Recent progress of proteomics in critical illness

Serum proteomics as a strategy to identify novel biomarkers of neurologic recovery after cardiac arrest: a feasibility study

BACKGROUND

Serum biomarkers may play a role in prognostication after cardiac arrest. This study was designed to assess the feasibility of using two-dimensional gel electrophoresis (2D-GE) coupled with mass spectrometry (MS) as a proteomic strategy to identify novel biomarkers that may predict neurological recovery.

METHODS

Adult comatose survivors of ventricular fibrillation or pulseless ventricular tachycardia were considered eligible. Blood was collected and serum separated within 6 h of hospital admission and then at 24 h afterwards. Neurological outcome was assessed at 3 months with the Cerebral Performance Category (CPC) score. Serum was assessed with 2D-GE with and without prior depletion of high abundance proteins. Protein differences between patients with good (CPC 1,2) vs. poor (CPC 3-5) neurological recovery were subsequently identified with MS.

RESULTS

From August 2010 to June 2014, 11 patients meeting eligibility criteria were recruited, from which serum was available from 9 (5 with good neurological outcome). On non-depleted serum, only high abundance acute phase proteins such as haptoglobin, cell-free hemoglobin, albumin, and amyloid were detected in both patients with good and poor neurological recovery. Following depletion of high abundance proteins, proteins identified by MS in both patient populations were the acute phase reactants c-reactive protein and retinol binding protein-4. Proteins uniquely identified in the serum of patients with poor neurological recovery included 14-3-3 (epsilon and zeta isoforms) and muskelin.

CONCLUSIONS

Two-D-GE coupled with MS is a feasible strategy to facilitate the identification of novel predictive biomarkers. The presence of muskelin and 14-3-3 in the serum of patients with poor neurological prognosis warrants further investigation.

The role of proteomics in understanding biological mechanisms of sepsis

Sepsis is a systemic inflammatory state caused by infection. Complications of this infection with multiple organ failure lead to more lethal conditions, such as severe sepsis and septic shock. Sepsis is one of the leading causes of US deaths. Novel biomarkers with high sensitivity and specificity may be helpful for early diagnosis of sepsis and for improvement of patient outcomes through the development of new therapies. Mass spectrometry-based proteomics offers powerful tools to identify such biomarkers and furthermore to give insight to fundamental mechanisms of this clinical condition. In this review, we summarize findings from proteomics studies of sepsis and how their applications have provided more understanding into the pathogenesis of septic infection. Literatures related to "proteomics", "sepsis", "systemic inflammatory response syndrome", "severe sepsis", "septic infection", and "multiple organ dysfunction syndrome" were searched using PubMed. Findings about neonatal and adult sepsis are discussed separately. Within the adult sepsis studies, results are grouped based on the models (e.g., human or animal). Across investigations in clinical populations and in rodent and mammalian animal models, biological pathways, such as inflammatory and acute phase response, coagulation, complement, mitochondrial energy metabolism, chaperones, and oxidative stress, are altered at the protein level. These proteomics studies have discovered many novel biomarker candidates of septic infection. Validation the clinical use of these biomarker candidates may significantly impact the diagnosis and prognosis of sepsis. In addition, the molecular mechanisms revealed by these studies may also guide the development of more effective treatments.

Bioinformatics insights into acute lung injury/acute respiratory distress syndrome

Bioinformatics is the application of omics science, information technology, mathematics and statistics in the field of biomarker detection. Clinical bioinformatics can be applied for identification and validation of new biomarkers to improve current methods of monitoring disease activity and identify new therapeutic targets. Acute lung injurt (ALI)/Acute respiratory distress syndrome (ARDS) affects a large number of patients with a poor prognosis. The present review mainly focused on the progress in understanding disease heterogeneity through the use of evolving biological, genomic, and genetic approaches and the role of clinical bioinformatics in the pathogenesis and treatment of ALI/ARDS. The remarkable advances in clinical bioinformatics can be a new way for understanding disease pathogenesis, diagnosis and treatment.

Computational approaches for translational clinical research in disease progression

Today, there is an ever-increasing amount of biological and clinical data available that could be used to enhance a systems-based understanding of disease progression through innovative computational analysis. In this article, we review a selection of published research regarding computational methods, primarily from systems biology, which support translational research from the molecular level to the bedside, with a focus on applications in trauma and critical care. Trauma is the leading cause of mortality in Americans younger than 45 years, and its rapid progression offers both opportunities and challenges for computational analysis of trends in molecular patterns associated with outcomes and therapeutic interventions.This review presents methods and domain-specific examples that may inspire the development of new algorithms and computational methods that use both molecular and clinical data for diagnosis, prognosis, and therapy in disease progression.

