Systems biology and theranostic approach to drug discovery and development to treat traumatic brain injury

A small antimicrobial peptide derived from a Burkholderia bacterium exhibits a broad-spectrum and high inhibiting activities against crop diseases

Crop diseases cause significant quality and yield losses to global crop products each year and are heavily controlled by chemicals along with very limited antibiotics composed of small molecules. However, these methods often result in environmental pollution and pest resistance, necessitating the development of new bio-controlling products to mitigate these hazards. To identify effective antimicrobial peptides (AMPs) considered as potential sources of future antibiotics, AMPs were screened from five bacterial strains showing antagonism against a representative phytopathogenic fungus (Rhizoctonia Solani) through the Bacillus subtilis expression system, which has been developed for identifying bacterial AMPs by displaying autolysis morphologies. A total of 5000 colonies were screened, and five displaying autolysis morphologies showed antagonism against R. solani. A novel AMP with the strongest antagonism efficiency was determined and tentatively named HR2-7, which is composed of 24 amino acids with an alpha-helical structure. HR2-7 has strong and broad-spectrum antimicrobial activity, tested against 10 g-positive and -negative bacteria and four phytopathogenic fungi by contact culture in plates with minimal lethal concentrations of 4.0 μM. When applied as purified peptide or in fermented B. subtilis culture solution, HR2-7 showed strong controlling efficiency on plants against diverse fungal and bacterial pathogens. Based on current understanding, HR2-7 is recognized as the first AMP derived from an agricultural antagonistic bacterium. It exhibits wide-ranging and notable antimicrobial efficacy, offering a supplementary approach for managing plant diseases, in addition to conventional chemical pesticides and antibiotics.

Comparing Brain and Blood Lipidome Changes following Single and Repetitive Mild Traumatic Brain Injury in Rats

Traumatic brain injury (TBI) is a major health concern in the United States and globally, contributing to disability and long-term neurological problems. Lipid dysregulation after TBI is underexplored, and a better understanding of lipid turnover and degradation could point to novel biomarker candidates and therapeutic targets. Here, we investigated overlapping lipidome changes in the brain and blood using a data-driven discovery approach to understand lipid alterations in the brain and serum compartments acutely following mild TBI (mTBI) and the potential efflux of brain lipids to peripheral blood. The cortices and sera from male and female Sprague-Dawley rats were analyzed via ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) in both positive and negative ion modes following single and repetitive closed head impacts. The overlapping lipids in the data sets were identified with an in-house data dictionary for investigating lipid class changes. MS-based lipid profiling revealed overall increased changes in the serum compartment, while the brain lipids primarily showed decreased changes. Interestingly, there were prominent alterations in the sphingolipid class in the brain and blood compartments after single and repetitive injury, which may suggest efflux of brain sphingolipids into the blood after TBI. Genetic algorithms were used for predictive panel selection to classify injured and control samples with high sensitivity and specificity. These overlapping lipid panels primarily mapped to the glycerophospholipid metabolism pathway with Benjamini-Hochberg adjusted q-values less than 0.05. Collectively, these results detail overlapping lipidome changes following mTBI in the brain and blood compartments, increasing our understanding of TBI-related lipid dysregulation while identifying novel biomarker candidates.

Metabolomics Analysis of Hippocampus and Cortex in a Rat Model of Traumatic Brain Injury in the Subacute Phase

Traumatic brain injury (TBI) is a complex and serious disease as its multifaceted pathophysiological mechanisms remain vague. The molecular changes of hippocampal and cortical dysfunction in the process of TBI are poorly understood, especially their chronic effects on metabolic profiles. Here we utilize metabolomics-based liquid chromatography coupled with tandem mass spectrometry coupled with bioinformatics method to assess the perturbation of brain metabolism in rat hippocampus and cortex on day 7. The results revealed a signature panel which consisted of 13 identified metabolites to facilitate targeted interventions for subacute TBI discrimination. Purine metabolism change in cortical tissue and taurine and hypotaurine metabolism change in hippocampal tissue were detected. Furthermore, the associations between the metabolite markers and the perturbed pathways were analyzed based on databases: 64 enzyme and one pathway were evolved in TBI. The findings represented significant profiling changes and provided unique metabolite-protein information in a rat model of TBI following the subacute phase. This study may inspire scientists and doctors to further their studies and provide potential therapy targets for clinical interventions.

