Mesenchymal Stromal Cell Secretome Is Affected by Tissue Source and Donor Age.

Variation in mesenchymal stromal cell (MSC) function depending on their origin is problematic, as it may confound clinical outcomes of MSC therapy. Current evidence suggests that the therapeutic benefits of MSCs are attributed to secretion of biologically active factors (secretome). However, the effect of donor characteristics on the MSC secretome remains largely unknown. Here, we examined the influence of donor age, sex, and tissue source, on the protein profile of the equine MSC secretome. We used dynamic metabolic labeling with stable isotopes combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify secreted proteins in MSC conditioned media (CM). Seventy proteins were classified as classically secreted based on the rate of label incorporation into newly synthesized proteins released into the extracellular space. Next, we analyzed CM of bone marrow- (n = 14) and adipose-derived MSCs (n = 16) with label-free LC-MS/MS. Clustering analysis of 314 proteins detected across all samples identified tissue source as the main factor driving variability in MSC CM proteomes. Linear modelling applied to the subset of 70 secreted proteins identified tissue-related difference in the abundance of 23 proteins. There was an age-related decrease in the abundance of CTHRC1 and LOX, further validated with orthogonal techniques. Due to the lack of flow cytometry characterization of MSC surface markers, the analysis could not account for the potential effect of cell population heterogeneity. This study provides evidence that tissue source and donor age contribute to differences in the protein composition of MSC secretomes which may influence the effects of MSC therapy.

microRNA-seq of cartilage reveals an overabundance of miR-140-3p which contains functional isomiRs.

miR-140 is selectively expressed in cartilage. Deletion of the entire Mir140 locus in mice results in growth retardation and early-onset osteoarthritis-like pathology; however, the relative contribution of miR-140-5p or miR-140-3p to the phenotype remains to be determined. An unbiased small RNA sequencing approach identified miR-140-3p as significantly more abundant (>10-fold) than miR-140-5p in human cartilage. Analysis of these data identified multiple miR-140-3p isomiRs differing from the miRBase annotation at both the 5' and 3' end, with >99% having one of two seed sequences (5' bases 2-8). Canonical (miR-140-3p.2) and shifted (miR-140-3p.1) seed isomiRs were overexpressed in chondrocytes and transcriptomics performed to identify targets. miR-140-3p.1 and miR-140-3p.2 significantly down-regulated 694 and 238 genes, respectively, of which only 162 genes were commonly down-regulated. IsomiR targets were validated using 3'UTR luciferase assays. miR-140-3p.1 targets were enriched within up-regulated genes in rib chondrocytes of Mir140-null mice and within down-regulated genes during human chondrogenesis. Finally, through imputing the expression of miR-140 from the expression of the host gene WWP2 in 124 previously published data sets, an inverse correlation with miR-140-3p.1 predicted targets was identified. Together these data suggest the novel seed containing isomiR miR-140-3p.1 is more functional than original consensus miR-140-3p seed containing isomiR.

XBP1 signalling is essential for alleviating mutant protein aggregation in ER-stress related skeletal disease.

The unfolded protein response (UPR) is a conserved cellular response to the accumulation of proteinaceous material in endoplasmic reticulum (ER), active both in health and disease to alleviate cellular stress and improve protein folding. Multiple epiphyseal dysplasia (EDM5) is a genetic skeletal condition and a classic example of an intracellular protein aggregation disease, whereby mutant matrilin-3 forms large insoluble aggregates in the ER lumen, resulting in a specific 'disease signature' of increased expression of chaperones and foldases, and alternative splicing of the UPR effector XBP1. Matrilin-3 is expressed exclusively by chondrocytes thereby making EDM5 a perfect model system to study the role of protein aggregation in disease. In order to dissect the role of XBP1 signalling in aggregation-related conditions we crossed a p.V194D Matn3 knock-in mouse model of EDM5 with a mouse line carrying a cartilage specific deletion of XBP1 and analysed the resulting phenotype. Interestingly, the growth of mice carrying the Matn3 p.V194D mutation compounded with the cartilage specific deletion of XBP1 was severely retarded. Further phenotyping revealed increased intracellular retention of amyloid-like aggregates of mutant matrilin-3 coupled with dramatically decreased cell proliferation and increased apoptosis, suggesting a role of XBP1 signalling in protein accumulation and/or degradation. Transcriptomic analysis of chondrocytes extracted from wild type, EDM5, Xbp1-null and compound mutant lines revealed that the alternative splicing of Xbp1 is crucial in modulating levels of protein aggregation. Moreover, through detailed transcriptomic comparison with a model of metaphyseal chondrodysplasia type Schmid (MCDS), an UPR-related skeletal condition in which XBP1 was removed without overt consequences, we show for the first time that the differentiation-state of cells within the cartilage growth plate influences the UPR resulting from retention of a misfolded mutant protein and postulate that modulation of XBP1 signalling pathway presents a therapeutic target for aggregation related conditions in cells undergoing proliferation.

