Biology subjects

Naba, A.

Publications and source records attributed to Naba, A..

16 recordsLinked to original sources

bioRxiv2026

MatriSpace: Identification and visualization of spatially resolved ECM gene expression patterns in health and disease

The extracellular matrix (ECM) is a highly dynamic network of proteins forming the structural organizer of all tissues. Different cell populations contribute to the assembly of the 150+ proteins of a functional ECM. In addition, different ECM subtypes, supporting distinct cellular functions, are found in every organ. Spatial transcriptomics (ST) provides a unique, yet untapped, opportunity to identify which cell populations contribute to ECM production with spatial context. Applied to healthy and diseased samples, this method can identify ECM changes that could be exploited for therapeutic purposes. Here, we introduce MatriSpace, a computational framework to mine ST datasets with a focus on ECM genes. MatriSpace offers two operating modes: researchers can either upload their own ST datasets or explore a large collection of public datasets. Upon analysis, MatriSpace returns spatially resolved maps of matrisome gene expression in relation to cell populations, at multiple levels: from single-gene analysis to tissue niches and functional ECM units. MatriSpace is available as an R package and an online Shiny App (https://matrinet.shinyapps.io/matrispace), making it accessible to all users regardless of their level of expertise. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/720198v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@3f8e28org.highwire.dtl.DTLVardef@8e20beorg.highwire.dtl.DTLVardef@107be22org.highwire.dtl.DTLVardef@153b911_HPS_FORMAT_FIGEXP M_FIG C_FIG KEY POINTSO_LIMatriSpace is a computational framework to interrogate ECM gene expression in spatial transcriptomic datasets. C_LIO_LIResearchers can upload their own spatial transcriptomic datasets for processing by MatriSpace. C_LIO_LIResearchers can interrogate a vast collection of public datasets of healthy and diseased tissues through MatriSpace. C_LIO_LIMatriSpace can identify, quantify, and interpret spatial expression patterns of matrisome genes, gene sets, and niches. C_LIO_LIMatriSpace can uncover regional coordinations of matrisome components and their relationships with non-matrisome genes, such as matrisome receptors. C_LI

systems biology↗

bioRxiv2026

SNED1 fibrillar assembly in the extracellular matrix requires fibronectin and collagen I

The extracellular matrix (ECM) is a meshwork of proteins that orchestrates a broad range of cellular phenotypes, including proliferation, adhesion, migration, and differentiation. SNED1 is a newly characterized ECM glycoprotein that promotes cell adhesion and is essential for embryonic development. Its upregulation is also associated with breast cancer metastasis and poor prognosis for breast cancer patients. We recently showed that SNED1 assembles into fibrillar structures, but the mechanisms guiding its incorporation into the ECM scaffold remain unknown. Combining biochemical assays and confocal immunofluorescence imaging, we found that SNED1 assembly in the ECM occurs early in the process of ECM building and is concomitant and overlaps with the deposition of fibronectin and collagen I, two major ECM proteins. By knocking down fibronectin or destabilizing collagen I fibers, we further demonstrate that SNED1 requires the presence of these proteins for its assembly. Last, using biolayer interferometry, we identify collagen I as the first direct binding partner of SNED1. Altogether, our results lay the foundation for future studies aimed at determining the mechanisms by which SNED1 fibers contribute to SNED1 pathophysiological functions. SUMMARY STATEMENTThe novel protein SNED1 requires the presence of fibronectin and collagen I to assemble into fibrillar structures in the extracellular matrix scaffold.

cell biology↗

bioRxiv2026

SNED1 modulates ECM architecture and cell proliferation via LDV-binding integrins

