bioRxiv Science⌕ Search

Biology subjects

Shichkova, P.

Publications and source records attributed to Shichkova, P..

3 recordsLinked to original sources

A flexible end-to-end automated sample preparation workflow enables reproducible large-scale bottom-up proteomics

Bottom-up proteomics holds significant promise for clinical applications due to its high sensitivity and precision, but is limited by labor-intensive, low-throughput sample preparation methods. Advanced automation is essential to enhance throughput, reproducibility, and accuracy and to allow standardization to make bottom-up proteomics amenable for large-scale studies. We developed a fully integrated, automated sample preparation platform that covers the entire process from biological sample input to mass spectrometry-ready peptide output and can be applied on a multitude of biological samples. With this end-to-end solution, we achieved high intra- and inter-plate reproducibility, as well as longitudinal consistency, resulting in precise and reproducible workflows. We showed that our automated workflow surpasses established manual and semi-automated workflows, while improving time efficiency. Finally, we demonstrated the suitability of our automated sample preparation platform for drug development by performing a high-content compound characterization for targeted protein degradation, where high throughput and quantitative accuracy are indispensable. For this, we coupled application-specific workflows to perform proteome profiling and confirm target degradation by precise protein quantification. Overall, our results highlight the selective degradation of specific proteins of interest for ten selected compounds across two cell lines. Thus, the automated sample preparation platform facilitates rapid adaptation to emerging developments in proteomics sample preparation, combining standardization, flexibility, and high-throughput capabilities to drive significant advancements in clinical assays and proteomics research.

biochemistry↗

A multiscale electro-metabolic model of a rat neocortical circuit reveals the impact of ageing on central cortical layers

The high energetic demands of the brain arise primarily from neuronal activity. Neurons consume substantial energy to transmit information as electrical signals and maintain their resting membrane potential. These energetic requirements are met by the neuro-glial-vascular (NGV) ensemble, which generates energy in a coupled metabolic process. In ageing, metabolic function becomes impaired, producing less energy and, consequently, the system is unable to sustain the neuronal energetic needs. We propose a multiscale model of electro-metabolic coupling in a reconstructed rat neocortex. This combines an electro-morphologically reconstructed electrophysiological model with a detailed NGV metabolic model. Our results demonstrate that the large-scale model effectively captures electro-metabolic processes at the circuit level, highlighting the importance of heterogeneity within the circuit, where energetic demands vary according to neuronal characteristics. Finally, in metabolic ageing, our model indicates that the middle cortical layers are particularly vulnerable to energy impairment.

neuroscience↗

Breakdown and rejuvenation of aging brain energy metabolism

The study presented explores the complex relationship between the aging brain, energy metabolism, blood flow and neuronal activity by introducing a comprehensive, data-driven molecular model of the neuro-glial vascular system, including all key enzymes, transporters, metabolites, and blood flow vital for neuronal electrical activity with 16800 interaction pathways. We find significant alterations in metabolite concentrations and differential effects on ATP supply in neurons and astrocytes and within subcellular compartments within aged brains, and identify reduced Na+/K+-ATPase as the leading cause of impaired neuronal action potentials. The model predicts that the metabolic pathways cluster more closely in the aged brain, suggesting a loss of robustness and adaptability. Additionally, the aged metabolic system displays reduced flexibility, undermining its capacity to efficiently respond to stimuli and recover from damage. Through transcription factor analysis, the estrogen-related receptor alpha (ESRRA) emerged as a central target connected to these aging-related changes. An unguided optimization search pinpointed potential interventions capable of restoring the brains metabolic flexibility and restoring action potential generation. These strategies include increasing the NADH cytosol-mitochondria shuttle, NAD+ pool, ketone {beta}-hydroxybutyrate, lactate and Na+/K+-ATPase and reducing blood glucose levels. The model is open-sourced to help guide further research in brain metabolism.

neuroscience↗