Proteomic analysis of human osteoarthritis synovial fluid

Background

Osteoarthritis is a chronic musculoskeletal disorder characterized mainly by progressive degradation of the hyaline cartilage. Patients with osteoarthritis often postpone seeking medical help, which results in the diagnosis being made at an advanced stage of cartilage destruction. Sustained efforts are needed to identify specific markers that might help in early diagnosis, monitoring disease progression and in improving therapeutic outcomes. We employed a multipronged proteomic approach, which included multiple fractionation strategies followed by high resolution mass spectrometry analysis to explore the proteome of synovial fluid obtained from osteoarthritis patients. In addition to the total proteome, we also enriched glycoproteins from synovial fluid using lectin affinity chromatography.

Results

We identified 677 proteins from synovial fluid of patients with osteoarthritis of which 545 proteins have not been previously reported. These novel proteins included ADAM-like decysin 1 (ADAMDEC1), alanyl (membrane) aminopeptidase (ANPEP), CD84, fibulin 1 (FBLN1), matrix remodelling associated 5 (MXRA5), secreted phosphoprotein 2 (SPP2) and spondin 2 (SPON2). We identified 300 proteins using lectin affinity chromatography, including the glycoproteins afamin (AFM), attractin (ATRN), fibrillin 1 (FBN1), transferrin (TF), tissue inhibitor of metalloproteinase 1 (TIMP1) and vasorin (VSN). Gene ontology analysis confirmed that a majority of the identified proteins were extracellular and are mostly involved in cell communication and signaling. We also confirmed the expression of ANPEP, dickkopf WNT signaling pathway inhibitor 3 (DKK3) and osteoglycin (OGN) by multiple reaction monitoring (MRM) analysis of osteoarthritis synovial fluid samples.

Conclusions

We present an in-depth analysis of the synovial fluid proteome from patients with osteoarthritis. We believe that the catalog of proteins generated in this study will further enhance our knowledge regarding the pathophysiology of osteoarthritis and should assist in identifying better biomarkers for early diagnosis.     

Membrane stress caused by octanoic acid in Saccharomyces cerevisiae

In order to compete with petroleum-based fuel and chemicals, engineering a robust biocatalyst that can convert renewable feedstocks into biorenewable chemicals, such as carboxylic acids, is increasingly important. However, product toxicity is often problematic. In this study, the toxicity of the carboxylic acids hexanoic, octanoic, and decanoic acid on Saccharomyces cerevisiae was investigated, with a focus on octanoic acid. These compounds are completely inhibitory at concentrations of magnitude 1 mM, and the toxicity increases as chain length increases and as media pH decreases. Transciptome analysis, reconstruction of gene regulatory network, and network component analysis suggested decreased membrane integrity during challenge with octanoic acid. This was confirmed by quantification of dose-dependent and chain length-dependent induction of membrane leakage, though membrane fluidity was not affected. This induction of membrane leakage could be significantly decreased by a period of pre-adaptation, and this pre-adaptation was accompanied by increased oleic acid content in the membrane, significantly increased production of saturated lipids relative to unsaturated lipids, and a significant increase in the average lipid chain length in the membrane. However, during adaptation cell surface hydrophobicity was not altered. The supplementation of oleic acid to the medium not only elevated the tolerance of yeast cells to octanoic acid but also attenuated the membrane leakiness. However, while attempts to mimic the oleic acid supplementation effects through expression of the Trichoplusia ni acyl-CoA Δ9 desaturase OLE1(TniNPVE desaturase) were able to increase the oleic acid content, the magnitude of the increase was not sufficient to reproduce the supplementation effect and increase octanoic acid tolerance. Similarly, introduction of cyclopropanated fatty acids through expression of the Escherichia coli cfa gene was not helpful for tolerance. Thus, we have provided quantitative evidence that carboxylic acids damage the yeast membrane and that manipulation of the lipid content of the membrane can increase tolerance, and possibly production, of these valuable products.     

160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA)

Background  

To infer homology and subsequently gene function, the Smith-Waterman (SW) algorithm is used to find the optimal local alignment between two sequences. When searching sequence databases that may contain hundreds of millions of sequences, this algorithm becomes computationally expensive.     

A third variant of glucose phosphate isomerase in pigs

A new variant of glucose phosphate isomerase (GPI), also known as phosphohexose isomerase (PHI), was detected in a primitive pig population.     

Microbial carbon metabolism associated with electrogenic sulphur oxidation in coastal sediments

Recently, a novel electrogenic type of sulphur oxidation was documented in marine sediments, whereby filamentous cable bacteria (Desulfobulbaceae) are mediating electron transport over cm-scale distances. These cable bacteria are capable of developing an extensive network within days, implying a highly efficient carbon acquisition strategy. Presently, the carbon metabolism of cable bacteria is unknown, and hence we adopted a multidisciplinary approach to study the carbon substrate utilization of both cable bacteria and associated microbial community in sediment incubations. Fluorescence in situ hybridization showed rapid downward growth of cable bacteria, concomitant with high rates of electrogenic sulphur oxidation, as quantified by microelectrode profiling. We studied heterotrophy and autotrophy by following ¹³C-propionate and -bicarbonate incorporation into bacterial fatty acids. This biomarker analysis showed that propionate uptake was limited to fatty acid signatures typical for the genus Desulfobulbus. The nanoscale secondary ion mass spectrometry analysis confirmed heterotrophic rather than autotrophic growth of cable bacteria. Still, high bicarbonate uptake was observed in concert with the development of cable bacteria. Clone libraries of 16S complementary DNA showed numerous sequences associated to chemoautotrophic sulphur-oxidizing Epsilon- and Gammaproteobacteria, whereas ¹³C-bicarbonate biomarker labelling suggested that these sulphur-oxidizing bacteria were active far below the oxygen penetration. A targeted manipulation experiment demonstrated that chemoautotrophic carbon fixation was tightly linked to the heterotrophic activity of the cable bacteria down to cm depth. Overall, the results suggest that electrogenic sulphur oxidation is performed by a microbial consortium, consisting of chemoorganotrophic cable bacteria and chemolithoautotrophic Epsilon- and Gammaproteobacteria. The metabolic linkage between these two groups is presently unknown and needs further study.     

Application of a generalized MWC model for the mathematical simulation of metabolic pathways regulated by allosteric enzymes

In our effort to elucidate the systems biology of the model organism, Escherichia coli, we have developed a mathematical model that simulates the allosteric regulation for threonine biosynthesis pathway starting from aspartate. To achieve this goal, we used kMech, a Cellerator language extension that describes enzyme mechanisms for the mathematical modeling of metabolic pathways. These mechanisms are converted by Cellerator into ordinary differential equations (ODEs) solvable by Mathematica. In this paper, we describe a more flexible model in Cellerator, which generalizes the Monod, Wyman, Changeux (MWC) model for enzyme allosteric regulation to allow for multiple substrate, activator and inhibitor binding sites. Furthermore, we have developed a model that describes the behavior of the bifunctional allosteric enzyme aspartate kinase I-homoserine dehydrogenase I (AKI-HDHI). This model predicts the partition of enzyme activities in the steady state which paves the way for a more generalized prediction of the behavior of bifunctional enzymes.