The extracellular matrix (ECM) is a complex scaffold of proteins that supports multicellular structures. Interactions between cells and the ECM via receptors, like integrins, govern cellular phenotypes (e.g., proliferation, adhesion), but also contribute to ECM assembly. Understanding how ECM-receptor interactions regulate matrix assembly is critical to uncover how alterations of the ECM cause or accompany congenital diseases, cancer, or fibrosis. SNED1 is a novel ECM protein with roles in development and metastasis. However, the mechanisms governing its assembly and signaling functions remain largely unknown. SNED1 contains two integrin-binding motifs, RGD and LDV, and we recently showed that its interaction with RGD-integrins mediates cell adhesion. Here, we investigated the role of SNED1/integrin interactions in SNED1 ECM assembly. While SNED1/integrin interactions were not necessary for its initial incorporation in the ECM, interaction with LDV-, but not RGD-, integrins, was required for ECM build-up and the patterning of SNED1 and the fibrillar proteins fibronectin and collagen I. Moreover, SNED1/LDV-integrin interaction promoted ECM alignment, cell alignment, and cell proliferation, processes essential to SNED1-driven neural crest cell migration during craniofacial development and breast cancer invasion. SUMMARY STATEMENTInteraction of SNED1 with LDV-binding integrins, but not RGD-binding integrins, mediates ECM remodeling and controls cytoskeletal rearrangement and cell proliferation.

cell biology↗

bioRxiv2025

In-depth proteomic profiling of the extracellular matrix of pancreatic ductal adenocarcinomas identifies signatures correlating with lymphocyte infiltration

The extracellular matrix (ECM) is a complex assembly of proteins surrounding cells. It is a critical component of the tumor microenvironment that plays an active role in tumor progression and modulation of tumor response to treatment. Pancreatic ductal adenocarcinoma (PDAC) is a cancer type characterized by one of the worst prognoses, as it is often diagnosed at an advanced stage. It is also characterized by a very dense ECM, which hinders efficient drug delivery. In addition, PDACs are considered "cold" tumors as they fail to elicit a strong immune response, challenging the use of immunotherapy for PDAC cancer patients. Yet, the interplay between the ECM and immune cells within the PDAC tumor microenvironment remains poorly understood. Here, we employed ECM-focused proteomics to profile the ECM compositions of PDAC mouse models characterized by different levels of CD8+ T-cell infiltration. We found that CD8lo, or "cold" tumors, and CD8hi, or "hot" tumors, exhibited different ECM compositions. Interrogation of publicly available single-cell RNA-sequencing datasets of human PDACs further revealed that the ECM proteins distinguishing hot and cold PDACs are secreted by multiple stromal cell populations, including cancer-associated fibroblasts, stellate cells, and macrophages. Last, we found that the expression of a subset of the genes encoding ECM proteins characteristic of the CD8lo phenotype correlated with CD8+ T-cell infiltration in human PDAC samples and patient survival. This study paves the way for the development of ECM-modulating interventions to enhance immune cell infiltration and responsiveness to immunotherapy. SignificanceWe report the identification of ECM protein signatures correlating with the level of CD8+ lymphocyte infiltration in murine models of pancreatic ductal adenocarcinomas and human samples. This work paves the way for the development of ECM-modulating therapeutic strategies to enhance lymphocyte infiltration and, hence, the efficacy of immunotherapies.

cancer biology↗

bioRxiv2025

Comparative proteomic analysis of the ECM composition of the human omentum and mesentery, the main sites of ovarian cancer metastasis

Due to its limited symptoms, high-grade serous ovarian cancer (HGSOC) has frequently metastasized extensively throughout the peritoneal cavity prior to its diagnosis, resulting in an overall five-year survival rate of less than 50%. The greater omentum and the small bowel mesentery are two of the most common metastatic sites in advanced HGSOC. However, the mechanisms underlying HGSOC metastatic tropism remain unknown. The extracellular matrix is a complex and dynamic meshwork of proteins that provides biochemical and mechanical signals to surrounding cells and has been shown to drive the dissemination of several cancer types to preferential distant sites. Here, using histological assessment and proteomics, we examined the composition of the extracellular matrix of paired omentum and mesentery samples from disease-free adult females. We found that the fibrillar collagen content of the mesothelial layer of the omentum was significantly higher than that of the mesentery. Using ECM-focused proteomics, we further defined the ECM composition - or matrisome - of these two tissues. We found that over 90% of the proteins detected were shared between the omentum and mesentery. Our analysis also revealed small subsets of tissue-specific ECM proteins. Future work will aim to test the possible functional contributions of these ECM proteins to HGSOC metastatic tropism. To facilitate the reuse of our dataset, we have deposited the raw mass spectrometry data and accompanying metadata files to the ProteomeXchange Consortium with the dataset identifier PXD061586.

