Plasma proteome response to severe burn injury revealed by 18O-labeled "universal" reference-based quantitative proteomics

Inflammatory proteins and neutrophil extracellular traps increase in burn blister fluid 24h after burn

Burn wound blister fluid is a valuable matrix for understanding the biological pathways associated with burn injury. In this study, 152 blister fluid samples collected from paediatric burn wounds at three different hospitals were analysed using mass spectrometry proteomic techniques. The protein abundance profile at different days after burn indicated more proteins were associated with cellular damage/repair in the first 24 h, whereas after this point more proteins were associated with antimicrobial defence. The inflammatory proteins persisted at a high level in the blister fluid for more than 7 days. This may indicate that removal of burn blisters prior to two days after burn is optimal to prevent excessive or prolonged inflammation in the wound environment. Additionally, many proteins associated with the neutrophil extracellular trap (NET) pathway were increased after burn, further implicating NETs in the post-burn inflammatory response. NET inhibitors may therefore be a potential treatment to reduce post-burn inflammation and coagulation pathology and enhance burn wound healing outcomes.

Local burn wound environment versus systemic response: Comparison of proteins and metabolites

In this study, paired blood plasma (BP) and blister fluid (BF) samples from five paediatric burn patients were analysed using mass spectrometry to compare their protein and metabolite composition. The relative quantification of proteins was achieved through a label-free data independent acquisition mode. The relative quantification of metabolites was achieved using a Shimadzu Smart Metabolite Database gas chromatography mass spectrometry (GCMS) targeted assay. In total, 562 proteins and 141 individual metabolites were identified in the samples. There was 81% similarity in the proteins present in the BP and BF, with 50 and 54 unique proteins found in each sample type respectively. BF contained keratinocyte proliferation-related proteins and blood plasma contained abundant blood clotting proteins and apolipoproteins. BF contained more carbohydrates and less alpha-hydroxy acid metabolites than the BP. In this study, there were unique proteins and metabolites in BF and BP which were reflective of the local wound environment and systemic environments respectively. The results from this study demonstrate that the biomolecule content of BF is mostly the same as blood, but it also contains information specific to the local wound environment.

Multi-Site Observational Study to Assess Biomarkers for Susceptibility or Resilience to Chronic Pain: The Acute to Chronic Pain Signatures (A2CPS) Study Protocol

Chronic pain has become a global health problem contributing to years lived with disability and reduced quality of life. Advances in the clinical management of chronic pain have been limited due to incomplete understanding of the multiple risk factors and molecular mechanisms that contribute to the development of chronic pain. The Acute to Chronic Pain Signatures (A2CPS) Program aims to characterize the predictive nature of biomarkers (brain imaging, high-throughput molecular screening techniques, or "omics," quantitative sensory testing, patient-reported outcome assessments and functional assessments) to identify individuals who will develop chronic pain following surgical intervention. The A2CPS is a multisite observational study investigating biomarkers and collective biosignatures (a combination of several individual biomarkers) that predict susceptibility or resilience to the development of chronic pain following knee arthroplasty and thoracic surgery. This manuscript provides an overview of data collection methods and procedures designed to standardize data collection across multiple clinical sites and institutions. Pain-related biomarkers are evaluated before surgery and up to 3 months after surgery for use as predictors of patient reported outcomes 6 months after surgery. The dataset from this prospective observational study will be available for researchers internal and external to the A2CPS Consortium to advance understanding of the transition from acute to chronic postsurgical pain.

A Multidimensional Bioinformatic Platform for the Study of Human Response to Surgery

OBJECTIVE

To design and establish a prospective biospecimen repository that integrates multi-omics assays with clinical data to study mechanisms of controlled injury and healing.

SUMMARY BACKGROUND DATA

Elective surgery is an opportunity to understand both the systemic and focal responses accompanying controlled and well-characterized injury to the human body. The overarching goal of this ongoing project is to define stereotypical responses to surgical injury, with the translational purpose of identifying targetable pathways involved in healing and resilience, and variations indicative of aberrant peri-operative outcomes.

METHODS

Clinical data from the electronic medical record combined with large-scale biological data sets derived from blood, urine, fecal matter, and tissue samples are collected prospectively through the peri-operative period on patients undergoing fourteen surgeries chosen to represent a range of injury locations and intensities. Specimens are subjected to genomic, transcriptomic, proteomic, and metabolomic assays to describe their genetic, metabolic, immunologic, and microbiome profiles, providing a multidimensional landscape of the human response to injury.

RESULTS

The highly multiplexed data generated includes changes in over 28,000 mRNA transcripts, 100 plasma metabolites, 200 urine metabolites, and 400 proteins over the longitudinal course of surgery and recovery. In our initial pilot dataset, we demonstrate the feasibility of collecting high quality multi-omic data at pre- and post-operative time points and are already seeing evidence of physiologic perturbation between timepoints.

CONCLUSIONS

This repository allows for longitudinal, state-of-the-art genomic, transcriptomic, proteomic, metabolomic, immunologic, and clinical data collection and provides a rich and stable infrastructure on which to fuel further biomedical discovery.

