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Review Articles

Sepsis Through the Eyes of Proteomics

The Progress in the Last Decade

Sharma, Narendra Kumar; Salomao, Reinaldo

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doi: 10.1097/SHK.0000000000000698
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Sepsis is a systemic manifestation of an infection and a leading cause of death not only in developing but also in developed countries. Numerous information is available for studying the mechanism of host response to infection, which explains the complexity of inflammatory and immunosuppressive response during sepsis (1). The diagnosis and the evaluation of sepsis severity is always challenging to clinicians due to its high variability and non-specific symptoms (2). Despite the advancement in technology and knowledge, sepsis still remains with very high mortality rates (3). Hundreds of clinical trials have been conducted in sepsis with limited success, which further support the extreme complexity of sepsis. Several biomarkers have been evaluated clinically in sepsis, none is sufficient to predict sepsis in early or advance stage (4). The immune response to endotoxin (lipopolysaccharide (LPS)) has greatly contributed to understand the molecular mechanism of sepsis and is also primary choice of researchers to study the cell-based models, animals, as well as human subjects (1). In this review, we discuss the proteomic studies that have been done in sepsis and/or in response to endotoxin in various kinds of samples such as biological fluids, tissues, and cells using different technical approaches and that contribution to our best understanding of sepsis pathogenesis. We reviewed proteomic studies published in the last decade in PubMed database using sepsis, LPS, and endotoxin as key words.


Proteomics is the protein equivalent of genomics and is the study of the function of all expressed proteins (5, 6). With the completion of human genome project, a major challenge lies in finding the genes, locating their coding regions and predicting their functions (7). This will help us to enhance our understanding of complex biological system as well as in the design of new molecular structures as potential novel diagnostic or drug discovery targets (8). Unlike the genome, the proteome is dynamic: it varies according to the cell type and the functional state of the cell. In addition, the proteome shows characteristic perturbations in response to disease and external stimuli (6). Thus, proteomics is emerging as a highly promising field of life sciences. The development and application of electrospray (ESI) and matrix-assisted laser-desorption ionization, which permits the ionization of large biomolecules, has led to significant improvements in the central step of a proteomics experiment and protein identification (9). In parallel with the advancement of proteomics, attempts to apply proteomic analysis to the discovery of new biomarkers for pathophysiology description have been reported for a wide range of diseases including sepsis.


Proteomic analysis techniques have allowed for better understanding of the molecular bases related to the identification of cell signaling, modifying protein, and post-translational modification pathways. Schematic representation of proteomics workflow is represented in Figure 1. Documenting certain proteins expressed in sepsis is a promising approach to elucidate pathophysiological, diagnostic, therapeutic, and prognostic aspects in this condition with a purpose of applying them to clinical practice (10). Novel biomarkers with high sensitivity and specificity may be helpful for early diagnosis of sepsis and for the development of new therapies. Mass spectrometry-based proteomics offers powerful tool to identify such biomarkers and furthermore to give insight into fundamental mechanism of this clinical. However, only a limited number of reports are available on application of proteomic analysis to clinical samples collected from patients with sepsis, and no results obtained by proteomic analysis for such patients have been fully validated by other well-established analytical technique (10, 11).

Fig. 1
Fig. 1:
Schematic representation of proteomics workflow in sepsis.


