Secondary Logo

Journal Logo

Basic Science Aspects

The Metabolopathy of Tissue Injury, Hemorrhagic Shock, and Resuscitation in a Rat Model

Slaughter, Anne L.; Nunns, Geoffrey R.; D’Alessandro, Angelo; Banerjee, Anirban; Hansen, Kirk C.; Moore, Ernest E.∗,‡; Silliman, Christopher C.∗,§,||; Nemkov, Travis; Moore, Hunter B.; Fragoso, Miguel∗,‡; Leasia, Kiara; Peltz, Erik D.

Author Information
doi: 10.1097/SHK.0000000000000948

Abstract

INTRODUCTION

While the overall incidence of postinjury multi-organ failure (MOF) is decreasing the rates of MOF-related resource utilization, morbidity and death are unchanged (1). Thus, despite improvements in prehospital life support, operative technique, and critical care, patients surviving critical injury remain at risk of poor outcome due to postinjury sequelae. Investigation has spanned decades; however, the comprehensive metabolic mechanisms driving these later events remain incompletely defined, limiting superior prognostic biomarkers and treatment targets (2, 3).

Cuthbertson initially described the sequential, metabolic, “ebb” and “flow” phases following injury, recognizing the intrinsic link between cellular anabolic/catabolic disequilibrium and clinical sequelae in the postinjury state (4). Biochemical adaptations acutely facilitate survival by shifting redox balance, and supplying catabolites for substrate-level phosphorylation to generate energy molecules under anoxic conditions (5). However, the resulting loss of homeostasis creates a reactionary system based on the evolving physiologic state, ultimately contributing to acidosis, inflammation, coagulopathy, cardiopulmonary pathophysiology, nitrogen imbalance, and malnutrition (2, 3, 6).

Plasma lactate levels, base deficit, and the anion gap represent traditional indicators of metabolic derangement in the post-shock state (7, 8). Confounding factors such as hypoalbuminemia, respiratory acidosis, and unmeasured anions may compromise sensitivity, specificity, and the diagnostic value of these traditional assessments. A physiochemical approach acknowledges the significance of unmeasured, non-lactate anions in post-traumatic metabolic imbalance (8, 9). Previous investigations have determined that physiochemical models, such as the strong ion gap, provide a better predictor of mortality, particularly in trauma patients with normal admission lactate levels (8). Despite an improved understanding of metabolic derangement in trauma patients, the precise constitution of the postinjury biochemical milieu remains incompletely defined. Recently, advances in Omics technologies (10–12) and the employment of mass spectrometry-based (MS) metabolomics have accommodated the interdependent details of a multicomponent and rapidly evolving cellular response to a variety of insults, including trauma (9, 13, 14). Within this biochemical noise, comprehensive analysis of the metabolome using high-throughput, sensitive, and specific metabolomics technologies simultaneously identifies hundreds of postinjury metabolic derangements.

Using MS-metabolomics to evaluate plasma samples from severely injured trauma patients (15), we have identified an immediate postinjury hypercatabolism with acidic metabolite production from multiple sources such as the tri-carboxylic acid (TCA) cycle, amino acids, free fatty acids, and urate. While this initial human study established the acute metabolic changes observed immediately following traumatic injury, compared with healthy subjects, translation to an animal model was essential to control for the separate components of tissue injury and subsequent shock as these are often concurrent in the human population. Translation to a controlled animal model was also essential to allow serial assessment of the dynamic metabolic changes following injury and shock. Our established rat model of tissue injury (laparotomy), followed by hemorrhagic shock and resuscitation (TI/HS/R), affords tightly controlled experimental conditions while minimizing genetic and environmental variability. This TI/HS/R animal model also provokes clinically relevant lung and kidney injury, and produces significant 12 to 24 h mortality approximating clinical course and outcome seen in severely injured humans (16). This model has been used in a focused fashion to investigate fluxes through the citric acid cycle following TI and HS, which raised interest in global changes with TI, HS, and resuscitation (17).

Better characterization of metabolic changes following critical injury supports accurate prediction, prevention, diagnosis, monitoring, and treatment of the postinjury metabolic aberrations that instigate systemic pathology. The purpose of this study is to evaluate metabolic contributions in a controlled and modifiable animal model of the time course of critical injury using MS-metabolomics analysis.

METHODS

Laboratory animals

Animal experiments were performed under a protocol approved by the Institutional Animal Care and Use Committee at the University of Colorado Denver. All animals were maintained in the accordance with the recommendations of the Guide for the Care and Use of Laboratory Animals. Animals were housed under barrier-sustained conditions with 12-h light–dark cycles and allowed free access to food and water before use. All materials were purchased from Sigma-Aldrich Corp (St. Louis, Mo) unless otherwise specified.