18Oxygen Substituted Nucleosides Combined with Proton Beam Therapy: Therapeutic Transmutation In Vitro

Purpose

Proton therapy precisely delivers radiation to cancers to cause damaging strand breaks to cellular DNA, kill malignant cells, and stop tumor growth. Therapeutic protons also generate short-lived activated nuclei of carbon, oxygen, and nitrogen atoms in patients as a result of atomic transmutations that are imaged by positron emission tomography (PET). We hypothesized that the transition of ¹⁸O to ¹⁸F in an ¹⁸O-substituted nucleoside irradiated with therapeutic protons may result in the potential for combined diagnosis and treatment for cancer with proton therapy.

Materials and Methods

Reported here is a feasibility study with a therapeutic proton beam used to irradiate H₂¹⁸O to a dose of 10 Gy produced by an 85 MeV pristine Bragg peak. PET imaging initiated >45 minutes later showed an ¹⁸F decay signal with T_1/2 of ∼111 minutes.

Results

The ¹⁸O to ¹⁸F transmutation effect on cell survival was tested by exposing SQ20B squamous carcinoma cells to physiologic ¹⁸O-thymidine concentrations of 5 μM for 48 hours followed by 1- to 9-Gy graded doses of proton radiation given 24 hours later. Survival analyses show radiation sensitization with a dose modification factor (DMF) of 1.2.

Conclusions

These data support the idea of therapeutic transmutation in vitro as a biochemical consequence of proton activation of ¹⁸O to ¹⁸F in substituted thymidine enabling proton radiation enhancement in a cancer cell. ¹⁸O-substituted molecules that incorporate into cancer targets may hold promise for improving the therapeutic window of protons and can be evaluated further for postproton therapy PET imaging.

Human body-fluid proteome: quantitative profiling and computational prediction

Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.

Meta-analysis of peptides to detect protein significance

Shotgun assays are widely used in biotechnologies to characterize large molecules, which are hard to be measured as a whole directly. For instance, in Liquid Chromatography - Mass Spectrometry (LC-MS) shotgun experiments, proteins in biological samples are digested into peptides, and then peptides are separated and measured. However, in proteomics study, investigators are usually interested in the performance of the whole proteins instead of those peptide fragments. In light of meta-analysis, we propose an adaptive thresholding method to select informative peptides, and combine peptide-level models to protein-level analysis. The meta-analysis procedure and modeling rationale can be adapted to data analysis of other types of shotgun assays.

Gene and Biochemical Pathway Evaluation of Burns Injury via Protein-Protein Interaction Network Analysis

Background:

Severe burns injury can affect several vital systems in the body and can cause inflammation in organs such as the heart, liver, and kidney. Many inflammatory mediators and regulatory hormones related to burn injuries are recognized. In this study, the genes related to burn injury interacted via network analysis, and the central nodes were enriched through gene ontology (GO).

Materials and Methods:

Disease query of STRING database was used for data gathering, and the network was constructed using Cytoscape software version 3.6.0. After gene screening, the central nodes were enriched via GO analysis by ClueGO. The highlighted genes and pathways were clustered and analyzed in detail.

Results:

Among 1067 genes, 35 critical genes that are involved in the 14 highlighted biochemical pathways were recognized. Interpretation of the finding indicates that a number of central genes can be considered as potential biomarkers related to burn injury.

Conclusion:

Can we revise to "Burn injuries have features that are common to several diseases and increases their risk.

Metabolomics and Precision Medicine in Trauma: The State of the Field

Trauma is a major problem in the United States. Mortality from trauma is the number one cause of death under the age of 45 in the United States and is the third leading cause of death for all age groups. There are approximately 200,000 deaths per year due to trauma in the United States at a cost of over $671 billion in combined healthcare costs and lost productivity. Unsurprisingly, trauma accounts for approximately 30% of all life-years lost in the United States. Due to immense development of trauma systems, a large majority of trauma patients survive the injury, but then go on to die from complications arising from the injury. These complications are marked by early and significant metabolic changes accompanied by inflammatory responses that lead to progressive organ failure and, ultimately, death. Early resuscitative and surgical interventions followed by close monitoring to identify and rescue treatment failures are key to successful outcomes. Currently, the adequacy of resuscitation is measured using vital signs, noninvasive methods such as bedside echocardiography or stroke volume variation, and other laboratory endpoints of resuscitation, such as lactate and base deficit. However, these methods may be too crude to understand cellular and subcellular changes that may be occurring in trauma patients. Better diagnostic and therapeutic markers are needed to assess the adequacy of interventions and monitor responses at a cellular and subcellular level and inform clinical decision-making before complications are clinically apparent. The developing field of metabolomics holds great promise in the identification and application of biochemical markers toward the clinical decision-making process.