cancer biology↗

bioRxiv2025

Fibronectin Composition and Transglutaminase 2 Cross-linking Cooperatively Regulate Ovarian Cancer Cell Adhesion in ECM-Mimetic Constructs

The extracellular matrix (ECM) plays a crucial role in tumor progression. Here, we analyzed collagen I and cellular fibronectin (cFN) in normal omentum and metastatic omentum from high-grade serous ovarian cancer (HGSOC). The levels of both proteins were significantly elevated and collagen I fibers were significantly thicker in HGSOC metastases. Moreover, the ECM cross-linking enzyme transglutaminase 2 (TG2) was increased in omental metastases, where it is enzymatically active in the extracellular environment. This information was used to develop ECM constructs recapitulating these key changes, alone and in combination, to investigate their impact on HGSOC cell adhesion. To our knowledge, this is the first report using TG2 as a cross-linking agent to generate constructs from multiple ECM components. Low levels of HGSOC cell adhesion were observed on colIagen-only (coll) gels, while inclusion of cFN or plasma fibronection (pFN) increased cell adhesion. TG2-mediated cross-linking of colI/cFN hydrogels promoted HGSOC cell adhesion, while cross-linking of coll/pFN had no effect. Cell adhesion was dependent on ligand identity and fiber diameter. When fiber thickness was held constant, the inclusion of cFN led to greater HGSOC cell adhesion relative to pFN or coll, due to interactions of {beta}1 integrins with the EDA and RGD domains of cFN. Meanwhile, when gel composition was held constant, HGSOC cell adhesion increased as fiber thickness was increased through modifications to gelation temperature. Combined, our results demonstrate how ECM changes associated with omental metastasis can support tumor progression and provide insights into methods to tailor biomaterials to support cell adhesion.

bioengineering↗

bioRxiv2025

Time-lapse tryptic digestion: a proteomic approach to improve sequence coverage of extracellular matrix proteins

The extracellular matrix (ECM) is a complex and dynamic meshwork of proteins providing structural support to cells. It also provides biochemical signals governing cellular processes, including proliferation, adhesion, and migration. Alterations of ECM structure and/or composition have been linked to many pathological processes, including cancer and fibrosis. Over the past decade, mass-spectrometry-based proteomics has become the state-of-the-art method to profile the protein composition of ECMs. However, existing methods do not fully capture the broad dynamic range of protein abundances in the ECM. They also do not permit to achieve the high coverage needed to gain finer biochemical on ECM proteoforms (e.g., isoforms, post-translational modifications) and topographical information critical to better understand ECM protein functions. Here, we present the development of a time-lapsed proteomic pipeline using limited tryptic proteolysis and sequential release of peptides over time. This experimental pipeline was combined with data-independent acquisition mass spectrometry and the assembly of a custom matrisome spectral library to enhance peptide-to-spectrum matching. This pipeline shows superior protein identification, peptide-to-spectrum matching, and significantly increased sequence coverage against standard ECM proteomic pipelines. Exploiting the spatio-temporal resolution of this method, we further demonstrate how time-resolved 3-dimensional peptide mapping can identify protein regions differentially susceptible to trypsin, which may aid in identifying protein-protein interaction sites.

biochemistry↗

bioRxiv2024

MatriCom: a scRNA-Seq data mining tool to infer ECM-ECM and cell-ECM communication systems

