Skip to main content

Advertisement

Log in

Quantification of Inflammasome Adaptor Protein ASC in Biological Samples by Multiple-Reaction Monitoring Mass Spectrometry

  • ORIGINAL ARTICLE
  • Published:
Inflammation Aims and scope Submit manuscript

Abstract

Inflammation is an integral component of many diseases, including chronic kidney disease (CKD). ASC (apoptosis-associated speck-like protein containing CARD, also PYCARD) is the key inflammasome adaptor protein in the innate immune response. Since ASC specks, a macromolecular condensate of ASC protein, can be released by inflammasome-activated cells into the extracellular space to amplify inflammatory responses, the ASC protein could be an important biomarker in diagnostic applications. Herein, we describe the development and validation of a multiple reaction monitoring mass spectrometry (MRM-MS) assay for the accurate quantification of ASC in human biospecimens. Limits of detection and quantification for the signature DLLLQALR peptide (used as surrogate for the target ASC protein) were determined by the method of standard addition using synthetic isotope-labeled internal standard (SIS) peptide and urine matrix from a healthy donor (LOQ was 8.25 pM, with a ~ 1000-fold linear range). We further quantified ASC in the urine of CKD patients (8.4 ± 1.3 ng ASC/ml urine, n = 13). ASC was positively correlated with proteinuria and urinary IL-18 in CKD samples but not with urinary creatinine. Unfortunately, the ASC protein is susceptible to degradation, and patient urine that was thawed and refrozen lost 85% of the ASC signal. In summary, the MRM-MS assay provides a robust means to quantify ASC in biological samples, including clinical biospecimens; however, sample collection and storage conditions will have a critical impact on assay reliability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

AKI:

acute kidney injury

AMBIC:

ammonium bicarbonate

ASC:

apoptosis-associated speck-like protein containing a CARD

CKD:

chronic kidney disease

CoV:

coefficient of variance

Cr:

creatinine;

DTT:

dithiothreitol

IL:

interleukin

LOD:

lower limit of detection

LOQ:

lower limit of quantification

MS:

mass spectrometry

MRM:

multiple reaction monitoring

SIS:

stable isotope-labeled internal standard

SRM:

selected reaction monitoring

References

  1. Addona, T.A., S.E. Abbatiello, B. Schilling, S.J. Skates, D.R. Mani, D.M. Bunk, C.H. Spiegelman, L.J. Zimmerman, A.J.L. Ham, H. Keshishian, S.C. Hall, S. Allen, R.K. Blackman, C.H. Borchers, C. Buck, H.L. Cardasis, M.P. Cusack, N.G. Dodder, B.W. Gibson, J.M. Held, T. Hiltke, A. Jackson, E.B. Johansen, C.R. Kinsinger, J. Li, M. Mesri, T.A. Neubert, R.K. Niles, T.C. Pulsipher, D. Ransohoff, H. Rodriguez, P.A. Rudnick, D. Smith, D.L. Tabb, T.J. Tegeler, A.M. Variyath, L.J. Vega-Montoto, Å. Wahlander, S. Waldemarson, M. Wang, J.R. Whiteaker, L. Zhao, N.L. Anderson, S.J. Fisher, D.C. Liebler, A.G. Paulovich, F.E. Regnier, P. Tempst, and S.A. Carr. 2009. Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma. Nature Biotechnology 27 (7): 633–641. https://doi.org/10.1038/nbt.1546.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Anders, H.J., and D.A. Muruve. 2011. The inflammasomes in kidney disease. J Am Soc Nephrol 22 (6): 1007–1018. https://doi.org/10.1681/ASN.2010080798.

    Article  PubMed  CAS  Google Scholar 

  3. Armbruster, D.A., and T. Pry. 2008. Limit of blank, limit of detection and limit of quantitation. Clinical Biochemist Reviews 29 (Suppl 1): S49–S52.

