Cryo-EM reveals the molecular basis oflaminin polymerization and LN-lamininopathies

Mechanisms of assembly and remodelling of the extracellular matrix

The extracellular matrix (ECM) is the complex meshwork of proteins and glycans that forms the scaffold that surrounds and supports cells. It exerts key roles in all aspects of metazoan physiology, from conferring physical and mechanical properties on tissues and organs to modulating cellular processes such as proliferation, differentiation and migration. Understanding the mechanisms that orchestrate the assembly of the ECM scaffold is thus crucial to understand ECM functions in health and disease. This Review discusses novel insights into the compositional diversity of matrisome components and the mechanisms that lead to tissue-specific assemblies and architectures tailored to support specific functions. The Review then highlights recently discovered mechanisms, including post-translational modifications and metabolic pathways such as amino acid availability and the circadian clock, that modulate ECM secretion, assembly and remodelling in homeostasis and human diseases. Last, the Review explores the potential of 'matritherapies', that is, strategies to normalize ECM composition and architecture to achieve a therapeutic benefit.

Biomechanical properties of laminins and their impact on cancer progression

Laminins (LMs) constitute a family of heterotrimeric glycoproteins essential for the formation of basement membranes (BM). They act as molecular bridges between cells and the extracellular matrix (ECM), thereby transmitting signals influencing cell behavior and tissue organization. In the realm of cancer pathobiology, LMs regulate key processes such as migration, differentiation, or fibrosis. This review critically examines the multifaceted impact of LMs on tumor progression, with a particular focus on the isoform-specific structure-function relationships, and how this structural diversity contributes to the biomechanical properties of BMs. LM interactions with integrin and non-integrin cell surface receptors, as well as with other ECM proteins, modify the response of cancer cells to the ECM stiffness, ultimately influencing the capacity of malignant cells to breach the BM, a limiting step in metastatic dissemination. Comprehension of the mechanisms underlying LM-driven tumor biomechanics holds potential for better understand cancer pathobiology and design new targeted therapeutic strategies.

Specific 3-O-sulfated heparan sulfate domains regulate salivary gland basement membrane metabolism and epithelial differentiation

Heparan sulfate (HS) regulation of FGFR function, which is essential for salivary gland (SG) development, is determined by the immense structural diversity of sulfated HS domains. 3-O-sulfotransferases generate highly 3-O-sulfated HS domains (3-O-HS), and Hs3st3a1 and Hs3st3b1 are enriched in myoepithelial cells (MECs) that produce basement membrane (BM) and are a growth factor signaling hub. Hs3st3a1;Hs3st3b1 double-knockout (DKO) mice generated to investigate 3-O-HS regulation of MEC function and growth factor signaling show loss of specific highly 3-O-HS and increased FGF/FGFR complex binding to HS. During development, this increases FGFR-, BM- and MEC-related gene expression, while in adult, it reduces MECs, increases BM and disrupts acinar polarity, resulting in salivary hypofunction. Defined 3-O-HS added to FGFR pulldown assays and primary organ cultures modulates FGFR signaling to regulate MEC BM synthesis, which is critical for secretory unit homeostasis and acinar function. Understanding how sulfated HS regulates development will inform the use of HS mimetics in organ regeneration.

Cryo-Electron Microscopy Studies of Biomolecular Structure and Dynamics

The technical innovation of the last decade has provided novel tools that are now transforming the field of biophysics by bringing remarkable atomic level insights into the mechanisms employed by bio-micromachines to sustain life [...].

Identifying the molecular basis of Laminin N-terminal domain Ca2+ binding using a hybrid approach

Ca2+ is a highly abundant ion involved in numerous biological processes, particularly in multicellular eukaryotic organisms where it exerts many of these functions through interactions with Ca2+ binding proteins. The laminin N-terminal (LN) domain is found in members of the laminin and netrin protein families where it plays a critical role in the function of these proteins. The LN domain of laminins and netrins is a Ca2+ binding domain and in many cases requires Ca2+ to perform its biological function. Here, we conduct a detailed examination of the molecular basis of the LN domain Ca2+ interaction combining structural, computational, bioinformatics, and biophysical techniques. By combining computational and bioinformatic techniques with x-ray crystallography we explore the molecular basis of the LN domain Ca2+ interaction and identify a conserved sequence present in Ca2+ binding LN domains. These findings enable a sequence-based prediction of LN domain Ca2+ binding ability. We use thermal shift assays and isothermal titration calorimetry to explore the biophysical properties of the LN domain Ca2+ interaction. We show that the netrin-1 LN domain exhibits a high affinity and specificity for Ca2+, which structurally stabilizes the LN domain. This study elucidates the molecular foundation of the LN domain Ca2+ binding interaction and provides a detailed functional characterization of this essential interaction, advancing our understanding of protein-Ca2+ dynamics within the context of the LN domain.

Polymerizing laminins in development, health, and disease

Polymerizing laminins are multi-domain basement membrane (BM) glycoproteins that self-assemble into cell-anchored planar lattices to establish the initial BM scaffold. Nidogens, collagen-IV and proteoglycans then bind to the scaffold at different domain loci to create a mature BM. The LN domains of adjacent laminins bind to each other to form a polymer node, while the LG domains attach to cytoskeletal-anchoring integrins and dystroglycan, as well as to sulfatides and heparan sulfates. The polymer node, the repeating unit of the polymer scaffold, is organized into a near-symmetrical triskelion. The structure, recently solved by cryo-electron microscopy in combination with AlphaFold2 modeling and biochemical studies, reveals how the LN surface residues interact with each other and how mutations cause failures of self-assembly in an emerging group of diseases, the LN-lamininopathies, that include LAMA2-related dystrophy and Pierson syndrome.