Vitamin D status and its influence on outcomes following major burn injury and critical illness

Vitamin D deficiency is common among the general population. It is also observed in up to 76% of critically ill patients. Despite the high prevalence of hypovitaminosis D in critical illness, vitamin D is often overlooked by medical staff as the clinical implications and consequences of vitamin D deficiency in acute contexts remain to be fully understood. Vitamin D has a broad range of pleotropic effects on various processes and systems including the immune-inflammatory response. 1α,25-dihydroxyvitamin D (1,25(OH)₂D), has been shown to promote a tolerogenic immune response limiting deleterious inflammatory effects, modulation of the innate immune system, and enhancement of anti-microbial peptides. Vitamin D deficiency is frequently observed in critically ill patients and has been related to extrinsic causes (i.e., limited sunlight exposure), magnitude of injury/illness, or the treatment started by medical doctors including fluid resuscitation. Low levels of vitamin D in critically ill patients have been associated with sepsis, organ failure, and mortality. Despite this, there are subpopulations of critical illness, such as burn patients, where the literature regarding vitamin D status and its influence on outcomes remain insufficient. Thermal injury results in damage to both burned and non-burned tissues, as well as induces an exaggerated and persistent immune-inflammatory and hypermetabolic response. In this review, we propose potential mechanisms in which burn injury affects the vitamin D status and summarizes current literature investigating the influence of vitamin D status on outcomes. In addition, we reviewed the literature and trials investigating vitamin D supplementation in critically ill patients and discuss the therapeutic potential of vitamin D supplementation in burn and critically ill patients. We also highlight current limitations of studies that have investigated vitamin D status and supplementation in critical illness. Thermal injury influences vitamin D status. More studies investigating vitamin D depletion in burn patients and its influence on prognosis, via standardized methodology, are required to reach definitive conclusions and influence clinical practice.

The blister fluid proteome of paediatric burns

Burn injury is highly traumatic for paediatric patients, with the severity of the burn often dictating the extent of scar formation. The diagnosis of burn wound severity is largely determined by the attending clinician's experience. Thus, a greater understanding of the biochemistry at burn wound site environment and the biology of burns of different severities at an earlier stage may reduce the reliance on subjective diagnoses. In this study, blister fluid was collected from superficial thickness, deep-partial thickness, and full-thickness paediatric burn wounds. Samples were combined together based on burn depth classification and then subjected to four different fractionation methods followed by trypsin digestion. Peptides were analysed by liquid chromatography tandem mass spectrometry in order to measure the proteome of each fraction. In total, 811 individual proteins were identified, including 107, 84, and 146 proteins unique to superficial, deep-partial thickness and full-thickness burn wounds, respectively. The differences in the protein inventory and the associated gene ontologies represented within each burn depth category demonstrated that there are subtle, yet significant, variations in the biochemistry of burn wounds according to severity. Importantly, this study has produced the most comprehensive catalogue of proteins from the paediatric burn wound microenvironment to date.

SIGNIFICANCE

To our knowledge, this study has been the first to comprehensively measure the paediatric burn blister fluid proteome and has provided insight into the proteomic response to burn injury. The study contributes to the knowledge of blister fluid biochemistry of burn injury and provides clinically relevant knowledge through the qualitative evaluation of biochemical differences between burns of different depths. A better understanding of the burn wound environment will ultimately assist with more accurate clinical decision making and improved wound healing and scar reduction procedures.

Rationalising the role of Keratin 9 as a biomarker for Alzheimer's disease

Keratin 9 was recently identified as an important component of a biomarker panel which demonstrated a high diagnostic accuracy (87%) for Alzheimer's disease (AD). Understanding how a protein which is predominantly expressed in palmoplantar epidermis is implicated in AD may shed new light on the mechanisms underlying the disease. Here we use immunoassays to examine blood plasma expression patterns of Keratin 9 and its relationship to other AD-associated proteins. We correlate this with the use of an in silico analysis tool VisANT to elucidate possible pathways through which the involvement of Keratin 9 may take place. We identify possible links with Dickkopf-1, a negative regulator of the wnt pathway, and propose that the abnormal expression of Keratin 9 in AD blood and cerebrospinal fluid may be a result of blood brain barrier dysregulation and disruption of the ubiquitin proteasome system. Our findings suggest that dysregulated Keratin 9 expression is a consequence of AD pathology but, as it interacts with a broad range of proteins, it may have other, as yet uncharacterized, downstream effects which could contribute to AD onset and progression.

The biochemistry of blister fluid from pediatric burn injuries: proteomics and metabolomics aspects

Burn injury is a prevalent and traumatic event for pediatric patients. At present, the diagnosis of burn injury severity is subjective and lacks a clinically relevant quantitative measure. This is due in part to a lack of knowledge surrounding the biochemistry of burn injuries and that of blister fluid. A more complete understanding of the blister fluid biochemistry may open new avenues for diagnostic and prognostic development. Burn insult induces a highly complex network of signaling processes and numerous changes within various biochemical systems, which can ultimately be examined using proteome and metabolome measurements. This review reports on the current understanding of burn wound biochemistry and outlines a technical approach for 'omics' profiling of blister fluid from burn wounds of differing severity.

PNGase F-mediated incorporation of 18O into glycans for relative glycan quantitation

An enzymatic four ¹⁸O-labeling strategy based on PNGase F-catalyzed glycan ¹⁸O-labeling (PCGOL) developed in this work can be used for simultaneous quantification of glycans, non-glycopeptides and glycopeptides in a single workflow.

