-associated signaling cascade that regulates a multienzyme metabolic assembly for glucose metabolism

We have previously demonstrated that human liver-type phosphofructokinase 1 (PFK1) recruits other rate-determining enzymes in glucose metabolism to organize multienzyme metabolic assemblies, the glucosomes, in human cells. However, it has remained largely elusive how glucosomes are reversibly assembled and disassembled to functionally regulate glucose metabolism in human cells. We developed a high-content quantitative high-throughput screening (qHTS) assay to evaluate the impact of small molecule libraries on the formation of PFK1-mediated glucosome assemblies from stably transfected HeLa Tet-On cells. Initial qHTS with a library of pharmacologically active compounds directed following efforts to kinase-inhibitor enriched collections. Consequently, three active compounds that were known to inhibit cyclin-dependent kinase 2, ribosomal protein S6 kinase and Aurora kinase A, respectively, were identified and further validated under high-resolution fluorescence single-cell microscopy. Subsequent knockdown studies using small-hairpin RNAs confirmed an active role of Aurora kinase A on the formation of PFK1 assemblies in HeLa cells. Importantly, all the identified protein kinases here have been investigated as key signaling nodes of one specific cascade that controls cell cycle progression in human cells. Collectively, our qHTS approaches unravel a cell cycle-associated signaling cascade that regulates the formation of PFK1-mediated glucosome assembly in human cells.

biochemistry↗

bioRxiv2022

Magneto-acoustic protein nanostructures for non-invasive imaging of tissue mechanics in vivo

Measuring cellular and tissue mechanics inside intact living organisms is essential for interrogating the roles of force in physiological and disease processes, and is a major goal in the field of mechanobiology. However, existing biosensors for 3D tissue mechanics, primarily based on fluorescent emissions and deformable materials, are limited for in vivo measurement due to the limited light penetration and poor material stability inside intact, living organisms. While magneto-motive ultrasound (MMUS), which uses superparamagnetic nanoparticles as imaging contrast agents, has emerged as a promising modality for real-time in vivo imaging of tissue mechanics, it has poor sensitivity and spatiotemporal resolution. To overcome these limitations, we introduce magneto-gas vesicles (MGVs), a unique class of protein nanostructures based on gas vesicles and magnetic nanoparticles that produces differential ultrasound signals in response to varying mechanical properties of surrounding tissues. These hybrid protein nanostructures significantly improve signal strength and detection sensitivity. Furthermore, MGVs enable non-invasive, long-term, and quantitative measurement of mechanical properties within 3D tissues and organs in vivo. We demonstrated the performance of MGV-based mechano-sensors in vitro, in fibrosis models of organoids, and in vivo in mouse liver fibrosis models.

biochemistry↗