The ECM is a complex and dynamic meshwork of proteins that forms the framework of all multicellular organisms. Protein interactions within the ECM are critical to building and remodeling the ECM meshwork, while interactions between ECM proteins and cell surface receptors are essential for the initiation of signal transduction and the orchestration of cellular behaviors. Here, we report the development of MatriCom, a web application (https://matrinet.shinyapps.io/matricom) and a companion R package (https://github.com/Izzilab/MatriCom), devised to mine scRNA-Seq datasets and infer communications between ECM components and between different cell populations and the ECM. To impute interactions from expression data, MatriCom relies on a unique database, MatriComDB, that includes over 25,000 curated interactions involving matrisome components, with data on 80% of the [~]1,000 genes that compose the mammalian matrisome. MatriCom offers the option to query open-access datasets sourced from large sequencing efforts (Tabula Sapiens, The Human Protein Atlas, HuBMAP) or to process user-generated datasets. MatriCom is also tailored to account for the specific rules governing ECM protein interactions and offers options to customize the output through stringency filters. We illustrate the usability of MatriCom with the example of the human kidney matrisome communication network. Last, we demonstrate how the integration of 46 scRNA-Seq datasets led to the identification of both ubiquitous and tissue-specific ECM communication patterns. We envision that MatriCom will become a powerful resource to elucidate the roles of different cell populations in ECM-ECM and cell-ECM interactions and their dysregulations in the context of diseases such as cancer or fibrosis. ONE SENTENCE SUMMARYMatriCom is a web application devised to mine scRNA sequencing datasets to infer ECM-ECM and cell-ECM communication systems in the context of the diverse cell populations that constitute any tissue or organ.

systems biology↗

bioRxiv2024

The novel ECM protein SNED1 mediates cell adhesion via α5β1 integrin

The extracellular matrix (ECM) is a complex meshwork comprising over 100 proteins. It serves as an adhesive substrate for cells and, hence, plays critical roles in health and disease. We have recently identified a novel ECM protein, SNED1, and have found that it is required for neural crest cell migration and craniofacial morphogenesis during development and in breast cancer, where it is necessary for the metastatic dissemination of tumor cells. Interestingly, both processes involve the dynamic remodeling of cell-ECM adhesions via cell surface receptors. Sequence analysis revealed that SNED1 contains two amino acid motifs, RGD and LDV, known to bind integrins, the largest class of ECM receptors. We thus sought to investigate the role of SNED1 in cell adhesion. Here, we report that SNED1 mediates breast cancer and neural crest cell adhesion via its RGD motif. We further demonstrate that cell adhesion to SNED1 is mediated by the RGD integrins 5{beta}1 and v{beta}3. These findings are a first step toward identifying the signaling pathways activated downstream of the SNED1-integrin interactions guiding craniofacial morphogenesis and breast cancer metastasis. SUMMARY STATEMENTWe report that the novel extracellular matrix protein SNED1 promotes the adhesion of breast cancer cells and neural crest cells via interaction with 5{beta}1 and v{beta}3 integrins, the first SNED1 receptors identified to date.

cell biology↗

bioRxiv2023

Matrisome AnalyzeR: A suite of tools to annotate and quantify ECM molecules in big datasets across organisms

The extracellular matrix (ECM) is a complex meshwork of proteins that forms the scaffold of all tissues in multicellular organisms. It plays critical roles in all aspects of life: from orchestrating cell migration during development, to supporting tissue repair. It also plays critical roles in the etiology or progression of diseases. To study this compartment, we defined the compendium of all genes encoding ECM and ECM-associated proteins for multiple organisms. We termed this compendium the "matrisome" and further classified matrisome components into different structural or functional categories. This nomenclature is now largely adopted by the research community to annotate -omics datasets and has contributed to advance both fundamental and translational ECM research. Here, we report the development of Matrisome AnalyzeR, a suite of tools including a web-based application (https://sites.google.com/uic.edu/matrisome/tools/matrisome-analyzer) and an R package (https://github.com/Matrisome/MatrisomeAnalyzeR). The web application can be used by anyone interested in annotating, classifying, and tabulating matrisome molecules in large datasets without requiring programming knowledge. The companion R package is available to more experienced users, interested in processing larger datasets or in additional data visualization options. SUMMARY STATEMENTMatrisome AnalyzeR is a suite of tools, including a web-based app and an R package, designed to facilitate the annotation and quantification of extracellular matrix components in big datasets.

bioinformatics↗

bioRxiv2022

Time-lapsed proteomics reveals a role for the novel protein, SNED1, in modulating ECM composition and protein folding