TI/HS/R. Adult male Sprague–Dawley rats (n = 8) weighing 350 g to 490 g (Harlan Labs, Indianapolis, Ind) underwent TI/HS/R (Fig. 1). They were anesthetized with intraperitoneal pentobarbital (50 mg/kg) at the beginning of the model and redosed intravenously (1 mg/kg) as necessary during the procedure. Lidocaine injection was administered at all incision sites for analgesia. A tracheostomy was performed and a tracheostomy tube was placed followed by cannulation of the femoral artery and vein. Femoral artery catheters were connected to Pro-Paq devices (Protocol Systems, Beaverton, Ore) to monitor heart rate and mean arterial pressure. Core body temperature was monitored rectally and normothermia (temperature >36) was maintained with a heat lamp. Pretissue injury (PT) blood samples were obtained, serving as baseline—internal control—for all subsequent time points. Tissue injury was produced with midline laparotomy and evisceration of bowel for 30 min. The bowel was covered with moist gauze during evisceration to prevent evaporative loss and was then replaced into the abdomen and the abdomen was closed. Post-tissue injury (T) blood samples were obtained. Nonlethal HS was induced via controlled hemorrhage from the femoral artery to an MAP of 30 mm Hg, which was maintained for 45 min. Post-shock (S) blood samples were obtained at the start of resuscitation. Animals were resuscitated via the femoral vein with administration of twice shed blood volume in normal saline (NS) over 30 min, half shed blood returned over the subsequent 30 min, and twice shed blood volume in NS over the final 2 h. Post-resuscitation (R) blood samples were obtained at the conclusion of resuscitation (18). A second group of animals (n = 6) underwent tracheostomy, arterial and venous cannulation, tissue injury with laparotomy and evisceration, and blood draws were performed at corresponding time points (PT, T, S, R). These animals were not subjected to HS or resuscitation (Tissue Injury only). All blood samples were heparinized at collection, centrifuged at 5,000 g × 10 min and flash frozen in liquid nitrogen and stored at −80°C (18).

Fig. 1
Fig. 1:
An overview of the experimental design of tissue injury by laparotomy, HS, and resuscitation (TI/HS/R) performed on Sprague–Dawley rats in this study, shock and tissue injury only.

Metabolomics analysis

Plasma samples (10 μL) were immediately extracted in ice-cold lysis/extraction buffer (methanol:acetonitrile:water 5:3:2) at 1:50 dilutions. Samples were then agitated at 4°C for 30 min and then centrifuged at 10,000 g for 15 min at 4°C. Protein pellets were discarded, while supernatants and the lipid fraction were stored at −80°C prior to metabolomics analyses. Ten microliters of sample extracts were injected into an Ultra High Pressure Liquid Chromatography (UHPLC) system (Ultimate 3000, Thermo, San Jose, Calif) and run on a Kinetex XB-C18 column (150 × 2.1 mm i.d., 1.7 μm particle size) (Phenomenex, Torrance, Calif) using either a 3 min isocratic runs (hydrophilic fraction) or a gradient from 5% to 95% B over 9 min (hydrophobic fraction) at 250 μL/min (mobile phase: 5% acetonitrile, 95% 18 mΩ H2O, 0.1% formic acid) (19). The UHPLC system was coupled online with a QExactive system (Thermo, San Jose, Calif), scanning in full MS mode (2 μscans) at 70,000 resolution in the 60 m/z to 900 m/z range (hydrophilic fraction) or 150 m/z to 2000 m/z (hydrophobic fraction), 4 kV spray voltage, 15 sheath gas and five auxiliary gas, operated in negative and then positive ion mode (four separate runs per sample). Calibration was performed before each analysis against positive or negative ion mode calibration mixes (Piercenet—Thermo Fisher, Rockford, Ill) to ensure sub ppm error of the intact mass. Metabolite assignments were performed using the software Maven (20) (Princeton, NJ), upon conversion of raw files into mzXML format through MassMatrix (Cleveland, Ohio). The software allows for peak picking, feature detection, and metabolite assignment against the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. Assignments were further confirmed against chemical formula determination (as gleaned from isotopic patterns and accurate intact mass), and retention times against a >630 standard compounds library including commercially available glycolytic and Krebs cycle intermediates, amino acids, glutathione homeostasis, and nucleoside phosphates (SIGMA Aldrich, St. Louis, Mo; IROATech, Bolton, Mass).

Statistical analysis

Relative quantitation was performed by exporting integrated peak areas values into Excel (Microsoft, Redmond, Calif) for statistical analysis (repeated-measures ANOVA with Tukey multiple column comparison test, significance threshold for P values < 0.01) and partial least square discriminant analysis (PLS-DA), calculated through the macro multibase (freely available at www.NumericalDynamics.com). Hierarchical clustering analysis was performed through the software GENE-E (Broad Institute, Cambridge, Mass). Box and whisker plots were graphed through GraphPad Prism 5.0 (GraphPad Software Inc, La Jolla, Calif) and figure panels were assembled through Photoshop CS5 (Adobe, Mountain View, Calif).

RESULTS

We identified 440 metabolites at each time point against external standards on the basis of the intact mass, isotopic pattern, and chemical composition. A comprehensive list of metabolites are reported in Supplemental Table 1, http://links.lww.com/SHK/A620, including metabolite name, Kyoto Encyclopedia of Genes and Genomes (KEGG) ID, pathway assignment, experimentally observed mass to charge ratios (median values), the polarity in which the metabolites were detected, and fold-change comparison between Tissue Injury only and Shock animals following laparotomy, HS, and resuscitation.

PLS-DA of metabolite levels in each biological replicate is reported in Figure 2. Tissue Injury only and Shock resulted in clustered metabolic phenotypes (Fig. 2A). PC1 + PC2 accounted for 25.8% total covariance (PC1 = 20.3%; PC2 = 5.5%). The top 16 metabolites showing highest covariance across the principal components (PCs) are labeled in Figure 2B. Lactate, TCA cycle intermediate fumarate, and purine catabolites (purine, hypoxanthine, cadaverine, arginine, allantoin, urate) were the key contributors to sample group clustering. Pathway-wise, time-course elaborations of our results detail the graded metabolic response to laparotomy, HS, and resuscitation (Figs. 3–8).

