Biology subjects

Petrosyan, A.

Publications and source records attributed to Petrosyan, A..

3 recordsLinked to original sources

bioRxiv2026

Nuclear acetyl-CoA accumulation drives reversible RBP hyperacetylation and transcriptome-wide splicing shifts in age-equivalent Alzheimer's disease neurons

Metabolic alterations and dysregulated alternative RNA splicing are central layers of Alzheimer's disease (AD) pathogenesis, yet whether and to what extent these changes are mechanistically linked in adult human neurons in the aging brain remains unclear. To assess this, we generated induced neurons (iNs) by direct conversion of fibroblasts from sporadic AD patients and age-matched control donors. Fibroblast-derived iNs retaining donor-specific aging signatures have been shown to display several AD-related phenotypes. Metabolomic analysis revealed that AD iNs divert citrate toward ATP-citrate lyase (ACLY)-dependent citrate-to-acetyl-CoA flux, which drives increased nuclear levels of the high-energy metabolite acetyl-CoA. Acetyl-proteomics showed that acetyl-CoA accumulation leads to widespread hyper-acetylation of RNA-binding proteins (RBPs) and splice regulators, suggestive of a direct mechanistic link between a metabolic shift and RNA processing. Indeed, single-cell long-read RNA sequencing identifies splicing alterations in AD-relevant transcripts whose isoform usage mirrors changes observed in post-mortem AD cortex samples. Subcellular acetyl-CoA imaging reveals that inhibition of ACLY enzymatic activity selectively reduces nuclear acetyl-CoA levels, and further improves citrate metabolic flux, normalizes RBP acetylation, and re-establishes a normal neuronal splicing landscape in AD iNs. Together, these findings reveal a nuclear acetyl-CoA-RNA processing axis that links age- and disease-related metabolic alterations to alternative splicing dysregulation in AD, and identify neuronal nuclear acetyl-CoA production as a causal and reversible node for restoring metabolic and RNA homeostasis in aging human AD neurons.

neuroscience↗

bioRxiv2022

Speech decoding from a small set of spatially segregated minimally invasive intracranial EEG electrodes with a compact and interpretable neural network

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSSpeech decoding, one of the most intriguing BCI applications, opens up plentiful opportunities from rehabilitation of patients to direct and seamless communication between human species. Typical solutions rely on invasive recordings with a large number of distributed electrodes implanted through craniotomy. Here we explored the possibility of creating speech prosthesis in a minimally invasive setting with a small number of spatially segregated intracranial electrodes. MethodsWe collected one hour of data (from two sessions) in two patients implanted with invasive electrodes. We then used only the contacts that pertained to a single sEEG shaft or an ECoG stripe to decode neural activity into 26 words and one silence class. We employed a compact convolutional network-based architecture whose spatial and temporal filter weights allow for a physiologically plausible interpretation. ResultsWe achieved on average 55% accuracy using only 6 channels of data recorded with a single minimally invasive sEEG electrode in the first patient and 70% accuracy using only 8 channels of data recorded for a single ECoG strip in the second patient in classifying 26+1 overtly pronounced words. Our compact architecture did not require the use of pre-engineered features, learned fast and resulted in a stable, interpretable and physiologically meaningful decision rule successfully operating over a contiguous dataset collected during a different time interval than that used for training. Spatial characteristics of the pivotal neuronal populations corroborate with active and passive speech mapping results and exhibit the inverse space-frequency relationship characteristic of neural activity. Compared to other architectures our compact solution performed on par or better than those recently featured in neural speech decoding literature. ConclusionsWe showcase the possibility of building a speech prosthesis with a small number of electrodes and based on a compact feature engineering free decoder derived from a small amount of training data.

neuroscience↗

bioRxiv2018

Golgi Renaissance: the pivotal role of the largest Golgi protein giantin

Golgi undergoes disorganization in response to the drugs or alcohol, but it is able to restore compact structure under recovery. This self-organization mechanism remains mostly elusive, as does the role of giantin, the largest Golgi matrix dimeric protein. Here, we found that in cells treated with Brefeldin A (BFA) or ethanol (EtOH), Golgi disassembly is associated with giantin de-dimerization, which was restored to the dimer form after BFA or EtOH washout. Cells lacking giantin are disabled for the restoration of the classical ribbon Golgi, and they demonstrate altered trafficking of proteins to the cell surface. The fusion of the nascent Golgi membranes is mediated by the cross-membrane interaction of Rab6a GTPase and giantin. Giantin is involved in the formation of long intercisternal connections, which in giantin-depleted cells was replaced by the short bridges that formed via oligomerization of GRASP65. This phenomenon occurs in advanced prostate cancer cells, in which a fragmented Golgi phenotype is maintained by the dimerization of GRASP65. Thus, we provide a model of Golgi Renaissance, which is impaired in aggressive prostate cancer.

cell biology↗