JOURNAL HOME CME HOME THIS MONTH PAST ISSUES ETOC COLLECTIONS AUTHORS REVIEWERS EDITORIAL BOARD FEEDBACK RSS HELP
		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a colleague Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via ISI Web of Science (2) Citing Articles via Google Scholar Google Scholar Articles by Kalenka, A. Articles by Fiedler, F. Search for Related Content PubMed PubMed Citation Articles by Kalenka, A. Articles by Fiedler, F. Related Collections Critical Care

---

CRITICAL CARE AND TRAUMA

Changes in the Serum Proteome of Patients with Sepsis and Septic Shock

Armin Kalenka, MD^*, Robert E. Feldmann, Jr, PhD, Kevin Otero^*, Martin H. Maurer, MD, Klaus F. Waschke, MD^*, and Fritz Fiedler, MD^*

From the *Department of Anesthesiology and Critical Care Medicine, Faculty of Clinical Medicine Mannheim, University of Heidelberg, Mannheim, Germany; and Department of Physiology and Pathophysiology, University of Heidelberg, Heidelberg, Germany.

Address correspondence and reprint requests to Dr. Armin Kalenka, Department of Anesthesiology and Critical Care Medicine, Faculty of Clinical Medicine Mannheim, University of Heidelberg, Theodor Kutzer Ufer 1-3, 68167 Mannheim, Germany. Address e-mail to armin.kalenka{at}urz.uni-hd.de.

	Abstract

Top Abstract Introduction METHODS RESULTS DISCUSSION REFERENCES

 
BACKGROUND: Sepsis is still the leading cause of death in the intensive care unit. Our goal was to elucidate potential early differences in serum between survivors (SURV) and non-survivors (NON-SURV) on day 28.

METHODS: We applied proteomic technology to serum samples of patients with sepsis and septic shock. Serum samples from 18 patients with sepsis and septic shock were obtained during the first 12 h after diagnosis of septic shock. Patients were grouped into SURV and NON-SURV on day 28.

RESULTS: Seven patients survived and 11 patients died. Using proteome analysis, two-dimensional gel electrophoresis detected more than 200 spots per gel. A differential protein expression was discovered between SURV and NON-SURV, whereby protein alterations not yet described in sepsis were revealed.

CONCLUSIONS: Our results show that proteomic profiling is a useful approach for detecting protein expression dynamics in septic patients, and may bring us closer to achieving a comprehensive molecular profiling compared with genetic studies alone.

	Introduction

Top Abstract Introduction METHODS RESULTS DISCUSSION REFERENCES

 
Sepsis is the leading cause of mortality in intensive care units (ICU). Mortality due to sepsis has decreased in the past decade. Nevertheless, the overall number of sepsis-related deaths, compared with other deaths in the ICU, has increased because the incidence of sepsis has increased (1). Several studies have suggested that the presence of specific genetic polymorphism during sepsis can predict the patient’s outcome (2). Other studies have used microarray technology to compare gene expression levels after endotoxin administration (3). However, gene expression studies cannot accurately predict the structure or dynamics of respective proteins. The RNA patterns do not reflect the proteomic pattern well (4,5), as it is the proteomic pattern where many regulatory processes, e.g., posttranslational modifications, take place (6).

Proteome analysis can be regarded as a peptide screening approach aiming to document the overall distribution of proteins in cells, organs, or other samples, to identify and characterize individual proteins of interest, and, finally, to elucidate their interactions and roles in cell function. Compared with the genomic microarray technique, the proteomic approach has the advantage of being able to detect previously unknown proteins, whereas microarrays allow only measurement of genes that are already defined. We therefore applied proteomic methods to investigate early protein profiles in patients with sepsis and septic shock, and to discover possible differences between survivors (SURV) and non-survivors (NON-SURV).

	METHODS

Top Abstract Introduction METHODS RESULTS DISCUSSION REFERENCES

 
Patients
Eighteen patients (10 men and 8 women; mean age 65.2 ± 11.8 yr) with putative sepsis and septic shock were prospectively enrolled in the study. Exclusion criteria were pregnancy, age <18 yr, cardiopulmonary resuscitation within the 72 h before the study, presence of an advanced directive to withhold or withdraw life-sustaining treatment, and the administration of corticosteroids or activated protein C.