Fig. 2
Fig. 2:
Partial least square analysis of metabolic changes in rat plasma following laparotomy, HS, and resuscitation.
Fig. 3
Fig. 3:
An overview of glycolysis in plasma samples from Shock rats undergoing laparotomy, HS, and resuscitation as compared with Tissue Injury only animals only subjected to laparotomy.
Fig. 4
Fig. 4:
An overview of the tricarboxylic acid (TCA) cycle in plasma samples from Shock rats undergoing laparotomy, HS, and resuscitation as compared with Tissue Injury only animals only subjected to laparotomy.
Fig. 5
Fig. 5:
An overview of the uric acid cycle in plasma samples from Shock rats undergoing laparotomy, HS, and resuscitation as compared with Tissue Injury only animals only subjected to laparotomy.
Fig. 6
Fig. 6:
An overview of fatty acid mobilization and glutathione homeostasis in plasma samples from Shock rats undergoing laparotomy, HS, and resuscitation as compared with Tissue Injury only animals only subjected to laparotomy.
Fig. 7
Fig. 7:
An overview of one-carbon metabolism and the pentose phosphate pathway in plasma samples from shock rats undergoing laparotomy, HS, and resuscitation as compared with tissue injury only animals only subjected to laparotomy.
Fig. 8
Fig. 8:
An overview of sulfur metabolism in plasma samples from Shock rats undergoing laparotomy, HS, and resuscitation as compared with Tissue Injury only animals only subjected to laparotomy.

Glycolysis. Hyperglycemia was observed in all animals following laparotomy compared with baseline (Fig. 3). Lactate rose significantly following HS (P < 0.01), and then normalized following resuscitation when compared with Tissue Injury only. HS and R caused significant increases in key glycolytic metabolites: pyruvate (P < 0.01), fructose bisphosphate (P < 0.01), and ATP (P < 0.01) after resuscitation versus Tissue Injury only.

Tri-carboxylic acid cycle. There were no changes in TCA cycle intermediate levels following laparotomy in comparison to the baseline plasma sample (Fig. 4). Conversely, increased levels of TCA intermediates (citrate, P < 0.001; 2-hydroxyglutarate, P < 0.01; succinate, P < 0.001; fumarate, P < 0.001; and malate, P < 0.01) following HS not seen in the Tissue Injury only group demonstrate a hypoperfusion associated, hyper-catabolic state potentiating acidosis. All of these TCA metabolites normalized to control (Tissue Injury only) levels following resuscitation except for 2-hydroxyglutarate/citramalate. These unexpected metabolites, identified at mass-to-charge ratio 147.029 in negative ion mode, are identical to those identified in our human trauma data (15). Identification of citramalate and 2-hydroxyglutarate was confirmed by accurate intact mass against the KEGG pathway database and brute formula determination as gleaned from isotopic pattern and available standards. These metabolites are not normally identified in plasma and are potentially of non-mammalian, bacterial, origin (P < 0.01 vs. baseline)(15).

Urea cycle and polyamines. There were no significant changes in metabolite levels in the urea cycle due to laparotomy versus Baseline (Fig. 5). Purine catabolism and nitrogen imbalance immediately following HS is evident by the accumulation of purine metabolites (purine (P < 0.001), nicotinamide (P < 0.001), hypoxanthine (P < 0.01), urate (P < 0.001) allantoin (P < 0.01), and allantoate (P < 0.01, data not shown) compared with Tissue Injury group. All of these metabolites except hypoxanthine returned to control plasma levels following resuscitation. Arginine, a precursor to nitric oxide (NO), and its catabolite, cadaverine, decreased following HS (P < 0.01 and P < 0.001, respectively), with normalization of cadaverine following resuscitation although arginine was unaffected. Resuscitation resulted in the progressive accrual of polyamines (spermidine, and spermine, P < 0.01) compared with Tissue Injury only.

Fatty acid metabolism. Tissue injury with laparotomy alone initiated derangements in fatty acid metabolism, specifically mono- and poly-unsaturated fatty acids (Supplemental Table 1, http://links.lww.com/SHK/A620) (Fig. 6). Lipolysis appeared to be provoked by HS following TI as the ketone body hydroxybutyrate increased, but not significantly, and reached a maximal plasma level following resuscitation in the Shock group versus Tissue Injury only (P < 0.001). Fatty acid-mobilization (butanoyl-carnitine and propanoyl-carnitine) showed a similar pattern to hydroxybutyrate with increases identified during HS, which reached statistically significant levels following resuscitation (P < 0.01 and P < 0.001, respectively) when compared with Tissue Injury only. HS following TI resulted in decreased plasma levels of medium chain fatty acids, and conversely, instigated a progressive accumulation of short and long chain fatty acids and poly-unsaturated fatty acids, highlighting a differential metabolic response among fatty acid metabolism (e.g., docosahexaenoic and dodecanedioic acid (P < 0.01) Supplemental Table 1, http://links.lww.com/SHK/A620). Enzymatic and chemical oxidation products of arachidonate metabolism increased in response to Shock, but not Tissue Injury alone (Supplemental Table 1, http://links.lww.com/SHK/A620). As further evidence of ongoing lipolysis, increased levels of phosphocholines and phosphoethanolamines versus control (P < 0.01) were observed following HS, which was not corrected by resuscitation (Supplemental Table 1, http://links.lww.com/SHK/A620). Consistently, lipid head groups increased in the Shock group, but not in the Tissue injury only group (P < 0.01), including glycerol phosphate, ethanolamine phosphate, and glycerol-phosphoethanolamine—Supplemental Table 1, http://links.lww.com/SHK/A620).