Two-dimensional gel electrophoresis is used as a separation method for proteins. Various proteomics studies have been carried out in sepsis in the last decade using gel-based methods (Table 1) (12–49). Among all of the studied samples, plasma/serum was the most extensively used in human subjects while tissue and cells were mostly used in animal models. There were a limited number of proteins (from 6 to 19 proteins) identified in plasma/serum samples of septic patients (12–19). These altered proteins were associated with various functions such as bacterial product recognition (19), inflammation (15, 18), coagulation (17, 18), complement system (17), cytoprotective signalling pathway (15), and pathophysiological events (16) under sepsis. In another study, Buhimschi et al. (12) described haptoglobin switch on pattern as a biomarker for sepsis, while Josic et al. (14) showed the potential role of IaIp for diagnosis and treatment of sepsis. Similarly, plasma/serum samples have also shown inflammatory response in mouse (20) and oxidative and nitrosative stress in pig (21). Various combinations of proteins such as Desmin, cystic fibrosis transmembrane conductance regulator, IL-4, IL-6 precursor (22) and DPYSL2, FGA, STIP1 (23) were reported as biomarkers in rabbit and rat, respectively, in response to endotoxin. In tissue samples from animal models, several altered proteins were identified related to mitochondrial functions (24, 25), cellular functions (26), renal injury (27), cell structure, energy production, signaling (28), endothelial damage (25), and also reported as biomarkers (29, 30). Chen et al. (31) have described the functional role of aldehyde dehydrogenase 2 family phosphorylation in pathogenesis of sepsis. Similar studies demonstrated the role of tsHMG protein in modulation of iNOS (32) and MMP-8 for recruitment of neutrophil to the lungs (33) during endotoxic shock and sepsis, respectively. In cell-based studies, altered proteins are associated with immune suppression (34, 35), inflammation (36–40), cytokines (41, 42), coagulation (40, 43), and signaling and metabolic pathways (37). Other studies demonstrated the biological role of endothelial cells and caveolin-1 (44), ubiquitination (45), phosphorylation of p38 and Annexin A1 (39), differentiation and maturation of DC (46), and macrophage activation (36) in sepsis or LPS treatment.

Table 1
Table 1:
List of proteomics studies in response to sepsis infection/LPS/CLP using gel-based methods
Table 1
Table 1:
(Continued) List of proteomics studies in response to sepsis infection/LPS/CLP using gel-based methods

Advantage and disadvantage

Gel-based proteomics is time consuming, costly, and less sensitive to low abundant proteins. It is also unable to separate all proteins in a complex mixture as well as resulted in less identification. With these limitations, gel-based proteomics is very useful to study protein modification especially isoforms. Difference gel electrophoresis system converted conventional method into quantitative proteomics, however, limited numbers of protein identification have been observed.


LC-based method is more sensitive and promising to identify low abundance proteins with higher peptide coverage which is unable to get in gel-based methods. Several studies have been carried out recently (Table 2) and identified proteins range from 100 to 3,000 proteins in sepsis (51–57). On comparison of plasma/serum of survival and non-survival septic patients and LPS stimulation, a number of differentially expressed proteins were identified which are associated with several inflammatory markers (52, 55), complement components, fatty acid transport (55), and lipid transport (53). Posttranslational study in septic plasma has suggested that survivors relied on extrinsic pathway of complement and coagulation cascade, while, non-survivors relied on intrinsic pathways (57). On the basis of expression pattern in plasma, multimerin 1, ficolin 1, carboxypeptidase N (CPN2), serine protease 1, and platelet factor 4 were reported as biomarker in survival and non-survival colipase induced in rats (58). Proteomics also revealed age-related differences in sepsis with opposite expression for acute phase response, coagulation, and lipid metabolism pathways in elderly population (56).

Table 2
Table 2:
List of proteomics studies in response to sepsis infection /LPS/CLP using LC based methods
Table 2
Table 2:
(Continued) List of proteomics studies in response to sepsis infection /LPS/CLP using LC based methods

Urine analysis is a noninvasive method and facilitated identification of several biomarkers in survival/non-survival septic patients (59–61) and in mouse model (62). Urinary proteome profile analysis also identified altered proteins associated with inflammation, immunity, structural, or cytoskeleton processes related proteins (60), and LAMP-1 is associated with early prognostic assessment of sepsis (59). In other biological fluid (interstitial fluid, lymph, spleen interstitial fluid), ADAMTS1 protein was altered after LPS treatment in rats (63), while degree of neutrophil activation is associated with human amniotic fluid (64). Only one study has been done in rodent tissue (heart) sample, where transformation of octameric to monomeric Pentraxin (PTX) 3 was investigated and reported as biomarker for survival in septic patients (65).