OATargets: a knowledge base of genes associated with osteoarthritis joint damage in animals.

OBJECTIVES: To collate the genes experimentally modulated in animal models of osteoarthritis (OA) and compare these data with OA transcriptomics data to identify potential therapeutic targets. METHODS: PubMed searches were conducted to identify publications describing gene modulations in animal models. Analysed gene expression data were retrieved from the SkeletalVis database of analysed skeletal microarray and RNA-Seq expression data. A network diffusion approach was used to predict new genes associated with OA joint damage. RESULTS: A total of 459 genes were identified as having been modulated in animal models of OA, with ageing and post-traumatic (surgical) models the most prominent. Ninety-eight of the 143 genes (69%) genetically modulated more than once had a consistent effect on OA joint damage severity. Several discrepancies between different studies were identified, providing lessons on interpretation of these data. We used the data collected along with OA gene expression data to expand existing annotations and prioritise the most promising therapeutic targets, which we validated using the latest reported associations. We constructed an online database OATargets to allow researchers to explore the collated data and integrate it with existing OA and skeletal gene expression data. CONCLUSIONS: We present a comprehensive survey and online resource for understanding gene regulation of animal model OA pathogenesis.

Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration.

OBJECTIVE: To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics. METHODS: This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joint replacement surgery, from which macroscopically unaffected (preserved, n = 56) and lesioned (n = 45) OA articular cartilage were collected [Research Arthritis and Articular Cartilage (RAAK) study]. Unsupervised hierarchical clustering analysis on preserved cartilage transcriptome followed by clinical data integration was performed. Protein-protein interaction (PPI) followed by pathway enrichment analysis were done for genes significant differentially expressed between subgroups with interactions in the PPI network. RESULTS: Analysis of preserved samples (n = 56) resulted in two OA subtypes with n = 41 (cluster A) and n = 15 (cluster B) patients. The transcriptomic profile of cluster B cartilage, relative to cluster A (DE-AB genes) showed among others a pronounced upregulation of multiple genes involved in chemokine pathways. Nevertheless, upon investigating the OA pathophysiology in cluster B patients as reflected by differentially expressed genes between preserved and lesioned OA cartilage (DE-OA-B genes), the chemokine genes were significantly downregulated with OA pathophysiology. Upon integrating radiographic OA data, we showed that the OA phenotype among cluster B patients, relative to cluster A, may be characterized by higher joint space narrowing (JSN) scores and low osteophyte (OP) scores. CONCLUSION: Based on whole-transcriptome profiling, we identified two robust OA subtypes characterized by unique OA, pathophysiological processes in cartilage as well as a clinical phenotype. We advocate that further characterization, confirmation and clinical data integration is a prerequisite to allow for development of treatments towards personalized care with concurrently more effective treatment response.

SkeletalVis: an exploration and meta-analysis data portal of cross-species skeletal transcriptomics data.

MOTIVATION: Skeletal diseases are prevalent in society, but improved molecular understanding is required to formulate new therapeutic strategies. Large and increasing quantities of available skeletal transcriptomics experiments give the potential for mechanistic insight of both fundamental skeletal biology and skeletal disease. However, no current repository provides access to processed, readily interpretable analysis of this data. To address this, we have developed SkeletalVis, an exploration portal for skeletal gene expression experiments. RESULTS: The SkeletalVis data portal provides an exploration and comparison platform for analysed skeletal transcriptomics data. It currently hosts 287 analysed experiments with 739 perturbation responses with comprehensive downstream analysis. We demonstrate its utility in identifying both known and novel relationships between skeletal expression signatures. SkeletalVis provides users with a platform to explore the wealth of available expression data, develop consensus signatures and the ability to compare gene signatures from new experiments to the analysed data to facilitate meta-analysis. AVAILABILITY AND IMPLEMENTATION: The SkeletalVis data portal is freely accessible at http://phenome.manchester.ac.uk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Stratification of knee osteoarthritis: two major patient subgroups identified by genome-wide expression analysis of articular cartilage.