Glutathione homeostasis. Metabolite levels within the glutathione redox pathway did not change following laparotomy alone (Fig. 6). However, HS potentiated increases in glutamate and glutathione disulfide (GSSG) (P < 0.01 for both), both of which normalized to Tissue Injury only levels with resuscitation. Despite increases in the total glutathione pool (GSH+GSSG), reduced to oxidized glutathione ratios (GSH/GSSG) decreased following HS (P < 0.001) and normalized with resuscitation versus Tissue Injury only levels. Lastly, 5-oxoproline was increased following resuscitation versus Tissue Injury only levels (P < 0.01)

One-carbon metabolism. Laparotomy did not alter steady-state one-carbon metabolism compared with baseline plasma levels (Fig. 7). Substrate flux through the folate and methionine cycles increased after HS: Methenyltetrahydrofolate, formyltetrahydrofolate, methionine, and S-adenosylhomomethionine (P < 0.01), and resuscitation: folate, tetrahydrofolate, and S-adenosylhomomethionine (P < 0.01). The glutathione precursor cysteine decreased significantly during HS (P < 0.01) and normalized following resuscitation as compared with Tissue Injury only levels.

Pentose phosphate pathway. The metabolites of the pentose phosphate pathway were in dynamic equilibrium following laparotomy alone (Fig. 7); however, sedoheptulose phosphate increased following HS (P < 0.001) versus Tissue Injury only and normalized following resuscitation. Phosphoserine was significantly decreased versus control (P < 0.01), as a consequence of HS following TI and also normalized following resuscitation; however, no significant changes in levels of any other metabolites were observed at any time point when compared with Tissue Injury only. NADPH levels were unaffected by laparotomy, HS, or resuscitation.

Sulfur metabolism. Laparotomy alone did not evoke changes in sulfur metabolism (Fig. 8). The osmoregulator hypotaurine increased during HS and continued to rise during resuscitation (P < 0.01 and P < 0.001, respectively), while taurine increased following resuscitation as well (P < 0.01) compared with Tissue injury only. The precursor metabolite cystathionine increased following HS (P < 0.01); however, a precursor to hydrogen sulfide, thiocysteine, (P < 0.001) decreased following HS compared with Tissue Injury only. Lastly, creatine, but not creatinine, increased following resuscitation (P < 0.001 and P < 0.1, respectively).

DISCUSSION

In the present study, a MS-metabolomics analysis of plasma from our validated TI/HS/R rat model was completed (16). Overall, 440 metabolites were identified for each time point, resulting in the most comprehensive study of the metabolomic time course of critical injury to date. From this analysis the metabolomic contributions were determined for tissue injury by laparotomy alone, HS, and resuscitation, independently and in succession. The reported data demonstrate that tissue injury alone does not significantly alter the plasma metabolome versus baseline, whereas HS following TI instigates immediate and global metabolic change with numerous metabolites increasing despite resuscitation with NS and blood (volume = twice the shed blood in NS followed by 50% of the shed blood, then another twice the shed blood in NS) and some metabolites remaining unchanged regardless of the intervention, e.g., cystine, homocysteine, creatinine, glycine, NADPH, glutamine, alanine, carnitine, and citrulline. For the increases in circulating metabolites from glycolysis and the TCA cycle, resuscitation selectively corrected discrete metabolites elevations toward preinjury baseline (i.e., select TCA intermediates and lactate) while other metabolites within the same metabolic pathways remain elevated (i.e., ATP, pyruvate, fructose bisphosphate). This selective metabolic correction invokes biochemical regulation with resuscitation and restoration of perfusion beyond a simple dilutional explanation related to the volume of resuscitation provided. Additional shock-related metabolopathies persist within the urea cycle, polyamine, and arginine metabolism, and lipolysis with discrete metabolite levels continuing to increase to maximally observed levels after blood and NS resuscitation.

Isotopic analysis of pathways will define to what extent shock plasma metabolomes represent deregulation or reduced delivery/clearance of metabolites, and post-resuscitation metabolomes reflect dilution, continued metabolic evolution, or return to baseline homeostasis. However, regardless of mechanism the circulating plasma concentrations presented in this analysis constitute the biochemical milieu that is delivered to the tissue, generating hypotheses about how the cell might respond to a given post-shock and post-resuscitation environment. Furthermore, it is not implicitly clear if metabolopathies following shock represent survival-supporting metabolic adaptations or pathologic derangement. The answer is likely dichotomous, and will require targeted investigations that alter specific metabolopathies identified by this comprehensive analysis to determine physiologic consequence.

