A QUANTITATIVE PROTEOMICS STUDY OF THE ADDITIVE EFFECT OF INFLAMMATORY CYTOKINES AND INJURIOUS COMPRESSION ON CARTILAGE DAMAGE JMASSACHUSniTS INSTITUTE OF TEcr-, Krishnakumar Swaminathan JUL 142011 B.Tech Biotechnology Indian Institute of Technology Madras, 2006 ARCHIVES Submitted to the Department of Biological Engineering in Partial Fulfillment of the Requirements for the Degree of Masters of Science in Biological Engineering at the Massachusetts Institute of Technology February 2011 © 2011 Massachusetts Institute of Technology All rights reserved V( Signature of Author Krishnakumar Swaminathan Department of Biological Engineering - // - .* Certified by -r - 1 4r Alan J. qrdznsky, th7TAdvs r Professor of Biological, Electrical and Mechanical Engi ~g /I I Accepted by Forest M. White, Graduate Program Committee Department of Biological Engineering ABSTRACT Objectives: 1) To perform a quantitative comparison of proteins released to media on combination with cytokine (IL-1p or TNF-a) and Injury as compared to either treatment alone, and to thus identify proteins which may be responsible for the synergism seen between cytokine and injury in causing catabolism of cartilage in vitro. 2) To identify proteins which contribute most to some commonly observed phenotypes on treatment of cartilage with cytokine or injury or both. Methods : Cartilage explants from calves were treated with (i)IL-1 (10 ng/ml), (ii)TNF- a (100 ng/ml), (iii)Injurious compression (50% strain at 100%/sec) and IL-1p (10 ng/ml) or (iv)Injurious compression (50% strain at 100%/sec) and TNF-a(10 ng/ml), cultured for 5 days post treatment, and the pooled media collected, labeled with one of four iTRAQ labels and subjected to nano-2D-LC/MS/MS on a quadrupole time of flight instrument. Peptides were identified and quantified using Protein PilotTM, and MATLAB scripts used to obtain protein ratios. These results were analyzed using different statistical techniques. Data from two iTRAQ experiments were combined to generate data for all possible injury and cytokine treatment conditions, and proteins on which injury and cytokines acted synergistically identified. PLSR analysis was performed using Unscrambler@X software with the combined data set to determine which proteins are most relevant to some observed phenotypes. The phenotypes chosen were sGAG released to media in 5 days post treatment, proline and sulfate incorporation rates on day 6 post treatment, and nitrite accumulation in media in 5 days post treatment Results and Discussion: TNF-a+injury and IL-1p +injury treatment conditions show a very high correlation with each other. Most cytosolic, ER lumen and nuclear protein levels are highly elevated with both cytokine+injury conditions, while ECM proteins are either highly down regulated or marginally elevated. Many collagen telopeptides are down regulated, possibly indicating reduced anabolism. However, attempts at repair exist, as shown by increased levels of TGF- and activin A, and reduced levels of LTBP1. Also, biglycan and lumican, SLRPs known to be involved in early development are significantly increased, possibly indicating repair attempts. Other SLRPs such as PRELP and chondroadherin are also highly elevated, with one or both injury+cytokine treatments. While MMPs are mildly down regulated or remain the same, ADAMTS1 increases with TNF-a+injury, indicating increased catabolism. Among ECM structural proteins, COMP shows high down regulation with TNF-a+injury, possibly due to reduced synthesis. Proenkephalin, a signaling molecule possibly involved in tissue/repair and apoptosis, AIMPI, a multifunctional proapoptotic, inflammatory and pro-repair cytokine and Annexin A5, a protein indicating mineralization and apoptosis are all highly elevated with cytokine+injury indicating heightened apoptosis and/or repair. When results of two 4-plex iTRAQ experiments are combined to obtain data for all possible combinations of injury and cytokine, we again find a very high correlation between TNF-a+injury and IL-1 +injury (-95%), slightly higher than the correlation between TNF-c alone and IL-1$ alone (-90%), and much higher than the correlation of either cytokine+injury condition with cytokine alone (-70%) or injury alone (-75%). This shows that IL-1P and TNF-a in combination with injury act through very similar pathways in chondrocytes to produce their effect on cartilage tissue. TNF-a and injury were seen to act synergistically in a positive fashion on aggrecan, CILP-2, COL6A3 and histone H4, and in a negative fashion on SPARC and IGFBP7, suggesting that these proteins may be involved in causing synergism between injury and cytokine in releasing sGAG to the media. A PLSR analysis shows that SPARC and IGFBP7 project close to proline and sulfate incorporation, and