bioRxiv Science⌕ Search

Biology subjects

Bruno, E.

Publications and source records attributed to Bruno, E..

3 recordsLinked to original sources

Z-AAT impairs organelle homeostasis and reduces adaptive response to lipids in alpha-1 antitrypsin deficiency models

Alpha-1 antitrypsin deficiency (AATD) caused by the Z variant leads to hepatic accumulation of misfolded AAT polymers and liver disease. Although proteotoxic stress is well established, its impact on lipid metabolism, mitochondrial function, and organelle homeostasis remains incompletely understood. The effects of Z-AAT accumulation were investigated in Z-HepG2 cells and 3D patient-derived ZZ hepatic organoids through protein aggregation, lipid storage, mitochondrial structure and function, peroxisomal dynamics, and comprehensive transcriptomic and proteomic analyses. Z-AAT expression led to intracellular polymer accumulation and reduced secretion, together with lipid accumulation, mitochondrial structural abnormalities, increased mitochondrial number but impaired respiratory capacity. Metabolic profiling revealed reduced oxidative phosphorylation and partial reliance on glucose metabolism. Peroxisomes displayed increased mass, consistent with altered lipid handling. Multi-omics analysis demonstrated widespread transcriptional and proteomic reprogramming related to protein synthesis, lipid metabolism, and mitochondrial function. Proteomic analysis confirmed proteotoxic stress-induced mitochondrial dysfunction, impaired lipid handling, and activation of stress response, inflammatory and vesicular trafficking pathways. Importantly, lipid supplementation elicited adaptive mitochondrial transcriptional responses in control cells, whereas Z-HepG2 cells showed a blunted response to lipid challenge. In conclusion, Z-AAT accumulation disrupts hepatic lipid processing and impaired mitochondrial and peroxisomal homeostasis, producing diminished metabolic flexibility likely contributing to AATD-associated liver disease.

molecular biology↗

ID-Seg: An Accurate and Reliable Infant Deep learning Segmentation Framework for Limbic Structures

Early postnatal period brain magnetic resonance imaging (MRI) is becoming an important approach to measure the impact of prenatal exposures on neurodevelopment and to investigate early biomarkers for risk. Among brain structures, Limbic structures are particular of interest in psychiatric disorder-related research. However, despite the promise of infant neuroimaging and the success of initial infant MRI studies, assessing limbic regions structure and function remains a significant challenge due to low inter-regional intensity contrast and high curvature (e.g., hippocampus). In addition, the agreement between existing automatic techniques and manual segmentation remains either untested or insufficient, particularly for the amygdala and hippocampus. In this work, we developed an accurate (based on three segmentation evaluation metrics), reliable and efficient infant deep learning segmentation framework (ID-Seg) to address the aforementioned challenges. Specifically, we leveraged a large dataset of 473 infant MRI scans to train ID-Seg and rigorously evaluated ID-Segs performance on internal and external datasets with manual segmentations. Compared with a state-of-the-art segmentation pipeline, we demonstrated that ID-Seg significantly improved the segmentation accuracy of limbic structures (hippocampus and amygdala) in newborn infants. Moreover, in a medium-size dataset, we found that ID-Seg-derived morphometric measures yield strong brain-behavior associations. As such, our ID-Seg may improve our capacity and efficiency to measure MRI-based brain features relevant to neuropsychological development and ultimately advance the success of quantitative analyses on large-scale datasets.

bioengineering↗

Structural insights into substrate recognition by the SOCS2 E3 ubiquitin ligase

The suppressor of cytokine signaling 2 (SOCS2) acts as substrate recognition subunit of a Cullin5 E3 ubiquitin ligase complex. SOCS2 binds to phosphotyrosine-modified epitopes as degrons for ubiquitination and proteasomal degradation, yet the molecular basis of substrate recognition has remained elusive. We solved cocrystal structures of SOCS2-ElonginB-ElonginC in complex with phosphorylated peptides from substrates growth hormone receptor (GHR-pY595) and erythropoietin receptor (EpoR-pY426) at 1.98 A{square} and 2.69 A{square}, respectively. Both peptides bind in an extended conformation recapitulating the canonical SH2 domain-pY pose, yet capture different conformations of the EF loop via specific hydrophobic interactions. The flexible BG loop, for the first time fully defined in the electron density, does not contact the substrate degrons directly. Cancer-associated SNPs located around the pY pocket weaken substrate-binding affinity in biophysical assays. Our findings reveal insights into substrate recognition and specificity by SOCS2, and provide a blueprint for small molecule ligand design.

biochemistry↗