Hyperglycemia following injury is well recognized, with contribution from hormone-mediated glycogenolysis, gluconeogenesis, and insulin resistance (21). These mechanisms provide glucose for tissues but also potentiate stress hyperglycemia, an independent risk factor for increased rates of infection, MOF, and mortality (22). These results confirm that tissue injury and HS deregulate the glycolytic pathway. Shock worsens hyperglycemia initiated by tissue injury; however, glucose concentration returns to pre-injury levels by the post-resuscitation time point.

Lactate is a longstanding clinical biomarker of poorly perfused tissue beds, often becoming a key measure in therapeutic and operative decision thresholds. These data support using lactate concentrations to warn of ongoing ischemia, because tissue injury alone was not sufficient to increase lactate levels, whereas subsequent shock was. Although resuscitation normalizes lactate concentrations in this model, it is important to recognize that shock-instigated metabolic derangements persist in many other pathways despite resuscitation. Thus, emphasizing lactate as a single endpoint in resuscitation ignores the immediate and ongoing metabolopathies within other pathways that contribute to acidosis, coagulopathy, inflammation, and malnutrition (3, 8, 23).

Severe injury provokes the accumulation of TCA cycle intermediates (15). The present data support this finding and further delineate that only the addition of HS to TI instigates accumulation of citrate, malate, succinate, and fumarate while tissue injury alone does not significantly alter TCA cycle steady state. These data corroborate longstanding clinical investigations describing changes in TCA cycle intermediate levels under anoxic/hypoxic conditions (5, 24). Increases in the plasma concentrations of these compounds likely represent both survival-supporting metabolic adaptations and pathologic derangements. Previous investigation has found that elevated levels of fumarate and succinate appropriately contribute to the hypoxic response by upregulating HIF1α (25), and that succinate accumulates due to substrate-level phosphorylation in the mitochondria to generate high-energy molecules under anoxic conditions (5).

However, TCA cycle intermediates have also been implicated in postinjury metabolic acidosis, ischemia/reperfusion injury, inflammation, and coagulopathy (8, 15, 24, 26, 27). Non-hemorrhagic ischemia/reperfusion models have recently demonstrated that concentrated succinate ultimately generates mitochondrial reactive oxygen species (ROS) byproducts upon reperfusion, capable of inducing IL-1β (24, 27). The presented data demonstrated similar succinate fluxes during hemorrhage and resuscitation, highlighting the potential for increased levels of succinate to contribute to oxidative stress and inflammation following critical injury.

Postinjury hypercatabolism in trauma patients is well documented and contributes to malnutrition, sepsis, MOF, and death (23, 28, 29). The presented results highlight that catabolism following severe injury is immediate, instigated by shock following tissue injury, and not fully attenuated by fluid/blood product resuscitation. Altered purine and arginine metabolism after shock indicates immediate nitrogen imbalance, and the potential to exacerbate acidosis via catabolite flux into the TCA cycle. However, elevated concentrations of certain catabolites, e.g., polyamines, taurine, and urate, support redox equipoise, osmoregulation, and pH balance mechanisms that are critical in maintaining homeostatic balance during systemic disturbance (30).

Arginine anabolic/catabolic disequilibrium contributes to dysregulated NO synthesis as demonstrated in a variety of disease states including cardiovascular disease, sepsis, liver failure, and cancer (31). In septic patients, decreased arginine levels correlate to worse survival (29). Documented here, arginine concentrations acutely decrease following HS and not with tissue injury alone. Importantly, citrulline—a cocontributor to NO synthesis—does not decrease, suggesting an alternative arginine catabolic by-product. For example, the polyamines spermine and spermidine accumulate during resuscitation. Polyamines are highly alkaline amino acid catabolites that can buffer pH, scavenge for reactive oxygen species and serve as osmolar agents (30), and have been previously reported in urine from trauma patients (32). The reported data suggest that increased concentrations may not simply be excreted by products of trauma-induced proteolysis, but rather are accumulating following the deregulation of multiple metabolic pathways with the potential to actively contribute to post-shock milieu. Experimental animal models that modulate these pathways are important next steps in designing resuscitation schema that exploit the homeostatic benefits of catabolites acutely following severe injury while supporting anabolic/catabolic balance during recovery.

In 2010, Cohen et al. (9) reported that evidence of disturbed lipid metabolism in severely injured trauma patients was the strongest predictor of clinical outcome. Aberrant levels of circulating lipid metabolites in trauma patients, when compared with healthy controls, were thought to reflect acutely dysfunctional metabolism within the liver, cell lysis, activated coagulation/fibrinolysis, and increased inflammation. The data from this controlled model present parallel findings, and delineate that the conditions of HS potentiate deregulation initiated by tissue injury and persist following resuscitation with NS and whole blood.

The reported data also demonstrate an increased concentration of the ketone body hydroxybutyrate during resuscitation, highlighting a possible cellular attempt at surviving shock stress. Hydroxybutyrate, mimicking the action of insulin, increases the efficiency of mitochondrial energy production, which corrects acidosis, prevents the generation of ROS, and stabilizes the ion gradients that contribute to cellular lysis (33, 34). As such, hydroxybutyrate has been suggested as a supplement in resuscitative fluids for critically ill patients. Our results support this as a potential therapeutic strategy in severely injured trauma patients to augment cellular metabolic adaptation in the post-shock state.

