Metabolomic similarities between bronchoalveolar lavage fluid and plasma in humans and mice

Scientific Reports

Volumn 7, Issue 1, 2017, Pages

  Cruickshank Quinn, Charmion ^a   Powell, Roger ^a   Jacobson, Sean ^b   Kechris, Katerina ^a   Bowler, Russell P ^b   Petrache, Irina ^b   Reisdorph, Nichole ^a  

^a UNIVERSITY OF COLORADO   (United States)

^b DEPARTMENT OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GLYCEROPHOSPHOLIPID;

AGED; ANIMAL; BRONCHOALVEOLAR LAVAGE FLUID; CHEMISTRY; COMPARATIVE STUDY; FEMALE; HUMAN; MALE; METABOLOMICS; MIDDLE AGED; MOUSE; PASSIVE SMOKING; PLASMA; PROCEDURES; SAMPLE SIZE; TANDEM MASS SPECTROMETRY;

AGED; ANIMALS; BRONCHOALVEOLAR LAVAGE FLUID; FEMALE; GLYCEROPHOSPHOLIPIDS; HUMANS; MALE; METABOLOMICS; MICE; MIDDLE AGED; PLASMA; SAMPLE SIZE; TANDEM MASS SPECTROMETRY; TOBACCO SMOKE POLLUTION;

EID: 85023185421     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/s41598-017-05374-1     Document Type: Article

References (62)

