Application of Systems Biology to Neuroproteomics: The Path to Enhanced Theranostics in Traumatic Brain Injury

Neurotrauma investigation through spatial omics guided by mass spectrometry imaging: Target identification and clinical applications

Traumatic brain injury (TBI) represents one of the major public health concerns worldwide due to the increase in TBI incidence as a result of injuries from daily life accidents such as sports and motor vehicle transportation as well as military-related practices. This type of central nervous system trauma is known to predispose patients to several neurological disorders such as Parkinson's disease, Alzheimer's disease, chronic trauamatic encephalopathy, and age-related Dementia. Recently, several proteomic and lipidomic platforms have been applied on different TBI studies to investigate TBI-related mechanisms that have broadened our understanding of its distinct neuropathological complications. In this study, we provide an updated comprehensive overview of the current knowledge and novel perspectives of the spatially resolved microproteomics and microlipidomics approaches guided by mass spectrometry imaging used in TBI studies and its applications in the neurotrauma field. In this regard, we will discuss the use of the spatially resolved microproteomics and assess the different microproteomic sampling methods such as laser capture microdissection, parafilm assisted microdissection, and liquid microjunction extraction as accurate and precise techniques in the field of neuroproteomics. Additionally, we will highlight lipid profiling applications and their prospective potentials in characterizing molecular processes involved in the field of TBI. Specifically, we will discuss the phospholipid metabolism acting as a precursor for proinflammatory molecules such as eicosanoids. Finally, we will survey the current state of spatial neuroproteomics and microproteomics applications and present the various studies highlighting their findings in these fields.

TMT-based proteomics analysis to screen potential biomarkers of acute-phase TBI in rats

AIMS

Traumatic brain injury (TBI) is a common nervous system injury. However, the detailed mechanisms about functional dysregulation and dignostic biomarkers post-TBI are still unclear. So we aimed to identify potential differentially expressed proteins and genes in TBI for clinical diagnosis and therapeutic purposes.

MAIN METHODS

Rat TBI model was established by the weight-drop method. First, through TMT-proteomics, we screened for the change in the proteins expression profile acute phase post-TBI. The DAVID and Reactome databases were used to analyze and visualize the dysregulation proteins. Then, using publicly available microarray datasets GSE45997, differentially expressed genes (DGEs) were identified for the 24 h post-TBI stage. Also, the proteomic data were compared with microarray data to analyze the similarity.

KEY FINDINGS

We found significant proteomics and transcriptomic changes in post-TBI samples. 989, 881, 832, 1057 proteins were quantitated at 1 h, 6 h, 24 h, and 3 d post-injury correspondingly. Concerning proteomics findings, oxygen transport, acute-phase response, and negative regulation of endopeptidase activity were influenced throughout the acute phrase of TBI. Also, pathways related to scavenging of heme from plasma, binding, and uptake of ligands by scavenger receptors were highly enriched in all time-points of TBI samples.

SIGNIFICANCE

We noticed that the interaction-networks trend to get complicated with more node connections following the progression of TBI. We inferred that Hk-1, PRKAR2A, and MBP could be novel candidate biomarkers related to time-injury in acute-phase TBI. Also, Ceruloplasmin and Complement C3 were found to be important proteins and genes are involved in the TBI.

Protein Expression Analysis of an In Vitro Murine Model of Prostate Cancer Progression: Towards Identification of High-Potential Therapeutic Targets