Patient data were recorded at the time of diagnosis of septic shock, and consisted of age, sex, APACHE II score, and SOFA score. Specimens for the diagnosis of infection were obtained as early as possible. Patients were followed up until day 28 either in the ICU or in the units to which they were transferred. This study was approved by the Ethics Committee of our institution, and informed consent was obtained from all patients or their relatives.

Samples
Blood samples were obtained from an arterial catheter during the first 12 h after diagnosis of septic shock, or after the operation in the control group. Samples were allowed to clot at room temperature and were centrifuged at 1500g for 10 min. Separated serum was stored at –80°C until further analysis. Blood samples from five nonsepsis patients who underwent elective intraabdominal operations were used to create the reference gel.

Two-Dimensional Gel Electrophoresis
We performed two-dimensional gel electrophoresis as previously described in detail (7). Briefly, we applied serum samples to an albumin/IgG removal kit following the manufacturer’s protocol (Proteo Extract^TM Albumin/IgG Removal Kit, Calbiochem, La Jolla, CA), as these high-abundance proteins tend to mask those of lower abundance (6). Next, the protein content in the eluate was determined (8). We diluted 100 µg of the albumin- and IgG-depleted samples 1:4 with ice-cold ethanol for protein precipitation. After 2 h at –20°C the mixture was centrifuged at 10,000g, 4°C for 10 min. The supernatants were carefully removed and the pellets were air dried. The pellets were resuspended in 20 µL of 2.5% SDS, 2.3% DTT, and heated at 95°C for 5 min. After the diluted samples were dissolved in sample buffer (Destreak Solution^TM, GE Healthcare, Chalfont St. Giles, UK), they were applied to pH 3–10 nonlinear IPG strips (Immobiline DryStrips pH 3–10 NL, 18 cm, GE Healthcare) for the first dimension. After 12 h of rehydrating at 30 V, voltage was increased to 500 and 1000 V for 1 h each and then gradually increased to 8000 V within 1 h, where it was kept constant for 12 h.

For the second dimension, we used 12.5% nonlinear polyacrylamide gels in the presence of 10% sodium dodecylsulfate. The gels were subjected to a water-cooled electrophoresis apparatus at 30 mA for 30 min and 100 mA for approximately 4 h. Each sample was run in triplicate to minimize inter-gel variability (9).

Image Analysis
For image analysis, gels were silver stained and matched to a reference gel developed from the pooled sera from the control group. Gels were digitized and images were analyzed using the Phoretix 2D Expression software (Nonlinear Dynamics, Newcastle-upon-Tyne, UK). Specific spots, representing a specific protein, in each gel were matched to a corresponding spot in a reference gel. Normalized spot volumes were generated from the optical densities for each individual spot to the ratio of the spot volumes total in each gel.

Statistical Analysis
We compared the corresponding normalized spot volumes of each single spot between SURV and NON-SURV using analysis of variance. A P value <0.01 was considered statistically significant. Only changes of more than two-fold in the expression factor in at least one group were considered as statistically significant.

Mass Spectrometry
For spot identification, gels with 250 µg protein load were stained with colloidal Coomassie blue and matched to the silver-stained reference gel. The spots of interest were excised, digested in the gel by trypsin, and subjected to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) at the Center for Molecular Medicine (University of Cologne, Cologne, Germany). Bioinformatic data mining was performed using the Mascot platform (http://www.matrixscience.com). A Mascot score more than 63 (P < 0.05) was considered statistically significant (10).

	RESULTS

Top Abstract Introduction METHODS RESULTS DISCUSSION REFERENCES

 
Baseline characteristics in both groups are illustrated in Table 1. Seventeen patients with intraabdominal infection were operated on, and one patient with pyelonephritis was treated with an interventional procedure. In all patients, infection could be confirmed by microbiological studies (Table 1). Initial antibiotic treatment was appropriate in all patients. The patients were divided into two groups, SURV and NON-SURV, at day 28. More than 200 spots could be detected per gel. Seven protein spots were differentially expressed between SURV and NON-SURV, six of which could be identified by mass spectrometry (Table 2). Clustering was identified in two spots, possibly reflecting two isoforms of the protein. Expression factors of the six differentially expressed spots ranged from 0.4 (a down-regulation of 2.5-fold) to 26.5 (an up-regulation of 26.5-fold) in comparison to the control group.

	DISCUSSION

Top Abstract Introduction METHODS RESULTS DISCUSSION REFERENCES

 
Our study yields two major results. First, proteome analysis is a feasible tool to exclude early alterations in protein expression in patients with septic shock. Second, there are specific protein alterations between SURV and NON-SURV at day 28 in an early stage of septic shock.