Detecting differential protein expression in large-scale population proteomics

MOTIVATION

Mass spectrometry (MS)-based high-throughput quantitative proteomics shows great potential in large-scale clinical biomarker studies, identifying and quantifying thousands of proteins in biological samples. However, there are unique challenges in analyzing the quantitative proteomics data. One issue is that the quantification of a given peptide is often missing in a subset of the experiments, especially for less abundant peptides. Another issue is that different MS experiments of the same study have significantly varying numbers of peptides quantified, which can result in more missing peptide abundances in an experiment that has a smaller total number of quantified peptides. To detect as many biomarker proteins as possible, it is necessary to develop bioinformatics methods that appropriately handle these challenges.

RESULTS

We propose a Significance Analysis for Large-scale Proteomics Studies (SALPS) that handles missing peptide intensity values caused by the two mechanisms mentioned above. Our model has a robust performance in both simulated data and proteomics data from a large clinical study. Because varying patients' sample qualities and deviating instrument performances are not avoidable for clinical studies performed over the course of several years, we believe that our approach will be useful to analyze large-scale clinical proteomics data.

AVAILABILITY AND IMPLEMENTATION

R codes for SALPS are available at http://www.stanford.edu/%7eclairesr/software.html.

Rapidly maturing field of proteomics: a gateway to studying diseases

The proteomics work reported by Smith et al. represents a giant step forward in characterizing the cerebrospinal fluid (CSF) proteome in mouse models of human diseases. Whereas prior studies were limited to analysis of CSF pools, Smith et al. (Proteomics 2014, 14, 1102-1106) base their conclusions on data derived from individual mice, thereby capturing a fuller range of the biological diversity present. These results underscore how far proteomics has come in the past few years, developing into a modern tool with the capacity to remove bottlenecks in the study of neuropsychiatric diseases. Past efforts with mass spectrometry (MS) have been hampered by limitations in access to CSF samples, and small volumes when available. These barriers have been overcome with newer MS platforms and advances in sample preparation. We are far closer than before to producing the production of clinically useful proteomic data for biomarker discovery and for deriving insights into pathogenesis that can lead to more effective treatments for many diseases.

From data patterns to mechanistic models in acute critical illness

The complexity of the physiologic and inflammatory response in acute critical illness has stymied the accurate diagnosis and development of therapies. The Society for Complex Acute Illness was formed a decade ago with the goal of leveraging multiple complex systems approaches to address this unmet need. Two main paths of development have characterized the society's approach: (i) data pattern analysis, either defining the diagnostic/prognostic utility of complexity metrics of physiologic signals or multivariate analyses of molecular and genetic data and (ii) mechanistic mathematical and computational modeling, all being performed with an explicit translational goal. Here, we summarize the progress to date on each of these approaches, along with pitfalls inherent in the use of each approach alone. We suggest that the next decade holds the potential to merge these approaches, connecting patient diagnosis to treatment via mechanism-based dynamical system modeling and feedback control and allowing extrapolation from physiologic signals to biomarkers to novel drug candidates. As a predicate example, we focus on the role of data-driven and mechanistic models in neuroscience and the impact that merging these modeling approaches can have on general anesthesia.

Identification of differentially expressed serum proteins in infectious purpura fulminans

Purpura fulminans (PF) is a life-threatening hemorrhagic condition. Because of the rarity and randomness of the disease, no improvement in treatment has been made for a long time. In this study, we assessed the serum proteome response to PF by comparing serum proteins between healthy controls and PF patient. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) approach was used after depleting 6 abundant proteins of serum. In total, 262 proteins were confidently identified with 2 unique peptides, and 38 proteins were identified significantly up- (≥2) or downregulated (≤0.5) based on spectral counting ratios (SpC_PF/N). In the 38 proteins with significant abundance changes, 11 proteins were previously known to be associated with burn or sepsis response, but 27 potentially novel proteins may be specifically associated with PF process. Two differentially expressed proteins, alpha-1-antitrypsin (SERPINA1) and alpha-2 antiplasmin (SERPINF2), were validated by Western blot. This is the first study where PF patient and healthy controls are compared in a proteomic study to elucidate proteins involved in the response to PF. This study provides an initial basis for future studies of PF, and the differentially expressed proteins might provide new therapeutic targets to decrease the mortality of PF.

