Biology subjects

Zhao, H.

Publications and source records attributed to Zhao, H..

At least 361 records · Page 20Linked to original sources

bioRxiv2023

Airway secretory cell-derived p63+ progenitors contribute to alveolar regeneration after sterile lung injury

Lung injury activates epithelial stem or progenitor cells for alveolar repair and regeneration. However, the origin and fate of injury-induced progenitors are poorly defined. Here, we report that p63-expressing progenitors emerge upon bleomycin-induced lung injury. These p63+ progenitors proliferate rapidly and differentiate into alveolar type 1 (AT1) and type 2 (AT2) cells through distinct trajectories. Dual recombinase-mediated sequential genetic lineage tracing reveals that p63+ progenitors originate from airway secretory cells and subsequently generate alveolar cells. Functionally, p63 activation is required for efficient alveolar regeneration from secretory cells. Our study identifies a secretory cell-derived p63+ progenitor that contributes to alveolar repair, indicating a potential therapeutic avenue for lung regeneration after injury.

cell biology↗

bioRxiv2023

Optimized SMRT-UMI protocol produces highly accurate sequence datasets from diverse populations - application to HIV-1 quasispecies

Pathogen diversity resulting in quasispecies can enable persistence and adaptation to host defenses and therapies. However, accurate quasispecies characterization can be impeded by errors introduced during sample handling and sequencing which can require extensive optimizations to overcome. We present complete laboratory and bioinformatics workflows to overcome many of these hurdles. The Pacific Biosciences single molecule real-time platform was used to sequence PCR amplicons derived from cDNA templates tagged with universal molecular identifiers (SMRT-UMI). Optimized laboratory protocols were developed through extensive testing of different sample preparation conditions to minimize between-template recombination during PCR and the use of UMI allowed accurate template quantitation as well as removal of point mutations introduced during PCR and sequencing to produce a highly accurate consensus sequence from each template. Handling of the large datasets produced from SMRT-UMI sequencing was facilitated by a novel bioinformatic pipeline, Probabilistic Offspring Resolver for Primer IDs (PORPIDpipeline), that automatically filters and parses reads by sample, identifies and discards reads with UMIs likely created from PCR and sequencing errors, generates consensus sequences, checks for contamination within the dataset, and removes any sequence with evidence of PCR recombination or early cycle PCR errors, resulting in highly accurate sequence datasets. The optimized SMRT-UMI sequencing method presented here represents a highly adaptable and established starting point for accurate sequencing of diverse pathogens. These methods are illustrated through characterization of human immunodeficiency virus (HIV) quasispecies. Author SummaryThere is a great need to understand the genetic diversity of pathogens in an accurate and timely manner, but many errors can be introduced during the sample handling and sequencing steps which may prevent accurate analyses. In some cases, the errors introduced during these steps can be indistinguishable from real genetic variation and prevent analyses from identifying true sequence variation present in the pathogen population. There are established methods which can help to prevent these types of errors, but can involve many different steps and variables, all of which must be optimized and tested together to ensure the desired effect. Here we show results from testing different methods on a set of HIV+ blood plasma samples and arrive at a streamlined laboratory protocol and bioinformatic pipeline which prevents or corrects for different types of errors that can arise in sequence datasets. These methods should be an accessible starting point for anyone wanting accurate sequencing without extensive optimizations.

molecular biology↗

bioRxiv2023

Retrieved Sequence Augmentation for Protein Representation Learning

The advancement of protein representation learning has been significantly influenced by the remarkable progress in language models. Accordingly, protein language models perform inference from individual sequences, thereby limiting their capacity to incorporate evolutionary knowledge present in sequence variations. Existing solutions, which rely on Multiple Sequence Alignments (MSA), suffer from substantial computational overhead and suboptimal generalization performance for de novo proteins. In light of these problems, we introduce a novel paradigm called Retrieved Sequence Augmentation (RSA) that enhances protein representation learning without necessitating additional alignment or preprocessing. RSA associates query protein sequences with a collection of structurally or functionally similar sequences in the database and integrates them for subsequent predictions. We demonstrate that protein language models benefit from retrieval enhancement in both structural and property prediction tasks, achieving a 5% improvement over MSA Transformer on average while being 373 times faster. Furthermore, our model exhibits superior transferability to new protein domains and outperforms MSA Transformer in de novo protein prediction. This study fills a much-encountered gap in protein prediction and brings us a step closer to demystifying the domain knowledge needed to understand protein sequences. Code is available at https://github.com/HKUNLP/RSA.