Effect of memantine hydrochloride on cisplatin-induced neurobehavioral toxicity in mice

Cisplatin is an anticancer agent widely used in the treatment of malignant tumors. One of the major adverse effects of cisplatin is its neurotoxicity. Memantine, an uncompetitive N-methyl-D-aspartate (NMDA) receptor antagonist, has been reported to have neuroprotective effects against neurological deficits. This study therefore investigated the possible protective role of memantine as an agent to minimize the neurobehavioral toxic side effects of cisplatin. Two different therapeutic doses of memantine (5 mg/kg) and (10 mg/kg) were orally administered for 30 days to 50 male BALB/c mice divided into 5 groups: G1: no treatment; G2: cisplatin treatment; G3: memantine treatment; G4: pretreatment of (5 mg/kg) memantine with cisplatin (4 mg/kg); G5: pretreatment of 10 mg/kg memantine with cisplatin (4 mg/kg). Weekly neurobehavioral investigations were conducted using the following battery of tests: open field activity, negative geotaxis, hole-board test, swimming test, and calculation of weight. At the end of the experimental period the mice were euthanized, and immunohistochemistry was then used to measure the expression scores of nicotinic acetylcholine receptors (nAChRs) in the muscles and brain. Results revealed that mice in G2 showed a significant decrease in the ability to perform neurobehavioral tasks. The mice in G5 exhibited a significantly improved ability on these tests, indicating a complete neurobehavioral protective effect, while the mice in G4 showed partial protection. The nAChRs score showed higher expression in the case of G2 in comparison with G3, G4, and G5. Weight loss was exhibited in G2, while in G3 and G1 these values were normal. A therapeutic dose of memantine 10 mg/kg yielded more protection than 5 mg/kg in the treatment of neuropathy; this highlights the importance of using memantine to decrease the main side effects of cisplatin.

Scaled traumatic brain injury results in unique metabolomic signatures between gray matter, white matter, and serum in a piglet model

Traumatic brain injury (TBI) is a leading cause of death and long-term disability in the United States. The heterogeneity of the disease coupled with the lack of comprehensive, standardized scales to adequately characterize multiple types of TBI remain to be major challenges facing effective therapeutic development. A systems level approach to TBI diagnosis through the use of metabolomics could lead to a better understanding of cellular changes post-TBI and potential therapeutic targets. In the current study, we utilize a GC-MS untargeted metabolomics approach to demonstrate altered metabolism in response to TBI in a translational pig model, which possesses many neuroanatomical and pathophysiologic similarities to humans. TBI was produced by controlled cortical impact (CCI) in Landrace piglets with impact velocity and depth of depression set to 2m/s;6mm, 4m/s;6mm, 4m/s;12mm, or 4m/s;15mm resulting in graded neural injury. Serum samples were collected pre-TBI, 24 hours post-TBI, and 7 days post-TBI. Partial least squares discriminant analysis (PLS-DA) revealed that each impact parameter uniquely influenced the metabolomic profile after TBI, and gray and white matter responds differently to TBI on the biochemical level with evidence of white matter displaying greater metabolic change. Furthermore, pathway analysis revealed unique metabolic signatures that were dependent on injury severity and brain tissue type. Metabolomic signatures were also detected in serum samples which potentially captures both time after injury and injury severity. These findings provide a platform for the development of a more accurate TBI classification scale based unique metabolomic signatures.

Discovery of Lipidome Alterations Following Traumatic Brain Injury via High-Resolution Metabolomics

Traumatic brain injury (TBI) can occur across wide segments of the population, presenting in a heterogeneous manner that makes diagnosis inconsistent and management challenging. Biomarkers offer the potential to objectively identify injury status, severity, and phenotype by measuring the relative concentrations of endogenous molecules in readily accessible biofluids. Through a data-driven, discovery approach, novel biomarker candidates for TBI were identified in the serum lipidome of adult male Sprague-Dawley rats in the first week following moderate controlled cortical impact (CCI). Serum samples were analyzed in positive and negative modes by ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). A predictive panel for the classification of injured and uninjured sera samples, consisting of 26 dysregulated species belonging to a variety of lipid classes, was developed with a cross-validated accuracy of 85.3% using omniClassifier software to optimize feature selection. Polyunsaturated fatty acids (PUFAs) and PUFA-containing diacylglycerols were found to be upregulated in sera from injured rats, while changes in sphingolipids and other membrane phospholipids were also observed, many of which map to known secondary injury pathways. Overall, the identified biomarker panel offers viable molecular candidates representing lipids that may readily cross the blood-brain barrier (BBB) and aid in the understanding of TBI pathophysiology.