In cells, monocytes, neutrophils, and macrophage have been studied after LPS treatment and identified proteins that were associated with structure maintenance (50, 66, 67), host defense against infection (67), activation of nuclear factor kappa-light-chain-enhancer of activated B cells, mitogen-activated protein kinases, interferon regulatory factor (66). In contrast, studies performed with endothelial cells suggested the involvement of heat shock protein in trafficking LPS to the Golgi apparatus (68) and 19 new biomarkers were identified in sepsis (69).

Advantage and disadvantage

The gel-free methods or LC-based proteomic separation is more sensitive to low abundant proteins in complex mixture such as plasma. Multidimensional chromatographic separation significantly improved quality of spectra with higher coverage of peptide identification. The LC-MS-based system is more sensitive and has ability to accurate quantitation by using various technologies. Unlike gel-based proteins, LC-based methods lack in the information of isoforms and protein modifications.


Proteins are the actual player in biological systems; hence, the proteomics study has ability to answer untold facts and molecular mechanisms. The broad analyses of proteins alterations in experimental and clinical sepsis allow us to evaluate the systemic host response to the injury, and offer comprehensive information about the complex host-response to infection. Even considering that we are in the dawn of proteomics studies in sepsis, the above-mentioned studies already improved our understanding of altered cell functions and interactions. Thus, in septic patients, increased production of reactive oxygen species, nitric oxide with antioxidant depletion leading to mitochondrial dysfunction was observed at protein level. Inflammatory response induces oxidative stress under sepsis which further alters mitochondrial function and decrease ATP level. These alterations affect homeostasis and may contribute to multiple organ dysfunctions. Evolving interactions driving to new targets and biomarkers are also in the horizon. Among others, PTX3, known to play an important role in innate immunity as a soluble pattern recognition receptor, has been shown to interact with proteins involved in complement activation, pathogen opsonization, and inflammation regulation. Proteomic analyses further evidenced interaction with components of neutrophil extracellular traps, leading to the discovery of a direct interaction of bactericidal proteins azurocidin 1 (AZU1) and myeloperoxidase with PTX3, thus suggesting, as stated by the authors, that “PTX3, as a soluble PRR, might help form the antipathogenic microenvironment by tethering bactericidal proteins in sepsis(54). In near future studies, focusing on organ, immune cells, and body fluids from sepsis patients will take advantage of the development in high throughput proteomics technology. Such studies will shed more light on molecular mechanism of sepsis with increased number of proteins identification.


