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Biology subjects

Panov, A.

Publications and source records attributed to Panov, A..

5 recordsLinked to original sources

Temporal control of acute protein aggregate turnover by UBE3C and NRF1-dependent proteasomal pathways

A hallmark of neurodegenerative diseases is the progressive loss of proteostasis, leading to the accumulation of misfolded proteins or protein aggregates, with subsequent cytotoxicity. To combat this toxicity, cells have evolved degradation pathways (ubiquitin-proteasome system and autophagy) that detect and degrade misfolded proteins. However, studying the underlying cellular pathways and mechanisms has remained a challenge, as formation of many types of protein aggregates is asynchronous, with individual cells displaying distinct kinetics, thereby hindering rigorous time-course studies. Here, we merge a kinetically tractable and synchronous agDD-GFP system for aggregate formation with targeted gene knockdowns, to uncover degradation mechanisms used in response to acute aggregate formation. We find that agDD-GFP forms amorphous aggregates by cryo-electron tomography at both early and late stages of aggregate formation. Aggregate turnover occurs in a proteasome-dependent mechanism in a manner that is dictated by cellular aggregate burden, with no evidence of the involvement of autophagy. Lower levels of misfolded agDD-GFP, enriched in oligomers, utilizes UBE3C-dependent proteasomal degradation in a pathway that is independent of RPN13 ubiquitylation by UBE3C. Higher aggregate burden activates the NRF1 transcription factor to increase proteasome subunit transcription, and subsequent degradation capacity of cells. Loss or gain of NRF1 function alters the turnover of agDD-GFP under conditions of high aggregate burden. Together, these results define the role of UBE3C in degradation of this class of misfolded aggregation-prone proteins and reveals a role for NRF1 in proteostasis control in response to widespread protein aggregation.

cell biology↗

Metabolic properties of murine kidney mitochondria

We show that mitochondria from the kidney of mice (MKM), rat brain (RBM), and heart (RHM) oxidize long-chain fatty acids at high rates in all metabolic states only in the presence of any other mitochondrial metabolites: succinate, glutamate, or pyruvate. All supporting substrates increased several folds the respiration rates in State 4 and State 3. The stimulations of the State 3 respiration with palmitoyl-carnitine + malate oxidation (100%) were: with succinate in MKM 340%, RBM 370%, and RHM 340%; with glutamate - MKM 200%, RBM 270%, and RHM 270%; and with pyruvate - MKM 150%, RBM 260%, and RHM 280%. The increases in O2 consumption in State 4 were due to increased leakage of electrons to produce superoxide radicals (O2*). Earlier, we have shown that the brain and heart mitochondria possess a strong intrinsic inhibition of succinate oxidation to prevent the excessive O2* production at diminished functional loads. We show that kidney mitochondria lack the intrinsic inhibition of SDH. The new methodology to study {beta}-oxidation of LCFAs opens the opportunity to study energy metabolism under normal and pathological conditions, particularly in the organs that utilize LCFAs as the main energy source.

biochemistry↗

Playing a P300-BCI VR game based leads to changes in cognitive function of healthy adults

In this paper, we present the results of a study to determine the effect of the P300-based brain-computer interface (BCI) virtual reality game on the cognitive functions of healthy human subjects. This study is a part of on-going research related to evaluation of the the long-term effect of P300 training in Virtual Reality surrounding (VR game) on the cognitive performance of the young healthy population. A comparison of results between 3 groups of participants (15 people each) revealed the progressing difference in cognitive assessment for experimental group played P300 BCI VR game, showing the positive increase in flanker and conjunction visual search task performance associated with selective attention and mental inhibition. We show that the effect is due to the use of P300 BCI paradigm. Our results suggest that P300 BCI games combined with virtual reality can not only be used for rehabilitation in patients with slight mental disorders or elderly, but for increasing some cognitive functions in healthy subjects, giving an additional improvement in learning in case of combination with possible educational tasks or used for attention training GRAPHICAL ABSTRACTPlease check the journals author guildines for whether a graphical abstract, key points, new findings, or other items are required for display in the Table of Contents.

neuroscience↗

Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome

Thousands of interactions assemble proteins into modules that impart spatial and functional organization to the cellular proteome. Through affinity-purification mass spectrometry, we have created two proteome-scale, cell-line-specific interaction networks. The first, BioPlex 3.0, results from affinity purification of 10,128 human proteins - half the proteome - in 293T cells and includes 118,162 interactions among 14,586 proteins; the second results from 5,522 immunoprecipitations in HCT116 cells. These networks model the interactome at unprecedented scale, encoding protein function, localization, and complex membership. Their comparison validates thousands of interactions and reveals extensive customization of each network. While shared interactions reside in core complexes and involve essential proteins, cell-specific interactions bridge conserved complexes, likely rewiring each cells interactome. Interactions are gained and lost in tandem among proteins of shared function as the proteome remodels to produce each cells phenotype. Viewable interactively online through BioPlexExplorer, these networks define principles of proteome organization and enable unknown protein characterization.

systems biology↗

Analysis of Independent Differences (AID) detects complex thermal proteome profiles independent of shape and identifies candidate panobinostat targets

Identifying global cellular targets of small molecules is a challenge for drug discovery. Thermal proteome profiling (TPP) is a recent technique that uses quantitative proteomics to identify all small molecule protein targets in a single experiment. One current TPP analysis method relies on two major assumptions: sigmoidal melting curve behavior and that intra-condition dependencies preclude an independent and identically distributed model. Herein, we use a previously published panobinostat TPP dataset to show that these assumptions do not hold true and present a novel, shape-independent method, named Analysis of Independent Differences (AID). For each temperature, AID models the differences between conditions of fractions of non-denatured protein as an independent Normal distribution, resulting in a Multivariate Normal observation for each protein. The log of a Multivariate Normal p-value ranks the proteins from most to least likely shifted, and individual Normal p-values within each protein allow for qualitative inspection. Applying AID to the panobinostat dataset revealed known targets in the top 3% of most shifted proteins, as well as candidate targets involved in myeloid leukocyte activation. AID detects complex melting profiles and can be extended to any number of temperature channels, ligand-protein or protein-protein interactions, or general curve data for deeper biological insight.

bioinformatics↗