Exploring the Early Molecular Pathogenesis of Osteoarthritis Using Differential Network Analysis of Human Synovial Fluid.

The molecular mechanisms that drive the onset and development of osteoarthritis (OA) remain largely unknown. In this exploratory study, we used a proteomic platform (SOMAscan assay) to measure the relative abundance of more than 6000 proteins in synovial fluid (SF) from knees of human donors with healthy or mildly degenerated tissues, and knees with late-stage OA from patients undergoing knee replacement surgery. Using a linear mixed effects model, we estimated the differential abundance of 6251 proteins between the three groups. We found 583 proteins upregulated in the late-stage OA, including MMP1, collagenase 3 and interleukin-6. Further, we selected 760 proteins (800 aptamers) based on absolute fold changes between the healthy and mild degeneration groups. To those, we applied Gaussian Graphical Models (GGMs) to analyze the conditional dependence of proteins and to identify key proteins and subnetworks involved in early OA pathogenesis. After regularization and stability selection, we identified 102 proteins involved in GGM networks. Notably, network complexity was lost in the protein graph for mild degeneration when compared to controls, suggesting a disruption in the regular protein interplay. Furthermore, among our main findings were several downregulated (in mild degeneration versus healthy) proteins with unique interactions in the healthy group, one of which, SLCO5A1, has not previously been associated with OA. Our results suggest that this protein is important for healthy joint function. Further, our data suggests that SF proteomics, combined with GGMs, can reveal novel insights into the molecular pathogenesis and identification of biomarker candidates for early-stage OA.

Identification and quantification of degradome components in human synovial fluid reveals an increased proteolytic activity in knee osteoarthritis patients vs controls.

Synovial fluid (SF) may contain cleavage products of proteolytic activities. Our aim was to characterize the degradome through analysis of proteolytic activity and differential abundance of these components in a peptidomic analysis of SF in knee osteoarthritis (OA) patients versus controls (n = 23). SF samples from end-stage knee osteoarthritis patients undergoing total knee replacement surgery and controls, that is, deceased donors without known knee disease were previously run using liquid chromatography mass spectrometry (LC-MS). This data was used to perform new database searches generating results for non-tryptic and semi-tryptic peptides for studies of degradomics in OA. We used linear mixed models to estimate differences in peptide-level expression between the two groups. Known proteolytic events (from the MEROPS peptidase database) were mapped to the dataset, allowing the identification of potential proteases and which substrates they cleave. We also developed a peptide-centric R tool, proteasy, which facilitates analyses that involve retrieval and mapping of proteolytic events. We identified 429 differentially abundant peptides. We found that the increased abundance of cleaved APOA1 peptides is likely a consequence of enzymatic degradation by metalloproteinases and chymase. We identified metalloproteinase, chymase, and cathepsins as the main proteolytic actors. The analysis indicated increased activity of these proteases irrespective of their abundance.

In Vitro Models and Proteomics in Osteoarthritis Research.

This review summarizes and exemplifies the current understanding of osteoarthritis in vitro models and describes their relevance for new insights in the future of osteoarthritis research. Our friend and highly appreciated colleague, Prof. Alan Grodzinsky has contributed greatly to the understanding of joint tissue biology and cartilage biomechanics. He frequently utilizes in vitro models and cartilage explant cultures, and recent work also includes proteomics studies. This review is dedicated to honor his 75-year birthday and will focus on recent proteomic in vitro studies related to osteoarthritis, and within this topic highlight some of his contributions to the field.

ProteoMill: efficient network-based functional analysis portal for proteomics data.

SUMMARY: Functional analysis has become a common approach to incorporate biological knowledge into the analysis of omics data, and to explore molecular events that govern a disease state. It is though only one step in a wider analytical pipeline that typically requires use of multiple individual analysis software. There is currently a need for a well-integrated omics analysis tool that performs all the steps. The ProteoMill portal is developed as an R Shiny application and integrates all necessary steps from data-upload, converting identifiers, to quality control, differential expression and network-based functional analysis into a single fast, interactive easy to use workflow. Further, it maintains annotation data sources up to date, overcoming a common problem with use of outdated information and seamlessly integrates multiple R-packages for an improved user-experience. The functionality provided in this software can benefit researchers by facilitating the exploratory analysis of proteomics data. AVAILABILITY AND IMPLEMENTATION: ProteoMill is available at https://proteomill.com.

Genetic Influence on Osteoarthritis Versus Other Rheumatic Diseases.