Anti-oxidant/oxidant imbalance under pathophysiologic conditions, such as ischemia/reperfusion, generates oxidative stress, contributing significantly to inflammation. Deviations in reduced/oxidized glutathione ratios have been correlated to cellular proliferation, differentiation, and death (24, 35), with implications for inflammation and organ failure. In the reported model tissue injury alone does not create anti-oxidant/oxidant imbalance, as metabolites within the glutathione redox pathway remain in steady state at the post-laparotomy time point. By contrast, the addition of HS to TI predictably generates oxidative stress as evidenced by a relative increase in oxidized glutathione with resultant decrease in the GSH/GSSG ratio, and this ratio did normalize following resuscitation. HS following TI also instigated the accumulation of glutathione catabolite, 5-oxoproline, a compound that has been previously associated with metabolic acidosis, representing an additional non-lactate contribution to acid/base imbalance (36). Unlike TCA intermediates, the increase in 5-oxoproline concentrations was not reversed by resuscitation.

When compared with prior experimental work in this field we see both similarities and differences. In a review of critically injured patients with heterogeneous combinations of HS and TI, there was an immediate postinjury hypercatabolic state with production of acidic metabolites from diverse pathways (15). Both the previous human study and this animal investigation reveal the hypermetabolic state following TI and HS, with accumulation of citric acid cycle intermediates, lipolysis, breakdown of nucleosides, and the presence of bacterial metabolites. However, the controlled animal model in this current study allows us to highlight the central role of TI/HS in producing these changes, rather than isolated TI. Additionally, this study provides a description of the role of resuscitation on either attenuating these changes (such as lactic acidosis) or exacerbating them (as in fatty acid pathways). Likewise, in a similar controlled animal model evaluating specific substrate contribution to Krebs cycle pathways we identified similar changes in both glycolysis and Krebs cycle pathway metabolites following TI/HS versus TI alone (17). The limited role of TI as opposed to TI/HS in producing metabolomics perturbations was reinforced here with a more extensive examination of other pathways.

This study has several potential limitations. We elected to study only isolated TI or combined TI/HS, and therefore these data cannot be extrapolated to the effects of isolated HS. However, isolated HS is an entity seen in other settings such as gastrointestinal or post-partum hemorrhage, and not in the trauma population of interest; therefore, it was not studied here. Additionally, all animals used in this study were male, which limits its applicability somewhat. However, female rats are resistant to organ dysfunction following trauma and hemorrhagic shock, rendering them a poor choice for simulating the human trauma population with a high burden of organ dysfunction (1, 37). Therefore, we elected to use a male rat model that has been shown to produce post-injury organ dysfunction (16).

This animal model highlights the acute changes in response to tissue injury, HS, and resuscitation but cannot be extrapolated to clinical outcome or progressive organ failure and survival. Longer survival models would provide for better correlation of acute metabolic phenotypes with later clinical morbidity and outcome. Survival models would also provide clinical end-points to assess the efficacy of early, targeted therapeutic strategies in metabolomic resuscitation aimed at preventing the development of clinical sequelae. While we cannot correlate specific metabolic profiles to clinical endpoints, this TI/HS/R animal model does provoke acute lung and kidney injury, as well as significant 12 to 24 h mortality (16). Future comparison of plasma and organ-specific “biofluid” metabolomes—e.g., bronchoalveolar lavage fluid—may better elucidate culprit mediators for organ-specific pathology.

This animal model reflects a discrete tissue injury from laparotomy and evisceration which cannot be extrapolated to the poly-trauma often encountered in human patients. Human trauma patients with severe shock often experience combine poly-trauma, with multiple sources of tissue injury, and uncontrolled hemorrhage. This is difficult to replicate in a controlled model while maintaining experimental control of distinct tissue injury and subsequent hemorrhagic contributions to pathologic response. In this investigation we chose a discrete, reproducible, tissue injury mechanism, which does not significantly contribute to additional uncontrolled blood loss as can occur with poly-trauma (i.e., solid organ injury of liver or spleen, or long bone fractures, etc.). Laparotomy and evisceration in this model does provide a discrete tissue injury with identifiable metabolic derangements that are experimentally separated from those potentiated by hemorrhagic shock. While this allows for a controlled comparison of two potential components to post-traumatic metabolic derangement this mild, specific, tissue injury does not replicate a poly-trauma injury mechanism seen in human trauma patients and cannot be widely generalized. Alternate tissue injury patterns may exert different, unique metabolic derangements (i.e., femur fracture, pelvic fracture, rib fracture with flail chest or solid organ injury of liver, spleen or kidney, etc.). For example, in our human study, proteolysis was seen which was not reproduced here, which may be due to a lesser degree of tissue injury in our experimental model (15). The foundational description provided in this investigation establishes a baseline for the differential effects of tissue injury and shock, and may allow for important future studies of specific organ injuries, multiple organ injuries, and combined injury patterns (i.e., orthopedic, thoracic, abdominal) with and without hemorrhagic shock. These injury mechanisms, as well as traumatic brain injury are future directions that would be important to study and would allow accurate translation to human poly-trauma patients.