bioinformatics↗

bioRxiv2023

Analysis of the SARS-CoV-2 spike protein revealed that blocked receptor-binding domain antigenicity decreases the production of neutralizing antibodies in vivo

The identification of SARS-CoV-2 spike protein distribution and function in target cells has raised concerns about its possible impacts on vaccine efficacy and pathogenic effect in host cells. Thus, a better understanding of such consequences is necessary. In this study, we studied the biological characteristics of six variants of SARS-CoV-2 in A549 and HEK293 cells using four different technologies. The results showed that compared to the other fragments, the full-length spike protein exhibited the highest expression on the cell surface and was detectable in the cell supernatant, cytoplasm, and nucleus. Except for the cell surface, the S1 subunit generally expressed higher than the full-length spike protein. RBD and S2 subunits were expressed in the cytoskeleton. The SS-RBD peptide, which consists of a 19-amino acid signal peptide sequence (SS)-linked RBD, exhibited the highest expression in the cell supernatant among all other studied peptides. The SS positively enhanced the expression, migration, and secretion of SS-RBD from the cytoskeleton to the supernatant. Importantly, the FACS assay results showed that neutralizing antibodies (NAbs) could recognize SS-RBD but not RBD in the transfected cells, suggesting that RBD was tightly bound by ACE2 in HEK293 cells. In contrast, the antigenicity of the RBD in the spike protein was revealed and efficiently monitored only by 6-His-tag mAbs. Thus, our findings demonstrated that ACE2 blocks crucial immunogenic epitopes of the RBD, and the full-length spike protein mainly induces non-neutralizing antibodies in vivo. Therefore, we suggest that reducing ACE2 binding affinity and exposing the immunogenicity of the RBD on the spike protein is imperative for improving vaccine efficacy and generating new SARS-CoV-2 mRNA vaccines.

microbiology↗

bioRxiv2023

High-throughput screening of functional neo-antigens and their specific TCRs via the Jurkat reporter system combine with droplet microfluidics

T-cell receptor (TCR)-engineered T cells can precisely recognize a broad repertoire of targets derived from both intracellular and surface proteins of tumor cells. TCR-T adoptive cell therapy has shown safety and promising efficacy in solid tumor immunotherapy. However, antigen-specific functional TCR screening is time-consuming and expensive, which limits its application clinically. Here, we developed a novel integrated antigen-TCR screening platform based on droplet microfluidics technology, enabling high-throughput peptide-major histocompatibility complex (pMHC) library-to-TCR library screening with high sensitivity and low background signal. We introduced DNA barcoding technology to label peptide antigen candidate-loaded antigen-presenting cells (APCs) and Jurkat reporter cells to check the specificity of pMHC-TCR candidates. Coupled with the next-generation sequencing pipeline, interpretation of the DNA barcodes and the gene expression level of the Jurkat T-cell activation pathway provided a clear peptide-MHC-TCR recognition relationship. Our proof-of-principle study demonstrates that the platform could achieve unbiased pMHC-TCR library-on-library screening, which is expected to be used in the cross-reactivity and off-target testing of candidate pMHC-TCR libraries in clinical applications.

bioengineering↗

bioRxiv2023

BinderSpace: A Package for Sequence Space Analyses for Datasets of Affinity-Selected Oligonucleotides and Peptide-Based Molecules

Discovery of target-binding molecules, such as aptamers and peptides, is usually performed with the use of high-throughput experimental screening methods. These methods typically generate large datasets of sequences of target-binding molecules, which can be enriched with high affinity binders. However, the identification of the highest affinity binders from these large datasets often requires additional low-throughput experiments or other approaches. Bioinformatics-based analyses could be helpful to better understand these large datasets and identify the parts of the sequence space enriched with high affinity binders. BinderSpace is an open-source Python package that performs motif analysis, sequence space visualization, clustering analyses, and sequence extraction from clusters of interest. The motif analysis, resulting in text-based and visual output of motifs, can also provide heat maps of previously measured user-defined functional properties for all the motif-containing molecules. Users can also run principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analyses on whole datasets and on motif-related subsets of the data. Functionally important sequences can also be highlighted in the resulting PCA and t-SNE maps. If points (sequences) in two-dimensional maps in PCA or t-SNE space form clusters, users can perform clustering analyses on their data, and extract sequences from clusters of interest. We demonstrate the use of BinderSpace on a dataset of oligonucleotides binding to single-wall carbon nanotubes in the presence and absence of a bioanalyte, and on a dataset of cyclic peptidomimetics binding to bovine carbonic anhydrase protein. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/528758v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@cf45aforg.highwire.dtl.DTLVardef@1e819eaorg.highwire.dtl.DTLVardef@fd9340org.highwire.dtl.DTLVardef@1ce7f78_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Rice Gene Index (RGI): a comprehensive pan-genome database for comparative and functional genomics of Asian rice