    Google Scholar 

  4. Auer, P.L., A.P. Reiner, G. Wang, H.M. Kang, G.R. Abecasis, D. Altshuler, M.J. Bamshad, D.A. Nickerson, R.P. Tracy, S.S. Rich, NHLBI GO Exome Sequencing Project, and S.M. Leal. 2016. Guidelines for large-scale sequence-based complex trait association studies: lessons learned from the NHLBI exome sequencing project. American Journal of Human Genetics 99 (4): 791–801. https://doi.org/10.1016/j.ajhg.2016.08.012.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Boja, E.S., and H. Rodriguez. 2012. Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins. Proteomics 12 (8): 1093–1110. https://doi.org/10.1002/pmic.201100387.

    Article  PubMed  CAS  Google Scholar 

  6. Bracey, N.A., P.L. Beck, D.A. Muruve, S.A. Hirota, J. Guo, H. Jabagi, J.R. Wright Jr., et al. 2013. The Nlrp3 inflammasome promotes myocardial dysfunction in structural cardiomyopathy through interleukin-1beta. Experimental Physiology 98 (2): 462–472. https://doi.org/10.1113/expphysiol.2012.068338.

    Article  PubMed  CAS  Google Scholar 

  7. Bryan, N.B., A. Dorfleutner, S.J. Kramer, C. Yun, Y. Rojanasakul, and C. Stehlik. 2010. Differential splicing of the apoptosis-associated speck like protein containing a caspase recruitment domain (ASC) regulates inflammasomes. J Inflamm (Lond) 7: 23. https://doi.org/10.1186/1476-9255-7-23.

    Article  CAS  Google Scholar 

  8. Carr, S.A., S.E. Abbatiello, B.L. Ackermann, C. Borchers, B. Domon, E.W. Deutsch, R.P. Grant, A.N. Hoofnagle, R. Hüttenhain, J.M. Koomen, D.C. Liebler, T. Liu, B. MacLean, D.R. Mani, E. Mansfield, H. Neubert, A.G. Paulovich, L. Reiter, O. Vitek, R. Aebersold, L. Anderson, R. Bethem, J. Blonder, E. Boja, J. Botelho, M. Boyne, R.A. Bradshaw, A.L. Burlingame, D. Chan, H. Keshishian, E. Kuhn, C. Kinsinger, J.S.H. Lee, S.W. Lee, R. Moritz, J. Oses-Prieto, N. Rifai, J. Ritchie, H. Rodriguez, P.R. Srinivas, R.R. Townsend, J. van Eyk, G. Whiteley, A. Wiita, and S. Weintraub. 2014. Targeted peptide measurements in biology and medicine: best practices for mass spectrometry-based assay development using a fit-for-purpose approach. Molecular & Cellular Proteomics 13 (3): 907–917. https://doi.org/10.1074/mcp.M113.036095.

    Article  CAS  Google Scholar 

  9. Chen, Y.T., H.W. Chen, D. Domanski, D.S. Smith, K.H. Liang, C.C. Wu, C.L. Chen, T. Chung, M.C. Chen, Y.S. Chang, C.E. Parker, C.H. Borchers, and J.S. Yu. 2012. Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers. Journal of Proteomics 75 (12): 3529–3545. https://doi.org/10.1016/j.jprot.2011.12.031.

    Article  PubMed  CAS  Google Scholar 

  10. Chun, J., H. Chung, X. Wang, R. Barry, Z.M. Taheri, J.M. Platnich, S.B. Ahmed, K. Trpkov, B. Hemmelgarn, H. Benediktsson, M.T. James, and D.A. Muruve. 2016. NLRP3 localizes to the tubular epithelium in human kidney and correlates with outcome in IgA nephropathy. Scientific Reports 6: 24667. https://doi.org/10.1038/srep24667.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Chung, I.C., C.N. OuYang, S.N. Yuan, H.P. Li, J.T. Chen, H.R. Shieh, Y.J. Chen, D.M. Ojcius, C.L. Chu, J.S. Yu, Y.S. Chang, and L.C. Chen. 2016. Pyk2 activates the NLRP3 inflammasome by directly phosphorylating ASC and contributes to inflammasome-dependent peritonitis. Scientific Reports 6: 36214. https://doi.org/10.1038/srep36214.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Collino, M., M. Rogazzo, A. Pini, E. Benetti, A.C. Rosa, F. Chiazza, R. Fantozzi, D. Bani, and E. Masini. 2013. Acute treatment with relaxin protects the kidney against ischaemia/reperfusion injury. Journal of Cellular and Molecular Medicine 17 (11): 1494–1505. https://doi.org/10.1111/jcmm.12120.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Craig, R., J.C. Cortens, D. Fenyo, and R.C. Beavis. 2006. Using annotated peptide mass spectrum libraries for protein identification. Journal of Proteome Research 5 (8): 1843–1849. https://doi.org/10.1021/pr0602085.