Resuscitation schema for trauma patients with hemorrhagic shock has experienced a significant transition from historically high volumes of crystalloids to current resuscitation pathways using blood products administered either in specific ratios of PRBC:FFP or specific blood component resuscitation directed by whole blood clotting assays (TEG or ROTEM). Blood product resuscitation is clinically most applicable upon patient arrival to the hospital, with many prehospital systems lacking capabilities to deliver blood products in the field. Largely, the prehospital support of profound hemorrhagic shock continues to rely on administration of crystalloid solutions. This controlled animal model was designed to reflect this clinical care of human trauma patients with initial crystalloid resuscitation, followed by blood product administration, and then ongoing support with crystalloids after control of hemorrhage and correction of coagulopathy. Crystalloid resuscitation in this model may impart metabolic aberrations by contributing to a hyperchloremic metabolic acidosis and subsequent downstream implications on compensatory metabolic mechanisms. While this reflects clinically relevant resuscitation strategies in use, and metabolic stimuli in human trauma patients, future investigation should evaluate comparative crystalloid or blood product resuscitation strategies, the effects of initial permissive hypotension with limited crystalloid and initial blood product resuscitation in lieu of any crystalloids for the support of hemorrhagic shock. These future studies could better evaluate the relative ability of crystalloid or blood product resuscitation to attenuate or correct the diverse metabolic dysfunction described in this study. This comprehensive time-course description of post-shock metabolopathy in a controlled model provides the foundation for these important future investigations.

CONCLUSION

Based on the reported results, we conclude that MS-metabolomics can be translated to a controlled animal model of severe traumatic injury, providing a time-course analysis of the metabolic evolution following trauma, HS, and resuscitation. Importantly, tissue injury alone does not instigate broad metabolic aberration, while TI/HS provokes significant metabolic changes in all major pathways, some of which may be normalized by resuscitation with intravenous fluid and whole blood. This type of resuscitation corrects multicomponent metabolic acidosis, while hypercatabolic metabolopathies persist in most pathways at the post-resuscitation time point. Results from this investigation are hypothesis-generating in that they identify potentially beneficial and pathogenic metabolic mediators in the post-shock state. Future experiments designed to isolate, manipulate, and supplement individual metabolic pathways will elucidate the precise contributions of specific substrates to postinjury systemic sequelae.