Background: Prostate cancer (PC) is the most frequently diagnosed cancer among men worldwide. The poor prognosis of PC is largely due to late diagnosis of the disease when it has progressed to advanced stages marked by androgen-independence. We interrogated proteomic signatures that embody the transition of PC from an androgen-dependent (AD) to an androgen-independent (AI) state. Methods: We have previously established AD and AI murine PC cell lines, PLum-AD and PLum-AI, respectively, which recapitulate primary and progressive PC at phenotypic and subcellular levels. We statistically surveyed global protein expression profiles in these cell lines. Differential profiles were functionally interrogated by pathways and protein–protein interaction network analyses. Results: Protein expression pattern analysis revealed a total of 683 proteins, among which 99 were significantly differentially altered in PLum-AI cells as compared to PLum-AD cells (45 increased and 54 decreased). Principal component analysis (PCA) revealed that the two different cell lines clearly separated apart, indicating a significant proteome expression difference between them. Four of the proteins (vimentin, catalase, EpCAM, and caspase 3) that were differentially expressed in PLum-AI cells compared to PLum-AD cells were subjected to biochemical validation by Western blotting. Biological process gene ontology (GO) analysis of the differentially expressed proteins demonstrated enrichment of biological functions and pathways in PLum-AI cells that are central to PI3 kinase and androgen receptor pathways. Besides, other relevant biological processes that are enriched in PLum-AI cells included cell adhesion and cell migration processes, cell and DNA damage, apoptosis, and cell cycle regulation. Conclusions: Our protein expression analysis of a murine in vitro model of PC progression identified differential protein spots that denote this progression and that comprise high-potential targets for early treatment of PC with a personalized patient-specific approach. Efforts are underway to functionally assess the potential roles of these proteins as therapeutic targets for PC progression.

Biomarkers in traumatic brain injury: new concepts

Traumatic brain injury is a multifaceted condition that encompasses a spectrum of injuries: contusions, axonal injuries in specific brain regions, edema, and hemorrhage. Brain injury determines a broad clinical and disability spectrum due to the implication of various cellular pathways, genetic phenotypes, and environmental factors. It is challenging to predict patient outcomes, to appropriately evaluate the patients, to determine a suitable treatment strategy and rehabilitation program, and to communicate with patient relatives. Biomarkers detected from body fluids are potential evaluation tools for traumatic brain injury patients. These may serve as internal indicators of cerebral damage, delivering valuable information about the dynamic cellular, biochemical, and molecular environments. The diagnostic and prognostic value of biomarkers tested both in animal models of traumatic brain injury is still under question, despite a considerable scientific literature. Recent publications emphasize that a more realistic approach involves combining multiple types of biomarkers with other investigative tools (imaging, outcome scales, and genetic polymorphisms). Additionally, there is increasing interest in the use of biomarkers as tools for treatment monitoring and as surrogate outcome variables to facilitate the design of distinct randomized controlled trials. This review highlights the latest available evidence regarding biomarkers in adults after traumatic brain injury and discusses new approaches in the evaluation of this patient group.

"Gestaltomics": Systems Biology Schemes for the Study of Neuropsychiatric Diseases

The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed.

Neuroproteomics Studies: Challenges and Updates

The Human Genome Project in 2003 has resulted in the complete sequence of ~99% of the human genome paving the road for the Human Proteome Project (HPP) assessing the full characterization of the translated protein map of the 20,300 protein-coding genes. Consequently, the emerging of the proteomics field has successfully been adopted as the method of choice for the proteome characterization. Proteomics is a term that is used to encompass multidisciplinary approaches combining different technologies that aim to study the entire spectrum of protein changes at a specific physiological condition. Proteomics research has shown excellent outcomes in different fields, among which is neuroscience; however, the complexity of the nervous systems necessitated the genesis of a new subdiscipline of proteomics termed as "neuroproteomics." Neuroproteomics studies involve assessing the quantitative and qualitative aspects of nervous system components encompassing global dynamic events underlying various brain-related disorders ranging from neuropsychiatric disorders, degenerative disorders, mental illness, and most importantly brain-specific neurotrauma-related injuries. In this introductory chapter, we will provide a brief historical perspective on the field of neuroproteomics. In doing so, we will highlight on the recent applications of neuroproteomics in the areas of neurotrauma, an area that has benefitted from neuroproteomics in terms of biomarker research, spatiotemporal injury mechanism, and its use to translate its findings from experimental settings to human translational applications. Importantly, this chapter will include some recommendation to the general studies in the area of neuroproteomics and the need to move from this field from being a descriptive, hypothesis-free approach to being an independent mature scientific discipline.