Mass spectrometry in cancer biomarker research: a case for immunodepletion of abundant blood-derived proteins from clinical tissue specimens

The discovery of clinically relevant cancer biomarkers using mass spectrometry (MS)-based proteomics has proven difficult, primarily because of the enormous dynamic range of blood-derived protein concentrations and the fact that the 22 most abundant blood-derived proteins constitute approximately 99% of the total plasma protein mass. Immunodepletion of clinical body fluid specimens (e.g., serum/plasma) for the removal of highly abundant proteins is a reasonable and reproducible solution. Often overlooked, clinical tissue specimens also contain a formidable amount of highly abundant blood-derived proteins present in tissue-embedded networks of blood/lymph capillaries and interstitial fluid. Hence, the dynamic range impediment to biomarker discovery remains a formidable obstacle, regardless of clinical sample type (solid tissue and/or body fluid). Thus, we optimized and applied simultaneous immunodepletion of blood-derived proteins from solid tissue and peripheral blood, using clear cell renal cell carcinoma as a model disease. Integrative analysis of data from this approach and genomic data obtained from the same type of tumor revealed concordant key pathways and protein targets germane to clear cell renal cell carcinoma. This includes the activation of the lipogenic pathway characterized by increased expression of adipophilin (PLIN2) along with 'cadherin switching', a phenomenon indicative of transcriptional reprogramming linked to renal epithelial dedifferentiation. We also applied immunodepletion of abundant blood-derived proteins to various tissue types (e.g., adipose tissue and breast tissue) showing unambiguously that the removal of abundant blood-derived proteins represents a powerful tool for the reproducible profiling of tissue proteomes. Herein, we show that the removal of abundant blood-derived proteins from solid tissue specimens is of equal importance to depletion of body fluids and recommend its routine use in the context of biological discovery and/or cancer biomarker research. Finally, this perspective presents the background, rationale and strategy for using tissue-directed high-resolution/accuracy MS-based shotgun proteomics to detect genuine tumor proteins in the peripheral blood of a patient diagnosed with nonmetastatic cancer, employing concurrent liquid chromatography-MS analysis of immunodepleted clinical tissue and blood specimens.

Mass spectrometry for proteomics-based investigation

Within the past years, we have witnessed a great improvement in mass spectrometry (MS) and proteomics approaches in terms of instrumentation, protein fractionation, and bioinformatics. With the current technology, protein identification alone is no longer sufficient. Both scientists and clinicians want not only to identify proteins but also to identify the protein's posttranslational modifications (PTMs), protein isoforms, protein truncation, protein-protein interaction (PPI), and protein quantitation. Here, we describe the principle of MS and proteomics and strategies to identify proteins, protein's PTMs, protein isoforms, protein truncation, PPIs, and protein quantitation. We also discuss the strengths and weaknesses within this field. Finally, in our concluding remarks we assess the role of mass spectrometry and proteomics in scientific and clinical settings in the near future. This chapter provides an introduction and overview for subsequent chapters that will discuss specific MS proteomic methodologies and their application to specific medical conditions. Other chapters will also touch upon areas that expand beyond proteomics, such as lipidomics and metabolomics.

Gene expression profile of cytokines and receptors of inflammation from cultured keratinocytes of burned patients

INTRODUCTION

At all stages of wound healing, growth factors and cytokines play a particularly important role in the interaction with keratinocytes cellular receptors. Keratinocytes have received little attention about their potential to act as a source and target of cytokines. Changes in the cytokine levels after the burning occur prior to the metabolic abnormalities. Thus, it may be possible to develop therapeutic interventions that can mitigate the acute inflammatory response and modulating expression of these cytokines. The objective was to evaluate the expression of 84 genes mediators of the inflammatory response by using PCR array in a primary human epidermal cultured keratinocytes from patients with burns.

METHODS

Keratinocytes cultured from normal skin around injury from small and large burn patient were treated for DNA synthesis. The samples were analyzed by the PCR Superarray(®) assay and curve analyses were performed for 84 relevant human genes and their involvement in the inflammatory cytokines pathway and receptors. These genes were checked for the up or down regulation. And it was used MetaCore™ for the analysis of networks and Gene Ontology (GO) processes.

RESULTS

Chemokines of the CXC family were more expressed in the large burn group, except CXCL12. The C, CC and CX3C chemokine family were downregulated, especially in the small burn group. The interleukins IL8 and IL1B were more expressed in large burn than in small burn; except IL13RA1, IL13 and IL5RA that were downregulated, mainly in the small burn group.

CONCLUSIONS

The cytokine profile showed some important differences between the large and small burn patients, and from this original database, we can create new interventional trials in acute inflammation in burns.

In silico modeling: methods and applications to trauma and sepsis

OBJECTIVES

To familiarize clinicians with advances in computational disease modeling applied to trauma and sepsis.

DATA SOURCES

PubMed search and review of relevant medical literature.

SUMMARY

Definitions, key methods, and applications of computational modeling to trauma and sepsis are reviewed.

CONCLUSIONS

Computational modeling of inflammation and organ dysfunction at the cellular, organ, whole-organism, and population levels has suggested a positive feedback cycle of inflammation → damage → inflammation that manifests via organ-specific inflammatory switching networks. This structure may manifest as multicompartment "tipping points" that drive multiple organ dysfunction. This process may be amenable to rational inflammation reprogramming.

