Connecting Brain Proteomics with Behavioural Neuroscience in Translational Animal Models of Neuropsychiatric Disorders. In: Guest PC, editor. Proteomic Methods in Neuropsychiatric Research. Cham: Springer International Publishing; 2017. pp. 97-114. [DOI: 10.1007/978-3-319-52479-5_6]

Nicotine Exposure in a Phencyclidine-Induced Mice Model of Schizophrenia: Sex-Selective Medial Prefrontal Cortex Protein Markers of the Combined Insults in Adolescent Mice

Tobacco misuse as a comorbidity of schizophrenia is frequently established during adolescence. However, comorbidity markers are still missing. Here, the method of label-free proteomics was used to identify deregulated proteins in the medial prefrontal cortex (prelimbic and infralimbic) of male and female mice modelled to schizophrenia with a history of nicotine exposure during adolescence. Phencyclidine (PCP), used to model schizophrenia (SCHZ), was combined with an established model of nicotine minipump infusions (NIC). The combined insults led to worse outcomes than each insult separately when considering the absolute number of deregulated proteins and that of exclusively deregulated ones. Partially shared Reactome pathways between sexes and between PCP, NIC and PCPNIC groups indicate functional overlaps. Distinctively, proteins differentially expressed exclusively in PCPNIC mice reveal unique effects associated with the comorbidity model. Interactome maps of these proteins identified sex-selective subnetworks, within which some proteins stood out: for females, peptidyl-prolyl cis-trans isomerase (Fkbp1a) and heat shock 70 kDa protein 1B (Hspa1b), both components of the oxidative stress subnetwork, and gamma-enolase (Eno2), a component of the energy metabolism subnetwork; and for males, amphiphysin (Amph), a component of the synaptic transmission subnetwork. These are proposed to be further investigated and validated as markers of the combined insult during adolescence.

Ketogenic diet for schizophrenia: clinical implication

PURPOSE OF REVIEW

The aim of this article is to review recent findings on the efficacy of ketogenic diet in preclinical models and in patients with schizophrenia. This review will also highlight emerging evidence for compromised glucose and energy metabolism in schizophrenia, which provides a strong rationale and a potential mechanism of action for ketogenic diet.

RECENT FINDINGS

Recent transcriptomic, proteomic and metabolomic evidence from postmortem prefrontal cortical samples and in-vivo NMR spectroscopy results support the hypothesis that there is a bioenergetics dysfunction characterized by abnormal glucose handling and mitochondrial dysfunctions resulting in impaired synaptic communication in the brain of people with schizophrenia. Ketogenic diet, which provides alternative fuel to glucose for bioenergetic processes in the brain, normalizes schizophrenia-like behaviours in translationally relevant pharmacological and genetic mouse models. Furthermore, recent case studies demonstrate that ketogenic diet produces improvement in psychiatric symptoms as well as metabolic dysfunctions and body composition in patients with schizophrenia.

SUMMARY

These results support that ketogenic diet may present a novel therapeutic approach through restoring brain energy metabolism in schizophrenia. Randomized controlled clinical trials are needed to further show the efficacy of ketogenic diet as a co-treatment to manage both clinical symptoms and metabolic abnormalities inherent to the disease and resulted by antipsychotic treatment.

Enhanced Molecular Appreciation of Psychiatric Disorders Through High-Dimensionality Data Acquisition and Analytics

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

Proteomic Analysis of the Human Olfactory Bulb

The importance of olfaction to human health and disease is often underappreciated. Olfactory dysfunction has been reported in association with a host of common complex diseases, including neurological diseases such as Alzheimer's disease and Parkinson's disease. For health, olfaction or the sense of smell is also important for most mammals, for optimal engagement with their environment. Indeed, animals have developed sophisticated olfactory systems to detect and interpret the rich information presented to them to assist in day-to-day activities such as locating food sources, differentiating food from poisons, identifying mates, promoting reproduction, avoiding predators, and averting death. In this context, the olfactory bulb is a vital component of the olfactory system receiving sensory information from the axons of the olfactory receptor neurons located in the nasal cavity and the first place that processes the olfactory information. We report in this study original observations on the human olfactory bulb proteome in healthy subjects, using a high-resolution mass spectrometry-based proteomic approach. We identified 7750 nonredundant proteins from human olfactory bulbs. Bioinformatics analysis of these proteins showed their involvement in biological processes associated with signal transduction, metabolism, transport, and olfaction. These new observations provide a crucial baseline molecular profile of the human olfactory bulb proteome, and should assist the future discovery of biomarker proteins and novel diagnostics associated with diseases characterized by olfactory dysfunction.

A new SWATH ion library for mouse adult hippocampal neural stem cells

Over the last years, the SWATH data-independent acquisition protocol (Sequential Window acquisition of All THeoretical mass spectra) has become a cornerstone for the worldwide proteomics community (Collins et al., 2017) [1]. In this approach, a high-resolution quadrupole-ToF mass spectrometer acquires thousands of MS/MS data by selecting not just a single precursor at a time, but by allowing a broad m/z range to be fragmented. This acquisition window is then sequentially moved from the lowest to the highest mass selection range. This technique enables the acquisition of thousands of high-resolution MS/MS spectra per minute in a standard LC–MS run. In the subsequent data analysis phase, the corresponding dataset is searched in a “triple quadrupole-like” mode, thus not considering the whole MS/MS scan spectrum, but by searching for several precursor to fragment transitions that identify and quantify the corresponding peptide. This search is made possible with the use of an ion library, previously acquired in a classical data dependent, full-spectrum mode (Fabre et al., 2017; Wu et al., 2017) [2], [3]. The SWATH protocol, combining the protein identification power of high-resolution MS/MS spectra with the robustness and accuracy in analyte quantification of triple-quad targeted workflows, has become very popular in proteomics research. The major drawback lies in the ion library itself, which is normally demanding and time-consuming to build. Conversely, through the realignment of chromatographic retention times, an ion library of a given proteome can relatively easily be tailored upon “any” proteomics experiment done on the same proteome. We are thus hereby sharing with the worldwide proteomics community our newly acquired ion library of mouse adult hippocampal neural stem cells. Given the growing effort in neuroscience research involving proteomics experiments (Pons-Espinal et al., 2017; Sarnyai and Guest, 2017; Sethi et al., 2015; Bramini et al., 2016) [4,[5], [6], [7], we believe that this data might be of great help for the neuroscience community. All the here reported data (RAW files, results and ion library) can be freely downloaded from the SWATHATLAS (Deutsch et al., 2008) [8] website (http://www.peptideatlas.org/PASS/PASS01110)