Joy Guingab-Cagmat

In vitro MS-based proteomic analysis and absolute quantification of neuronal-glial injury biomarkers in cell culture system.

MS‐based proteomics has been the method of choice for biomarker discovery in the field of traumatic brain injury (TBI). Due to its high sensitivity and specificity, MS is now being explored for biomarker quantitative validation in tissue and biofluids. In this study, we demonstrate the use of MS in both qualitative protein identification and targeted detection of acute TBI biomarkers released from degenerating cultured rat cortical mixed neuronal cells, mimicking intracellular fluid in the central nervous system after TBI. Calpain activation was induced by cell treatment with maitotoxin (MTX), a known calcium channel opener. Separate plates of mixed neuronal‐glial culture were subjected to excitotoxin N‐methyl‐D‐aspartate (NMDA) and apoptotic inducer staurosporine. Acute TBI biomarkers, GFAP and UCH‐L1, were first detected and assessed in the culture media by Western blot. The cell‐conditioned media were then trypsinized and subjected to bottom up proteomic analysis. GFAP was readily detected by data‐dependent scanning but not UCH‐L1. As a proof‐of‐principle study, rat glia‐enriched cell cultures treated with MTX were used to investigate the time‐dependent release of GFAP breakdown product by Western blot and for isotope dilution MS absolute quantitation method development. Absolute quantitation of the GFAP release was conducted using the three cortical mixed neuronal cell cultures treated with different agents. Other differentially expressed proteins identified in the glial‐enriched and cortical mixed neuronal cell culture models were further analyzed by bioinformatic tools. In summary, this study demonstrates the use of MS in both protein identification and targeted quantitation of acute TBI biomarkers and is the preliminary step toward development of TBI biomarker validation by targeted MS.

Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery

Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed.

Leveraging biomarker platforms and systems biology for rehabilomics and biologics effectiveness research.

Although traumatic brain injury (TBI) remains a major health problem, with approximately 2 million incidents occurring annually in the United States, no therapeutic agents to treat TBI have been approved by the Food and Drug Administration despite several clinical trials. It is estimated that 3.5 million Americans now have a lifelong condition that might be termed “chronic traumatic brain injury disease.” Some health care providers categorize TBI as an “event” for which patients require brief periods of rehabilitation with no further treatment. On the contrary, TBI should be seen as a chronic disease process that fits the World Health Organization definition as being a non‐reversible pathologic condition requiring special rehabilitation training. Among the major obstacles that contribute to this type of misconception is the absence of brain injury–specific diagnostic biomarker(s) that can indicate and monitor the long‐term health status of patients with TBI after use of conventional therapeutics and a rehabilitation process. It is of interest that recent advances in genomics, proteomics, and systems biology have enabled us to use these high throughput–based approaches in developing biomarkers and therapeutic targets in the area of TBI. One aim of this article is to provide an overview that evaluates the current status of TBI biomarker discovery using neuroproteomics/systems biology techniques, along with their clinical utilization. In addition, we discuss the need for strengthening the role of biomarker‐based neuroproteomics/systems biology and its potential utility in the field of rehabilitation, which would lead to the establishment of rehabilomics studies, where biomarkers would indicate and predict the long‐term efficacy and health status of patients with chronic TBI conditions.

Assessment of Serum UCH-L1 and GFAP in Acute Stroke Patients

A rapid and reliable diagnostic test to distinguish ischemic from hemorrhagic stroke in patients presenting with stroke-like symptoms is essential to optimize management and triage for thrombolytic therapy. The present study measured serum concentrations of ubiquitin C-terminal hydrolase (UCH-L1) and glial fibrillary astrocytic protein (GFAP) in acute stroke patients and healthy controls and investigated their relation to stroke severity and patient characteristics. We also assessed the diagnostic performance of these markers for the differentiation of intracerebral hemorrhage (ICH) from ischemic stroke (IS). Both UCH-L1 and GFAP concentrations were significantly greater in ICH patients than in controls (p < 0.0001). However, exclusively GFAP differed in ICH compared with IS (p < 0.0001). GFAP yielded an AUC of 0.86 for differentiating between ICH and IS within 4.5hrs of symptom onset with a sensitivity of 61% and a specificity of 96% using a cut-off of 0.34ng/ml. Higher GFAP levels were associated with stroke severity and history of prior stroke. Our results demonstrate that blood UCH-L1 and GFAP are increased early after stroke and distinct biomarker-specific release profiles are associated with stroke characteristics and type. We also confirmed the potential of GFAP as a tool for early rule-in of ICH, while UCH-L1 was not clinically useful.