1. Kazachkov, M. Y., Muhlebach, M. S., Livasy, C. A. & Noah, T. L. Lipid-laden macrophage index and inflammation in bronchoalveolar lavage fluids in children. Eur. Respir. J 18, 790-795 (2001).
2. Tufvesson, E., Ekberg, M. & Bjermer, L. Inflammatory Biomarkers in Sputum Predict COPD Exacerbations. Lung 191, 413-416, doi: 10.1007/s00408-013-9473-5 (2013).
3. Chow, S., Thomas, P. S., Malouf, M. & Yates, D. H. Exhaled breath condensate (EBC) biomarkers in pulmonary fibrosis. Journal of Breath Research 6, 016004, doi: 10.1088/1752-7155/6/1/016004 (2012).
4. Little, F. F. et al. Salivary Inflammatory Mediator Profiling and Correlation to Clinical Disease Markers in Asthma. PLoS ONE 9, e84449, doi: 10.1371/journal.pone.0084449 (2014).
5. Röpcke, S. et al. Repeatability of and Relationship between Potential COPD Biomarkers in Bronchoalveolar Lavage, Bronchial Biopsies, Serum, and Induced Sputum. PLoS ONE 7, e46207, doi: 10.1371/journal.pone.0046207 (2012).
6. Ohlmeier, S. et al. Lung tissue proteomics identifies elevated transglutaminase 2 levels in stable chronic obstructive pulmonary disease. American Journal of Physiology. Lung Cellular and Molecular Physiology 310, L1155-L1165, doi: 10.1152/ajplung.00021.2016 (2016).
7. Cruickshank-Quinn, C. et al. Transient and persistent metabolomic changes in plasma following chronic cigarette smoke exposure in a mouse model. PLoS ONE 9, e101855, doi: 10.1371/journal.pone.0101855 (2014).
8. Bowler, R. P. et al. Plasma Sphingolipids Associated with Chronic Obstructive Pulmonary Disease Phenotypes. Am. J. Respir. Crit. Care Med. 191, 275-284, doi: 10.1164/rccm.201410-1771OC (2015).
9. Gu, F. et al. Cigarette smoking behaviour and blood metabolomics. Int. J. Epidemiol. 45, 1421-1432, doi: 10.1093/ije/dyv330 (2015).
10. Neal, R. E. et al. Developmental cigarette smoke exposure: Hippocampus proteome and metabolome profiles in low birth weight pups. Toxicology 317, 40-49, doi: 10.1016/j.tox.2014.01.006 (2014).
11. Barr, J. et al. Liquid chromatography-mass spectrometry-based parallel metabolic profiling of human and mouse model serum reveals putative biomarkers associated with the progression of nonalcoholic fatty liver disease. Journal of Proteome Research 9, 4501-4512 (2010).
12. Ho, W. E. et al. Metabolomics Reveals Inflammatory-Linked Pulmonary Metabolic Alterations in a Murine Model of House Dust Mite-Induced Allergic Asthma. Journal of Proteome Research 13, 3771-3782, doi: 10.1021/pr5003615 (2014).
13. Conlon, T. M. et al. Metabolomics screening identifies reduced L-carnitine to be associated with progressive emphysema. Clinical Science 130, 273-287, doi: 10.1042/CS20150438 (2016).
14. Yang, Y. et al. New sample preparation approach for mass spectrometry-based profiling of plasma results in improved coverage of metabolome. J. Chromatogr. 1300, 217-226, doi: 10.1016/j.chroma.2013.04.030 (2013).
15. Alberts, B. et al. In The Lipid Bilayer (New York: Garland Science, 2002).
16. Peng, J., St. Laurent, C. D., Befus, A. D., Zhou, R. & Li, L. Metabolomic profiling of bronchoalveolar lavage fluids by isotope labeling liquid chromatography mass spectrometry: a promising approach to studying experimental asthma. Metabolomics 10, 1305-1317, doi: 10.1007/s11306-014-0667-5 (2014).
17. Evans, C. R. et al. Untargeted LC-MS Metabolomics of Bronchoalveolar Lavage Fluid Differentiates Acute Respiratory Distress Syndrome from Health. Journal of Proteome Research 13, 640-649, doi: 10.1021/pr4007624 (2014).
18. Ho, W. E. et al. Metabolomics Reveals Altered Metabolic Pathways in Experimental Asthma. American Journal of Respiratory Cell and Molecular Biology 48, 204-211, doi: 10.1165/rcmb.2012-0246OC (2013).
19. Yoder, M. et al. Bioactive lysophosphatidylcholine 16:0 and 18:0 are elevated in lungs of asthmatic subjects. Allergy, Asthma & Immunology Research 6, 61-65, doi: 10.4168/aair.2014.6.1.61 (2014).