    Article  PubMed  CAS  Google Scholar 

  14. Craig, R., J.P. Cortens, and R.C. Beavis. 2004. Open source system for analyzing, validating, and storing protein identification data. Journal of Proteome Research 3 (6): 1234–1242. https://doi.org/10.1021/pr049882h.

    Article  PubMed  CAS  Google Scholar 

  15. Craig, R., J.P. Cortens, and R.C. Beavis. 2005. The use of proteotypic peptide libraries for protein identification. Rapid Communications in Mass Spectrometry 19 (13): 1844–1850. https://doi.org/10.1002/rcm.1992.

    Article  PubMed  CAS  Google Scholar 

  16. Ebhardt, H.A., A. Root, C. Sander, and R. Aebersold. 2015. Applications of targeted proteomics in systems biology and translational medicine. Proteomics 15 (18): 3193–3208. https://doi.org/10.1002/pmic.201500004.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Franklin, B.S., L. Bossaller, D. De Nardo, J.M. Ratter, A. Stutz, G. Engels, C. Brenker, et al. 2014. The adaptor ASC has extracellular and ‘prionoid’ activities that propagate inflammation. Nature Immunology 15 (8): 727–737. https://doi.org/10.1038/ni.2913.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Franklin, B.S., E. Latz, and F.I. Schmidt. 2018. The intra- and extracellular functions of ASC specks. Immunological Reviews 281 (1): 74–87. https://doi.org/10.1111/imr.12611.

    Article  PubMed  CAS  Google Scholar 

  19. Gillette, M.A., and S.A. Carr. 2013. Quantitative analysis of peptides and proteins in biomedicine by targeted mass spectrometry. Nature Methods 10 (1): 28–34. https://doi.org/10.1038/nmeth.2309.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Gomez, H., C. Ince, D. De Backer, P. Pickkers, D. Payen, J. Hotchkiss, and J.A. Kellum. 2014. A unified theory of sepsis-induced acute kidney injury: inflammation, microcirculatory dysfunction, bioenergetics, and the tubular cell adaptation to injury. Shock 41 (1): 3–11. https://doi.org/10.1097/SHK.0000000000000052.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Guo, H., J.B. Callaway, and J.P. Ting. 2015. Inflammasomes: mechanism of action, role in disease, and therapeutics. Nature Medicine 21 (7): 677–687. https://doi.org/10.1038/nm.3893.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Hara, H., K. Tsuchiya, I. Kawamura, R. Fang, E. Hernandez-Cuellar, Y. Shen, J. Mizuguchi, E. Schweighoffer, V. Tybulewicz, and M. Mitsuyama. 2013. Phosphorylation of the adaptor ASC acts as a molecular switch that controls the formation of speck-like aggregates and inflammasome activity. Nature Immunology 14 (12): 1247–1255. https://doi.org/10.1038/ni.2749.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. James, M.T., M. Tonelli, and Network Alberta Kidney Disease. 2011. Financial aspects of renal replacement therapy in acute kidney injury. Seminars in Dialysis 24 (2): 215–219. https://doi.org/10.1111/j.1525-139X.2011.00836.x.

    Article  PubMed  Google Scholar 

  24. Keshishian, H., T. Addona, M. Burgess, D.R. Mani, X. Shi, E. Kuhn, M.S. Sabatine, R.E. Gerszten, and S.A. Carr. 2009. Quantification of cardiovascular biomarkers in patient plasma by targeted mass spectrometry and stable isotope dilution. Molecular & Cellular Proteomics 8 (10): 2339–2349. https://doi.org/10.1074/mcp.M900140-MCP200.