Staying in the game: a pilot study examining the efficacy of protective headgear in an animal model of mild traumatic brain injury (mTBI)

PRIMARY OBJECTIVE

Rugby is one of the few contact sports that do not mandate protective headgear, possibly because studies have shown poor efficacy for protection related to concussion pathology with existing headguards.

RESEARCH DESIGN

Following innovative material technology utilization to produce headgear believed to have protective capabilities, this study examined the effects of a soft-shell headgear constructed from a novel viscoelastic material, on both behaviour and serum biomarkers after high and average impact force mild traumatic brain injuries (mTBI).

METHODS AND PROCEDURES

Seventy-five male Sprague Dawley rats were divided into five groups: control, average - 37G impact, with and without headgear, and high - 106G impact, with and without headgear. Rats were sacrificed at 3 or 48 hours and serum samples were analyzed for levels of TNF-α, NEF-L, and GFAP. Animals sacrificed at 48 hours also underwent testing for balance and motor coordination, and exploratory/locomotor behaviour.

MAIN OUTCOMES AND RESULTS

The novel headgear offered significant protection against mTBI symptomology and biomarkers in the group that experienced an average impact force, but only moderated protection for the animals in the high impact group.

CONCLUSIONS

This innovative headgear may prevent some of the negative sequel associated with concussion pathology.

Large animal models of traumatic brain injury

Purpose/Aim: Animal models of traumatic brain injury (TBI) provide powerful tools to study TBI in a controlled, rigorous and cost-efficient manner. The mostly used animals in TBI studies so far are rodents. However, compared with rodents, large animals (e.g. swine, rabbit, sheep, ferret, etc.) show great advantages in modeling TBI due to the similarity of their brains to human brain. The aim of our review was to summarize the development and progress of common large animal TBI models in past 30 years.

MATERIALS AND METHODS

Mixed published articles and books associated with large animal models of TBI were researched and summarized.

RESULTS

We majorly sumed up current common large animal models of TBI, including discussion on the available research methodologies in previous studies, several potential therapies in large animal trials of TBI as well as advantages and disadvantages of these models.

CONCLUSIONS

Large animal models of TBI play crucial role in determining the underlying mechanisms and screening putative therapeutic targets of TBI.

Differential Neuroproteomic and Systems Biology Analysis of Spinal Cord Injury

Acute spinal cord injury (SCI) is a devastating condition with many consequences and no known effective treatment. Although it is quite easy to diagnose traumatic SCI, the assessment of injury severity and projection of disease progression or recovery are often challenging, as no consensus biomarkers have been clearly identified. Here rats were subjected to experimental moderate or severe thoracic SCI. At 24h and 7d postinjury, spinal cord segment caudal to injury center versus sham samples was harvested and subjected to differential proteomic analysis. Cationic/anionic-exchange chromatography, followed by 1D polyacrylamide gel electrophoresis, was used to reduce protein complexity. A reverse phase liquid chromatography-tandem mass spectrometry proteomic platform was then utilized to identify proteome changes associated with SCI. Twenty-two and 22 proteins were up-regulated at 24 h and 7 day after SCI, respectively; whereas 19 and 16 proteins are down-regulated at 24 h and 7 day after SCI, respectively, when compared with sham control. A subset of 12 proteins were identified as candidate SCI biomarkers - TF (Transferrin), FASN (Fatty acid synthase), NME1 (Nucleoside diphosphate kinase 1), STMN1 (Stathmin 1), EEF2 (Eukaryotic translation elongation factor 2), CTSD (Cathepsin D), ANXA1 (Annexin A1), ANXA2 (Annexin A2), PGM1 (Phosphoglucomutase 1), PEA15 (Phosphoprotein enriched in astrocytes 15), GOT2 (Glutamic-oxaloacetic transaminase 2), and TPI-1 (Triosephosphate isomerase 1), data are available via ProteomeXchange with identifier PXD003473. In addition, Transferrin, Cathepsin D, and TPI-1 and PEA15 were further verified in rat spinal cord tissue and/or CSF samples after SCI and in human CSF samples from moderate/severe SCI patients. Lastly, a systems biology approach was utilized to determine the critical biochemical pathways and interactome in the pathogenesis of SCI. Thus, SCI candidate biomarkers identified can be used to correlate with disease progression or to identify potential SCI therapeutic targets.