Exploring a Solvent Dependent Strategy to Control Self-Assembling Behavior and Cellular Interaction in Laminin-Mimetic Short Peptide based Supramolecular Hydrogels

Self-assembled hydrogels, fabricated through diverse non-covalent interactions, have been extensively studied in regenerative medicines. Inspired from bioactive functional motifs of ECM protein, short peptide sequences have shown remarkable abilities to replicate the intrinsic features of the natural extracellular milieu. In this direction, we have fabricated two short hydrophobic bioactive sequences derived from the laminin protein i. e., IKVAV and YIGSR. Based on the substantial hydrophobicity of these peptides, we selected a co-solvent approach as a suitable gelation technique that included different concentrations of DMSO as an organic phase along with an aqueous solution containing 0.1 % TFA. These hydrophobic laminin-based bioactive peptides with limited solubility in aqueous physiological environment showed significantly enhanced solubility with higher DMSO content in water. The enhanced solubility resulted in extensive intermolecular interactions that led to the formation of hydrogels with a higher-order entangled network along with improved mechanical properties. Interestingly, by simply modulating DMSO content, highly tunable gels were accessed in the same gelator domain that displayed differential physicochemical properties. Further, the cellular studies substantiated the potential of these laminin-derived hydrogels in enhancing cell-matrix interactions, thereby reinforcing their applications in tissue engineering.

Observing Dynamic Conformational Changes within the Coiled-Coil Domain of Different Laminin Isoforms Using High-Speed Atomic Force Microscopy

Laminins are trimeric glycoproteins with important roles in cell-matrix adhesion and tissue organization. The laminin α, ß, and γ-chains have short N-terminal arms, while their C-termini are connected via a triple coiled-coil domain, giving the laminin molecule a well-characterized cross-shaped morphology as a result. The C-terminus of laminin alpha chains contains additional globular laminin G-like (LG) domains with important roles in mediating cell adhesion. Dynamic conformational changes of different laminin domains have been implicated in regulating laminin function, but so far have not been analyzed at the single-molecule level. High-speed atomic force microscopy (HS-AFM) is a unique tool for visualizing such dynamic conformational changes under physiological conditions at sub-second temporal resolution. After optimizing surface immobilization and imaging conditions, we characterized the ultrastructure of laminin-111 and laminin-332 using HS-AFM timelapse imaging. While laminin-111 features a stable S-shaped coiled-coil domain displaying little conformational rearrangement, laminin-332 coiled-coil domains undergo rapid switching between straight and bent conformations around a defined central molecular hinge. Complementing the experimental AFM data with AlphaFold-based coiled-coil structure prediction enabled us to pinpoint the position of the hinge region, as well as to identify potential molecular rearrangement processes permitting hinge flexibility. Coarse-grained molecular dynamics simulations provide further support for a spatially defined kinking mechanism in the laminin-332 coiled-coil domain. Finally, we observed the dynamic rearrangement of the C-terminal LG domains of laminin-111 and laminin-332, switching them between compact and open conformations. Thus, HS-AFM can directly visualize molecular rearrangement processes within different laminin isoforms and provide dynamic structural insight not available from other microscopy techniques.

Artificial intelligence and the analysis of cryo-EM data provide structural insight into the molecular mechanisms underlying LN-lamininopathies

Laminins (Lm) are major components of basement membranes (BM), which polymerize to form a planar lattice on cell surface. Genetic alternations of Lm affect their oligomerization patterns and lead to failures in BM assembly manifesting in a group of human disorders collectively defined as Lm N-terminal domain lamininopathies (LN-lamininopathies). We have employed a recently determined cryo-EM structure of the Lm polymer node, the basic repeating unit of the Lm lattice, along with structure prediction and modeling to systematically analyze structures of twenty-three pathogenic Lm polymer nodes implicated in human disease. Our analysis provides the detailed mechanistic explanation how Lm mutations lead to failures in Lm polymerization underlining LN-lamininopathies. We propose the new categorization scheme of LN-lamininopathies based on the insight gained from the structural analysis. Our results can help to facilitate rational drug design aiming in the treatment of Lm deficiencies.

Novel Artificial Intelligence-Based Approaches for Ab Initio Structure Determination and Atomic Model Building for Cryo-Electron Microscopy

Single particle cryo-electron microscopy (cryo-EM) has emerged as the prevailing method for near-atomic structure determination, shedding light on the important molecular mechanisms of biological macromolecules. However, the inherent dynamics and structural variability of biological complexes coupled with the large number of experimental images generated by a cryo-EM experiment make data processing nontrivial. In particular, ab initio reconstruction and atomic model building remain major bottlenecks that demand substantial computational resources and manual intervention. Approaches utilizing recent innovations in artificial intelligence (AI) technology, particularly deep learning, have the potential to overcome the limitations that cannot be adequately addressed by traditional image processing approaches. Here, we review newly proposed AI-based methods for ab initio volume generation, heterogeneous 3D reconstruction, and atomic model building. We highlight the advancements made by the implementation of AI methods, as well as discuss remaining limitations and areas for future development.