To integrate the genomic information of the rice pan-genome, we performed comparative analyses and established a user-friendly Rice Gene Index (RGI, https://riceome.hzau.edu.cn) platform with 16 platinum standard reference genomes and supplementary transcriptome data. To logically organize and scientifically the index of 744,233 genes among rice accessions, we detected 112,658 Ortholog Gene Indices, and provide GeneCard pages to query genomic, transcriptomic, and homology information for each gene. The RGI allows users to search for relationships and comprehensive information of genes in keyword-based, sequence-based, and relationship-based ways. Furthermore, users can visualize these relationships at local and global scales corresponding to Microcollinearity and Macrocollinearity modules.

genomics↗

bioRxiv2023

A COVID-19 DNA Vaccine Candidate Elicits Broadly Neutralizing Antibodies Against Multiple SARS-CoV-2 Variants Including the Currently Circulating Omicron BF.5, BF.7, BQ.1 and XBB

Waves of breakthrough infections by SARS-CoV-2 Omicron subvariants pose a global challenge to pandemic control today. We have previously reported a pVAX1-based DNA vaccine candidate, pAD1002, which encodes a receptor-binding domain (RBD) chimera of SARS-CoV-1 and Omicron BA.1. In mouse and rabbit models, pAD1002 plasmid induced cross-neutralizing Abs against heterologous Sarbecoviruses, including SARS-CoV-1 and SARS-CoV-2 prototype, Delta and Omicron variants. However, these antisera failed to block the recent emerging Omicron subvariants BF.7 and BQ.1. To solve this problem, we replaced the BA.1-encoding DNA sequence in pAD1002 with that of BA.4/5. The resulting construct, namely pAD1016, elicited SARS-CoV-1 and SARS-CoV-2 RBD-specific IFN-{gamma}+ cellular responses in BALB/c and C57BL/6 mice. More importantly, pAD1016 vaccination in mice and rabbits generated serum Abs capable of neutralizing pseudoviruses representing multiple SARS-CoV-2 Omicron subvariants including BA.2, BA.4/5, BF.7, BQ.1 and XBB. As a booster vaccine for inactivated SARS-CoV-2 virus preimmunization in C57BL/6 mice, pAD1016 broadened the serum Ab neutralization spectrum to cover the Omicron BA.4/5, BF7 and BQ.1 subvariants. These data highlight the potential benefit of pAD1016 in eliciting neutralizing Abs against broad spectrum Omicron subvariants in individuals previously vaccinated with inactivated prototype SARS-CoV-2 virus and suggests that pAD1016 is worthy further translational study as a COVID-19 vaccine candidate.

immunology↗

bioRxiv2023

Biallelic Variants in MAD2L1BP (p31comet) Cause Female Infertility Characterized by Oocyte Maturation Arrest

Human oocyte maturation arrest represents one of the severe conditions for female patients with primary infertility. However, the genetic factors underlying this human disease remain largely unknown. The spindle assembly checkpoint (SAC) is an intricate surveillance mechanism that ensures accurate segregation of chromosomes throughout cell cycles. Once the kinetochores of chromosomes are correctly attached to bipolar spindles and the SAC is satisfied, the MAD2L1BP, best known as p31comet, binds MAD2 and recruits the AAA+-ATPase TRIP13 to disassemble the mitotic checkpoint complex (MCC), leading to the cell cycle progression. In this study, by whole-exome sequencing (WES), we identified homozygous and compound heterozygous MAD2L1BP variants in three families with female patients diagnosed with primary infertility owing to oocyte metaphase I (MI) arrest. Functional studies revealed that the protein variants resulting from the C-terminal truncation of MAD2L1BP lost their binding ability to MAD2. cRNA microinjection of full-length or truncated MAD2L1BP uncovered their discordant roles in driving the extrusion of polar body 1 (PB1) in mouse oocytes. Furthermore, the patients oocytes carrying the mutated MAD2L1BP variants resumed polar body extrusion (PBE) when rescued by microinjection of full-length MAD2L1BP cRNAs. Together, our studies identified and characterized novel biallelic variants in MAD2L1BP responsible for human oocyte maturation arrest at MI, and thus prompted new therapeutic avenues for curing female primary infertility.