Bride and groom in systemic inflammation--the bells ring for complement and Toll in cooperation

Attenuating the sepsis-induced systemic inflammatory response, with subsequent homeostatic imbalance, has for years been one of the main tasks in sepsis related research. Complement and the TLR family constitute two important upstream sensor and effector-systems of innate immunity. Although they act as partly independent branches of pattern recognition, recent evidence indicate a considerable cross-talk implying that they can either compensate, synergize or antagonize each other. Combined inhibition of these pathways is therefore a particularly interesting approach with a profound anti-inflammatory potential. In previous preclinical studies, we demonstrated that targeting the key molecules C3 or C5 of complement and CD14 of the TLR family had a vast anti-inflammatory effect on Gram-negative bacteria-induced inflammation and sepsis. In this review, we elucidate the significance of these key molecules as important targets for intervention in sepsis and systemic inflammatory response syndrome. Finally, we argue that a combined inhibition of complement and CD14 represent a potential general treatment regimen, beyond the limit of sepsis, including non-infectious systemic inflammation and ischemia reperfusion injury.

Applications of Mass Spectrometry in Proteomics

Characterisation of proteins and whole proteomes can provide a foundation to our understanding of physiological and pathological states and biological diseases or disorders. Constant development of more reliable and accurate mass spectrometry (MS) instruments and techniques has allowed for better identification and quantification of the thousands of proteins involved in basic physiological processes. Therefore, MS-based proteomics has been widely applied to the analysis of biological samples and has greatly contributed to our understanding of protein functions, interactions, and dynamics, advancing our knowledge of cellular processes as well as the physiology and pathology of the human body. This review will discuss current proteomic approaches for protein identification and characterisation, including post-translational modification (PTM) analysis and quantitative proteomics as well as investigation of protein–protein interactions (PPIs).

Trypsin-mediated ¹⁸O/¹⁶O labeling for biomarker discovery

Differential (18)O/(16)O stable isotopic labeling that relies on post-digestion (18)O exchange is a simple and efficient method for the relative quantitation of proteins in complex mixtures. This method incorporates two (18)O atoms onto the C-termini of proteolytic peptides resulting in a 4 Da mass-tag difference between (18)O- and (16)O-labeled peptides. This allows for wide-range relative quantitation of proteins in complex mixtures using shotgun proteomics. Because of minimal sample consumption and unrestricted peptide tagging, the post-digestion (18)O exchange is suitable for labeling of low-abundance membrane proteins enriched from cancer cell lines or clinical specimens, including tissues and body fluids. This chapter describes a protocol that applies post-digestion (18)O labeling to elucidate putative endogenous tumor hypoxia markers in the plasma membrane fraction enriched from a hypoxia-adapted malignant melanoma cell line. Plasma membrane proteins from hypoxic and normoxic cells were differentially tagged using (18)O/(16)O stable isotopic labeling. The initial tryptic digestion and solubilization of membrane proteins were carried out in a buffer containing 60 % methanol followed by post-digestion (18)O exchange/labeling in buffered 20 % methanol. The differentially labeled peptides were mixed in a 1:1 ratio and fractionated using off-line strong cation exchange (SCX) liquid chromatography followed by on-line reversed-phase nano-flow RPLC-MS identification and quantitation of peptides/proteins in respective SCX fractions. The present protocol illustrates the utility of (18)O/(16)O stable isotope labeling in the context of quantitative shotgun proteomics that provides a basis for the discovery of hypoxia-induced membrane protein markers in malignant melanoma cell lines.

It's not your grandfather's field plasma

Initiating prehospital resuscitation with plasma in patients with trauma-associated hemorrhagic shock will result in more rapid and durable clot formation and, thus, the need for fewer packed cell infusions, less frequent use of cryoprecipitate, and more ventilator-free hospital days compared with those of patients randomized to standard crystalloid field resuscitation.

Mass spectrometry-based proteomics: existing capabilities and future directions

Mass spectrometry (MS)-based proteomics is emerging as a broadly effective means for identification, characterization, and quantification of proteins that are integral components of the processes essential for life. Characterization of proteins at the proteome and sub-proteome (e.g., the phosphoproteome, proteoglycome, or degradome/peptidome) levels provides a foundation for understanding fundamental aspects of biology. Emerging technologies such as ion mobility separations coupled with MS and microchip-based-proteome measurements combined with MS instrumentation and chromatographic separation techniques, such as nanoscale reversed phase liquid chromatography and capillary electrophoresis, show great promise for both broad undirected and targeted highly sensitive measurements. MS-based proteomics increasingly contribute to our understanding of the dynamics, interactions, and roles that proteins and peptides play, advancing our understanding of biology on a systems wide level for a wide range of applications including investigations of microbial communities, bioremediation, and human health.

Mass spectrometry-based proteomics: existing capabilities and future directions

Mass spectrometry (MS)-based proteomics is emerging as a broadly effective means for identification, characterization, and quantification of proteins that are integral components of the processes essential for life. Characterization of proteins at the proteome and sub-proteome (e.g., the phosphoproteome, proteoglycome, or degradome/peptidome) levels provides a foundation for understanding fundamental aspects of biology. Emerging technologies such as ion mobility separations coupled with MS and microchip-based-proteome measurements combined with MS instrumentation and chromatographic separation techniques, such as nanoscale reversed phase liquid chromatography and capillary electrophoresis, show great promise for both broad undirected and targeted highly sensitive measurements. MS-based proteomics increasingly contribute to our understanding of the dynamics, interactions, and roles that proteins and peptides play, advancing our understanding of biology on a systems wide level for a wide range of applications including investigations of microbial communities, bioremediation, and human health.