1. Salomao R, Brunialti MK, Rapozo MM, Baggio-Zappia GL, Galanos C, Freudenberg M. Bacterial sensing, cell signaling, and modulation of the immune response during sepsis. Shock 2012; 38:227–242.
2. Lever A, Mackenzie I. Sepsis: definition, epidemiology, and diagnosis. BMJ 2007; 335:879–883.
3. Vincent JL, Rello J, Marshall J, Silva E, Anzueto A, Martin CD, Moreno R, Lipman J, Gomersall C, Sakr Y, et al. International study of the prevalence and outcomes of infection in intensive care units. JAMA 2009; 302:2323–2329.
4. Pierrakos C, Vincent JL. Sepsis biomarkers: a review. Crit Care 2010; 14:R15.
5. Tyers M, Mann M. From genomics to proteomics. Nature 2003; 422:193–197.
6. Marshall T, Williams KM. Proteomics and its impact upon biomedical science. Br J Biomed Sci 2002; 59:47–64.
7. Haberkorn U, Altmann A, Eisenhut M. Functional genomics and proteomics—the role of nuclear medicine. Eur J Nucl Med Mol Imaging 2002; 29:115–132.
8. Jeffery DA, Bogyo M. Chemical proteomics and its application to drug discovery. Drug Discov Today 2004; 9:S19–26.
9. Macaulay IC, Carr P, Gusnanto A, Ouwehand WH, Fitzgerald D, Watkins NA. Platelet genomics and proteomics in human health and disease. J Clin Invest 2005; 115:3370–3377.
10. Siqueira-Batista R, Mendonca EG, Gomes AP, Vitorino RR, Miyadahira R, Alvarez-Perez MC, Oliveira MG. Proteomic updates on sepsis. Rev Assoc Med Bras 2012; 58:376–382.
11. Hattori N, Oda S, Sadahiro T, Nakamura M, Abe R, Shinozaki K, Nomura F, Tomonaga T, Matsushita K, Kodera Y, et al. YKL-40 identified by proteomic analysis as a biomarker of sepsis. Shock 2009; 32:393–400.
12. Buhimschi CS, Bhandari V, Dulay AT, Nayeri UA, Abdel-Razeq SS, Pettker CM, Thung S, Zhao G, Han YW, Bizzarro M, et al. Proteomics mapping of cord blood identifies haptoglobin “switch-on” pattern as biomarker of early-onset neonatal sepsis in preterm newborns. PLoS One 2011; 6:e26111.
13. Gong Y, Chen N, Wang FQ, Wang ZH, Xu HX. Serum proteome alteration of severe sepsis in the treatment of continuous renal replacement therapy. Nephrol Dial Transplant 2009; 24:3108–3114.
14. Josic D, Brown MK, Huang F, Lim YP, Rucevic M, Clifton JG, Hixson DC. Proteomic characterization of inter-alpha inhibitor proteins from human plasma. Proteomics 2006; 6:2874–2885.
15. Kalenka A, Feldmann RE Jr, Otero K, Maurer MH, Waschke KF, Fiedler F. Changes in the serum proteome of patients with sepsis and septic shock. Anesth Analg 2006; 103:1522–1526.
16. Lin CH, Wang PW, Pan TL, Bazylak G, Liu EK, Wei FC. Proteomic profiling of oxidative stress in human victims of traffic-related injuries after lower limb revascularization and indication for secondary amputation. J Pharm Biomed Anal 2010; 51:784–794.
17. Paiva RA, David CM, Domont GB. Proteomics in sepsis: a pilot study. Rev Bras Ter Intensiva 2010; 22:403–412.
18. Soares AJ, Santos MF, Trugilho MR, Neves-Ferreira AG, Perales J, Domont GB. Differential proteomics of the plasma of individuals with sepsis caused by Acinetobacter baumannii. J Proteomics 2009; 73:267–278.
19. Triantafilou M, Mouratis MA, Lepper PM, Haston RM, Baldwin F, Lowes S, Ahmed MA, Schumann C, Boyd O, Triantafilou K. Serum proteins modulate lipopolysaccharide and lipoteichoic acid-induced activation and contribute to the clinical outcome of sepsis. Virulence 2012; 3:136–145.
20. McDunn JE, Townsend RR, Cobb JP. The murine plasma protein response to polymicrobial intra-abdominal sepsis. Proteomics Clin Appl 2007; 1:373–386.
21. Thongboonkerd V, Chiangjong W, Mares J, Moravec J, Tuma Z, Karvunidis T, Sinchaikul S, Chen ST, Opatrny K, Matejovic M. Altered plasma proteome during an early phase of peritonitis-induced sepsis. Clin Sci (Lond) 2009; 116:721–730.