developmental biology↗

bioRxiv2023

The junctional mechanosensor AmotL2 regulates YAP promotor accessibility

Endothelial cells (ECs) are constantly exposed to mechanical forces in the form of fluid shear stress, extracellular stiffness, and cyclic strain. How these forces are sensed by ECs remains an understudied aspect in the homeostatic regulation of the circulatory system. Angiomotin-like 2 (AmotL2) is localised to EC junctions and is required for alignment and actin reorganisation under conditions of high shear stress. Here we show that AmotL2 crucially regulates transcription and promotor activity of the YAP gene. Functionally, density-dependent proliferation of ECs in vitro and proliferation of a subpopulation of ECs within the inner aortic arch, were both reliant on AmotL2 and Yap/Taz endothelial expression in vivo. Mechanistically, depletion of AmotL2 led to altered nuclear morphology, chromatin accessibility and suppression of YAP-promotor activity through increased H3K27me3 mediated by the polycromb repressive complex component EZH2. Our data describe a previously unknown role for junctional mechanotransduction in shaping the epigenetic landscape and transcriptional regulation of YAP in vascular homeostasis.

cell biology↗

bioRxiv2022

Effect of Ascosphaera apis infestation on the activities of four antioxidant enzymes in Asian honey bee larval guts

Ascosphaera apis exclusively infects bee larvae and causes chalkbrood, a lethal fungal disease that results in the sharp reduction in adult bees and colony productivity. However, little is known about the effect of A. apis infestation on the activities of antioxidant enzymes in bee larvae. Here, A. apis spores were purified and used to inoculate Asian honey bee (Apis cerana) larvae, followed by detection of the host survival rate and evaluation of the activities of four major antioxidant enzymes. At 6 days post inoculation (dpi) with A. apis spores, white mycelia penetrated the posterior end of the larva, extended to the anterior end, and eventually covered the entire larval body surface, presenting an obvious symptom of chalkbrood disease similar to that occurs in Apis mellifera larvae. Additionally, PCR identification showed that the expected fragment was amplified from the A. apis-inoculated larval guts and the A. apis spores, verifying the A. apis infection of A. cerana larvae. The survival rate of larvae inoculated with A. apis was high at 1-2 dpi, sharply decreased to 4.16% at 4 dpi, and reached 0% at 5 dpi; whereas that of un-inoculated larvae was always high at 1~8 dpi, with an average survival rate of 95.37%, indicating the negative impact of A. apis infection on larval survival. Furthermore, in comparison with those in the corresponding un-inoculated groups, the superoxide dismutase (SOD) and catalase (CAT) activities in the 4-day-old larval gut in the A. apis-inoculated groups were reduced (p > 0.05), while those in the 5- and 6-day-old larval guts were significantly decreased (p < 0.05); the glutathione S-transferase (GST) activity in the 4- and 5-day-old larval guts was significantly increased (p < 0.05), while that in the 6-day-old larval gut was reduced (p > 0.05); the polyphenol oxidase (PPO) activity in 4-day-old larval gut was increased (p > 0.05) and that in the 5-day-old larval gut was significantly increased (p < 0.05), whereas that in the 6-day-old larval gut was significantly reduced (p < 0.01). These results together suggested that the activities of SOD and CAT in the larval guts were suppressed during the process of A. apis infestation, while the GST activity was induced to activation, and the PPO activity was first enhanced and then inhibited. Our findings not only unravel the response of A. cerana larvae to A. apis infestation from a biochemical perspective, but also offer a valuable insight into the interaction between Asian honey bee larvae and A. apis.

