Umeå University's logo

T-2 toxin and deoxynivalenol (DON) are two prevalent mycotoxins that cause cartilage damage in Kashin-Beck disease (KBD). Cartilage extracellular matrix (ECM) degradation in chondrocytes is a significant pathological feature of KBD. It has been shown that the Hippo pathway is involved in cartilage ECM degradation. This study aimed to examine the effect of YAP, a major regulator of the Hippo pathway, on the ECM degradation in the hiPS-derived chondrocytes (hiPS-Ch) model of KBD. The hiPS-Ch injury models were established via treatment with T-2 toxin/DON alone or in combination. We found that T-2 toxin and DON inhibited the proliferation of hiPS-Ch in a dose-dependent manner; significantly increased the levels of YAP, SOX9, and MMP13; and decreased the levels of COL2A1 and ACAN (all p values < 0.05). Immunofluorescence revealed that YAP was primarily located in the nuclei of hiPS-Ch, and its expression level increased with toxin concentrations. The inhibition of YAP resulted in the dysregulated expression of chondrogenic markers (all p values < 0.05). These findings suggest that T-2 toxin and DON may inhibit the proliferation of, and induce the ECM degradation, of hiPS-Ch mediated by YAP, providing further insight into the cellular and molecular mechanisms contributing to cartilage damage caused by toxins.

Cartilage defects and osteoarthritis are health problems which are major burdens on health care systems globally, especially in aging populations. Cartilage is a vulnerable tissue, which generally faces a progressive degenerative process when injured. This makes it the 11th most common cause of global disability. Conservative methods are used to treat the initial phases of the illness, while orthopedic management is the method used for more progressed phases. These include, for instance, arthroscopic shaving, microfracturing and mosaicplasty, and joint replacement as the final treatment. Cell-based implantation methods have also been developed. Despite reports of successful treatments, they often suffer from the non-optimal nature of chondrocyte phenotype in the repair tissue. Thus, improved strategies to control the phenotype of the regenerating cells are needed. Avascular tissue cartilage relies on diffusion for nutrients acquisition and the removal of metabolic waste products. A low oxygen content is also present in cartilage, and the chondrocytes are, in fact, well adapted to it. Therefore, this raises an idea that the regulation of oxygen tension could be a strategy to control the chondrocyte phenotype expression, important in cartilage tissue for regenerative purposes. This narrative review discusses the aspects related to oxygen tension in the metabolism and regulation of articular and growth plate chondrocytes and progenitor cell phenotypes, and the role of some microenvironmental factors as regulators of chondrocytes.

Spatial transcriptomics, proteomics, and epigenomics are innovative technologies which offer an unparalleled resolution and wealth of data in understanding and the interpretation of cellular functions and interactions. These techniques allow researchers to investigate gene and protein expressions at an individual cell level, revealing cellular heterogeneity within, for instance, bioengineered tissues and classifying novel and rare cell populations that could be essential for the function of the tissues and in disease processes. It is possible to analyze thousands of cells simultaneously, which gives thorough insights into the transcriptomic view of complex tissues. Spatial transcriptomics combines gene expressions with spatial information, conserving tissue architecture and making the mapping of gene activity across different tissue regions possible. Despite recent advancements in these technologies, they face certain limitations. Single-cell transcriptomics can suffer from technical noise and dropout events, leading to incomplete data. Its applicability has been limited by the complexity of data integration and interpretation, although better resolution and tools for the interpretation of data are developing fast. Spatial proteomics and spatial epigenomics provide data on the distribution of proteins and the gene regulatory aspects in tissues, respectively. The disadvantages of these approaches include rather costly and time-consuming analyses. Nevertheless, combining these techniques promises a more comprehensive understanding of cell function and tissue organization, which can be predicted to be useful in achieving better knowledge of cell guidance in tissue-engineered constructs and a higher quality of tissue technology products.

OBJECTIVES: Single-cell and spatial transcriptomics analysis of human knee articular cartilage tissue to present a comprehensive transcriptome landscape and osteoarthritis (OA)-critical cell populations.

METHODS: Single-cell RNA sequencing and spatially resolved transcriptomic technology have been applied to characterise the cellular heterogeneity of human knee articular cartilage which were collected from 8 OA donors, and 3 non-OA control donors, and a total of 19 samples. The novel chondrocyte population and marker genes of interest were validated by immunohistochemistry staining, quantitative real-time PCR, etc. The OA-critical cell populations were validated through integrative analyses of publicly available bulk RNA sequencing data and large-scale genome-wide association studies.