The extracellular matrix (ECM) is a complex and dynamic meshwork of proteins providing structural support to cells. It also provides biochemical signals governing cellular processes including proliferation and migration. Alterations of ECM structure and/or composition has been shown to lead to, or accompany, many pathological processes including cancer and fibrosis. To understand how the ECM contributes to diseases, we first need to obtain a comprehensive characterization of the ECM of tissues and of its changes during disease progression. Over the past decade, mass-spectrometry-based proteomics has become the state-of-the-art method to profile the protein composition of ECMs. However, existing methods do not fully capture the broad dynamic range of protein abundance in the ECM, nor do they permit to achieve the high coverage needed to gain finer biochemical information, including the presence of isoforms or post-translational modifications. In addition, broadly adopted proteomic methods relying on extended trypsin digestion do not provide structural information on ECM proteins, yet, gaining insights into ECM protein structure is critical to better understanding protein functions. Here, we present the optimization of a time-lapsed proteomic method using limited proteolysis of partially denatured samples and the sequential release of peptides to achieve superior sequence coverage as compared to standard ECM proteomic workflow. Exploiting the spatio-temporal resolution of this method, we further demonstrate how 3-dimensional time-lapsed peptide mapping can identify protein regions differentially susceptible to trypsin and can thus identify sites of post-translational modifications, including protein-protein interactions. We further illustrate how this approach can be leveraged to gain insight on the role of the novel ECM protein SNED1 in ECM homeostasis. We found that the expression of SNED1 by mouse embryonic fibroblasts results in the alteration of overall ECM composition and the sequence coverage of certain ECM proteins, raising the possibility that SNED1 could modify accessibility to trypsin by engaging in protein-protein interactions.

cell biology↗

bioRxiv2021

Multi-modal profiling of the extracellular matrix of human fallopian tubes and serous tubal Intraepithelial carcinomas

Recent evidence supports the fimbriae of the fallopian tube as a potential origin site for high-grade serous ovarian cancer (HGSOC). The progression of many solid tumors is accompanied by changes in the microenvironment, including alterations of the extracellular matrix (ECM). The ECM of fallopian tube and HGSOC has not been well characterized. Therefore, we sought to determine the ECM composition of the benign fallopian tube and how it changes with the onset of serous intraepithelial carcinomas (STICs), precursor of HGSOC. The ECM composition of benign human fallopian tube was first defined from a meta-analysis of published proteomic datasets and identified 190 ECM proteins. We then conducted de novo proteomics using ECM enrichment and identified 88 proteins, 7 of which were not identified in prior studies. We further investigated the levels and localization of seven of these ECM proteins (type I, III, and IV collagens, fibronectin, laminin, versican, perlecan) and hyaluronic acid using multi-spectral immunohistochemical staining of fimbriae from patients with benign conditions or STICs. Quantification revealed an increase in stromal fibronectin and a decrease in epithelial versican in STICs. Our results provide an in-depth picture of the ECM in the benign fallopian tube and identified ECM changes that accompany STIC formation.

cancer biology↗

bioRxiv2020

Computational and experimental characterization of the novel ECM glycoprotein SNED1 and prediction of its interactome

The extracellular matrix (ECM) protein SNED1 has been shown to promote breast cancer metastasis and control neural crest cell-specific craniofacial development, but the cellular and molecular mechanisms by which it does so remain unknown. ECM proteins exert their functions by binding to cell surface receptors, sequestering growth factors, and interacting with other ECM proteins, actions that can be predicted using knowledge of proteins sequence, structure and post-translational modifications. Here, we combined in-silico and in-vitro approaches to characterize the physico-chemical properties of SNED1 and infer its putative functions. To do so, we established a mammalian cell system to produce and purify SNED1 and its N-terminal fragment, which contains a NIDO domain. We have determined experimentally SNED1s potential to be glycosylated, phosphorylated, and incorporated into insoluble ECM produced by cells. In addition, we used biophysical and computational methods to determine the secondary and tertiary structures of SNED1 and its N-terminal fragment. The tentative ab-initio model we built of SNED1 suggests that it is an elongated protein presumably able to bind multiple partners. Using computational predictions, we identified 114 proteins as putative SNED1 interactors. Pathway analysis of the newly-predicted SNED1 interactome further revealed that binding partners of SNED1 contribute to signaling through cell surface receptors, such as integrins, and participate in the regulation of ECM organization and developmental processes. Altogether, we provide a wealth of information on an understudied yet important ECM protein with the potential to decipher its functions in physiology and diseases.

