Metabolic Signature of Articular Cartilage Following Mechanical Injury: An Integrated Transcriptomics and Metabolomics Analysis

Abstract

Mechanical injury to the articular cartilage is a key risk factor in joint damage and predisposition to osteoarthritis. Integrative multi-omics approaches provide a valuable tool to understand tissue behavior in response to mechanical injury insult and help to identify key pathways linking injury to tissue damage. Global or untargeted metabolomics provides a comprehensive characterization of the metabolite content of biological samples. In this study, we aimed to identify the metabolic signature of cartilage tissue post injury. We employed an integrative analysis of transcriptomics and global metabolomics of murine epiphyseal hip cartilage before and after injury. Transcriptomics analysis showed a significant enrichment of gene sets involved in regulation of metabolic processes including carbon metabolism, biosynthesis of amino acids, and steroid biosynthesis. Integrative analysis of enriched genes with putatively identified metabolite features post injury showed a significant enrichment for carbohydrate metabolism (glycolysis, galactose, and glycosylate metabolism and pentose phosphate pathway) and amino acid metabolism (arginine biosynthesis and tyrosine, glycine, serine, threonine, and arginine and proline metabolism). We then performed a cross analysis of global metabolomics profiles of murine and porcine ex vivo cartilage injury models. The top commonly modulated metabolic pathways post injury included arginine and proline metabolism, arginine biosynthesis, glycolysis/gluconeogenesis, and vitamin B6 metabolic pathways. These results highlight the significant modulation of metabolic responses following mechanical injury to articular cartilage. Further investigation of these pathways would provide new insights into the role of the early metabolic state of articular cartilage post injury in promoting tissue damage and its link to disease progression of osteoarthritis.

Keywords: arginine metabolic pathways; cartilage; glycolysis (glycolytic pathway); injury; metabolomics; osteoarthritis; transcriptomics analysis.

FIGURE 1

Injury to murine cartilage significantly modulates the expression profile of a large set of genes involved in regulation of metabolic processes. Microarray transcriptomic analysis of murine cartilage hips before and after injury was performed as described in “Materials and Methods.” (A) Volcano plot of gene expression profiles in injured cartilage compared to control. Differentially regulated genes post injury are highlighted in red (upregulated) and blue (downregulated). Examples of modulated metabolic genes are labeled in black. Genes significantly regulated in response to injury were analyzed for pathway enrichment using WebGestalt and STRING databases. (B) Gene Ontology biological processes of enriched genes post injury. Analysis shows that more than 800 genes are involved in metabolic processes. (C) Enriched metabolic pathways post injury retrieved from the STRING database using the list of significantly modulated genes.

FIGURE 2

Mechanical injury to murine hip cartilage significantly modulates the tissue metabolic profile. Injury to murine hips was induced, and tissue metabolites were extracted followed by global metabolomics profiling of the tissue before and after injury using LC–MS. Extracted metabolites were analyzed in positive and negative ion modes as described in “Materials and Methods.” Principal component analysis and volcano plots of detected metabolites in positive mode (A) and negative mode (B). Enriched metabolite features post injury are labeled in red (upregulated) and blue (downregulated). Numbers on volcano plots represent spectral bins of enriched features post injury in positive mode (C) and negative mode (D). (E) K-mean clustering of enriched-metabolite post hip cartilage injury shows six clusters of modulated features that could be distinguished based on their profile post injury. (F) Top enriched metabolic pathways post cartilage injury were identified using the modulated metabolite features list in the MetaboAnalyst 4.0 pathway analysis module. Numbers shown are of matched putative metabolite hits per total number of metabolites in each pathway. (G) Top enriched pathways of differentially modulated m/z metabolites features in positive and negative ion modes using mummichog metabolomics analysis software (http://mummichog-2.appspot.com/).

FIGURE 3

Integrative pathway analysis of differentially regulated genes and putative metabolite features post injury shows significant enrichment of arginine biosynthesis, arginine/proline metabolism, and glycolysis/gluconeogenesis metabolic pathways. (A) Top enriched pathways using genes–metabolites joint pathway analysis module in MetaboAnalyst 4.0. (B) Heat map of significant genes post injury in arginine metabolism and glycolysis/gluconeogenesis. (C) Heat map of putative metabolite features enriched in arginine metabolism and glycolysis/gluconeogenesis. D(m/z) for detected peaks, A(m/z) for accurate peaks, M for mode, N for negative ion mode, and P for positive ion mode. In (B,C) Fc is for gene expression or putative metabolite feature fold of change in injured cartilage compared to uninjured control. LogP is for –log10 of p-value identified by Student’s t-test. Heat maps were generated using MORPHEUS matrix analysis software (https://software.broadinstitute.org/morpheus/).

FIGURE 4

Enriched metabolite features and metabolic pathways post mechanical injury in porcine articular cartilage and cross analysis with differentially modulated features in injured murine cartilage. (A) Principal component analysis (PCA) of metabolite features in porcine cartilage tissue samples after 0, 1, 2, and 4 h and overnight (ON) post injury (combined positive and negative ion modes). (B) Volcano plots of detected metabolite features post cartilage injury at indicated times compared to uninjured control. Numbers on plots are for annotated enriched metabolite features spectral bins. Upregulated features after injury are shown in red, and downregulated features are shown in blue compared to control. (C) Pathway analysis of enriched metabolite features post injury to porcine cartilage using MetaboAnalyst 4.0. (D) Cross analysis of enriched features (m/z) in murine and porcine cartilage post mechanical injury. (E) Pathways commonly enriched in murine and porcine cartilage. A list of 290 common metabolite features between the two ex vivo cartilage injury models was used for pathway analysis in MetaboAnalyst 4.0. Numbers on the bar chart are for the matched metabolite hits per total number of metabolites in each pathway.