RESULTS: We identified 33 cell population-specific marker genes that define 11 chondrocyte populations, including 9 known populations and 2 new populations, that is, pre-inflammatory chondrocyte population (preInfC) and inflammatory chondrocyte population (InfC). The novel findings that make this an important addition to the literature include: (1) the novel InfC activates the mediator MIF-CD74; (2) the prehypertrophic chondrocyte (preHTC) and hypertrophic chondrocyte (HTC) are potentially OA-critical cell populations; (3) most OA-associated differentially expressed genes reside in the articular surface and superficial zone; (4) the prefibrocartilage chondrocyte (preFC) population is a major contributor to the stratification of patients with OA, resulting in both an inflammatory-related subtype and a non-inflammatory-related subtype.

CONCLUSIONS: Our results highlight InfC, preHTC, preFC and HTC as potential cell populations to target for therapy. Also, we conclude that profiling of those cell populations in patients might be used to stratify patient populations for defining cohorts for clinical trials and precision medicine.

Objective: This study aimed to investigate the roles of accessible chromatin in understanding the different pathogeneses between Kashin-Beck disease (KBD) and primary osteoarthritis (OA).

Methods: Articular cartilages of KBD and OA patients were collected, and after tissue digestion, primary chondrocytes were cultured in vitro. Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) was performed to compare the accessible chromatin differences of chondrocytes between KBD and OA groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were executed for the promoter genes. Then, the IntAct online database was used to generate networks of significant genes. Finally, we overlapped the analysis of differentially accessible region (DAR)-associated genes and differentially expressed genes (DEGs) obtained from whole-genomic microarray.

Results: We obtained 2,751 total DARs, which contained 1,985 loss and 856 gain DARs and belonged to 11 location distributions. We obtained 218 motifs associated with loss DARs, 71 motifs associated with gain DARs, 30 motif enrichments of loss DARs, and 30 motif enrichments of gain DARs. In total, 1,749 genes are associated with loss DARs, and 826 genes are associated with gain DARs. Among them, 210 promoter genes are associated with loss DARs, and 112 promoter genes are associated with gain DARs. We obtained 15 terms of GO enrichment and 5 terms of KEGG pathway enrichment from loss DAR promoter genes, and 15 terms of GO enrichment and 3 terms of KEGG pathway enrichment from gain DAR promoter genes. We obtained CAPN6 and other 2 overlap genes from loss DARs-vs-down DEGs, AMOTL1 from gain DARs-vs-down DEGs, EBF3 and other 12 overlap genes from loss DARs-vs-up DEGs, and ADARB1 and other 10 overlap genes from 101 gain DARs-vs-up DEGs. These overlap genes were built into 4 gene interaction networks.

Conclusion: FGF7, GPD1L, NFIB, RUNX2, and VCAM1 were the overlapped genes from the DAR-associated genes and DEGs. These genes were associated with the abnormal chondrocyte function, which may play crucial roles in different processes between KBD and OA in the way of accessible chromatin.

Background: Osteoarthritis (OA) and Kashin-Beck disease (KBD) both are two severe osteochondral disorders. In this study, we aimed to compare the gut microbiota structure between OA and KBD patients.

Methods: Fecal samples collected from OA and KBD patients were used to characterize the gut microbiota using 16S rDNA gene sequencing. To identify whether gut microbial changes at the species level are associated with the genes or functions of the gut bacteria between OA and KBD groups, metagenomic sequencing of fecal samples from OA and KBD subjects was performed.

Results: The OA group was characterized by elevated Epsilonbacteraeota and Firmicutes levels. A total of 52 genera were identified to be significantly differentially abundant between the two groups. The genera Raoultella, Citrobacter, Flavonifractor, g__Lachnospiraceae_UCG-004, and Burkholderia-Caballeronia-Paraburkholderia were more abundant in the OA group. The KBD group was characterized by higher Prevotella_9, Lactobacillus, Coprococcus_2, Senegalimassilia, and Holdemanella. The metagenomic sequencing showed that the Subdoligranulum_sp._APC924/74, Streptococcus_parasanguinis, and Streptococcus_salivarius were significantly increased in abundance in the OA group compared to those in the KBD group, and the species Prevotella_copri, Prevotella_sp._CAG:386, and Prevotella_stercorea were significantly decreased in abundance in the OA group compared to those in the KBD group by using metagenomic sequencing.

Conclusion: Our study provides a comprehensive landscape of the gut microbiota between OA and KBD patients and provides clues for better understanding the mechanisms underlying the pathogenesis of OA and KBD.

