Integrative metabolomics-genomics analysis identifies key networks in a stem cell-based model of schizophrenia.

Schizophrenia (SCZ) is a neuropsychiatric disorder, caused by a combination of genetic and environmental factors. The etiology behind the disorder remains elusive although it is hypothesized to be associated with the aberrant response to neurotransmitters, such as dopamine and glutamate. Therefore, investigating the link between dysregulated metabolites and distorted neurodevelopment holds promise to offer valuable insights into the underlying mechanism of this complex disorder. In this study, we aimed to explore a presumed correlation between the transcriptome and the metabolome in a SCZ model based on patient-derived induced pluripotent stem cells (iPSCs). For this, iPSCs were differentiated towards cortical neurons and samples were collected longitudinally at various developmental stages, reflecting neuroepithelial-like cells, radial glia, young and mature neurons. The samples were analyzed by both RNA-sequencing and targeted metabolomics and the two modalities were used to construct integrative networks in silico. This multi-omics analysis revealed significant perturbations in the polyamine and gamma-aminobutyric acid (GABA) biosynthetic pathways during rosette maturation in SCZ lines. We particularly observed the downregulation of the glutamate decarboxylase encoding genes GAD1 and GAD2, as well as their protein product GAD65/67 and their biochemical product GABA in SCZ samples. Inhibition of ornithine decarboxylase resulted in further decrease of GABA levels suggesting a compensatory activation of the ornithine/putrescine pathway as an alternative route for GABA production. These findings indicate an imbalance of cortical excitatory/inhibitory dynamics occurring during early neurodevelopmental stages in SCZ. Our study supports the hypothesis of disruption of inhibitory circuits to be causative for SCZ and establishes a novel in silico approach that enables for integrative correlation of metabolic and transcriptomic data of psychiatric disease models.

Proteome Coverage after Simultaneous Proteo-Metabolome Liquid-Liquid Extraction.

Proteomics and metabolomics are essential in systems biology, and simultaneous proteo-metabolome liquid-liquid extraction (SPM-LLE) allows isolation of the metabolome and proteome from the same sample. Since the proteome is present as a pellet in SPM-LLE, it must be solubilized for quantitative proteomics. Solubilization and proteome extraction are critical factors in the information obtained at the proteome level. In this study, we investigated the performance of two surfactants (sodium deoxycholate (SDC), sodium dodecyl sulfate (SDS)) and urea in terms of proteome coverage and extraction efficiency of an interphase proteome pellet generated by methanol-chloroform based SPM-LLE. We also investigated how the performance differs when the proteome is extracted from the interphase pellet or by direct cell lysis. We quantified 12 lipids covering triglycerides and various phospholipid classes, and 25 polar metabolites covering central energy metabolism in chloroform and methanol extracts. Our study reveals that the proteome coverages between the two surfactants and urea for the SPM-LLE interphase pellet were similar, but the extraction efficiencies differed significantly. While SDS led to enrichment of basic proteins, which were mainly ribosomal and ribonuclear proteins, urea was the most efficient extraction agent for simultaneous proteo-metabolome analysis. The results of our study also show that the performance of surfactants for quantitative proteomics is better when the proteome is extracted through direct cell lysis rather than an interphase pellet. In contrast, the performance of urea for quantitative proteomics was significantly better when the proteome was extracted from an interphase pellet than by direct cell lysis. We demonstrated that urea is superior to surfactants for proteome extraction from SPM-LLE interphase pellets, with a particularly good performance for the extraction of proteins associated with metabolic pathways. Data are available via ProteomeXchange with identifier PXD027338.

Protein speciation is likely to increase the chance of proteins to be determined in 2-DE/MS.

Multiple spotting due to protein speciation might increase a protein's chance of being captured in a random selection of 2-DE spots. We tested this expectation in new (PXD015649) and previously published 2-DE/MS data of porcine and human tissues. For comparison, we included bottom-up proteomics studies (BU-LC/MS) of corresponding biological materials. Analyses of altogether ten datasets proposed that amino acid modification fosters multispotting in 2-DE. Thus, the number of 2-DE spots containing a particular protein more tightly associated with a peptide diversity measure accounting for amino acid modification than with an alternative one disregarding it. Furthermore, every 11th amino acid was a post-translational modification candidate site in 2-DE/MS proteins, whereas in BU-LC/MS proteins this was merely the case in every 21st amino acid. Alternative splicing might contribute to multispotting, since genes encoding 2-DE/MS proteins were found to have on average about 0.3 more transcript variants than their counterparts from BU-LC/MS studies. Correspondingly, resolution completeness as estimated from the representation of transcript variant-rich genes was higher in 2-DE/MS than BU-LC/MS datasets. These findings suggest that the ability to resolve proteomes down to protein species can lead to enrichment of multispotting proteins in 2-DE/MS. Low sensitivity of stains and MS instruments appears to enhance this effect.

Combined Metabolic and Chemical (CoMetChem) Labeling Using Stable Isotopes-a Strategy to Reveal Site-Specific Histone Acetylation and Deacetylation Rates by LC-MS.