20. Moffatt, M. F. et al. A large-scale, consortium-based genomewide association study of asthma. New Engl. J. Med 363, 1211-1121, doi: 10.1056/NEJMoa0906312 (2010).
21. Paul, G. et al. Vitamin D and Asthma. Am. J. Respir. Crit. Care Med. 185, 124-132, doi: 10.1164/rccm.201108-1502CI (2012).
22. Litonjua, A. A. Vitamin D Deficiency as a risk factor for childhood allergic disease and asthma. Current Opinion in Allergy and Clinical Immunology 12, 179-185, doi: 10.1097/ACI.0b013e3283507927 (2012).
23. Ubhi, B. K. et al. Targeted metabolomics identifies perturbations in amino acid metabolism that sub-classify patients with COPD. Molecular BioSystems 8, 3125-3133 (2012).
24. Luykx, J. J. et al. D-Amino Acid Aberrations in Cerebrospinal Fluid and Plasma of Smokers. Neuropsychopharmacology 38, 2019-2026, doi: 10.1038/npp.2013.103 (2013).
25. Brodlie, M. et al. Ceramide Is Increased in the Lower Airway Epithelium of People with Advanced Cystic Fibrosis Lung Disease. Am. J. Respir. Crit. Care Med. 182, 369-375, doi: 10.1164/rccm.200905-0799OC (2010).
26. Nicholson, G. et al. Human metabolic profiles are stably controlled by genetic and environmental variation. Mol. Syst. Biol. 7, 10.1038/msb.2011.57 (2011).
27. Řezanka, T. & Sigler, K. Odd-numbered very-long-chain fatty acids from the microbial, animal and plant kingdoms. Progress in Lipid Research 48, 206-238, doi: 10.1016/j.plipres.2009.03.003 (2009).
28. Jenkins, B., West, J. A. & Koulman, A. A Review of Odd-Chain Fatty Acid Metabolism and the Role of Pentadecanoic Acid (C15:0) and Heptadecanoic Acid (C17:0) in Health and Disease. Molecules 20, 2425-2444, doi: 10.3390/molecules20022425 (2015).
29. Hishikawa, D., Hashidate, T., Shimizu, T. & Shindou, H. Diversity and function of membrane glycerophospholipids generated by the remodeling pathway in mammalian cells. J. Lipid Res. 55, 799-807, doi: 10.1194/jlr.R046094 (2014).
30. Quehenberger, O. et al. Lipidomics reveals a remarkable diversity of lipids in human plasma. J. Lipid Res. 51, 3299-3305, doi: 10.1194/jlr.M009449 (2010).
31. Calder, P. C. Fatty acids and inflammation: the cutting edge between food and pharma. Eur. J. Pharmacol. 668, S50-S58, doi: 10.1016/j.ejphar.2011.05.085 (2011).
32. Calder, P. C. n-3 Polyunsaturated fatty acids, inflammation, and inflammatory diseases. Am. J. Clin. Nutr. 83, S1505-S1519 (2006).
33. Chait, A. & Kim, F. Saturated Fatty Acids and Inflammation: Who Pays the Toll Atertio. Thromb. Vasc. Biol 30, 692-693, doi: 10.1161/ATVBAHA.110.203984 (2010).
34. Yang, Z., Matteson, E. L., Goronzy, J. J. & Weyand, C. M. T-cell metabolism in autoimmune disease. Arthrit. Res. Ther 17, 29, doi: 10.1186/s13075-015-0542-4 (2015).
35. Kiebish, M. A. et al. Dysfunctional cardiac mitochondrial bioenergetic, lipidomic, and signaling in a murine model of Barth syndrome. J. Lipid Res. 54, 1312-1325, doi: 10.1194/jlr.M034728 (2013).
36. Chicco, A. J. & Sparagna, G. C. Role of cardiolipin alterations in mitochondrial dysfunction and disease. American Journal of Physiology. Cell Physiology 292, C33-C44, doi: 10.1152/ajpcell.00243.2006 (2007).
37. Kolter, T. & Sandhoff, K. Sphingolipid metabolism diseases. Biochimica et Biophysica Acta 1758, 2057-2079 (2006).
38. Petrache, I. et al. Ceramide upregulation causes pulmonary cell apoptosis and emphysema-like disease in mice. Nat. Med 11, 491-498 (2005).
39. Speck, K. & Magauer, T. The chemistry of isoindole natural products. Beilstein Journal of Organic Chemistry 9, 2048-2078, doi: 10.3762/bjoc.9.243 (2013).
40. Centers for Disease Control and Prevention. Tobacco Products; Cigarette Additives, http://www.cdc.gov/tobacco/data-statistics/sgr/2000/highlights/tobacco/ (2000) (Date of Access: 08/04/2016).
41. American Tobacco Company et al. List of ingredients added to tobacco in the manufacture of cigarettes (as of 931231). Bates number 89284138/89284169, http://legacy.library.ucsf.edu/tid/ayy10e00 (1993) (Date of Access: 08/04/2016).