All samples were obtained within the first 12 h after diagnosis of septic shock, whereby the early stage of sepsis revealed significant differences in protein expression in patients having survived sepsis and septic shock in comparison with NON-SURV (Fig. 1).

View larger version (45K): [in this window] [in a new window]   Figure 1. Typical two-dimensional protein map of serum. Protein separation was performed with immobilized nonlinear pH 3–10 gradient IPG strips (horizontal arrow) and subsequent SDS-PAGE in a 12.5% matrix (vertical arrow shows the direction of a decrease in molecular weight [MW]) followed by silver staining. Spots marked by their numbers show the location of the proteins, which were differentially expressed between SURV and NON-SURV (Table 2).

Six differentially expressed spots could be identified. The Bb Segment of Factor B (spot no. 308, spot no. 320), a member of the alternative pathway of the complement system, provides a first-line defense against infection. Factor B is required for the initiation of this pathway and is a cofactor in antibody-independent monocyte-mediated cytotoxicity (11), macrophage spreading, activation of plasminogen (12), and proliferation of B lymphocytes (13). In our study, SURV exhibited a stronger activation of proteins involved in this pathway (spot no. 308, spot no. 320) than NON-SURV. It may be speculated that there is a more competent immune reaction in SURV.

-1-B-Glycoprotein (spot no. 447) was up-regulated to a greater extent in NON-SURV than in SURV as compared with control. It is a member of the immunoglobulin superfamily and a known plasma protein, whereas its biological function is still not fully known.

Haptoglobin (spot no. 641), an acute phase protein with known genetic polymorphism, demonstrates increased protein levels in inflammation, infection, and cancer (14). Haptoglobin acts as a potent antiinflammatory agent (14). Haptoglobin extenuated lipopolysaccharide-induced inflammation from human monocytes, and has been shown to have antiendotoxic effects in vivo (15). The higher up-regulation of haptoglobin in SURV related to a possible more competent immune reaction needs further investigation.

Clusterin (spot no. 660, spot no. 662) is a multifaceted glycoprotein (16). It is synthesized in many tissues and serves multiple functions (17,18). The predominant hypothesis on the functional role of clusterin is that it is involved in the cellular clearance of toxic substances through its ability to bind to unfolded proteins, cell debris, and immune complexes. We identified clusterin in two spots (Fig. 1), reflecting the ability of a proteome approach to separate proteins with possible posttranslational modifications. Clusterin was highly up-regulated in SURV, with expression factors of 26.5 and 14.9, whereas NON-SURV exhibited only up-regulation levels of 3.1 and 5.9. In acute meningococcal sepsis, clusterin concentrations in plasma were lower in NON-SURV than in SURV (19). Clusterin is potentially protective in leukocyte-induced acute lung injury (20). The mechanism of beneficial effects of higher clusterin concentrations, however, needs further evaluation.

Our study is preliminary, and therefore has several limitations. First, because of the small number of patients, we could not compare plasma profiles from patients of the same gender, which may be of interest. Second, serum proteins often serve as a source for biomarker discovery, especially with a screening method like proteomics. Although a prefractionation step such as the one applied with the albumin and IgG removal kit can assist in the detection of less abundant proteins (6); this procedure may also have eliminated other proteins, including cytokines (21). Therefore, the reported data are only a section of the potentially analyzable blood sample. In further studies, other components of the blood, such as leukocytes, may as well be analyzed by the proteome approach.

Gel-electrophoresis and MALDI-TOF-MS have been used successfully to characterize proteins in a complex mixture. This quantitative approach allowed us to find several proteins of potential interest. The next step could be to use a more quantitative technique, such as ELISA, for the specific proteins differentially expressed in the proteomic approach and their specific role in sepsis.

In conclusion, we here provide the first serum proteome analysis of patients with sepsis and septic shock. Several proteins were found to be differentially expressed in SURV and NON-SURV. The proteins identified in this study are members of inflammation and cytoprotective signaling pathways. Further studies are needed to examine their potential roles as predictive outcome markers, as well as their precise functional roles in sepsis. This study shows that proteomics may be a useful approach in closing the gap towards a comprehensive molecular profiling as compared with genetic studies alone.

	Footnotes

 
Accepted for publication August 8, 2006.