far away from sGAG, indicating that SPARC and IGFBP7 may be proteins involved in anabolism. The highest phenotype-protein positive correlations obtained using PLSR are sGAG with Perlecan, SAA3, Complement factor B, CILP-2 and pleiotropin, indicating that all these 5 proteins are associated strongly with catabolism and can serve as markers of catabolism. The correlation of inflammatory proteins SAA3 and complement factor B with sGAG indicates the role of inflammation with catabolism. Conclusion: The combination of injury and cytokine affects tissue differently at a molecular level as compared to either chemical or mechanical stresses alone. Increased catabolism and increased attempts at tissue repair are observed due to a combination of injury and cytokine, and a combination of injury and cytokine may thus serve as a useful model to study OA in vitro. ACKNOWLEDGEMENTS I am grateful to the Biological Engineering Department and MIT for giving me the best of education, and teaching me what true scientific research and thinking is all about. My sincere thanks to Linda Bragman and Han-Hwa Hung for help in many small ways and to Dalia Fares for taking care of administrative issues. Dr. Anna Stevens performed the cartilage explantation experiments, and Dr.Ramesh Indrakanti ran the Mass Spec, my grateful thanks to them. My heartfelt thanks to Anna, who guided me into this work, and was always there for any questions I had (and there were many!). And most important of all, I am indebted to Prof. Alan Grodzinsky who stood by me through thick and thin, and was a constant source of motivation and inspiration. TABLE OF CONTENTS A bstract........................................................................... .. 2 Acknowledgements................................................................4 L ist of Figures.........................................................................7 L ist of T ables........................................................................ 8 Chapter 1: Introduction .............................................................. 9 1.1 Arthritis - An Overview......................................9 1.2 Osteoarthritis : Pathology, Symptoms and Treatment........9 1.3 A rticular Cartilage...............................................10 1.4 Cartilage Components........................................10 1.5 Post-traumatic GA.............................................18 1.6 Cytokines in GA ................................................. 20 1.7 In vitro models combining injury and cytokine..............23 1.8 Thesis Objectives.............................................23 Chapter 2: M ethods.............................................................. 25 2.1 O verview ....................................................... 25 2.2 Cartilage explantation, Mechanical Injury and Cytokine T reatm ent..............................................................25 2.3 sGAG removal, trypsin digestion and iTRAQ labeling.....26 2.4 SCX chromatography and LC/MS/MS.....................28 2.5 Data Analysis..................................................29 2.6 Comparison of biological duplicates and final protein list com pilation......................................................... 31 2.7 Global proteomic analysis and clustering..................31 2.8 Merging data between two iTRAQ experiments............32 2.9 Finding proteins on which injury and cytokines act synergistically.........................................................33 2.10 Partial Least Square Regression (PLSR).................33 Chapter 3: R esults............................................................. .. 35 3.1 Reproducibility between biological replicates...............35 3.2 Global proteomic analysis...................................36 3.3 Effect of combination of cytokine and injury on specific p rotein s................................................................37 3.4 Effect of combination of injury and cytokine as opposed to either treatment alone.............................................40 3.5 Partial Least Square Regression (PLSR) between protein ratios and phenotypes................................................43 Chapter 4: Discussion 4.1 Methodology for correcting for multiple comparisons - The Benjamini Hochberg Procedure.................................63 4.2 Variation between biological replicates....................63 4.3 A global proteomic analysis of the effect of cytokine+injury.......................................................64 4.4 Effect of cytokine+injury on specific protein classes.......66 4.5 Effect of combination of cytokine and injury as opposed to either treatment alone.............................................86 4.6 Partial Least Square Regression (PLSR) Analysis..........92