REFERENCES

1. Sauaia A, Moore EE, Johnson JL, Chin TL, Banerjee A, Sperry JL, Maier RV, Burlew CC. Temporal trends of postinjury multiple-organ failure: still resource intensive, morbid, and lethal. J Trauma Acute Care Surg 2014; 76 3:582–592.
2. Moore FA, Moore EE. Evolving concepts in the pathogenesis of postinjury multiple organ failure. Surg Clin North Am 1995; 75 2:257–277.
3. Lenz A, Franklin GA, Cheadle WG. Systemic inflammation after trauma. Injury 2007; 38 12:1336–1345.
4. Cuthbertson DP. Post-shock metabolic response. Lancet 1942; 1:433–437.
5. Chinopoulos C. Which way does the citric acid cycle turn during hypoxia? The critical role of alpha-ketoglutarate dehydrogenase complex. J Neurosci Res 2013; 91 8:1030–1043.
6. Moore FA, McKinley BA, Moore EE, Nathens AB, West M, Shapiro MB, Bankey P, Freeman B, Harbrecht BG, Johnson JL, et al. Inflammation and the Host Response to Injury, a large-scale collaborative project: patient-oriented research core—standard operating procedures for clinical care. III. Guidelines for shock resuscitation. J Trauma 2006; 61 1:82–89.
7. Kaplan LJ, Kellum JA. Initial pH, base deficit, lactate, anion gap, strong ion difference, and strong ion gap predict outcome from major vascular injury. Crit Care Med 2004; 32 5:1120–1124.
8. Martin M, Murray J, Berne T, Demetriades D, Belzberg H. Diagnosis of acid-base derangements and mortality prediction in the trauma intensive care unit: the physiochemical approach. J Trauma 2005; 58 2:238–243.
9. Cohen MJ, Serkova NJ, Wiener-Kronish J, Pittet JF, Niemann CU. 1H-NMR-based metabolic signatures of clinical outcomes in trauma patients—beyond lactate and base deficit. J Trauma 2010; 69 1:31–40.
10. Serkova NJ, Standiford TJ, Stringer KA. The emerging field of quantitative blood metabolomics for biomarker discovery in critical illnesses. Am J Respir Crit Care Med 2011; 184 6:647–655.
11. Buescher JM, Moco S, Sauer U, Zamboni N. Ultrahigh performance liquid chromatography-tandem mass spectrometry method for fast and robust quantification of anionic and aromatic metabolites. Anal Chem 2010; 82 11:4403–4412.
12. Dzieciatkowska M, Wohlauer MV, Moore EE, Damle S, Peltz E, Campsen J, Kelher M, Silliman C, Banerjee A, Hansen KC. Proteomic analysis of human mesenteric lymph. Shock 2011; 35 4:331–338.
13. Dettmer K, Aronov PA, Hammock BD. Mass spectrometry-based metabolomics. Mass Spectrom Rev 2007; 26 1:51–78.
14. Kinross JM, Alkhamesi N, Barton RH, Silk DB, Yap IK, Darzi AW, Holmes E, Nicholson JK. Global metabolic phenotyping in an experimental laparotomy model of surgical trauma. J Proteome Res 2011; 10 1:277–287.
15. Peltz ED, D’Alessandro A, Moore EE, Chin T, Silliman CC, Sauaia A, Hansen KC, Banerjee A. Pathologic metabolism: an exploratory study of the plasma metabolome of critical injury. J Trauma Acute Care Surg 2015; 78 4:742–751.
16. Masuno T, Moore EE, Cheng AM, Sarin EL, Banerjee A. Bioactivity of postshock mesenteric lymph depends on the depth and duration of hemorrhagic shock. Shock 2006; 26 3:285–289.
17. D’Alessandro A, Slaughter AL, Peltz ED, Moore EE, Silliman CC, Wither M, Nemkov T, Bacon AW, Fragoso M, Banerjee A, et al. Trauma/hemorrhagic shock instigates aberrant metabolic flux through glycolytic pathways, as revealed by preliminary (13)C-glucose labeling metabolomics. J Transl Med 2015; 13:253.
18. Peltz ED, Moore EE, Zurawel AA, Jordan JR, Damle SS, Redzic JS, Masuno T, Eun J, Hansen KC, Banerjee A. Proteome and system ontology of hemorrhagic shock: exploring early constitutive changes in postshock mesenteric lymph. Surgery 2009; 146 2:347–357.
19. Nemkov T, Hansen KC, D’Alessandro A. A three-minute method for high-throughput quantitative metabolomics and quantitative tracing experiments of central carbon and nitrogen pathways. Rapid Commun Mass Spectrom 2017; 31 8:663–673.
20. Clasquin MF, Melamud E, Rabinowitz JD. LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine. Curr Protoc Bioinformatics Chapter 14:Unit14.11, 2012.
21. Li L, Messina JL. Acute insulin resistance following injury. Trends Endocrinol Metab 2009; 20 9:429–435.
22. van den Berghe G, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P, Bouillon R. Intensive insulin therapy in critically ill patients. N Engl J Med 2001; 345 19:1359–1367.
23. Hasenboehler E, Williams A, Leinhase I, Morgan SJ, Smith WR, Moore EE, Stahel PF. Metabolic changes after polytrauma: an imperative for early nutritional support. World J Emerg Surg 2006; 1:29.
24. Chouchani ET, Pell VR, Gaude E, Aksentijevic D, Sundier SY, Robb EL, Logan A, Nadtochiy SM, Ord EN, Smith AC, et al. Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS. Nature 2014; 515 7527:431–435.
25. Serra-Perez A, Planas AM, Nunez-O’Mara A, Berra E, Garcia-Villoria J, Ribes A, Santalucia T. Extended ischemia prevents HIF1alpha degradation at reoxygenation by impairing prolyl-hydroxylation: role of Krebs cycle metabolites. J Biol Chem 2010; 285 24:18217–18224.
26. Forni LG, McKinnon W, Lord GA, Treacher DF, Peron JM, Hilton PJ. Circulating anions usually associated with the Krebs cycle in patients with metabolic acidosis. Crit care 2005; 9 5:R591–R595.
27. Tannahill GM, Curtis AM, Adamik J, Palsson-McDermott EM, McGettrick AF, Goel G, Frezza C, Bernard NJ, Kelly B, Foley NH, et al. Succinate is an inflammatory signal that induces IL-1beta through HIF-1alpha. Nature 2013; 496 7444:238–242.
28. Moldawer LL, Bistrian BR, Sobrado J, Blackburn GL. Muscle proteolysis in sepsis or trauma. N Engl J Med 1983; 309 8:494–495.
29. Freund H, Atamian S, Holroyde J, Fischer JE. Plasma amino acids as predictors of the severity and outcome of sepsis. Ann Surg 1979; 190 5:571–576.
30. Zahedi K, Huttinger F, Morrison R, Murray-Stewart T, Casero RA, Strauss KI. Polyamine catabolism is enhanced after traumatic brain injury. J Neurotrauma 2010; 27 3:515–525.
31. Luiking YC, Ten Have GA, Wolfe RR, Deutz NE. Arginine de novo and nitric oxide production in disease states. Am J Physiol Endocrinol Metab 2012; 303 10:E1177–E1189.
32. Jeevanandam M, Ali MR, Young DH, Schiller WR. Polyamine levels as biomarkers of injury response in polytrauma victims. Metabolism 1989; 38 7:625–630.
33. Robert Valeri C, Veech RL. The unrecognized effects of the volume and composition of the resuscitation fluid used during the administration of blood products. Transfus Apher Sci 2012; 46 2:121–123.
34. Youm YH, Nguyen KY, Grant RW, Goldberg EL, Bodogai M, Kim D, D’Agostino D, Planavsky N, Lupfer C, Kanneganti TD, et al. The ketone metabolite beta-hydroxybutyrate blocks NLRP3 inflammasome-mediated inflammatory disease. Nat Med 2015; 21 3:263–269.
35. Banerjee R. Redox outside the box: linking extracellular redox remodeling with intracellular redox metabolism. J Biol Chem 2012; 287 7:4397–4402.
36. Fenves AZ, Kirkpatrick HM 3rd, Patel VV, Sweetman L, Emmett M. Increased anion gap metabolic acidosis as a result of 5-oxoproline (pyroglutamic acid): a role for acetaminophen. Clin J Am Soc Nephrol 2006; 1 3:441–447.
37. Ananthakrishnan P, Cohen DB, Xu DZ, Lu Q, Feketeova E, Deitch EA. Sex hormones modulate distant organ injury in both a trauma/hemorrhagic shock model and a burn model. Surgery 2005; 137 1:56–65.
Keywords:

Acidosis; catabolism; mass spectrometry; metabolomics; metabolopathy

Supplemental Digital Content

Copyright © 2017 by the Shock Society