	REFERENCES

Top Abstract Introduction METHODS RESULTS DISCUSSION REFERENCES

 

1. Martin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med 2003;348:1546–54.[Abstract/Free Full Text]
2. Holmes CL, Russell JA, Walley KR. Genetic polymorphisms in sepsis and septic shock: role in prognosis and potential for therapy. Chest 2003;124:1103–15.
3. Calvano SE, Xiao W, Richards DR, et al. A network-based analysis of systemic inflammation in humans. Nature 2005;437: 1032–7.[Medline]
4. Anderson L, Seilhamer J. A comparison of selected mRNA and protein abundances in human liver. Electrophoresis 1997;18: 533–7.[ISI][Medline]
5. Haynes P, Gygi S, Figeys D, Aebersold R. Proteome analysis: biological assay or data archive? Electrophoresis 1998;19: 1862–71.[ISI][Medline]
6. Anderson N, Anderson N. The human plasma proteome: history, character, and diagnostic prospects. Mol Cell Proteomics 2002;1:845–67.[Abstract/Free Full Text]
7. Björhall K, Miliotis T, Davidsson P. Comparison of different depletion strategies for improved resolution in proteomic analysis of human serum samples. Proteomics 2005;5:307–17.[ISI][Medline]
8. Bradford MM. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 1976;72:248–54.[ISI][Medline]
9. Choe L, Lee K. Quantitative and qualitative measure of intralaboratory two-dimensional protein gel reproducibility and the effects of sample preparation, sample load, and image analysis. Electrophoresis 2003;24:3500–7.[ISI][Medline]
10. Perkins D, Pappin D, Creasy D, Cottrell J. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 1999;20:3551–67.[ISI][Medline]
11. Hall RE, Blaese RM, Davis AE III, et al. Cooperative interaction of factor B and other complement components with mononuclear cells in the antibody-independent lysis of xenogeneic erythrocytes. J Exp Med 1982;156:834–43.[Abstract/Free Full Text]
12. Sundsmo J, Gotze O. Human monocyte spreading induced by factor Bb of the alternative pathway of complement activation. A possible role for C5 in monocyte spreading. J Exp Med 1984;154:763–77.
13. Peters M, Ambrus JJ, Fauci A, Brown E. The Bb fragment of complement factor B acts as a B cell growth factor. J Exp Med 1988;168:1225–35.[Abstract/Free Full Text]
14. Dobryszycka W. Biological functions of haptoglobin—new pieces to an old puzzle. Eur J Clin Chem Clin Biochem 1997;35:647–54.[ISI][Medline]
15. Arredouani MS, Kasran A, Vanoirbeek JA, et al. Haptoglobin dampens endotoxin-induced inflammatory effects both in vitro and in vivo. Immunology 2005;114:263–71.[ISI][Medline]
16. Rosenberg M, Silkensen J. Clusterin: physiologic and pathophysiologic considerations. Int J Biochem Cell Biol 1995;27: 633–45.[ISI][Medline]
17. Jones S, Jomary C. Clusterin. Int J Biochem Cell Biol 2002;34: 427–31.[ISI][Medline]
18. Viard I, Wehrli P, Jornot L, et al. Clusterin gene expression mediates resistance to apoptotic cell death induced by heat shock and oxidative stress. J Investig Dermatol 1999;112:290–6.[ISI][Medline]
19. Hogasen K, Mollnes T, Brandtzaeg P. Low levels of vitronectin and clusterin in acute meningococcal disease are closely associated with formation of the terminal-complement complex and the vitronectin-thrombin-antithrombin complex. Infect Immun 1994;62:4874–80.[Abstract/Free Full Text]
20. Heller A, Fiedler F, Braun P, et al. Clusterin protects the lung from leukocyte-induced injury. Shock 2003;20:166–70.[ISI][Medline]
21. Granger J, Siddiqui J, Copeland S, Remick D. Albumin depletion of human plasma also removes low abundance proteins including the cytokines. Proteomics 2005;5:4713–8.[ISI][Medline]

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a colleague Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via ISI Web of Science (2) Citing Articles via Google Scholar Google Scholar Articles by Kalenka, A. Articles by Fiedler, F. Search for Related Content PubMed PubMed Citation Articles by Kalenka, A. Articles by Fiedler, F. Related Collections Critical Care

Anesthesia & Analgesia® is published for the International Anesthesia Research Society® by Lippincott Williams & Wilkins with the assistance of Stanford University Libraries' HighWire Press®. Copyright 2006 by the International Anesthesia Research Society. Online ISSN: 1526-7598   Print ISSN: 0003-2999