Computational and systems biology in trauma and sepsis: current state and future perspectives

Trauma, often accompanied by hemorrhage, is a leading cause of death worldwide, often leading to inflammation-related late complications that include sepsis and multiple organ failure. These secondary complications are a manifestation of the complexity of biological responses elicited by trauma/hemorrhage, responses that span most, if not all, cell types, tissues, and organ systems. This daunting complexity at the patient level is manifest by the near total dearth of available therapeutics, and we suggest that this dire condition is due in large part to the lack of a rational, systems-oriented framework for drug development, clinical trial design, in-hospital diagnostics, and post-hospital care. We have further suggested that mechanistic computational modeling can form the basis of such a rational framework, given the maturity of systems biology/computational biology. Herein, we briefly summarize the state of the art of these approaches, and highlight the biological insights and novel hypotheses derived from these approaches. We propose a rational framework for transitioning through the currently fragmented process from identification of biological networks that are potential therapeutic targets, through clinical trial design, to personalized diagnosis and care. Insights derived from systems and computational biology in trauma and sepsis include the centrality of Damage-Associated Molecular Pattern molecules as drivers of both beneficial and detrimental inflammation, along with a novel view of multiple organ dysfunction as a cascade of containment failures with distinct implications for therapy. Finally, we suggest how these insights might be best implemented to drive transformational change in the fields of trauma and sepsis.

Sepsis: from pattern to mechanism and back

Sepsis is a clinical entity in which complex inflammatory and physiological processes are mobilized, not only across a range of cellular and molecular interactions, but also in clinically relevant physiological signals accessible at the bedside. There is a need for a mechanistic understanding that links the clinical phenomenon of physiologic variability with the underlying patterns of the biology of inflammation, and we assert that this can be facilitated through the use of dynamic mathematical and computational modeling. An iterative approach of laboratory experimentation and mathematical/computational modeling has the potential to integrate cellular biology, physiology, control theory, and systems engineering across biological scales, yielding insights into the control structures that govern mechanisms by which phenomena, detected as biological patterns, are produced. This approach can represent hypotheses in the formal language of mathematics and computation, and link behaviors that cross scales and domains, thereby offering the opportunity to better explain, diagnose, and intervene in the care of the septic patient.

Plasma biomarkers for detecting Hodgkin's lymphoma in HIV patients

The lifespan of people with human immunodeficiency virus (HIV) infection has increased as a result of effective antiretroviral therapy, and the incidences of the AIDS-defining cancers, non-Hodgkin's lymphoma and Kaposi sarcoma, have declined. Even so, HIV-infected individuals are now at greater risk of other cancers, including Hodgkin's lymphoma (HL). To identify candidate biomarkers for the early detection of HL, we undertook an accurate mass and elution time tag proteomics analysis of individual plasma samples from either HIV-infected patients without HL (controls; n = 14) and from HIV-infected patient samples with HL (n = 22). This analysis identified 60 proteins that were statistically (p<0.05) altered and at least 1.5-fold different between the two groups. At least three of these proteins have previously been reported to be altered in the blood of HL patients that were not known to be HIV positive, suggesting that these markers may be broadly useful for detecting HL. Ingenuity Pathway Analysis software identified "inflammatory response" and "cancer" as the top two biological functions associated with these proteins. Overall, this study validated three plasma proteins as candidate biomarkers for detecting HL, and identified 57 novel candidate biomarkers that remain to be validated. The relationship of these novel candidate biomarkers with cancer and inflammation suggests that they are truly associated with HL and therefore may be useful for the early detection of this cancer in susceptible populations.

18O-labeled proteome reference as global internal standards for targeted quantification by selected reaction monitoring-mass spectrometry

Selected reaction monitoring (SRM)-MS is an emerging technology for high throughput targeted protein quantification and verification in biomarker discovery studies; however, the cost associated with the application of stable isotope-labeled synthetic peptides as internal standards can be prohibitive for screening a large number of candidate proteins as often required in the preverification phase of discovery studies. Herein we present a proof of concept study using an (18)O-labeled proteome reference as global internal standards (GIS) for SRM-based relative quantification. The (18)O-labeled proteome reference (or GIS) can be readily prepared and contains a heavy isotope ((18)O)-labeled internal standard for every possible tryptic peptide. Our results showed that the percentage of heavy isotope ((18)O) incorporation applying an improved protocol was >99.5% for most peptides investigated. The accuracy, reproducibility, and linear dynamic range of quantification were further assessed based on known ratios of standard proteins spiked into the labeled mouse plasma reference. Reliable quantification was observed with high reproducibility (i.e. coefficient of variance <10%) for analyte concentrations that were set at 100-fold higher or lower than those of the GIS based on the light ((16)O)/heavy ((18)O) peak area ratios. The utility of (18)O-labeled GIS was further illustrated by accurate relative quantification of 45 major human plasma proteins. Moreover, quantification of the concentrations of C-reactive protein and prostate-specific antigen was illustrated by coupling the GIS with standard additions of purified protein standards. Collectively, our results demonstrated that the use of (18)O-labeled proteome reference as GIS provides a convenient, low cost, and effective strategy for relative quantification of a large number of candidate proteins in biological or clinical samples using SRM.