    Article  CAS  Google Scholar 

  25. Komada, T., H. Chung, A. Lau, J.M. Platnich, P.L. Beck, H. Benediktsson, H.J. Duff, C.N. Jenne, and D.A. Muruve. 2018. Macrophage uptake of necrotic cell DNA activates the AIM2 inflammasome to regulate a proinflammatory phenotype in CKD. J Am Soc Nephrol. 29: 1165–1181. https://doi.org/10.1681/ASN.2017080863.

    Article  PubMed  Google Scholar 

  26. Komada, T., F. Usui, A. Kawashima, H. Kimura, T. Karasawa, Y. Inoue, M. Kobayashi, Y. Mizushina, T. Kasahara, S.’. Taniguchi, S. Muto, D. Nagata, and M. Takahashi. 2015. Role of NLRP3 inflammasomes for rhabdomyolysis-induced acute kidney injury. Scientific Reports 5: 10901. https://doi.org/10.1038/srep10901.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Lange, V., P. Picotti, B. Domon, and R. Aebersold. 2008. Selected reaction monitoring for quantitative proteomics: a tutorial. Molecular Systems Biology 4: 222. https://doi.org/10.1038/msb.2008.61.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Latz, E., T.S. Xiao, and A. Stutz. 2013. Activation and regulation of the inflammasomes. Nature Reviews. Immunology 13 (6): 397–411. https://doi.org/10.1038/nri3452.

    Article  PubMed  CAS  Google Scholar 

  29. Lau, A., H. Chung, T. Komada, J. Platnich, C. Sandall, S. Choudhury, J. Chun, V. Naumenko, B. Surewaard, M.T. Nelson, P.L. Beck, H. Benediktsson, A. Jevnikar, S. Snelgrove, M. Hickey, D. Senger, M.T. James, J.A. MacDonald, P. Kubes. C.N. Jenne, and D.A. Muruve. 2018. Immune surveillance by renal phagocytes and tubular dipeptidase-1 are essential for contrast-induced acute kidney injury. J Clin Inv (In press).

  30. Lek, M., K.J. Karczewski, E.V. Minikel, K.E. Samocha, E. Banks, T. Fennell, A.H. O'Donnell-Luria, et al. 2016. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536 (7616): 285–291. https://doi.org/10.1038/nature19057.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Lin, Y.C., D.Y. Huang, J.S. Wang, Y.L. Lin, S.L. Hsieh, K.C. Huang, and W.W. Lin. 2015. Syk is involved in NLRP3 inflammasome-mediated caspase-1 activation through adaptor ASC phosphorylation and enhanced oligomerization. Journal of Leukocyte Biology 97 (5): 825–835. https://doi.org/10.1189/jlb.3HI0814-371RR.

    Article  PubMed  CAS  Google Scholar 

  32. Lin, Y., H. Lin, Z. Liu, K. Wang, and Y. Yan. 2014. Improvement of a sample preparation method assisted by sodium deoxycholate for mass-spectrometry-based shotgun membrane proteomics. Journal of Separation Science 37 (22): 3321–3329. https://doi.org/10.1002/jssc.201400569.

    Article  PubMed  CAS  Google Scholar 

  33. Liu, X., S.J. Valentine, M.D. Plasencia, S. Trimpin, S. Naylor, and D.E. Clemmer. 2007. Mapping the human plasma proteome by SCX-LC-IMS-MS. Journal of the American Society for Mass Spectrometry 18 (7): 1249–1264. https://doi.org/10.1016/j.jasms.2007.04.012.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. MacLean, B., D.M. Tomazela, N. Shulman, M. Chambers, G.L. Finney, B. Frewen, R. Kern, D.L. Tabb, D.C. Liebler, and M.J. MacCoss. 2010. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26 (7): 966–968. https://doi.org/10.1093/bioinformatics/btq054.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Malhotra, R., and E.D. Siew. 2017. Biomarkers for the early detection and prognosis of acute kidney injury. Clinical Journal of the American Society of Nephrology 12 (1): 149–173. https://doi.org/10.2215/CJN.01300216.