Biomarkers: the future

The future application of biomarkers in critical illness will be to select and guide therapy. Specific biomarkers could identify a pathophysiologic perturbation or noxious mediator to counteract or the need to replete a deficient protective protein. Functional genomics could identify patients at risk for illness or at risk for a poor outcome in critical illness. Genetic expression studies could help differentiate patients with sepsis from those with noninfectious inflammation and could also help to monitor illnesses over time. Expressional and functional proteomics could lead to the identification of new biomarkers and organ-specific therapies.

Hypoxia-inducible factor 1α regulates the expression of the mitochondrial ATPase inhibitor protein (IF1) in rat liver

A growing number of reports indicate that bioenergetic failure plays a crucial role in the development of multiple organ failure during sepsis. Our previous results showed that the suppression of IF1 (mitochondrial ATPase inhibitor protein) expression and subsequent elevated mitochondrial F(o)F₁-ATPase activity might contribute to the bioenergetic failure in the liver during sepsis, and the influence of the decreased transcriptional level of IF1 might be an important factor. In this study, we investigated the interaction of IF1 protein expression and hypoxia-inducible factor 1 (HIF-1), a transcription factor that is correlated with the inflammatory status in sepsis. The results showed that nuclear HIF-1α protein, a subunit of HIF-1, and IF1 mRNA expression were coincidently reduced in late septic liver of rats. Furthermore, in vitro, overexpression of HIF-1α by hypoxia or CoCl₂ (HIF-1α activator) treatment augmented IF1 protein levels. On the contrary, HIF-1α antisense oligonucleotide and siRNA were used to specifically downregulate HIF-1α expression, and then IF1 protein levels were significantly decreased in clone 9 cells. Meanwhile, downregulation of HIF-1α expression led to elevate the mitochondrial F(o)F₁-ATPase activity in the presence of Bis-Tris buffer (pH 6.5). In conclusion, these results suggested for the first time that the HIF-1 might play a crucial role in regulating IF1 protein expression in late septic liver.

Pathophysiology and treatment of septic shock in neonates

Neonatal septic shock is a devastating condition associated with high morbidity and mortality. Definitions for the sepsis continuum and treatment algorithms specific for premature neonates are needed to improve studies of septic shock and assess benefit from clinical interventions. Unique features of the immature immune system and pathophysiologic responses to sepsis, particularly those of extremely preterm infants, necessitate that clinical trials consider them as a separate group. Keen clinical suspicion and knowledge of risk factors will help to identify those neonates at greatest risk for development of septic shock. Genomic and proteomic approaches, particularly those that use very small sample volumes, will increase our understanding of the pathophysiology and direct the development of novel agents for prevention and treatment of severe sepsis and shock in the neonate. Although at present antimicrobial therapy and supportive care remain the foundation of treatment, in the future immunomodulatory agents are likely to improve outcomes for this vulnerable population.

Differential proteomics of the plasma of individuals with sepsis caused by Acinetobacter baumannii

This study examines alterations in the plasma proteome in ten adults affected by sepsis caused by Acinetobacter baumannii as compared to paired healthy controls. 2-DE profiles of plasma from patients and paired healthy donors, depleted of the six most abundant proteins, were analysed by the DIGE technique. Protein spot detection and quantification were performed with the Differential In-gel Analysis and Biological Variation Analysis modules of the DeCyder() software. Differentially expressed proteins were identified by mass spectrometry (MALDI-TOF/TOF) after colloidal Coomassie blue staining. Almost 900 spots were detected on a unique 2-D gel by the DIGE technique. A total of 269 protein spots of differential abundance were shown to be statistically significant (2.5-fold) with p values of p< or =0.01 (135 spots) and p< or =0.05 (134 spots) as determined by the t test. Seventy-one spots were submitted to mass spectrometry and about 30% could be successfully identified. This multiplex approach significantly reduced experimental variability, allowing for the confident detection of small differences in protein levels. Results include differentially expressed lipoproteins as well as proteins belonging to inflammatory/coagulation pathways and the kallikrein-kinin system. These data improves the knowledge for future developments in sepsis diagnosis, staging and therapy.