Hippocampal network hyperexcitability is considered an early indicator of Alzheimer's disease (AD) memory impairment. Some AD mouse models exhibit similar network phenotypes. In this study we focused on dentate gyrus (DG) granule cell spontaneous and evoked properties in 9-month-old Tg2576 mice that model AD amyloidosis and cognitive deficits. Using whole-cell patch-clamp recordings, we found that Tg2576 DG granule cells exhibited spontaneous EPSCs that were higher in frequency but not amplitude compared with wild-type mice, suggesting hyperactivity of DG granule cells via a presynaptic mechanism. Further support of a presynaptic mechanism was revealed by increased I-O relationships and probability of release in Tg2576 DG granule cells. Since we and others have shown that activation of the peroxisome proliferator-activated receptor gamma (PPAR?) axis improves hippocampal cognition in mouse models for AD as well as benefitting memory performance in some humans with early AD, we investigated how PPAR? agonism affected synaptic activity in Tg2576 DG. We found that PPAR? agonism normalized the I-O relationship of evoked EPSCs, frequency of spontaneous EPSCs, and probability of release that, in turn, correlated with selective expression of DG proteins essential for presynaptic SNARE function that are altered in patients with AD. These findings provide evidence that DG principal cells may contribute to early AD hippocampal network hyperexcitability via a presynaptic mechanism, and that hippocampal cognitive enhancement via PPAR? activation occurs through regulation of presynaptic vesicular proteins critical for proper glutamatergic neurotransmitter release, synaptic transmission, and short-term plasticity.
We describe a method for ratio estimations in (18)O-water labeling experiments acquired from low resolution isotopically resolved data. The method is implemented in a software package specifically designed for use in experiments making use of zoom-scan mode data acquisition. Zoom-scan mode data allow commonly used ion trap mass spectrometers to attain isotopic resolution, which makes them amenable to use in labeling schemes such as (18)O-water labeling, but algorithms and software developed for high resolution instruments may not be appropriate for the lower resolution data acquired in zoom-scan mode. The use of power spectrum analysis is proposed as a general approach that may be uniquely suited to these data types. The software implementation uses a power spectrum to remove high-frequency noise and band-filter contributions from coeluting species of differing charge states. From the elemental composition of a peptide sequence, we generate theoretical isotope envelopes of heavy-light peptide pairs in five different ratios; these theoretical envelopes are correlated with the filtered experimental zoom scans. To automate peptide quantification in high-throughput experiments, we have implemented our approach in a computer program, MassXplorer. We demonstrate the application of MassXplorer to two model mixtures of known proteins and to a complex mixture of mouse kidney cortical extract. Comparison with another algorithm for ratio estimations demonstrates the increased precision and automation of MassXplorer.
Numerous metabolic pathways have been implicated in diabetes-induced renal injury, yet few studies have utilized unbiased systems biology approaches for mapping the interconnectivity of diabetes-dysregulated proteins that are involved. We utilized a global, quantitative, differential proteomic approach to identify a novel retinoic acid hub in renal cortical protein networks dysregulated by type 2 diabetes.
We previously reported that the peroxisome proliferator-activated receptor ? (PPAR?) agonist rosiglitazone (RSG) improved hippocampus-dependent cognition in the Alzheimers disease (AD) mouse model, Tg2576. RSG had no effect on wild-type littermate cognitive performance. Since extracellular signal-regulated protein kinase mitogen-activated protein kinase (ERK MAPK) is required for many forms of learning and memory that are affected in AD, and since both PPAR? and ERK MAPK are key mediators of insulin signaling, the current study tested the hypothesis that RSG-mediated cognitive improvement induces a hippocampal PPAR? pattern of gene and protein expression that converges with the ERK MAPK signaling axis in Tg2576 AD mice. In the hippocampal PPAR? transcriptome, we found significant overlap between peroxisome proliferator response element-containing PPAR? target genes and ERK-regulated, cAMP response element-containing target genes. Within the Tg2576 dentate gyrus proteome, RSG induced proteins with structural, energy, biosynthesis and plasticity functions. Several of these proteins are known to be important for cognitive function and are also regulated by ERK MAPK. In addition, we found the RSG-mediated augmentation of PPAR? and ERK2 activity during Tg2576 cognitive enhancement was reversed when hippocampal PPAR? was pharmacologically antagonized, revealing a coordinate relationship between PPAR? transcriptional competency and phosphorylated ERK that is reciprocally affected in response to chronic activation, compared with acute inhibition, of PPAR?. We conclude that the hippocampal transcriptome and proteome induced by cognitive enhancement with RSG harnesses a dysregulated ERK MAPK signal transduction pathway to overcome AD-like cognitive deficits in Tg2576 mice. Thus, PPAR? represents a signaling system that is not crucial for normal cognition yet can intercede to restore neural networks compromised by AD.
The National NeuroAIDS Tissue Consortium (NNTC) performed a brain gene expression array to elucidate pathophysiologies of Human Immunodeficiency Virus type 1 (HIV-1)-associated neurocognitive disorders.
Traumatic brain injury (TBI) is a complex and common problem resulting in the loss of cognitive function. In order to build a comprehensive knowledge base of the proteins that underlie these cognitive deficits, we employed unbiased quantitative mass spectrometry, proteomics, and bioinformatics to identify and quantify dysregulated proteins in the CA3 subregion of the hippocampus in the fluid percussion model of TBI in rats. Using stable isotope 18O-water differential labeling and multidimensional tandem liquid chromatography (LC)-MS/MS with high stringency statistical analyses and filtering, we identified and quantified 1002 common proteins, with 124 increased and 76 decreased. The ingenuity pathway analysis (IPA) bioinformatics tool identified that TBI had profound effects on downregulating global energy metabolism, including glycolysis, the Krebs cycle, and oxidative phosphorylation, as well as cellular structure and function. Widespread upregulation of actin-related cytoskeletal dynamics was also found. IPA indicated a common integrative signaling node, calcineurin B1 (CANB1, CaNB?, or PPP3R1), which was downregulated by TBI. Western blotting confirmed that the calcineurin regulatory subunit, CANB1, and its catalytic binding partner PP2BA, were decreased without changes in other calcineurin subunits. CANB1 plays a critical role in downregulated networks of calcium signaling and homeostasis through calmodulin and calmodulin-dependent kinase II to highly interconnected structural networks dominated by tubulins. This large-scale knowledge base lays the foundation for the identification of novel therapeutic targets for cognitive rescue in TBI.
Like many diseases, diabetic nephropathy is defined in a histopathological context and studied using reductionist approaches that attempt to ameliorate structural changes. Novel technologies in mass spectrometry-based proteomics have the ability to provide a deeper understanding of the disease beyond classical histopathology, redefine the characteristics of the disease state, and identify novel approaches to reduce renal failure. The goal is to translate these new definitions into improved patient outcomes through diagnostic, prognostic, and therapeutic tools. Here, we review progress made in studying the proteomics of diabetic nephropathy and provide an introduction to the informatics tools used in the analysis of systems biology data, while pointing out statistical issues for consideration. Novel bioinformatics methods may increase biomarker identification, and other tools, including selective reaction monitoring, may hasten clinical validation.
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