Role of Systems Biology in Brain Injury Biomarker Discovery: Neuroproteomics Application

Years of research in the field of neurotrauma have led to the concept of applying systems biology as a tool for biomarker discovery in traumatic brain injury (TBI). Biomarkers may lead to understanding mechanisms of injury and recovery in TBI and can be potential targets for wound healing, recovery, and increased survival with enhanced quality of life. The literature available on neurotrauma studies from both animal and clinical studies has provided rich insight on the molecular pathways and complex networks of TBI, elucidating the proteomics of this disease for the discovery of biomarkers. With such a plethora of information available, the data from the studies require databases with tools to analyze and infer new patterns and associations. The role of different systems biology tools and their use in biomarker discovery in TBI are discussed in this chapter.

Glial fibrillary acidic protein: from intermediate filament assembly and gliosis to neurobiomarker

Glial fibrillary acidic protein (GFAP) is an intermediate filament (IF) III protein uniquely found in astrocytes in the central nervous system (CNS), non-myelinating Schwann cells in the peripheral nervous system (PNS), and enteric glial cells. GFAP mRNA expression is regulated by several nuclear-receptor hormones, growth factors, and lipopolysaccharides (LPSs). GFAP is also subject to numerous post-translational modifications (PTMs), while GFAP mutations result in protein deposits known as Rosenthal fibers in Alexander disease. GFAP gene activation and protein induction appear to play a critical role in astroglial cell activation (astrogliosis) following CNS injuries and neurodegeneration. Emerging evidence also suggests that, following traumatic brain and spinal cord injuries and stroke, GFAP and its breakdown products are rapidly released into biofluids, making them strong candidate biomarkers for such neurological disorders.

How implementation of systems biology into clinical trials accelerates understanding of diseases

Systems biology comprises a series of concepts and approaches that have been used successfully both to delineate novel biological mechanisms and to drive translational advances. The goal of systems biology is to re-integrate putatively critical elements extracted from multi-modality datasets in order to understand how interactions among multiple components form functional networks at the organism/patient-level, and how dysfunction of these networks underlies a particular disease. Due to the genetic and environmental diversity of human subjects, identification of critical elements related to a particular disease process from cross-sectional studies requires prohibitively large cohorts. Alternatively, implementation of systems biology principles to interventional clinical trials represents a unique opportunity to gain predictive understanding of complex diseases in comparatively small cohorts of patients. This paper reviews systems biology principles applicable to translational research, focusing on lessons from systems approaches to inflammation applied to multiple sclerosis. We suggest that employing systems biology methods in the design and execution of biomarker-supported, proof-of-principle clinical trials provides a singular opportunity to merge therapeutic development with a basic understanding of disease processes. The ultimate goal is to develop predictive computational models of the disease, which will revolutionize diagnostic process and provide mechanistic understanding necessary for personalized therapeutic approaches. Added, biologically meaningful information can be derived from diagnostic tests, if they are interpreted in functional relationships, rather than as independent measurements. Such systems biology based diagnostics will transform disease taxonomies from phenotypical to molecular and will allow physicians to select optimal therapeutic regimens for individual patients.

Evaluation of impact-induced traumatic brain injury in the Göttingen Minipig using two input modes

OBJECTIVES

Two novel injury devices were used to characterize impact-induced traumatic brain injury (TBI). One imparts pure translation, and the other produces combined translation and rotation. The objective of this study was to evaluate the neuropathology associated with two injury devices using proton magnetic resonance spectroscopy (1H-MRS) to quantify metabolic changes and immunohistochemistry (IHC) to evaluate axonal damage in the corpus callosum.

METHODS

Young adult female Göttingen minipigs were exposed to impact-induced TBI with either the translation-input injury device or the combined-input injury device (n=11/group). Sham animals were treated identically except for the injury event (n=3). The minipigs underwent 1H-MRS scans prior to injury (baseline), approximately 1 h after injury, and 24 h post injury, at which point the brains were extracted for IHC. Metabolites of interest include glutamate (Glu), glutamine (Gln), N-acetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), and γ-aminobutyric acid (GABA). Repeated measures analysis of variance with a least significant difference post hoc test were used to compare the three time points. IHC was performed on paraffin-embedded sections of the corpus callosum with light and heavy neurofilament antibodies. Stained pixel percentages were compared between shams and 24-h survival animals.

RESULTS

For the translation-input group (27.5-70.1 g), 16 significant metabolite differences were found. Three of these include a significant increase in Gln, both 1 h and 24 h postinjury, and an increase in GABA 24 h after injury. For the combined-input group (40.1-95.9 g; 1,014.5-3,814.9 rad/s2; 7.2-10.8 rad/s), 20 significant metabolite differences were found. Three of these include a significant increase in Glu, an increase in the ratio Glu/Gln, and an increase in the ratio Glu/NAAG 24 h after injury. The IHC analysis revealed significant increases in light and heavy neurofilament for both groups 24 h after injury.