22. Zhou Z, Ren J, Liu H, Gu G, Li J. Serum proteomic analysis from bacteremic and leucopenic rabbits. J Surg Res 2011; 171:749–754.
23. Hinkelbein J, Feldmann RE Jr, Schubert C, Peterka A, Schelshorn D, Maurer MH, Kalenka A. Alterations in rat serum proteome and metabolome as putative disease markers in sepsis. J Trauma 2009; 66:1065–1075.
24. Crouser ED, Julian MW, Huff JE, Mandich DV, Green-Church KB. A proteomic analysis of liver mitochondria during acute endotoxemia. Intensive Care Med 2006; 32:1252–1262.
25. Robichaud S, Lalu M, Udenberg T, Schulz R, Sawicki G. Proteomics analysis of changes in myocardial proteins during endotoxemia. J Proteomics 2009; 72:648–655.
26. Duan X, Berthiaume F, Yarmush D, Yarmush ML. Proteomic analysis of altered protein expression in skeletal muscle of rats in a hypermetabolic state induced by burn sepsis. Biochem J 2006; 397:149–158.
27. Dear JW, Leelahavanichkul A, Aponte A, Hu X, Constant SL, Hewitt SM, Yuen PS, Star RA. Liver proteomics for therapeutic drug discovery: inhibition of the cyclophilin receptor CD147 attenuates sepsis-induced acute renal failure. Crit Care Med 2007; 35:2319–2328.
28. Hinkelbein J, Feldmann RE Jr, Peterka A, Schubert C, Schelshorn D, Maurer MH, Kalenka A. Alterations in cerebral metabolomics and proteomic expression during sepsis. Curr Neurovasc Res 2007; 4:280–288.
29. Hinkelbein J, Kalenka A, Schubert C, Peterka A, Feldmann RE Jr. Proteome and metabolome alterations in heart and liver indicate compromised energy production during sepsis. Protein Pept Lett 2010; 17:18–31.
30. Struck J, Uhlein M, Morgenthaler NG, Furst W, Hoflich C, Bahrami S, Bergmann A, Volk HD, Redl H. Release of the mitochondrial enzyme carbamoyl phosphate synthase under septic conditions. Shock 2005; 23:533–538.
31. Chen HW, Kuo HT, Hwang LC, Kuo MF, Yang RC. Proteomic alteration of mitochondrial aldehyde dehydrogenase 2 in sepsis regulated by heat shock response. Shock 2007; 28:710–716.
32. Liu Z, Liu J, Wang J, Xu J, Liu Y, Sun X, Su L, Wang JH, Jiang Y. Role of testis-specific high-mobility-group protein in transcriptional regulation of inducible nitric oxide synthase expression in the liver of endotoxic shock mice. FEBS J 2014; 281:2202–2213.
33. Gonzalez-Lopez A, Aguirre A, Lopez-Alonso I, Amado L, Astudillo A, Fernandez-Garcia MS, Suarez MF, Batalla-Solis E, Colado E, Albaiceta GM. MMP-8 deficiency increases TLR/RAGE ligands S100A8 and S100A9 and exacerbates lung inflammation during endotoxemia. PLoS One 2012; 7:e39940.
34. Chen T, Lin X, Xu J, Tan R, Ji J, Shen P. Redox imbalance provokes deactivation of macrophages in sepsis. Proteomics Clin Appl 2009; 3:1000–1009.
35. Zhang PH, Yang LR, Li LL, Zeng JZ, Ren LC, Liang PF, Huang XY. Proteomic change of peripheral lymphocytes from scald injury and Pseudomonas aeruginosa sepsis in rabbits. Burns 2010; 36:82–88.
36. Gadgil HS, Pabst KM, Giorgianni F, Umstot ES, Desiderio DM, Beranova-Giorgianni S, Gerling IC, Pabst MJ. Proteome of monocytes primed with lipopolysaccharide: analysis of the abundant proteins. Proteomics 2003; 3:1767–1780.
37. Tseng HW, Juan HF, Huang HC, Lin JY, Sinchaikul S, Lai TC, Chen CF, Chen ST, Wang GJ. Lipopolysaccharide-stimulated responses in rat aortic endothelial cells by a systems biology approach. Proteomics 2006; 6:5915–5928.
38. Zhang PH, Li LL, Zeng JZ, Yang LR, Ren LC, Liang PF, Huang XY. Preliminary proteomic analysis of circulating polymorphonuclear neutrophils from rabbits experiencing scald injury and Staphylococcus aureus sepsis. Inflamm Res 2010; 59:307–314.