42. Petrache, I. & Petrusca, D. N. The Involvement of Sphingolipids in Chronic Obstructive Pulmonary Diseases. Handbook of Experimental Pharmacology 216, 247-264, doi: 10.1007/978-3-7091-1511-4-12 (2013).
43. Al-Biltagi, M., Isa, M., Bediwy, A. S., Helaly, N. & El Lebedy, D. D. L-Carnitine Improves the Asthma Control in Children with Moderate Persistent Asthma. Journal of Allergy 2012, 7 pages, doi: 10.1155/2012/509730 (2012).
44. Nguyen, L. T. et al. L-Carnitine reverses maternal cigarette smoke exposure-induced renal oxidative stress and mitochondrial dysfunction in mouse offspring. American Journal of Physiology: Renal Physiology 308, F689-F696, doi: 10.1152/ajprenal.00417.2014 (2015).
45. Sundar, I. K. & Rahman, I. Vitamin d and susceptibility of chronic lung diseases: role of epigenetics. Frontiers in pharmacology 2, 50, doi: 10.3389/fphar.2011.00050 (2011).
46. Finklea, J. D., Grossmann, R. E. & Tangpricha, V. Vitamin D and chronic lung disease: a review of molecular mechanisms and clinical studies. Advances in nutrition (Bethesda, Md.) 2, 244-253, doi: 10.3945/an.111.000398 (2011).
47. Regan, E. A. et al. Genetic epidemiology of COPD (COPDGene) study design. COPD 7, 32-43, doi: 10.3109/15412550903499522 (2010).
48. Clauss, M. et al. Lung endothelial monocyte-activating protein 2 is a mediator of cigarette smoke-induced emphysema in mice. J. Clin. Invest. 121, 2470-2479, doi: 10.1172/jci43881 (2011).
49. Schweitzer, K. S. et al. Adipose Stem Cell Treatment in Mice Attenuates Lung and Systemic Injury Induced by Cigarette Smoking. Am. J. Respir. Crit. Care Med. 183, 215-225, doi: 10.1164/rccm.201001-0126OC (2011).
50. Miller, A. M. et al. Gene and metabolite time-course response to cigarette smoking in mouse lung and plasma. PLOS ONE 12(6), e0178281 (2017).
51. Carolan, B. J. et al. The association of plasma biomarkers with computed tomography-assessed emphysema phenotypes. Respir Res 15, 127, doi: 10.1186/s12931-014-0127-9 (2014).
52. More, J. M. et al. Smoking reduces surfactant protein D and phospholipids in patients with and without chronic obstructive pulmonary disease. BMC Pulmonary Medicine 10, 53, doi: 10.1186/1471-2466-10-53 (2010).
53. Cruickshank-Quinn, C. et al. Multi-step preparation technique to recover multiple metabolite compound classes for in-depth and informative metabolomic analysis. Journal of Visualized Experiments 89, e51670, doi: 10.3791/51670 (2014).
54. Hughes, G. et al. MSPrep - Summarization, normalization and diagnostics for processing of mass spectrometry-based metabolomic data. Bioinformatics 30, 133-134, doi: 10.1093/bioinformatics/btt589 (2014).
55. Cazzola, M. & Novelli, G. Biomarkers in COPD. Pulmonary Pharmacology & Therapeutics 23, 493-500 (2010).
56. Ejigu, B. A. et al. Evaluation of Normalization Methods to Pave the Way Towards Large-Scale LC-MS-Based Metabolomics Profiling Experiments. OMICS: A Journal of Integrative Biology 17, 473-485, doi: 10.1089/omi.2013.0010 (2013).
57. Yang, X., Neta, P. & Stein, S. E. Quality Control for Building Libraries from Electrospray Ionization Tandem Mass Spectra. Analytical chemistry 86, 6393-6400, doi: 10.1021/ac500711m (2014).
58. Sumner, L. W. et al. Proposed Minimum Reporting Standards for Chemical Analysis: Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI). Metabolomics 3, 211-221, doi: 10.1007/s11306-007-0082-2 (2007).
59. Stein, S. NIST MS Search Program, http://chemdata.nist.gov/ (2011) (Date of Access: 08/06/2016).
60. NIST/EPA/NIH Mass Spectral Library with Search Program (Data Version: NIST 14, Software Version 2.2g), http://www.nist.gov/srd/nist1a.cfm (2014) (Date of Access: 27/02/2016).
61. Stein, S. E. Estimating probabilities of correct identification from results of mass spectral library searches. J. Am. Soc. Mass Spectrom 5, 316-323, doi: 10.1016/1044-0305(94)85022-4 (1994).
62. Newcombe, R. G. Interval estimation for the difference between independent proportions: comparison of eleven methods. Statistics in Medicine 17, 873-890 (1998).