INTRODUCTION: Osteoarthritis (OA) is a heterogeneous and complex disease. We have used a network biology approach based on genome-wide analysis of gene expression in OA knee cartilage to seek evidence for pathogenic mechanisms that may distinguish different patient subgroups. METHODS: Results from RNA-Sequencing (RNA-Seq) were collected from intact knee cartilage at total knee replacement from 44 patients with OA, from 16 additional patients with OA and 10 control patients with non-OA. Results were analysed to identify patient subsets and compare major active pathways. RESULTS: The RNA-Seq results showed 2692 differentially expressed genes between OA and non-OA. Analysis by unsupervised clustering identified two distinct OA groups: Group A with 24 patients (55%) and Group B with 18 patients (41%). A 10 gene subgroup classifier was validated by RT-qPCR in 16 further patients with OA. Pathway analysis showed increased protein expression in both groups. PhenomeExpress analysis revealed group differences in complement activation, innate immune responses and altered Wnt and TGFß signalling, but no activation of inflammatory cytokine expression. Both groups showed suppressed circadian regulators and whereas matrix changes in Group A were chondrogenic, in Group B they were non-chondrogenic with changes in mechanoreceptors, calcium signalling, ion channels and in cytoskeletal organisers. The gene expression changes predicted 478 potential biomarkers for detection in synovial fluid to distinguish patients from the two groups. CONCLUSIONS: Two subgroups of knee OA were identified by network analysis of RNA-Seq data with evidence for the presence of two major pathogenic pathways. This has potential importance as a new basis for the stratification of patients with OA for drug trials and for the development of new targeted treatments.

PhenomeScape: a cytoscape app to identify differentially regulated sub-networks using known disease associations.

PhenomeScape is a Cytoscape app which provides easy access to the PhenomeExpress algorithm to interpret gene expression data. PhenomeExpress integrates protein interaction networks with known phenotype to gene associations to find active sub-networks enriched in differentially expressed genes. It also incorporates cross-species phenotypes and associations to include results from animal models of disease. With expression data imported into PhenomeScape, the user can quickly generate and visualise interactive sub-networks. PhenomeScape thus enables researchers to use prior knowledge of a disease to identify differentially regulated sub-networks and to generate an overview of altered biologically processes specific to that disease. AVAILABILITY AND IMPLEMENTATION: Freely available for download at https://github.com/soulj/PhenomeScape CONTACT: jamie.soul@postgrad.manchester.ac.uk or jean-marc.schwartz@manchester.ac.uk.

Epigenetic mechanisms of osteoarthritis risk in human skeletal development.

The epigenome, including the methylation of cytosine bases at CG dinucleotides, is intrinsically linked to transcriptional regulation. The tight regulation of gene expression during skeletal development is essential, with ~1/500 individuals born with skeletal abnormalities. Furthermore, increasing evidence is emerging to link age-associated complex genetic musculoskeletal diseases, including osteoarthritis (OA), to developmental factors including joint shape. Multiple studies have shown a functional role for DNA methylation in the genetic mechanisms of OA risk using articular cartilage samples taken from aged patients. Despite this, our knowledge of temporal changes to the methylome during human cartilage development has been limited. We quantified DNA methylation at ~700,000 individual CpGs across the epigenome of developing human articular cartilage in 72 samples ranging from 7-21 post-conception weeks, a time period that includes cavitation of the developing knee joint. We identified significant changes in 8% of all CpGs, and >9400 developmental differentially methylated regions (dDMRs). The largest hypermethylated dDMRs mapped to transcriptional regulators of early skeletal patterning including MEIS1 and IRX1. Conversely, the largest hypomethylated dDMRs mapped to genes encoding extracellular matrix proteins including SPON2 and TNXB and were enriched in chondrocyte enhancers. Significant correlations were identified between the expression of these genes and methylation within the hypomethylated dDMRs. We further identified 811 CpGs at which significant dimorphism was present between the male and female samples, with the majority (68%) being hypermethylated in female samples. Following imputation, we captured the genotype of these samples at >5 million variants and performed epigenome-wide methylation quantitative trait locus (mQTL) analysis. Colocalization analysis identified 26 loci at which genetic variants exhibited shared impacts upon methylation and OA genetic risk. This included loci which have been previously reported to harbour OA-mQTLs (including GDF5 and ALDH1A2), yet the majority (73%) were novel (including those mapping to CHST3, FGF1 and TEAD1). To our knowledge, this is the first extensive study of DNA methylation across human articular cartilage development. We identify considerable methylomic plasticity within the development of knee cartilage and report active epigenomic mediators of OA risk operating in prenatal joint tissues.

Quantitative proteomic analysis of the adipocyte plasma membrane.