39. Tang J, Chen X, Tu W, Guo Y, Zhao Z, Xue Q, Lin C, Xiao J, Sun X, Tao T, et al. Propofol inhibits the activation of p38 through up-regulating the expression of annexin A1 to exert its anti-inflammation effect. PLoS One 2011; 6:e27890.
40. Liu J, Li J, Deng X. Proteomic analysis of differential protein expression in platelets of septic patients. Mol Biol Rep 2014; 41:3179–3185.
41. Pabst MJ, Pabst KM, Handsman DB, Beranova-Giorgianni S, Giorgianni F. Proteome of monocyte priming by lipopolysaccharide, including changes in interleukin-1beta and leukocyte elastase inhibitor. Proteome Sci 2008; 6:13.
42. Fessler MB, Malcolm KC, Duncan MW, Worthen GS. A genomic and proteomic analysis of activation of the human neutrophil by lipopolysaccharide and its mediation by p38 mitogen-activated protein kinase. J Biol Chem 2002; 277:31291–31302.
43. Hu JY, Li CL, Wang YW. Altered proteomic pattern in platelets of rats with sepsis. Blood Cells Mol Dis 2012; 48:30–35.
44. Huang X, Pan L, Pu H, Wang Y, Zhang X, Li C, Yang Z. Loss of caveolin-1 promotes endothelial-mesenchymal transition during sepsis: a membrane proteomic study. Int J Mol Med 2013; 32:585–592.
45. Wu CH, Chan JY, Chou JL, Chan SH, Chang AY. Engagement of ubiquitination and de-ubiquitination at rostral ventrolateral medulla in experimental brain death. J Biomed Sci 2012; 19:48.
46. Pereira SR, Faca VM, Gomes GG, Chammas R, Fontes AM, Covas DT, Greene LJ. Changes in the proteomic profile during differentiation and maturation of human monocyte-derived dendritic cells stimulated with granulocyte macrophage colony stimulating factor/interleukin-4 and lipopolysaccharide. Proteomics 2005; 5:1186–1198.
47. Ren Y, Wang J, Xia J, Jiang C, Zhao K, Li R, Xu N, Xu Y, Liu S. The alterations of mouse plasma proteins during septic development. J Proteome Res 2007; 6:2812–2821.
48. Holly MK, Dear JW, Hu X, Schechter AN, Gladwin MT, Hewitt SM, Yuen PS, Star RA. Biomarker and drug-target discovery using proteomics in a new rat model of sepsis-induced acute renal failure. Kidney Int 2006; 70:496–506.
49. Bowler RP, Reisdorph N, Reisdorph R, Abraham E. Alterations in the human lung proteome with lipopolysaccharide. BMC Pulm Med 2009; 9:20.
50. Zhang H, Zhao C, Li X, Zhu Y, Gan CS, Wang Y, Ravasi T, Qian PY, Wong SC, Sze SK. Study of monocyte membrane proteome perturbation during lipopolysaccharide-induced tolerance using iTRAQ-based quantitative proteomic approach. Proteomics 2010; 10:2780–2789.
51. Qian WJ, Jacobs JM, Camp DG 2nd, Monroe ME, Moore RJ, Gritsenko MA, Calvano SE, Lowry SF, Xiao W, Moldawer LL, et al. Comparative proteome analyses of human plasma following in vivo lipopolysaccharide administration using multidimensional separations coupled with tandem mass spectrometry. Proteomics 2005; 5:572–584.
52. Qian WJ, Monroe ME, Liu T, Jacobs JM, Anderson GA, Shen Y, Moore RJ, Anderson DJ, Zhang R, Calvano SE, et al. Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach. Mol Cell Proteomics 2005; 4:700–709.
53. Shen Z, Want EJ, Chen W, Keating W, Nussbaumer W, Moore R, Gentle TM, Siuzdak G. Sepsis plasma protein profiling with immunodepletion, three-dimensional liquid chromatography tandem mass spectrometry, and spectrum counting. J Proteome Res 2006; 5:3154–3160.
54. Daigo K, Yamaguchi N, Kawamura T, Matsubara K, Jiang S, Ohashi R, Sudou Y, Kodama T, Naito M, Inoue K, et al. The proteomic profile of circulating pentraxin 3 (PTX3) complex in sepsis demonstrates the interaction with azurocidin 1 and other components of neutrophil extracellular traps. Mol Cell Proteomics 2012; 11:M111.