OBJECTIVE: We aimed to compare the genetic contribution to osteoarthritis (OA) versus other rheumatic/musculoskeletal diseases (RMDs) in the same population and to explore the role for any shared genetics between OA and other RMDs. METHODS: In 59,970 Swedish twins aged 35 years or older, we estimated the heritability (the variance explained by genetic factors) of OA in peripheral joints, back and neck pain, shoulder pain (adhesive capsulitis, impingement syndrome, etc), rheumatoid arthritis, spondyloarthritis (SpA) and psoriatic arthritis, myalgia, and osteoporosis diagnosed in specialist and inpatient care. We also studied how much covariance between OA and each of the RMDs could be explained by genetics by studying phenotypic correlations in bivariate classical twin models. RESULTS: Any-site OA and hip OA (50% and 64%) were among the most heritable RMDs (as compared with 23% for fibromyalgia [lowest] and 63% for SpA [highest]). The highest phenotypic correlations were between OA (any joint site) and shoulder pain in the same individual (r = 0.33, 95% confidence interval 0.31-0.35), of which 70% (95% confidence interval 52-88) could be explained by shared genetics. The phenotypic correlation between OA and back/neck pain was r = 0.25, with 25% to 75% explained by genetics. Phenotypic correlations between OA and each of the other RMDs were lower (r ~ 0.1 to r ~ 0.2), with inconclusive sources of variation. CONCLUSION: OA has relatively large heritability as compared with other RMDs. The coexistence of OA and shoulder pain, as well as back pain, was common and could often be explained by genetic factors. Findings imply similar etiologies of OA and several pain conditions.

A human meniscus explant model for studying early events in osteoarthritis development by proteomics.

Degenerative meniscus lesions have been associated with both osteoarthritis etiology and its progression. We, therefore, sought to establish a human meniscus ex vivo model to study the meniscal response to cytokine treatment using a proteomics approach. Lateral menisci were obtained from five knee-healthy donors. The meniscal body was cut into vertical slices and further divided into an inner (avascular) and outer region. Explants were either left untreated (controls) or stimulated with cytokines. Medium changes were conducted every 3 days up to Day 21 and liquid chromatography-mass spectrometry was performed at all the time points for the identification and quantification of proteins. Mixed-effect linear regression models were used for statistical analysis to estimate the effect of treatments versus control on protein abundance. Treatment by IL1ß increased release of cytokines such as interleukins, chemokines, and matrix metalloproteinases but a limited catabolic effect in healthy human menisci explants. Further, we observed an increased release of matrix proteins (collagens, integrins, prolargin, tenascin) in response to oncostatin M (OSM) + tumor necrosis factor (TNF) and TNF+interleukin-6 (IL6) + sIL6R treatments, and analysis of semitryptic peptides provided additional evidence of increased catabolic effects in response to these treatments. The induced activation of catabolic processes may play a role in osteoarthritis development.

Characterization of choroid plexus in the preterm rabbit pup following subcutaneous administration of recombinant human IGF-1/IGFBP-3.

Insulin-like growth factor-1 (IGF-1) is essential for normal brain development and regulates essential processes of vascular maturation and stabilization. Importantly, preterm birth is associated with reduced serum levels of IGF-1 as compared to in utero levels. Using a preterm rabbit pup model, we investigated the uptake of systemic recombinant human (rh) IGF-1 in complex with its main binding protein IGF-binding protein 3 (BP-3) to the brain parenchyma via the choroid plexus. Five hours after subcutaneous administration, labeled rhIGF-1/rhIGFBP-3 displayed a widespread presence in the choroid plexus of the lateral and third ventricle, however, to a less degree in the fourth, as well as in the perivascular and subarachnoid space. We found a time-dependent uptake of IGF-1 in cerebrospinal fluid, decreasing with postnatal age, and a translocation of IGF-1 through the choroid plexus. The impact of systemic rhIGF-1/rhIGFBP-3 on IGF-1 receptor activation in the choroid plexus decreased with postnatal age, correlating with IGF-1 uptake in cerebrospinal fluid. In addition, choroid plexus gene expression was observed to increase with postnatal age. Moreover, using choroid plexus in vitro cell cultures, gene expression and protein synthesis were further investigated upon rhIGF-1/rhIGFBP-3 stimulation as compared to rhIGF-1 alone, and found not to be differently altered. Here, we characterize the uptake of systemic rhIGF-1/rhIGFBP-3 to the preterm brain, and show that the interaction between systemic rhIGF-1/rhIGFBP-3 and choroid plexus varies over time.

Naming the untouchable - environmental sequences and niche partitioning as taxonomical evidence in fungi.