The mechanism of environmental factors in Kashin-Beck disease (KBD) remains unknown. We aimed to identify single nucleotide polymorphisms (SNPs) and protein alterations of selenium- and T-2 toxin-responsive genes to provide new evidence of chondrocytic damage in KBD. This study sampled the cubital venous blood of 258 subjects including 129 sex-matched KBD patients and 129 healthy controls for SNP detection. We applied an additive model, a dominant model, and a recessive model to identify significant SNPs. We then used the Comparative Toxicogenomics Database (CTD) to select selenium- and T-2 toxin-responsive genes with the candidate SNP loci. Finally, immunohistochemistry was applied to verify the protein expression of candidate genes in knee cartilage obtained from 15 subjects including 5 KBD, 5 osteoarthritis (OA), and 5 healthy controls. Forty-nine SNPs were genotyped in the current study. The C allele of rs6494629 was less frequent in KBD than in the controls (OR = 0.63, p = 0.011). Based on the CTD database, PPARG, ADAM12, IL6, SMAD3, and TIMP2 were identified to interact with selenium, sodium selenite, and T-2 toxin. KBD was found to be significantly associated with rs12629751 of PPARG (additive model: OR = 0.46, p = 0.012; dominant model: OR = 0.45, p = 0.049; recessive model: OR = 0.18, p = 0.018), rs1871054 of ADAM12 (dominant model: OR = 2.19, p = 0.022), rs1800796 of IL6 (dominant model: OR = 0.30, p = 0.003), rs6494629 of SMAD3 (additive model: OR = 0.65, p = 0.019; dominant model: OR = 0.52, p = 0.012), and rs4789936 of TIMP2 (recessive model: OR = 5.90, p = 0.024). Immunohistochemistry verified significantly upregulated PPARG, ADAM12, SMAD3, and TIMP2 in KBD compared with OA and normal controls (p < 0.05). Genetic polymorphisms of PPARG, ADAM12, SMAD3, and TIMP2 may contribute to the risk of KBD. These genes could promote the pathogenesis of KBD by disturbing ECM homeostasis.

Glycoproteins are involved in the development of many diseases, while the type and content of N-glycoproteins in the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) are still unclear. This research aims to identify N-glycoproteins in knee cartilage patients with OA and KBD compared with normal control (N) adults. The cartilage samples were collected from gender- and age-matched OA (n = 9), KBD (n = 9) patients, and N (n = 9) adults. Glycoproteomics and label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) obtained N-glycoproteins of KBD and OA. A total of 594 N-glycoproteins and 1146 N-glycosylation peptides were identified. The identified data were further compared and analyzed with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interactions (PPI). Pairwise comparison of the glycoproteins detected in the three groups showed that integrin beta-1 (ITGB1), collagen alpha-1 (II) chain (COL2A1), collagen alpha-1 (VII) chain (COL7A1), carbohydrate sulfotransferase 3 (CHST-3), carbohydrate sulfotransferase 4 (CHST-4), thrombospondin 2 (THBS2), bone morphogenetic protein 8A (BMP8A), tenascin-C (TNC), lysosome-associated membrane protein (LAMP2), and beta-glucuronidase (GUSB) were significantly differentially expressed. GO results suggested N-glycoproteins mainly belonged to protein metabolic process, single-multicellular and multicellular organism process, cell adhesion, biological adhesion, and multicellular organism development. KEGG and PPI results revealed that key N-glycoproteins were closely related to pathways for OA and KBD, such as phagosome, ECM-receptor interaction, lysosome, focal adhesion, protein digestion, and absorption. These results reflected glycoprotein expression for OA and KBD in the process of ECM degradation, material transport, cell-cell or cell-ECM interaction, and information transduction. These key significantly differentially expressed N-glycoproteins and pathways lead to the degeneration and degradation of the cartilage of OA and KBD mainly by disrupting the synthesis and catabolism of basic components of ECM and chondrocytes and interfering with the transfer of material or information. The key N-glycoproteins or pathways in this research are potential targets for pathological mechanisms and therapies of OA and KBD.

The aim of this study was to identify crucial proteins and N-glycosylated sites in the pathological mechanism of Kashin-Beck Disease (KBD) compared with osteoarthritis (OA). Nine KBD knee subjects and nine OA knee subjects were selected for the study. Quantitative proteomics and N-glycoproteomics data of KBD and OA were obtained by protein and N-glycoprotein enrichment and LC-MS/MS analysis. Differentially expressed proteins or N-glycosylation sites were examined with a comparative analysis between KBD and OA. Total 2205 proteins were identified in proteomic analysis, of which 375 were significantly different. Among these, 121 proteins were up-regulated and 254 were down-regulated. In N-glycoproteomic analysis, 278 different N-glycosylated sites that were related to 187 N-glycoproteins were identified. Proteins and their N-glycosylated sites are associated with KBD pathological process including ITGB1, LRP1, ANO6, COL1A1, MXRA5, DPP4, and CSPG4. CRLF1 and GLG1 are proposed to associate with both KBD and OA pathological processes. Key pathways in KBD vs. OA proteomic and N-glycoproteomic analysis contained extracellular matrix receptor interaction, focal adhesion, phagosome, protein digestion, and absorption. N-glycosylation may influence the pathological process by affecting the integrity of chondrocytes or cartilage. It regulated the intercellular signal transduction pathway, which contributes to cartilage destruction in KBD.