Contaminants in Commercial Preparations of ‘Purified’ Small Leucine-Rich Proteoglycans May Distort Mechanistic Studies

This paper reports the perplexing results that came about because of seriously impure commercially available reagents. Commercial reagents and chemicals are routinely ordered by scientists and are expected to have been rigorously assessed for their purity. Unfortunately, we found this assumption to be risky. Extensive work was carried out within our laboratory using commercially-sourced preparations of the small leucine-rich proteoglycans, decorin and biglycan, to investigate their influence on nerve cell growth. Unusual results compelled us to analyse the composition and purity of both preparations of these proteoglycans using both mass spectrometry and Western blotting, with and without various enzymatic deglycosylations. Commercial ‘decorin’ and ‘biglycan’ were found to contain a mixture of proteoglycans including not only both decorin and biglycan but also fibromodulin and aggrecan. The unexpected effects of ‘decorin’ and ‘biglycan’ on nerve cell growth could be explained by these impurities. Decorin and biglycan contain either chondroitin or dermatan sulphate glycosaminoglycan chains whilst fibromodulin only contains keratan sulphate and the large (>2,500 kDa), highly glycosylated aggrecan, contains both keratan and chondroitin sulphate. The different structure, molecular weights and composition of these impurities significantly affected our work and any conclusions that could be made. These findings beg the question as to whether scientists need to verify the purity of each commercially obtained reagent used in their experiments. The implications of these findings are vast, since the effects of these impurities may already have led to inaccurate conclusions and reports in the literature with concomitant loss of researchers’ funds and time

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Understanding the intra- and extracellular proteins involved in the development of the corticospinal tract (CST) may offer insights into how the pathway could be regenerated following traumatic spinal cord injury. Currently, however, little is known about the proteome of the developing corticospinal system. The present study, therefore, has used quantitative proteomics and bioinformatics to detail the protein profile of the rat CST during its formation in the spinal cord. This analysis identified increased expression of 65 proteins during the early ingrowth of corticospinal axons into the spinal cord, and 36 proteins at the period of heightened CST growth. A majority of these proteins were involved in cellular assembly and organization, with annotations being most highly associated with cytoskeletal organization, microtubule dynamics, neurite outgrowth, and the formation, polymerization and quantity of microtubules. In addition, 22 proteins were more highly expressed within the developing CST in comparison to other developing white matter tracts of the spinal cord of age-matched animals. Of these differentially expressed proteins, only one, stathmin 1 (a protein known to be involved in microtubule dynamics), was both highly enriched in the developing CST and relatively sparse in other developing descending and ascending spinal tracts. Immunohistochemical analyses of the developing rat spinal cord and fetal human brain stem confirmed the enriched pattern of stathmin expression along the developing CST, and in vitro growth assays of rat corticospinal neurons showed a reduced length of neurite processes in response to pharmacological perturbation of stathmin activity. Combined, these findings suggest that stathmin activity may modulate axonal growth during development of the corticospinal projection, and reinforces the notion that microtubule dynamics could play an important role in the generation and regeneration of the CST

Autologous chondrocyte implantation- derived synovial fluids display distinct responder and non-responder proteomic profiles

Background Autologous chondrocyte implantation (ACI) can be used in the treatment of focal cartilage injuries to prevent the onset of osteoarthritis (OA). However, we are yet to understand fully why some individuals do not respond well to this intervention. Identification of a reliable and accurate biomarker panel that can predict which patients are likely to respond well to ACI is needed in order to assign the patient to the most appropriate therapy. This study aimed to compare the baseline and mid-treatment proteomic profiles of synovial fluids (SFs) obtained from responders and non-responders to ACI. Methods SFs were derived from 14 ACI responders (mean Lysholm improvement of 33 (17–54)) and 13 non-responders (mean Lysholm decrease of 14 (4–46)) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Label-free proteome profiling of dynamically compressed SFs was used to identify predictive markers of ACI success or failure and to investigate the biological pathways involved in the clinical response to ACI. Results Only 1 protein displayed a =2.0-fold differential abundance in the preclinical SF of ACI responders versus non-responders. However, there is a marked difference between these two groups with regard to their proteome shift in response to cartilage harvest, with 24 and 92 proteins showing =2.0-fold differential abundance between Stages I and II in responders and non-responders, respectively. Proteomic data has been uploaded to ProteomeXchange (identifier: PXD005220). We have validated two biologically relevant protein changes associated with this response, demonstrating that matrix metalloproteinase 1 was prominently elevated and S100 calcium binding protein A13 was reduced in response to cartilage harvest in non-responders. Conclusions The differential proteomic response to cartilage harvest noted in responders versus non-responders is completely novel. Our analyses suggest several pathways which appear to be altered in non-responders that are worthy of further investigation to elucidate the mechanisms of ACI failure. These protein changes highlight many putative biomarkers that may have potential for prediction of ACI treatment success

The proteome signatures of fibroblasts from patients with severe, intermediate and mild spinal muscular atrophy show limited overlap

Most research to characterise the molecular consequences of spinal muscular atrophy (SMA) have focused on SMA I. Here, proteomic profiling of skin fibroblasts from severe (SMA I), intermediate (SMA II), and mild (SMA III) patients, alongside age-matched controls was conducted using SWATH mass spectrometry analysis. Differentially expressed proteome profiles showed limited overlap across each SMA type, and variability was greatest within SMA II fibroblasts which was not explained by SMN2 copy number. Despite limited proteomic overlap, enriched canonical pathways common to two of three SMA severities with at least one differentially expressed pro-tein from the third included mTOR signaling, regulation of eIF2 and eIF4 signaling, and protein ubiquitination. Network expression clustering analysis identified protein profiles that may dis-criminate or correlate with SMA severity. From these clusters, the differential expression of PYGB (SMA I), RAB3B (SMA II), and IMP1 and STAT1 (SMA III) was verified by western blot. All SMA fibroblasts were transfected with an SMN-enhanced construct but only RAB3B expression in SMA II fibroblasts demonstrated an SMN-dependent response. The diverse proteome profiles and pathways identified here pave the way for studies to determine their utility as biomarkers for patient stratification or monitoring treatment efficacy, and for identification of severity-specific treatments

ACUTE PHASE RESPONSE SIGNALLING IS ALTERED FOLLOWING CARTILAGE HARVEST IN NON-RESPONDERS TO AUTOLOGOUS CHONDROCYTE IMPLANTATION

Background: Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However, we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on the basis of which more of the biology underlying ACI success or failure can be understood. Methods: Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF from ACI responders (mean Lysholm improvement of 33; n = 14) and non-responders (mean Lysholm decrease of 14; n = 13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins in iTRAQ and combined iTRAQ and LF datasets were investigated using pathway and network analyses. Results: iTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that was used to generate interactome networks representing ACI success or failure. Functional pathways that are dysregulated in ACI non-responders were identified, including acute-phase response signalling. Conclusions: Several candidate biomarkers for baseline prediction of ACI outcome were identified. A holistic overview of the SF proteome in responders and non-responders to ACI has been profiled, providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in nonresponders. Keywords: Autologous chondrocyte implantation (ACI), iTRAQ proteomics, Label-free quantitation proteomics, Synovial fluid, Cartilage repair, Complement C1S subcomponent, Matrix metalloproteinase 3, MMP