Due to their submerged and cryptic lifestyle, the vast majority of fungal species are difficult to observe and describe morphologically, and many remain known to science only from sequences detected in environmental samples. The lack of practices to delimit and name most fungal species is a staggering limitation to communication and interpretation of ecology and evolution in kingdom Fungi. Here, we use environmental sequence data as taxonomical evidence and combine phylogenetic and ecological data to generate and test species hypotheses in the class Archaeorhizomycetes (Taphrinomycotina, Ascomycota). Based on environmental amplicon sequencing from a well-studied Swedish pine forest podzol soil, we generate 68 distinct species hypotheses of Archaeorhizomycetes, of which two correspond to the only described species in the class. Nine of the species hypotheses represent 78% of the sequenced Archaeorhizomycetes community, and are supported by long read data that form the backbone for delimiting species hypothesis based on phylogenetic branch lengths.Soil fungal communities are shaped by environmental filtering and competitive exclusion so that closely related species are less likely to co-occur in a niche if adaptive traits are evolutionarily conserved. In soil profiles, distinct vertical horizons represent a testable niche dimension, and we found significantly differential distribution across samples for a well-supported pair of sister species hypotheses. Based on the combination of phylogenetic and ecological evidence, we identify two novel species for which we provide molecular diagnostics and propose names. While environmental sequences cannot be automatically translated to species, they can be used to generate phylogenetically distinct species hypotheses that can be further tested using sequences as ecological evidence. We conclude that in the case of abundantly and frequently observed species, environmental sequences can support species recognition in the absences of physical specimens, while rare taxa remain uncaptured at our sampling and sequencing intensity.

Proteomic analysis reveals dexamethasone rescues matrix breakdown but not anabolic dysregulation in a cartilage injury model.

OBJECTIVES: In this exploratory study, we used discovery proteomics to follow the release of proteins from bovine knee articular cartilage in response to mechanical injury and cytokine treatment. We also studied the effect of the glucocorticoid Dexamethasone (Dex) on these responses. DESIGN: Bovine cartilage explants were treated with either cytokines alone (10 ng/ml TNFα, 20 ng/ml IL-6, 100 ng/ml sIL-6R), a single compressive mechanical injury, cytokines and injury, or no treatment, and cultured in serum-free DMEM supplemented with 1% ITS for 22 days. All samples were incubated with or without addition of 100 nM Dex. Mass spectrometry and western blot analyses were performed on medium samples for the identification and quantification of released proteins. RESULTS: We identified 500 unique proteins present in all three biological replicates. Many proteins involved in the catabolic response of cartilage degradation had increased release after inflammatory stress. Dex rescued many of these catabolic effects. The release of some proteins involved in anabolic and chondroprotective processes was inconsistent, indicating differential effects on processes that may protect cartilage from injury. Dex restored only a small fraction of these to the control state, while others had their effects exacerbated by Dex exposure. CONCLUSIONS: We identified proteins that were released upon cytokine treatment which could be potential biomarkers of the inflammatory contribution to cartilage degradation. We also demonstrated the imperfect rescue of Dex on the effects of cartilage degradation, with many catabolic factors being reduced, while other anabolic or chondroprotective processes were not.

Proteomic characterization of the normal human medial meniscus body using data-independent acquisition mass spectrometry.

Recent research suggests an important role of the meniscus in the development of knee osteoarthritis. We, therefore, aimed to analyze the proteome of the normal human meniscus body, and specifically to gain new knowledge on global protein expression in the different radial zones. Medial menisci were retrieved from the right knees of 10 human cadaveric donors, from which we cut a 2 mm radial slice from the mid-portion of the meniscal body. This slice was further divided into three zones: inner, middle, and peripheral. Proteins were extracted and prepared for mass spectrometric analysis using data-independent acquisition. We performed subsequent data searches using Spectronaut Pulsar and used fixed-effect linear regression models for statistical analysis. We identified 638 proteins and after statistical analysis, we observed the greatest number of differentially expressed proteins between the inner and peripheral zones (163 proteins) and the peripheral and middle zones (136 proteins), with myocilin being the protein with the largest fold-change in both comparisons. Chondroadherin was one of eight proteins that differed between the inner and middle zones. Functional enrichment analyses showed that the peripheral one-third of the medial meniscus body differed substantially from the two more centrally located zones, which were more similar to each other. This is probably related to the higher content of cells and vascularization in the peripheral zone, whereas the middle and inner zones of the meniscal body appear to be more similar to hyaline cartilage, with high levels of extracellular matrix proteins such as aggrecan and collagen type II.

Global network of computational biology communities: ISCB's Regional Student Groups breaking barriers.

Regional Student Groups (RSGs) of the International Society for Computational Biology Student Council (ISCB-SC) have been instrumental to connect computational biologists globally and to create more awareness about bioinformatics education. This article highlights the initiatives carried out by the RSGs both nationally and internationally to strengthen the present and future of the bioinformatics community. Moreover, we discuss the future directions the organization will take and the challenges to advance further in the ISCB-SC main mission: "Nurture the new generation of computational biologists".