Single-Cell Patch-Clamp/Proteomics of Human Alzheimer's Disease iPSC-Derived Excitatory Neurons Versus Isogenic Wild-Type Controls Suggests Novel Causation and Therapeutic Targets.

Standard single-cell (sc) proteomics of disease states inferred from multicellular organs or organoids cannot currently be related to single-cell physiology. Here, a scPatch-Clamp/Proteomics platform is developed on single neurons generated from hiPSCs bearing an Alzheimer's disease (AD) genetic mutation and compares them to isogenic wild-type controls. This approach provides both current and voltage electrophysiological data plus detailed proteomics information on single-cells. With this new method, the authors are able to observe hyperelectrical activity in the AD hiPSC-neurons, similar to that observed in the human AD brain, and correlate it to ≈1400 proteins detected at the single neuron level. Using linear regression and mediation analyses to explore the relationship between the abundance of individual proteins and the neuron's mutational and electrophysiological status, this approach yields new information on therapeutic targets in excitatory neurons not attainable by traditional methods. This combined patch-proteomics technique creates a new proteogenetic-therapeutic strategy to correlate genotypic alterations to physiology with protein expression in single-cells.

DNA damage response proteins synergistically affect the cancer prognosis and resistance.

Amplification of oxidative stress can be utilized as a strategy to attenuate cancer progression by instigating apoptosis. However, the duration of positive response to such therapies is limited, as cancer cells eventually develop resistance. The underlying molecular mechanisms of cancer cells to escape apoptosis under oxidative stress is unknown. Employing big data, and its integration with transcriptome, proteome and network analysis in six cancer types revealed system-level interactions between DNA damage response (DDR) proteins, including; DNA damage repair, cell cycle checkpoints and anti-apoptotic proteins. Cancer system biology is used to elucidate mechanisms for cancer progression, but networks defining mechanisms causing resistance is less explored. Using system biology, we identified DDR hubs between G1-S and M phases that were associated with bad prognosis. The increased expression of DDR network was involved in resistance under high oxidative stress. We validated our findings by combining H2O2 induced oxidative stress and DDR inhibitors in human lung cancer cells to conclude the necessity of targeting a 'disease-causing network'. Collectively, our work provides insights toward designing strategies for network pharmacology to combat resistance in cancer research.

Deciphering key regulators involved in epilepsy-induced cardiac damage through whole transcriptome and proteome analysis in a rat model.

OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) is a major outcome of cardiac dysfunction in patients with epilepsy. In continuation of our previous work, the present study was envisaged to explore the key regulators responsible for cardiac damage associated with chronic seizures using whole transcriptome and proteome analysis in a rat model of temporal lobe epilepsy. METHODS: A standard lithium-pilocarpine protocol was used to induce recurrent seizures in rats. The isolated rat heart tissue was subjected to transcriptomic and proteomic analysis. An integrated approach of RNA-Seq, proteomics, and system biology analysis was used to identify key regulators involved in seizure-linked cardiac changes. The analyzed differential expression patterns and network interactions were supported by gene and protein expression studies. RESULTS: Altogether, 1157 differentially expressed genes and 1264 proteins were identified in the cardiac tissue of epileptic animals through RNA-Seq and liquid chromatography with tandem mass spectrometry-based proteomic analysis, respectively. The network analysis revealed seven critical genes-STAT3, Myc, Fos, Erbb2, Erbb3, Notch1, and Mapk8-that could play a role in seizure-mediated cardiac changes. The LC-MS/MS analysis supported the activation of the transforming growth factor ß (TGF-ß) pathway in the heart of epileptic animals. Furthermore, our gene and protein expression studies established a key role of STAT3, Erbb, and Mapk8 to develop cardiac changes linked with recurrent seizures. SIGNIFICANCE: The present multi-omics study identified STAT3, Mapk8, and Erbb as key regulators involved in seizure-associated cardiac changes. It provided a deeper understanding of molecular, cellular, and network-level operations of the identified regulators that lead to cardiac changes in epilepsy.