Histone acetylation is an important, reversible post-translational protein modification and a hallmark of epigenetic regulation. However, little is known about the dynamics of this process, due to the lack of analytical methods that can capture site-specific acetylation and deacetylation reactions. We present a new approach that combines metabolic and chemical labeling (CoMetChem) using uniformly 13C-labeled glucose and stable isotope-labeled acetic anhydride. Thereby, chemically equivalent, fully acetylated histone species are generated, enabling accurate relative quantification of site-specific lysine acetylation dynamics in tryptic peptides using high-resolution mass spectrometry. We show that CoMetChem enables site-specific quantification of the incorporation or loss of lysine acetylation over time, allowing the determination of reaction rates for acetylation and deacetylation. Thus, the CoMetChem methodology provides a comprehensive description of site-specific acetylation dynamics.

PI(18:1/18:1) is a SCD1-derived lipokine that limits stress signaling.

Cytotoxic stress activates stress-activated kinases, initiates adaptive mechanisms, including the unfolded protein response (UPR) and autophagy, and induces programmed cell death. Fatty acid unsaturation, controlled by stearoyl-CoA desaturase (SCD)1, prevents cytotoxic stress but the mechanisms are diffuse. Here, we show that 1,2-dioleoyl-sn-glycero-3-phospho-(1'-myo-inositol) [PI(18:1/18:1)] is a SCD1-derived signaling lipid, which inhibits p38 mitogen-activated protein kinase activation, counteracts UPR, endoplasmic reticulum-associated protein degradation, and apoptosis, regulates autophagy, and maintains cell morphology and proliferation. SCD1 expression and the cellular PI(18:1/18:1) proportion decrease during the onset of cell death, thereby repressing protein phosphatase 2 A and enhancing stress signaling. This counter-regulation applies to mechanistically diverse death-inducing conditions and is found in multiple human and mouse cell lines and tissues of Scd1-defective mice. PI(18:1/18:1) ratios reflect stress tolerance in tumorigenesis, chemoresistance, infection, high-fat diet, and immune aging. Together, PI(18:1/18:1) is a lipokine that links fatty acid unsaturation with stress responses, and its depletion evokes stress signaling.

Pharmacological characterization of mutant huntingtin aggregate-directed PET imaging tracer candidates.

Huntington's disease (HD) is caused by a CAG trinucleotide repeat expansion in the first exon of the huntingtin (HTT) gene coding for the huntingtin (HTT) protein. The misfolding and consequential aggregation of CAG-expanded mutant HTT (mHTT) underpin HD pathology. Our interest in the life cycle of HTT led us to consider the development of high-affinity small-molecule binders of HTT oligomerized/amyloid-containing species that could serve as either cellular and in vivo imaging tools or potential therapeutic agents. We recently reported the development of PET tracers CHDI-180 and CHDI-626 as suitable for imaging mHTT aggregates, and here we present an in-depth pharmacological investigation of their binding characteristics. We have implemented an array of in vitro and ex vivo radiometric binding assays using recombinant HTT, brain homogenate-derived HTT aggregates, and brain sections from mouse HD models and humans post-mortem to investigate binding affinities and selectivity against other pathological proteins from indications such as Alzheimer's disease and spinocerebellar ataxia 1. Radioligand binding assays and autoradiography studies using brain homogenates and tissue sections from HD mouse models showed that CHDI-180 and CHDI-626 specifically bind mHTT aggregates that accumulate with age and disease progression. Finally, we characterized CHDI-180 and CHDI-626 regarding their off-target selectivity and binding affinity to beta amyloid plaques in brain sections and homogenates from Alzheimer's disease patients.

Meso scale discovery-based assays for the detection of aggregated huntingtin.

Huntington's disease (HD) is a monogenic neurodegenerative disorder caused by an expansion of the CAG trinucleotide repeat domain in the huntingtin (HTT) gene, leading to an expanded poly-glutamine (polyQ) stretch in the HTT protein. This mutant HTT (mHTT) protein is highly prone to intracellular aggregation, causing significant damage and cellular loss in the striatal, cortical, and other regions of the brain. Therefore, modulation of mHTT levels in these brain regions in order to reduce intracellular mHTT and aggregate levels represents a direct approach in the development of HD therapeutics. To this end, assays that can be used to detect changes in HTT levels in biological samples are invaluable tools to assess target engagement and guide dose selection in clinical trials. The Meso Scale Discovery (MSD) ELISA-based assay platform is a robust and sensitive method previously employed for the quantification of HTT. However, the currently available MSD assays for HTT are primarily detecting the monomeric soluble form of the protein, but not aggregated species. In this study, we describe the development of novel MSD assays preferentially detecting mHTT in an aggregated form. Recombinant monomeric HTT(1-97)-Q46, which forms aggregates in a time-dependent manner, was used to characterize the ability of each established assay to distinguish between HTT monomers and HTT in a higher assembly state. Further validation of these assays was performed using brain lysates from R6/2, zQ175 knock-in, and BACHD mouse models, to replicate a previously well-characterized age-dependent increase in brain aggregate signals, as well as a significant reduction of aggregate levels in the striatum following mHTT knockdown with a CAG-directed allele-specific zinc-finger repressor protein (ZFP). Lastly, size exclusion chromatography was used to separate and characterize HTT species from brain tissue lysates to demonstrate specificity of the assays for the fractions containing aggregated HTT. In summary, we demonstrate that the newly developed assays preferentially detect aggregated HTT with improved performance in comparison to previous assay technologies. These assays complement the existing MSD platform assays specific for soluble HTT monomers, allowing for a more comprehensive analysis of disease-relevant HTT species in preclinical models of HD.