molecular biology↗

bioRxiv2022

Quantifying constraint in human mitochondrial DNA

Mitochondrial DNA (mtDNA) has an important, yet often overlooked, role in health and disease. Constraint models quantify the removal of deleterious variation from the population by selection, representing a powerful tool for identifying genetic variation underlying human phenotypes1-4. However, a constraint model for the mtDNA has not been developed, due to its unique features. Here we describe the development of a mitochondrial constraint model and its application to the Genome Aggregation Database (gnomAD), a large-scale population dataset reporting mtDNA variation across 56,434 humans5. Our results demonstrate strong depletion of expected variation, suggesting most deleterious mtDNA variants remain undiscovered. To aid their identification, we compute constraint metrics for every mitochondrial protein, tRNA, and rRNA gene, revealing a spectrum of intolerance to variation. We characterize the most constrained regions within genes via regional constraint, and positions across the entire mtDNA via local constraint, showing their enrichment in pathogenic variation and functionally critical sites, including topological clustering in 3D protein and RNA structures. Notably, we identify constraint at often overlooked sites, such as rRNAs and non-coding regions. Lastly, we demonstrate how these metrics can improve the discovery of mtDNA variation underlying rare and common human phenotypes.

genetics↗

bioRxiv2022

Cell-type-specific co-expression inference from single cell RNA-sequencing data

The inference of gene co-expressions from microarray and RNA-sequencing data has led to rich insights on biological processes and disease mechanisms. However, the bulk samples analyzed in most studies are a mixture of different cell types. As a result, the inferred co-expressions are confounded by varying cell type compositions across samples and only offer an aggregated view of gene regulations that may be distinct across different cell types. The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. However, the high sequencing depth variations and measurement errors in scRNA-seq data present significant challenges in inferring cell-type-specific gene co-expressions, and these issues have not been adequately addressed in the existing methods. We propose a statistical approach, CS-CORE, for estimating and testing cell-type-specific co-expressions, built on a general expression-measurement model that explicitly accounts for sequencing depth variations and measurement errors in the observed single cell data. Systematic evaluations show that most existing methods suffer from inflated false positives and biased co-expression estimates and clustering analysis, whereas CS-CORE has appropriate false positive control, unbiased co-expression estimates, good statistical power and satisfactory performance in downstream co-expression analysis. When applied to analyze scRNA-seq data from postmortem brain samples from Alzheimers disease patients and controls and blood samples from COVID-19 patients and controls, CS-CORE identified cell-type-specific co-expressions and differential co-expressions that were more reproducible and/or more enriched for relevant biological pathways than those inferred from other methods.

bioinformatics↗

bioRxiv2022

Experimental study of modified human tendon stem cells to promote graft ligamentation and tendon-bone healing after anterior cruciate ligament reconstruction

Restoring the normal structure and function of injured tendons is one of the biggest challenges faced by the Department of Orthopedics and Sports Medicine. Tendon-derived stem cells (TDSCs), a new type of pluripotent stem cells with multidirectional differentiation potential, are expected to be promising cell seeds for the treatment of tendon injury and tendon-bone healing in the future. In this study, tendon stem cells were successfully isolated from human tissues, which were positive for markers CD44, CD90, and CD105, and exhibited clonality and multilineage differentiation ability. Analysis of single-cell sequencing results and mass spectrometry identification results showed that there were differences in protein expression during CTGF-induced TDSC tendon differentiation. Reverse Co-IP, qPCR, WB, and immunofluorescence detection all confirmed that CTGF directly interacts with KIT, thereby mediating the transcription factor HES1 to regulate the Wnt/{beta}-catenin signaling pathway (GSK3{beta}, {beta}-catenin, TCF4). ChIP-qPCR and dual-luciferase reporter gene assays indicated that HES1 regulates stem cell differentiation by directly regulating the expression of GSK3{beta} in the Wnt/{beta}-catenin pathway. Rats were treated with TDSCs overexpressing the KIT gene after repair surgery. This method had a more ideal recovery effect than other methods through animal behavioral scores, mechanical properties testing, and HE staining tissue observation. This study found that the use of modified human tendon stem cells (hTDSC) could promote graft ligamentization and tendon-bone healing after ACL reconstruction, which could provide an effective way for faster and better recovery from tendon injury.

cell biology↗

bioRxiv2022

Fast and accurate protein function prediction from sequence through pretrained language model and homology-based label diffusion