The adipocyte is a key regulator of mammalian metabolism. To advance our understanding of this important cell, we have used quantitative proteomics to define the protein composition of the adipocyte plasma membrane (PM) in the presence and absence of insulin. Using this approach, we have identified a high confidence list of 486 PM proteins, 52 of which potentially represent novel cell surface proteins, including a member of the adiponectin receptor family and an unusually high number of hydrolases with no known function. Several novel insulin-responsive proteins including the sodium/hydrogen exchanger, NHE6 and the collagens III and VI were also identified, and we provide evidence of PM-ER association suggestive of a unique functional association between these two organelles in the adipocyte. Together these studies provide a wealth of potential therapeutic targets for the manipulation of adipocyte function and a valuable resource for metabolic research and PM biology.

The angiogenic potential of CD271+ human adipose tissue-derived mesenchymal stem cells.

BACKGROUND: Autologous fat grafting is often a crucial aspect of reconstructive and aesthetic surgeries, yet poor graft retention is a major issue with this technique. Enriching fat grafts with adipose tissue-derived mesenchymal stem cells (AD-MSCs) improves graft survival-however, AD-MSCs represent a heterogeneous population. Selection of subpopulations of AD-MSCs would allow the targeting of specific AD-MSCs that may benefit fat graft survival more than the general AD-MSC population. METHODS: Human AD-MSCs were selected for the surface marker CD271 using magnetic-activated cell sorting and compared to the CD271 negative phenotype.  These subpopulations were analysed for gene expression using Real-Time qPCR and RNA sequencing; surface marker characteristics using immunostaining; ability to form tubules when cultured with endothelial cells; and gene and protein expression of key angiogenic mediators when cultured with ex-vivo adipose tissue. RESULTS: Human AD-MSCs with the surface marker CD271 express angiogenic genes at higher levels, and inflammatory genes at lower levels, than the CD271- AD-MSC population. A greater proportion of CD271+ AD-MSCs also possess the typical complement of stem cell surface markers and are more likely to promote effective neoangiogenesis, compared to CD271- AD-MSCs. CONCLUSION: Enriching grafts with the CD271+ AD-MSC subpopulation holds potential for the improvement of reconstructive and aesthetic surgeries involving adipose tissue.

Transgenic inhibition of interleukin-6 trans-signaling does not prevent skeletal pathologies in mucolipidosis type II mice.

Severe skeletal alterations are common symptoms in patients with mucolipidosis type II (MLII), a rare lysosomal storage disorder of childhood. We have previously reported that progressive bone loss in a mouse model for MLII is caused by an increased number of bone-resorbing osteoclasts, which is accompanied by elevated expression of the cytokine interleukin-6 (IL-6) in the bone microenvironment. In the present study we addressed the question, if pharmacological blockade of IL-6 can prevent the low bone mass phenotype of MLII mice. Since the cellular IL-6 response can be mediated by either the membrane-bound (classic signaling) or the soluble IL-6 receptor (trans-signaling), we first performed cell culture assays and found that both pathways can increase osteoclastogenesis. We then crossed MLII mice with transgenic mice expressing the recombinant soluble fusion protein sgp130Fc, which represents a natural inhibitor of IL-6 trans-signaling. By undecalcified histology and bone-specific histomorphometry we found that high circulating sgp130Fc levels do not affect skeletal growth or remodeling in wild-type mice. Most importantly, blockade of IL-6 trans-signaling did neither reduce osteoclastogenesis, nor increase bone mass in MLII mice. Therefore, our data clearly demonstrate that the bone phenotype of MLII mice cannot be corrected by blocking the IL-6 trans-signaling.

Increased hippocampal excitability in miR-324-null mice.

MicroRNAs are non-coding RNAs that act to downregulate the expression of target genes by translational repression and degradation of messenger RNA molecules. Individual microRNAs have the ability to specifically target a wide array of gene transcripts, therefore allowing each microRNA to play key roles in multiple biological pathways. miR-324 is a microRNA predicted to target thousands of RNA transcripts and is expressed far more highly in the brain than in any other tissue, suggesting that it may play a role in one or multiple neurological pathways. Here we present data from the first global miR-324-null mice, in which increased excitability and interictal discharges were identified in vitro in the hippocampus. RNA sequencing was used to identify differentially expressed genes in miR-324-null mice which may contribute to this increased hippocampal excitability, and 3'UTR luciferase assays and western blotting revealed that two of these, Suox and Cd300lf, are novel direct targets of miR-324. Characterisation of microRNAs that produce an effect on neurological activity, such as miR-324, and identification of the pathways they regulate will allow a better understanding of the processes involved in normal neurological function and in turn may present novel pharmaceutical targets in treating neurological disease.

Imbalanced cellular metabolism compromises cartilage homeostasis and joint function in a mouse model of mucolipidosis type III gamma.