55. Langley RJ, Tsalik EL, van Velkinburgh JC, Glickman SW, Rice BJ, Wang C, Chen B, Carin L, Suarez A, Mohney RP, et al. An integrated clinico-metabolomic model improves prediction of death in sepsis. Sci Transl Med 2013; 5:195ra195.
56. Cao Z, Yende S, Kellum JA, Angus DC, Robinson RA. Proteomics reveals age-related differences in the host immune response to sepsis. J Proteome Res 2014; 13:422–432.
57. DeCoux A, Tian Y, DeLeon-Pennell KY, Nguyen NT, de Castro Bras LE, Flynn ER, Cannon PL, Griswold ME, Jin YF, Puskarich MA, et al. Plasma glycoproteomics reveals sepsis outcomes linked to distinct proteins in common pathways. Crit Care Med 2015; 43:2049–2058.
58. Jiao J, Gao M, Zhang H, Wang N, Xiao Z, Liu K, Yang M, Wang K, Xiao X. Identification of potential biomarkers by serum proteomics analysis in rats with sepsis. Shock 2014; 42:75–81.
59. Su L, Cao L, Zhou R, Jiang Z, Xiao K, Kong W, Wang H, Deng J, Wen B, Tan F, et al. Identification of novel biomarkers for sepsis prognosis via urinary proteomic analysis using iTRAQ labeling and 2D-LC-MS/MS. PLoS One 2013; 8:e54237.
60. Su L, Zhou R, Liu C, Wen B, Xiao K, Kong W, Tan F, Huang Y, Cao L, Xie L. Urinary proteomics analysis for sepsis biomarkers with iTRAQ labeling and two-dimensional liquid chromatography-tandem mass spectrometry. J Trauma Acute Care Surg 2013; 74:940–945.
61. Sylvester KG, Ling XB, Liu GY, Kastenberg ZJ, Ji J, Hu Z, Wu S, Peng S, Abdullah F, Brandt ML, et al. Urine protein biomarkers for the diagnosis and prognosis of necrotizing enterocolitis in infants. J Pediatr 2014; 164:607–612.
62. Maddens B, Ghesquiere B, Vanholder R, Demon D, Vanmassenhove J, Gevaert K, Meyer E. Chitinase-like proteins are candidate biomarkers for sepsis-induced acute kidney injury. Mol Cell Proteomics 2012; 11:M111.
63. Oveland E, Karlsen TV, Haslene-Hox H, Semaeva E, Janaczyk B, Tenstad O, Wiig H. Proteomic evaluation of inflammatory proteins in rat spleen interstitial fluid and lymph during LPS-induced systemic inflammation reveals increased levels of ADAMST1. J Proteome Res 2012; 11:5338–5349.
64. Buhimschi CS, Bhandari V, Hamar BD, Bahtiyar MO, Zhao G, Sfakianaki AK, Pettker CM, Magloire L, Funai E, Norwitz ER, et al. Proteomic profiling of the amniotic fluid to detect inflammation, infection, and neonatal sepsis. PLoS Med 2007; 4:e18.
65. Cuello F, Shankar-Hari M, Mayr U, Yin X, Marshall M, Suna G, Willeit P, Langley SR, Jayawardhana T, Zeller T, et al. Redox state of pentraxin 3 as a novel biomarker for resolution of inflammation and survival in sepsis. Mol Cell Proteomics 2014; 13:2545–2557.
66. Du R, Long J, Yao J, Dong Y, Yang X, Tang S, Zuo S, He Y, Chen X. Subcellular quantitative proteomics reveals multiple pathway cross-talk that coordinates specific signaling and transcriptional regulation for the early host response to LPS. J Proteome Res 2010; 9:1805–1821.
67. Malmstrom E, Davidova A, Morgelin M, Linder A, Larsen M, Qvortrup K, Nordenfelt P, Shannon O, Dzupova O, Holub M, et al. Targeted mass spectrometry analysis of neutrophil-derived proteins released during sepsis progression. Thromb Haemost 2014; 112:1230–1243.
68. Karsan A, Blonder J, Law J, Yaquian E, Lucas DA, Conrads TP, Veenstra T. Proteomic analysis of lipid microdomains from lipopolysaccharide-activated human endothelial cells. J Proteome Res 2005; 4:349–357.
69. Kwon OK, Lee W, Kim SJ, Lee YM, Lee JY, Kim JY, Bae JS, Lee S. In-depth proteomics approach of secretome to identify novel biomarker for sepsis in LPS-stimulated endothelial cells. Electrophoresis 2015; 36:2851–2858.

LPS and CLP; proteomics; sepsis

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