Longevity interventions modulate mechanotransduction and extracellular matrix homeostasis in C. elegans.

Dysfunctional extracellular matrices (ECM) contribute to aging and disease. Repairing dysfunctional ECM could potentially prevent age-related pathologies. Interventions promoting longevity also impact ECM gene expression. However, the role of ECM composition changes in healthy aging remains unclear. Here we perform proteomics and in-vivo monitoring to systematically investigate ECM composition (matreotype) during aging in C. elegans revealing three distinct collagen dynamics. Longevity interventions slow age-related collagen stiffening and prolong the expression of collagens that are turned over. These prolonged collagen dynamics are mediated by a mechanical feedback loop of hemidesmosome-containing structures that span from the exoskeletal ECM through the hypodermis, basement membrane ECM, to the muscles, coupling mechanical forces to adjust ECM gene expression and longevity via the transcriptional co-activator YAP-1 across tissues. Our results provide in-vivo evidence that coordinated ECM remodeling through mechanotransduction is required and sufficient to promote longevity, offering potential avenues for interventions targeting ECM dynamics.

Assessing Collagen Deposition During Aging in Mammalian Tissue and in Caenorhabditis elegans.

Proper collagen homeostasis is essential for development and aging of any multicellular organism. During aging, two extreme scenarios are commonly occurring: a local excess in collagen deposition, for instance during fibrosis, or a gradual overall reduction of collagen mass. Here, we describe a histological and a colorimetric method to assess collagen levels in mammalian tissues and in the nematode Caenorhabditis elegans. The first method is the polychrome Herovici staining to distinguish between young and mature collagen ratios. The second method is based on hydroxyproline measurements to estimate collagen protein levels. In addition, we show how to decellularize the multicellular organism C. elegans in order to harvest its cuticle, one of the two major extracellular matrices, mainly composed of collagen. These methods allow assessing collagen deposition during aging either in tissues or in whole organisms.

The in-silico characterization of the Caenorhabditis elegans matrisome and proposal of a novel collagen classification.

Proteins are the building blocks of life. While proteins and their localization within cells and sub-cellular compartments are well defined, the proteins predicted to be secreted to form the extracellular matrix - or matrisome - remain elusive in the model organism C. elegans. Here, we used a bioinformatic approach combining gene orthology and protein structure analysis and an extensive curation of the literature to define the C. elegans matrisome. Similar to the human genome, we found that 719 out of ~20,000 genes (~4%) of the C. elegans genome encodes matrisome proteins, including 181 collagens, 35 glycoproteins, 10 proteoglycans, and 493 matrisome-associated proteins. We report that 173 out of the 181 collagen genes are unique to nematodes and are predicted to encode cuticular collagens, which we are proposing to group into five clusters. To facilitate the use of our lists and classification by the scientific community, we developed an automated annotation tool to identify ECM components in large datasets. We also established a novel database of all C. elegans collagens (CeColDB). Last, we provide examples of how the newly defined C. elegans matrisome can be used for annotations and gene ontology analyses of transcriptomic, proteomic, and RNAi screening data. Because C. elegans is a widely used model organism for high throughput genetic and drug screens, and to study biological and pathological processes, the conserved matrisome genes may aid in identifying potential drug targets. In addition, the nematode-specific matrisome may be exploited for targeting parasitic infection of man and crops.

Overcoming Autofluorescence to Assess GFP Expression During Normal Physiology and Aging in Caenorhabditis elegans.

Green fluorescent protein (GFP) is widely used as a molecular tool to assess protein expression and localization. In C. elegans, the signal from weakly expressed GFP fusion proteins is masked by autofluorescence emitted from the intestinal lysosome-related gut granules. For instance, the GFP fluorescence from SKN-1 transcription factor fused to GFP is barely visible with common GFP (FITC) filter setups. Furthermore, this intestinal autofluorescence increases upon heat stress, oxidative stress (sodium azide), and during aging, thereby masking GFP expression even from proximal tissues. Here, we describe a triple band GFP filter setup that separates the GFP signal from autofluorescence, displaying GFP in green and autofluorescence in yellow. In addition, yellow fluorescent protein (YFP) remains distinguishable from both the yellowish autofluorescence and GFP with this triple band filter setup. Although some GFP intensity might be lost with the triple band GFP filter setup, the advantage is that no modification of currently used transgenic GFP lines is needed and these GFP filters are easy to install. Hence, by using this triple band GFP filter setup, the investigators can easily distinguish autofluorescence from GFP and YFP in their favorite transgenic C. elegans lines.