Identification of tyrosine nitration in UCH‐L1 and GAPDH

Protein tyrosine nitration is a post‐translational modification commonly used as a marker of cellular oxidative stress associated with numerous pathophysiological conditions. We focused on ubiquitin carboxyl terminal hydrolase‐L1 (UCH‐L1) and glyceraldehyde‐3‐phosphate (GAPDH) which are high‐abundant brain proteins that have been identified to be highly susceptible to oxidative modification. Both UCH‐L1 and GAPDH have been linked to the pathogenesis of Alzheimers and Parkinsons disease, however specific nitration sites have not been elucidated. Identification of specific nitration sites and quantitation of endogenous nitrated proteins are important in correlating this modification to disease pathology. In this study, purified UCH‐L1 and GAPDH were nitrated in vitro with peroxynitrite and the presence of nitrated proteins was confirmed by anti‐3‐nitrotyrosine Western blots. Data‐dependent LC‐MS/MS analysis identified several distinct tyrosine nitration sites in UCH‐L1 (Tyr‐80) and GAPDH (Tyr‐47, Tyr‐92, and Tyr‐312). Subsequent validation with synthetic peptides was conducted for selected nitropeptides. An LC‐MS/MS method was developed for semi‐quantitative determination of the synthetic nitropeptides: KGQEVSPKVY*(UCH‐L1) and mFQY*DSTHGKF (GAPDH). The nitropeptides were detectable in the mid‐attomole range and the peak area response was linear over three orders of magnitude. Targeted analysis of endogenous UCH‐L1 and GAPDH nitration was then conducted in an in vivo second‐hand smoke rat model to evaluate the utility of this approach.

Post-Genomics Nanotechnology Is Gaining Momentum: Nanoproteomics and Applications in Life Sciences

The post-genomics era has brought about new Omics biotechnologies, such as proteomics and metabolomics, as well as their novel applications to personal genomics and the quantified self. These advances are now also catalyzing other and newer post-genomics innovations, leading to convergences between Omics and nanotechnology. In this work, we systematically contextualize and exemplify an emerging strand of post-genomics life sciences, namely, nanoproteomics and its applications in health and integrative biological systems. Nanotechnology has been utilized as a complementary component to revolutionize proteomics through different kinds of nanotechnology applications, including nanoporous structures, functionalized nanoparticles, quantum dots, and polymeric nanostructures. Those applications, though still in their infancy, have led to several highly sensitive diagnostics and new methods of drug delivery and targeted therapy for clinical use. The present article differs from previous analyses of nanoproteomics in that it offers an in-depth and comparative evaluation of the attendant biotechnology portfolio and their applications as seen through the lens of post-genomics life sciences and biomedicine. These include: (1) immunosensors for inflammatory, pathogenic, and autoimmune markers for infectious and autoimmune diseases, (2) amplified immunoassays for detection of cancer biomarkers, and (3) methods for targeted therapy and automatically adjusted drug delivery such as in experimental stroke and brain injury studies. As nanoproteomics becomes available both to the clinician at the bedside and the citizens who are increasingly interested in access to novel post-genomics diagnostics through initiatives such as the quantified self, we anticipate further breakthroughs in personalized and targeted medicine.

Different expression of ubiquitin C-terminal hydrolase-L1 and αII-spectrin in ischemic and hemorrhagic stroke: Potential biomarkers in diagnosis.

The two primary categories of stroke, ischemic and hemorrhagic, both have fundamentally different mechanisms and thus different treatment options. These two stroke categories were applied to rat models to identify potential biomarkers that can distinguish between them. Ischemic stroke was induced by middle cerebral artery occlusion (MCAO) without reperfusion while hemorrhagic stroke was induced by injecting collagenase IV into the striatum. Brain hemispheres and biofluids were collected at two time points: 3 and 6h after stroke. Known molecules were tested on the rat samples via quantitative immunoblotting (injured brain, CSF) and Banyans proprietary ELISA assays (CSF, serum). The injured brain quantitative analyses revealed that αII-spectrin breakdown products (SBDP150, SBDP145) were strongly increased after 6h ischemia. In CSF, SBDP145 and ubiquitin C-terminal hydrolase-L1 (UCH-L1) levels were elevated after 6h ischemic stroke detected by Western blot and ELISA. In serum UCH-L1 levels were increased after 3 and 6h of ischemia detected by ELISA. However, levels of those proteins in hemorrhagic stroke remain normal. In summary, in both the brain and the biofluids, SBDPs and UCH-L1 were elevated after ischemic but not hemorrhagic stroke. These molecules behaved differently in the two stroke models and thus may be capable of being differentiated.