    Article  PubMed  CAS  Google Scholar 

  36. Martin, B.N., C. Wang, J. Willette-Brown, T. Herjan, M.F. Gulen, H. Zhou, K. Bulek, L. Franchi, T. Sato, E.S. Alnemri, G. Narla, X.P. Zhong, J. Thomas, D. Klinman, K.A. Fitzgerald, M. Karin, G. Nuñez, G. Dubyak, Y. Hu, and X. Li. 2014. IKKalpha negatively regulates ASC-dependent inflammasome activation. Nature Communications 5: 4977. https://doi.org/10.1038/ncomms5977.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Martinon, F., K. Burns, and J. Tschopp. 2002. The inflammasome: a molecular platform triggering activation of inflammatory caspases and processing of proIL-beta. Mol Cell 10 (2): 417–426. https://doi.org/10.1016/S1097-2765(02)00599-3.

    Article  PubMed  CAS  Google Scholar 

  38. Mason, D.R., P.L. Beck, and D.A. Muruve. 2012. Nucleotide-binding oligomerization domain-like receptors and inflammasomes in the pathogenesis of non-microbial inflammation and diseases. Journal of Innate Immunity 4 (1): 16–30. https://doi.org/10.1159/000334247.

    Article  PubMed  CAS  Google Scholar 

  39. Mischak, H., C. Delles, A. Vlahou, and R. Vanholder. 2015. Proteomic biomarkers in kidney disease: issues in development and implementation. Nature Reviews. Nephrology 11 (4): 221–232. https://doi.org/10.1038/nrneph.2014.247.

    Article  PubMed  CAS  Google Scholar 

  40. Muruve, D.A., M.C. Mann, K. Chapman, J.F. Wong, P. Ravani, S.A. Page, and H. Benediktsson. 2017. The biobank for the molecular classification of kidney disease: research translation and precision medicine in nephrology. BMC Nephrology 18 (1): 252. https://doi.org/10.1186/s12882-017-0669-4.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Parikh, C.R., I. Butrymowicz, A. Yu, V.M. Chinchilli, M. Park, C.Y. Hsu, W.B. Reeves, P. Devarajan, P.L. Kimmel, E.D. Siew, K.D. Liu, and ASSESS-AKI Study Investigators. 2014. Urine stability studies for novel biomarkers of acute kidney injury. American Journal of Kidney Diseases 63 (4): 567–572. https://doi.org/10.1053/j.ajkd.2013.09.013.

    Article  PubMed  CAS  Google Scholar 

  42. Percy, A.J., J. Yang, D.B. Hardie, A.G. Chambers, J. Tamura-Wells, and C.H. Borchers. 2015. Precise quantitation of 136 urinary proteins by LC/MRM-MS using stable isotope labeled peptides as internal standards for biomarker discovery and/or verification studies. Methods 81: 24–33. https://doi.org/10.1016/j.ymeth.2015.04.001.

    Article  PubMed  CAS  Google Scholar 

  43. Pino, L.K., B.C. Searle, J.G. Bollinger, B. Nunn, B. MacLean, and M.J. MacCoss. 2017. The skyline ecosystem: informatics for quantitative mass spectrometry proteomics. Mass Spectrometry Reviews. https://doi.org/10.1002/mas.21540.

  44. Rifai, N., M.A. Gillette, and S.A. Carr. 2006. Protein biomarker discovery and validation: the long and uncertain path to clinical utility. Nature Biotechnology 24 (8): 971–983. https://doi.org/10.1038/nbt1235.

    Article  PubMed  CAS  Google Scholar 

  45. Romanovsky, A., C. Morgan, and S.M. Bagshaw. 2014. Pathophysiology and management of septic acute kidney injury. Pediatric Nephrology 29 (1): 1–12. https://doi.org/10.1007/s00467-013-2427-6.