Mucolipidosis type III (MLIII) gamma is a rare inherited lysosomal storage disorder caused by mutations in GNPTG encoding the γ-subunit of GlcNAc-1-phosphotransferase, the key enzyme ensuring proper intracellular location of multiple lysosomal enzymes. Patients with MLIII gamma typically present with osteoarthritis and joint stiffness, suggesting cartilage involvement. Using Gnptg knockout (Gnptgko ) mice as a model of the human disease, we showed that missorting of a number of lysosomal enzymes is associated with intracellular accumulation of chondroitin sulfate in Gnptgko chondrocytes and their impaired differentiation, as well as with altered microstructure of the cartilage extracellular matrix (ECM). We also demonstrated distinct functional and structural properties of the Achilles tendons isolated from Gnptgko and Gnptab knock-in (Gnptabki ) mice, the latter displaying a more severe phenotype resembling mucolipidosis type II (MLII) in humans. Together with comparative analyses of joint mobility in MLII and MLIII patients, these findings provide a basis for better understanding of the molecular reasons leading to joint pathology in these patients. Our data suggest that lack of GlcNAc-1-phosphotransferase activity due to defects in the γ-subunit causes structural changes within the ECM of connective and mechanosensitive tissues, such as cartilage and tendon, and eventually results in functional joint abnormalities typically observed in MLIII gamma patients. This idea was supported by a deficit of the limb motor function in Gnptgko mice challenged on a rotarod under fatigue-associated conditions, suggesting that the impaired motor performance of Gnptgko mice was caused by fatigue and/or pain at the joint.This article has an associated First Person interview with the first author of the paper.

Cartilage endoplasmic reticulum stress may influence the onset but not the progression of experimental osteoarthritis.

BACKGROUND: Osteoarthritis has been associated with a plethora of pathological factors and one which has recently emerged is chondrocyte endoplasmic reticulum (ER) stress. ER stress is sensed by key ER-resident stress sensors, one of which is activating transcription factor 6 (ATF6). The purpose of this study is to determine whether increased ER stress plays a role in OA. METHODS: OA was induced in male wild-type (+/+), ColIITgcog (c/c) and Atf6α-/- mice by destabilisation of the medial meniscus (DMM). c/c mice have increased ER stress in chondrocytes via the collagen II promoter-driven expression of ER stress-inducing Tgcog. Knee joints were scored histologically for OA severity. RNA-seq was performed on laser-micro-dissected RNA from cartilage of +/+ and c/c DMM-operated mice. RESULTS: In situ hybridisation demonstrated a correlation between the upregulation of ER stress marker, BiP, and early signs of proteoglycan loss and cartilage damage in DMM-operated +/+ mice. Histological analysis revealed a significant reduction in OA severity in c/c mice compared with +/+ at 2 weeks post-DMM. This chondroprotective effect in c/c mice was associated with a higher ambient level of BiP protein prior to DMM and a delay in chondrocyte apoptosis. RNA-seq analysis suggested Xbp1-regulated networks to be significantly enriched in c/c mice at 2 weeks post-DMM. Compromising the ER through genetically ablating Atf6α, a key ER stress sensor, had no effect on DMM-induced OA severity. CONCLUSION: Our studies indicate that an increased capacity to effectively manage increases in ER stress in articular cartilage due either to pre-conditioning as a result of prior exposure to ER stress or to genetic pre-disposition may be beneficial in delaying the onset of OA, but once established, ER stress plays no significant role in disease progression.

PhenomeExpress: a refined network analysis of expression datasets by inclusion of known disease phenotypes.

We describe a new method, PhenomeExpress, for the analysis of transcriptomic datasets to identify pathogenic disease mechanisms. Our analysis method includes input from both protein-protein interaction and phenotype similarity networks. This introduces valuable information from disease relevant phenotypes, which aids the identification of sub-networks that are significantly enriched in differentially expressed genes and are related to the disease relevant phenotypes. This contrasts with many active sub-network detection methods, which rely solely on protein-protein interaction networks derived from compounded data of many unrelated biological conditions and which are therefore not specific to the context of the experiment. PhenomeExpress thus exploits readily available animal model and human disease phenotype information. It combines this prior evidence of disease phenotypes with the experimentally derived disease data sets to provide a more targeted analysis. Two case studies, in subchondral bone in osteoarthritis and in Pax5 in acute lymphoblastic leukaemia, demonstrate that PhenomeExpress identifies core disease pathways in both mouse and human disease expression datasets derived from different technologies. We also validate the approach by comparison to state-of-the-art active sub-network detection methods, which reveals how it may enhance the detection of molecular phenotypes and provide a more detailed context to those previously identified as possible candidates.