A neuroproteomic and systems biology analysis of rat brain post intracerebral hemorrhagic stroke

Intracerebral hemorrhage (ICH) is a devastating form of stroke leading to a high rate of death and disability worldwide. Although it has been hypothesized that much of the IHC insult occurs in the subacute period mediated via a series of complex pathophysiological cascades, the molecular mechanisms involved in ICH have not been systematically characterized. Among the best approaches to understand the underlying mechanisms of injury and recovery, protein dynamics assessment via proteomics/systems biology platforms represent one of the cardinal techniques optimized for mechanisms investigation and biomarker identification. A proteomics approach may provide a biomarker focused framework from which to identify candidate biomarkers of pathophysiological processes involved in brain injury after stroke. In this work, a neuroproteomic approach (LC-MS/MS) was applied to investigate altered expression of proteins that are induced in brain tissue 3 h after injury in a rat model of ICH. Data from sham and focal ischemic models were also obtained and used for comparison. Based on the differentially expressed protein profile, systems biology analysis was conducted to identify associated cellular processes and related interaction maps. After LC-MS/MS analysis of the 3 h brain lysates, 86 proteins were differentially expressed between hemorrhagic and sham tissues. Furthermore, 38 proteins were differentially expressed between ischemic and sham tissues. On the level of global pathway analysis, hemorrhagic stroke proteins were shown to be involved in autophagy, ischemia, necrosis, apoptosis, calpain activation, and cytokine secretion. Moreover, ischemic stroke proteins were related to cell death, ischemia, inflammation, oxidative stress, caspase activation and apoptotic injury. In conclusion, the proteomic responses identified in this study provide key information about target proteins involved in specific pathological pathways.

Neuroproteomics and systems biology approach to identify temporal biomarker changes post experimental traumatic brain injury in rats

Traumatic brain injury (TBI) represents a critical health problem of which diagnosis, management, and treatment remain challenging. TBI is a contributing factor in approximately one-third of all injury-related deaths in the United States. The Centers for Disease Control and Prevention estimate that 1.7 million people suffer a TBI in the United States annually. Efforts continue to focus on elucidating the complex molecular mechanisms underlying TBI pathophysiology and defining sensitive and specific biomarkers that can aid in improving patient management and care. Recently, the area of neuroproteomics–systems biology is proving to be a prominent tool in biomarker discovery for central nervous system injury and other neurological diseases. In this work, we employed the controlled cortical impact (CCI) model of experimental TBI in rat model to assess the temporal–global proteome changes after acute (1 day) and for the first time, subacute (7 days), post-injury time frame using the established cation–anion exchange chromatography-1D SDS gel electrophoresis LC–MS/MS platform for protein separation combined with discrete systems biology analyses to identify temporal biomarker changes related to this rat TBI model. Rather than focusing on any one individual molecular entity, we used in silico systems biology approach to understand the global dynamics that govern proteins that are differentially altered post-injury. In addition, gene ontology analysis of the proteomic data was conducted in order to categorize the proteins by molecular function, biological process, and cellular localization. Results show alterations in several proteins related to inflammatory responses and oxidative stress in both acute (1 day) and subacute (7 days) periods post-TBI. Moreover, results suggest a differential upregulation of neuroprotective proteins at 7 days post-CCI involved in cellular functions such as neurite growth, regeneration, and axonal guidance. Our study is among the first to assess temporal neuroproteome changes in the CCI model. Data presented here unveil potential neural biomarkers and therapeutic targets that could be used for diagnosis, for treatment and, most importantly, for temporal prognostic assessment following brain injury. Of interest, this work relies on in silico bioinformatics approach to draw its conclusion; further work is conducted for functional studies to validate and confirm the omics data obtained.

Methods in tobacco abuse: proteomic changes following second-hand smoke exposure.

Smoking is one of the leading preventable causes of disease, disability, and death in the USA and leads to more than 400,000 preventable deaths per year. Nicotine is the major alkaloid present in tobacco smoke, and many of the negative effects of smoking are attributed to nicotine. Nicotine is not only the addictive component of tobacco smoke, but also highly associated with carcinogenesis and induces oxidative stress. Furthermore, the administration of nicotine via subcutaneous mini-osmotic pumps or by injection is an established method in preclinical studies for this area of research. Thus, preclinical research on the negative effects of tobacco smoke and tobacco addiction has focused primarily on the effects of nicotine. However, there are over 4,500 components found in tobacco smoke, many of which are highly toxic. Other components may also contribute to the addictive properties of tobacco smoke. Furthermore, the negative effects of tobacco smoke are not isolated to the smoker but can have negative effects to those exposed to the secondhand smoke (SHS) stream. SHS exposure is the third leading cause of preventable death. Approximately 38,000 deaths per year are attributed to SHS exposure in the USA. SHS exposure increases the risk of heart disease by approximately 30% and is associated with increased risk of stroke, cancer, type II diabetes, as well as pulmonary disease. Thus, methods of administering tobacco smoke in a controlled environment will further our understanding of tobacco addiction and the role tobacco smoke in other disease states. Moreover, combining smoke exposure with proteomics can lead to the discovery of biomarkers that can be potentially useful tools in screening, early diagnosis, prevention, and treatment of diseases caused by SHS.