    Article  PubMed  Google Scholar 

  46. Rost, H., L. Malmstrom, and R. Aebersold. 2012. A computational tool to detect and avoid redundancy in selected reaction monitoring. Molecular & Cellular Proteomics 11 (8): 540–549. https://doi.org/10.1074/mcp.M111.013045.

    Article  CAS  Google Scholar 

  47. Rowczenio, D.M., S. Pathak, J.I. Arostegui, A. Mensa-Vilaro, E. Omoyinmi, P. Brogan, D. Lipsker, T. Scambler, R. Owen, H. Trojer, A. Baginska, J.D. Gillmore, A.D. Wechalekar, T. Lane, R. Williams, T. Youngstein, P.N. Hawkins, S. Savic, and H.J. Lachmann. 2017. Molecular genetic investigation, clinical features and response to treatment in 21 patients with Schnitzler’s syndrome. Blood 131: 974–981. https://doi.org/10.1182/blood-2017-10-810366.

    Article  PubMed  CAS  Google Scholar 

  48. Schrezenmeier, E.V., J. Barasch, K. Budde, T. Westhoff, and K.M. Schmidt-Ott. 2017. Biomarkers in acute kidney injury—pathophysiological basis and clinical performance. Acta Physiologica (Oxford, England) 219 (3): 554–572. https://doi.org/10.1111/apha.12764.

    Article  CAS  Google Scholar 

  49. Schuh, M.P., E. Nehus, Q. Ma, C. Haffner, M. Bennett, C.D. Krawczeski, and P. Devarajan. 2016. Long-term stability of urinary biomarkers of acute kidney injury in children. American Journal of Kidney Diseases 67 (1): 56–61. https://doi.org/10.1053/j.ajkd.2015.04.040.

    Article  PubMed  CAS  Google Scholar 

  50. Shum, H.P., W.W. Yan, and T.M. Chan. 2016. Recent knowledge on the pathophysiology of septic acute kidney injury: a narrative review. Journal of Critical Care 31 (1): 82–89. https://doi.org/10.1016/j.jcrc.2015.09.017.

    Article  PubMed  CAS  Google Scholar 

  51. Solini, A., S. Menini, C. Rossi, C. Ricci, E. Santini, C. Blasetti Fantauzzi, C. Iacobini, and G. Pugliese. 2013. The purinergic 2X7 receptor participates in renal inflammation and injury induced by high-fat diet: possible role of NLRP3 inflammasome activation. The Journal of Pathology 231 (3): 342–353. https://doi.org/10.1002/path.4237.

    Article  PubMed  CAS  Google Scholar 

  52. Tao, W.A., and R. Aebersold. 2003. Advances in quantitative proteomics via stable isotope tagging and mass spectrometry. Current Opinion in Biotechnology 14 (1): 110–118. https://doi.org/10.1016/S0958-1669(02)00018-6.

    Article  PubMed  CAS  Google Scholar 

  53. Tonelli, M., N. Wiebe, M. T. James, S. W. Klarenbach, B. J. Manns, P. Ravani, G. F. M. Strippoli, B. R. Hemmelgarn, and Network Alberta Kidney Disease. 2018. A population-based cohort study defines prognoses in severe chronic kidney disease. Kidney International doi:10.1016/j.kint.2017.12.013.

  54. Uhlen, M., L. Fagerberg, B.M. Hallstrom, C. Lindskog, P. Oksvold, A. Mardinoglu, A. Sivertsson, C. Kampf, E. Sjostedt, A. Asplund, I. Olsson, K. Edlund, E. Lundberg, S. Navani, C.A.K. Szigyarto, J. Odeberg, D. Djureinovic, J.O. Takanen, S. Hober, T. Alm, P.H. Edqvist, H. Berling, H. Tegel, J. Mulder, J. Rockberg, P. Nilsson, J.M. Schwenk, M. Hamsten, K. von Feilitzen, M. Forsberg, L. Persson, F. Johansson, M. Zwahlen, G. von Heijne, J. Nielsen, and F. Ponten. 2015. Proteomics. Tissue-based map of the human proteome. Science 347 (6220): 1260419. https://doi.org/10.1126/science.1260419.