CONCLUSIONS

Only five metabolite differences were similar between the input modes, most of which are related to inflammation or myelin disruption. The observed metabolite differences indicate important dissimilarities. For the translation-input group, an increase in Gln and GABA suggests a response in the GABA shunt system. For the combined-input group, an increase in Glu, Glu/Gln, and Glu/NAAG suggests glutamate excitotoxicity. Importantly, both of these input modes lead to similar light and heavy neurofilament damage, which indicates axonal disruption. Identifying neuropathological changes that are unique to different injury mechanisms is critical in defining the complexity of TBI and can lead to improved prevention strategies and the development of effective drug therapies.

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.

Pathway analysis reveals common pro-survival mechanisms of metyrapone and carbenoxolone after traumatic brain injury

Developing new pharmacotherapies for traumatic brain injury (TBI) requires elucidation of the neuroprotective mechanisms of many structurally and functionally diverse compounds. To test our hypothesis that diverse neuroprotective drugs similarly affect common gene targets after TBI, we compared the effects of two drugs, metyrapone (MT) and carbenoxolone (CB), which, though used clinically for noncognitive conditions, improved learning and memory in rats and humans. Although structurally different, both MT and CB inhibit a common molecular target, 11β hydroxysteroid dehydrogenase type 1, which converts inactive cortisone to cortisol, thereby effectively reducing glucocorticoid levels. We examined injury-induced signaling pathways to determine how the effects of these two compounds correlate with pro-survival effects in surviving neurons of the injured rat hippocampus. We found that treatment of TBI rats with MT or CB acutely induced in hippocampal neurons transcriptional profiles that were remarkably similar (i.e., a coordinated attenuation of gene expression across multiple injury-induced cell signaling networks). We also found, to a lesser extent, a coordinated increase in cell survival signals. Analysis of injury-induced gene expression altered by MT and CB provided additional insight into the protective effects of each. Both drugs attenuated expression of genes in the apoptosis, death receptor and stress signaling pathways, as well as multiple genes in the oxidative phosphorylation pathway such as subunits of NADH dehydrogenase (Complex1), cytochrome c oxidase (Complex IV) and ATP synthase (Complex V). This suggests an overall inhibition of mitochondrial function. Complex 1 is the primary source of reactive oxygen species in the mitochondrial oxidative phosphorylation pathway, thus linking the protective effects of these drugs to a reduction in oxidative stress. The net effect of the drug-induced transcriptional changes observed here indicates that suppressing expression of potentially harmful genes, and also, surprisingly, reduced expression of pro-survival genes may be a hallmark of neuroprotective therapeutic effects.

Systems biology, bioinformatics, and biomarkers in neuropsychiatry

Although neuropsychiatric (NP) disorders are among the top causes of disability worldwide with enormous financial costs, they can still be viewed as part of the most complex disorders that are of unknown etiology and incomprehensible pathophysiology. The complexity of NP disorders arises from their etiologic heterogeneity and the concurrent influence of environmental and genetic factors. In addition, the absence of rigid boundaries between the normal and diseased state, the remarkable overlap of symptoms among conditions, the high inter-individual and inter-population variations, and the absence of discriminative molecular and/or imaging biomarkers for these diseases makes difficult an accurate diagnosis. Along with the complexity of NP disorders, the practice of psychiatry suffers from a "top-down" method that relied on symptom checklists. Although checklist diagnoses cost less in terms of time and money, they are less accurate than a comprehensive assessment. Thus, reliable and objective diagnostic tools such as biomarkers are needed that can detect and discriminate among NP disorders. The real promise in understanding the pathophysiology of NP disorders lies in bringing back psychiatry to its biological basis in a systemic approach which is needed given the NP disorders' complexity to understand their normal functioning and response to perturbation. This approach is implemented in the systems biology discipline that enables the discovery of disease-specific NP biomarkers for diagnosis and therapeutics. Systems biology involves the use of sophisticated computer software "omics"-based discovery tools and advanced performance computational techniques in order to understand the behavior of biological systems and identify diagnostic and prognostic biomarkers specific for NP disorders together with new targets of therapeutics. In this review, we try to shed light on the need of systems biology, bioinformatics, and biomarkers in neuropsychiatry, and illustrate how the knowledge gained through these methodologies can be translated into clinical use providing clinicians with improved ability to diagnose, manage, and treat NP patients.