biochemistry↗

bioRxiv2020

Proteomic Profiling of the Human Dentin Identifies Age-Related Differences in the Composition and Solubility of the Matrisome

ObjectiveDevise a pipeline to investigate the protein composition of the human root dentin extracellular matrix (ECM) from single individuals of different age cohorts. DesignIndividual cervical root dentin of sound human molars from two age brackets, young (18-25 years old; n=3) and old (75-85 years old; n=3), were cut and pulverized. Protein extraction and fractionation were completed by sequential demineralization with EDTA buffer, chaotropic extraction with guanidine hydrochloride, and urea. The resulting protein extracts of differential solubility were digested into peptides and peptides were analyzed by mass spectrometry. Data generated for this study are available via ProteomeXchange, identifier PXD018320. ResultsWe found that protein extracts of different solubilities present distinct biochemical compositions. We further define the matrisome of young (48 proteins) and old (50 proteins) human root dentin and report the identification of compositional and structural differences in ECM proteins from young and old teeth. ConclusionOur study provides a rigorous pipeline, from sample preparation to data analysis, to investigate the ECM composition - or matrisome - of the dentin. This pipeline has the potential to lead to the discovery of biomarkers of tooth aging and health.

physiology↗

bioRxiv2019

In-silico definition of the Drosophila melanogaster matrisome

The extracellular matrix (ECM) is an assembly of hundreds of proteins that structurally supports the cells it surrounds and biochemically regulates their functions. Drosophila has emerged as a powerful model organism to study fundamental mechanisms underlying ECM protein secretion, ECM assembly, and ECM roles in pathophysiological processes. However, as of today, we do not possess a well-defined list of the components forming the ECM of this organism. We previously reported the development of computational pipelines to define the matrisome - the ensemble of genes encoding ECM and ECM-associated proteins - of humans, mice, zebrafish and C. elegans. Using a similar approach, we report here that the Drosophila matrisome is composed of 641 genes. We further classify these genes into different structural and functional categories, including an expanded way to classify genes encoding proteins forming apical ECMs. We illustrate how having a comprehensive list of Drosophila matrisome proteins can be used to annotate large proteomic datasets and identify unsuspected roles for the ECM in pathophysiological processes. Last, to aid the dissemination and usage of the proposed definition and categorization of the Drosophila matrisome by the scientific community, our list has been made available through three public portals: The Matrisome Project, FlyBase, and GLAD.

cell biology↗

bioRxiv2018

Knockout of the gene encoding the extracellular matrix protein Sned1 results in craniofacial malformations and early neonatal lethality.

BackgroundThe extracellular matrix (ECM) is a fundamental component of multicellular organisms that orchestrates developmental processes and controls cell and tissue organization. We previously identified the novel ECM protein SNED1 as a promoter of breast cancer metastasis and showed that its level of expression negatively correlated with survival of breast cancer patients. Here we sought to identify the roles of SNED1 during murine development and in physiology. ResultsWe generated two novel Sned1 knockout mouse strains and showed that Sned1 is essential since homozygous ablation of the gene led to ~67% early neonatal lethality. Phenotypic analysis of the surviving knockout mice obtained revealed a role for SNED1 in the development of craniofacial and skeletal structures since Sned1 knockout resulted in growth defects, nasal cavity occlusion, and craniofacial malformations. Sned1 is widely expressed in embryos, notably in neural-crest derivatives. We further show here that mice with a neural-crest-cell-specific deletion of Sned1 survive, but display facial anomalies partly phenocopying the global knockout mice. ConclusionsOur results demonstrate requisite roles for SNED1 during development and neonatal survival. Importantly, the deletion of 2q37.3 in humans, a region that includes the SNED1 locus, has been associated with facial dysmorphism and short stature.

developmental biology↗