Protein function prediction is an essential task in bioinformatics which benefits disease mechanism elucidation and drug target discovery. Due to the explosive growth of proteins in sequence databases and the diversity of their functions, it remains challenging to fast and accurately predict protein functions from sequences alone. Although many methods have integrated protein structures, biological networks or literature information to improve performance, these extra features are often unavailable for most proteins. Here, we propose SPROF-GO, a Sequence-based alignment-free PROtein Function predictor which leverages a pretrained language model to efficiently extract informative sequence embeddings and employs self-attention pooling to focus on important residues. The prediction is further advanced by exploiting the homology information and accounting for the overlapping communities of proteins with related functions through the label diffusion algorithm. SPROF-GO was shown to surpass state-of-the-art sequence-based and even network-based approaches by more than 14.5%, 27.3% and 10.1% in AUPR on the three sub-ontology test sets, respectively. Our method was also demonstrated to generalize well on non-homologous proteins and unseen species. Finally, visualization based on the attention mechanism indicated that SPROF-GO is able to capture sequence domains useful for function prediction. Key pointsO_LISPROF-GO is a sequence-based protein function predictor which leverages a pretrained language model to efficiently extract informative sequence embeddings, thus bypassing expensive database searches. C_LIO_LISPROF-GO employs self-attention pooling to capture sequence domains useful for function prediction and provide interpretability. C_LIO_LISPROF-GO applies hierarchical learning strategy to produce consistent predictions and label diffusion to exploit the homology information. C_LIO_LISPROF-GO is accurate and robust, with better performance than state-of-the-art sequence-based and even network-based approaches, and great generalization ability on non-homologous proteins and unseen species C_LI

bioinformatics↗

bioRxiv2022

GEMC1 and MCIDAS interactions with SWI/SNF complexes regulate the multiciliated cell-specific transcriptional program

Multiciliated cells (MCCs) project dozens to hundreds of motile cilia from their apical surface to promote the movement of fluids or gametes in the mammalian brain, airway or reproductive organs. Differentiation of MCCs requires the sequential action of the Geminin family transcriptional activators, GEMC1 and MCIDAS, that both interact with E2F4/5-DP1. How these factors activate transcription and the extent to which they play redundant functions remains poorly understood. Here, we demonstrate that the transcriptional targets and proximal proteomes of GEMC1 and MCIDAS are highly similar. However, we identified distinct interactions with SWI/SNF subcomplexes; GEMC1 interacts primarily with the ARID1A containing BAF complex while MCIDAS interacts primarily with BRD9 containing ncBAF complexes. Treatment with a BRD9 inhibitor impaired MCIDAS-mediated activation of several target genes and compromised the MCC differentiation program in multiple cell based models. Our data suggest that the differential engagement of distinct SWI/SNF subcomplexes by GEMC1 and MCIDAS is required for MCC-specific transcriptional regulation and mediated by their distinct C-terminal domains.

cell biology↗

bioRxiv2022

An HBV mRNA vaccine with favorable virological suppression and superior immunity

BRIEF ABSTRACTHere we report on the development and comprehensive evaluations of an mRNA vaccine for chronic hepatitis B (CHB) treatment. In two different HBV carrier mouse models generated by viral vector-mediated HBV transfection (pAAV-HBV1.2 and rAAV8-HBV1.3), this vaccine demonstrates sufficient and persistent virological suppression, and robust immunogenicity in terms of induction of strong innate immune activation, high-level virus-specific antibodies, memory B cells and T cells. mRNA platform therefore holds prospects for therapeutic vaccine development to combat CHB.

immunology↗

bioRxiv2022

Initiation of fibronectin fibrillogenesis is an enzyme-dependent process

Fibronectin fibrillogenesis and mechanosensing both depend on integrin-mediated force transmission to the extracellular-matrix. However, force transmission is in itself dependent on fibrillogenesis, and fibronectin fibrils are found in soft embryos where high forces cannot be applied, suggesting that force cannot be the sole initiator of fibrillogenesis. Here we identify a nucleation step prior to force transmission, driven by fibronectin oxidation mediated by lysyl-oxidase enzyme family members. This oxidation induces fibronectin clustering that promotes early adhesion, alters cellular response to soft matrices, and enhances force transmission to the matrix. In contrast, absence of fibronectin oxidation abrogates fibrillogenesis, perturbs cell-matrix adhesion, and compromises mechanosensation. Moreover, fibronectin oxidation promotes cancer cells colony formation in soft agar as well as collective and single-cell migration. These results reveal a force-independent enzyme-dependent mechanism that initiates fibronectin fibrillogenesis, establishing a critical step in cell adhesion and mechanosensing.

cell biology↗