    Article  PubMed  Google Scholar 

  55. Umbro, I., G. Gentile, F. Tinti, P. Muiesan, and A.P. Mitterhofer. 2016. Recent advances in pathophysiology and biomarkers of sepsis-induced acute kidney injury. The Journal of Infection 72 (2): 131–142. https://doi.org/10.1016/j.jinf.2015.11.008.

    Article  PubMed  Google Scholar 

  56. Vajjhala, P.R., T. Ve, A. Bentham, K.J. Stacey, and B. Kobe. 2017. The molecular mechanisms of signaling by cooperative assembly formation in innate immunity pathways. Molecular Immunology 86: 23–37. https://doi.org/10.1016/j.molimm.2017.02.012.

    Article  PubMed  CAS  Google Scholar 

  57. Vilaysane, A., J. Chun, M.E. Seamone, W. Wang, R. Chin, S. Hirota, Y. Li, S.A. Clark, J. Tschopp, K. Trpkov, B.R. Hemmelgarn, P.L. Beck, and D.A. Muruve. 2010. The NLRP3 inflammasome promotes renal inflammation and contributes to CKD. J Am Soc Nephrol 21 (10): 1732–1744. https://doi.org/10.1681/ASN.2010020143.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Wu, Q., X.L. Wang, Q. Yu, H. Pan, X.S. Zhang, Q.R. Zhang, H.D. Wang, and X. Zhang. 2016. Inflammasome proteins in cerebrospinal fluid of patients with subarachnoid hemorrhage are biomarkers of early brain injury and functional outcome. World Neurosurgery 94: 472–479. https://doi.org/10.1016/j.wneu.2016.07.039.

    Article  PubMed  Google Scholar 

  59. Yang, J., Z. Liu, and T.S. Xiao. 2017. Post-translational regulation of inflammasomes. Cellular & Molecular Immunology 14 (1): 65–79. https://doi.org/10.1038/cmi.2016.29.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors acknowledge Jaye Platnich and Jae Hyun Chung for their technical support. Additional technical support was provided by Shu Li and the Biobank for the Molecular Classification of Kidney Disease at the Snyder Institute for Chronic Diseases. J.A.M. was the holder of a Marie (Sklodowska-) Curie International Incoming Fellowship from the European Commission. D.A.M. holds a Tier II Canada Research Chair. A.L. held a Postdoctoral Scholarship Award from Alberta Innovates—Health Solutions.

Funding

Research was supported by the Canadian Institutes of Health Research (CIHR) Health Challenges in Chronic Disease Signature Initiative (#THC-13523), the Canadian National Transplantation Research Program (CNTRP), and the Canada Foundation for Innovation.

Author information

Authors and Affiliations

Authors

Contributions

A.U.-L. designed and performed the MRM-MS experiments and analyzed the data. A.L. generated HEK-293T and THP-1 samples for analysis and measured IL-18 levels in patient urine by ELISA. J.A.M. secured funding and conceived the project. M.C.N. acted as the clinical research coordinator, collected urinary specimens, and managed the Biobank for the Molecular Classification of Kidney Disease. D.A.M. and M.T.J. provided expertise and led the clinical CKD study. J.A.M. wrote the manuscript and manufactured the figures with assistance from A.U.-L. All authors have given approval to the final version of the manuscript.

Corresponding author

Correspondence to Justin A. MacDonald.

Ethics declarations

Competing Financial Interests

J.A.M. and D.A.M. are co-founders and hold equity positions in Arch Biopartners Inc.

Electronic supplementary material

ESM 1

(DOCX 171 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ulke-Lemée, A., Lau, A., Nelson, M.C. et al. Quantification of Inflammasome Adaptor Protein ASC in Biological Samples by Multiple-Reaction Monitoring Mass Spectrometry. Inflammation 41, 1396–1408 (2018). https://doi.org/10.1007/s10753-018-0787-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10753-018-0787-6

KEY WORDS

Navigation