IgY14 and SuperMix immunoaffinity separations coupled with liquid chromatography-mass spectrometry for human plasma proteomics biomarker discovery

Interest in the application of advanced proteomics technologies to human blood plasma- or serum-based clinical samples for the purpose of discovering disease biomarkers continues to grow; however, the enormous dynamic range of protein concentrations in these types of samples (often >10 orders of magnitude) represents a significant analytical challenge, particularly for detecting low-abundance candidate biomarkers. In response, immunoaffinity separation methods for depleting multiple high- and moderate-abundance proteins have become key tools for enriching low-abundance proteins and enhancing detection of these proteins in plasma proteomics. Herein, we describe IgY14 and tandem IgY14-Supermix separation methods for removing 14 high-abundance and up to 60 moderate-abundance proteins, respectively, from human blood plasma and highlight their utility when combined with liquid chromatography-tandem mass spectrometry for interrogating the human plasma proteome.

Software for quantitative proteomic analysis using stable isotope labeling and data independent acquisition

Many software tools have been developed for analyzing stable isotope labeling (SIL)-based quantitative proteomic data using data dependent acquisition (DDA). However, programs for analyzing SIL-based quantitative proteomics data obtained with data independent acquisition (DIA) have yet to be reported. Here, we demonstrated the development of a new software for analyzing SIL data using the DIA method. Performance of the DIA on SYNAPT G2MS was evaluated using SIL-labeled complex proteome mixtures with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10) and compared with the DDA on linear ion trap (LTQ)-Orbitrap MS. The DIA displays relatively high quantitation accuracy for peptides cross all intensity regions, while the DDA shows an intensity dependent distribution of H/L ratios. For the three proteome mixtures, the number of detected SIL-peptide pairs and dynamic range of protein intensities using DIA drop stepwise, whereas no significant changes in these aspects using DDA were observed. The new software was applied to investigate the proteome difference between mouse embryonic fibroblasts (MEFs) and MEF-derived induced pluripotent stem cells (iPSCs) using (16)O/(18)O labeling. Our study expanded the capacities of our UNiquant software pipeline and provided valuable insight into the performance of the two cutting-edge MS platforms for SIL-based quantitative proteomic analysis today.

Liquid chromatography-mass spectrometry-based quantitative proteomics

LC-MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications due to growing capabilities for broad proteome coverage and good accuracy and precision in quantification. Herein, we review the current LC-MS-based quantification methods with respect to their advantages and limitations and highlight their potential applications.

Proteomic biomarker discovery: it's more than just mass spectrometry

The previous decade witnessed an enormous number of studies with the singular goal of identifying protein biomarkers for diseases such as cancer. A large majority of these studies have focused on comparative studies of serum or plasma obtained from disease-affected and control patients. In these studies, proteins identified in the samples using MS were compared with the hope that differences between samples would reveal useful biomarkers. Unfortunately, finding clinically relevant biomarkers has often been elusive and frustrating. As with most research efforts, both successes and failures, much has been learned about what strategies work and which do not. Part of the problem can be attributed to underestimating the effort required to discover novel biomarkers and depending too heavily on MS analysis of peripheral blood samples. Fortunately, the future for biomarker discovery still appears bright. MS technology continues to increase in sensitivity, throughput, and accuracy while novel types of samples and clever experimental designs coupled with innovative bioinformatics will make this vision of routine biomarker discovery a reality. To achieve ultimate success is going to require concomitant application of a number of different technologies, all providing the information necessary for discovering and validating clinically useful biomarkers.

Proteomic analysis of HIV-infected macrophages

Mononuclear phagocytes (monocytes, macrophages, and microglia) play an important role in innate immunity against pathogens including HIV. These cells are also important viral reservoirs in the central nervous system and secrete inflammatory mediators and toxins that affect the tissue environment and function of surrounding cells. In the era of antiretroviral therapy, there are fewer of these inflammatory mediators. Proteomic approaches including surface enhancement laser desorption ionization, one- and two-dimensional difference in gel electrophoresis, and liquid chromatography tandem mass spectrometry have been used to uncover the proteins produced by in vitro HIV-infected monocytes, macrophages, and microglia. These approaches have advanced the understanding of novel mechanisms for HIV replication and neuronal damage. They have also been used in tissue macrophages that restrict HIV replication to understand the mechanisms of restriction for future therapies. In this review, we summarize the proteomic studies on HIV-infected mononuclear phagocytes and discuss other recent proteomic approaches that are starting to be applied to this field. As proteomic instruments and methods evolve to become more sensitive and quantitative, future studies are likely to identify more proteins that can be targeted for diagnosis or therapy and to uncover novel disease mechanisms.

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.