Biology subjects

Carraro, M.

Publications and source records attributed to Carraro, M..

5 recordsLinked to original sources

bioRxiv2024

Sociality shapes mitochondrial adaptations supporting hypoxia tolerance

Oxygen deprivation or hypoxia is poorly dealt with by most terrestrial species and often leads to permanent tissue damage and death. One prominent exception is the naked mole-rat (Heterocephalus glaber) which is remarkably adapted to withstand prolonged periods ([~]18 mins) of severe hypoxia, a trait likely driven by its crowded underground lifestyle. Other African mole-rat species are less social or entirely solitary like the Cape mole-rat (Georychus capensis). Here, we asked whether cellular and molecular adaptations to hypoxia map to social traits. We discovered that at the cellular level naked mole-rat fibroblasts survive >30 hours in 1% oxygen, while fibroblasts from terrestrial or non-social mole-rat species (human, mouse and Cape mole-rat) die rapidly under hypoxic conditions. We further show that naked mole-rat mitochondria have evolved morphological, functional and proteomic adaptations crucial for hypoxia resistance, remaining unaffected after long periods of severe hypoxia. We identify the mitochondrial protein Optic Atrophy 1 (OPA1) as a key player in naked mole-rat hypoxia resilience. Naked mole-rat mitochondria not only express more protective forms of OPA1, but also harbor a structurally unique isoform that likely protects cells from hypoxic damage. We show that evolutionary changes including the functionalization of a unique Opa1 exon support mitochondrial mediated cellular protection. Indeed, knockdown of OPA1 in naked mole-rat cells is sufficient to render them equally susceptible to hypoxia as human cells or cells from non-social African species. Our study demonstrates how molecular evolution drives unique adaptations that enable cells to achieve unprecedented resistance to hypoxic damage. We also show that molecular changes at the level of mitochondria are crucial in conferring hypoxia resistance. Our results thus chart a novel molecular path to understand how robust cellular hypoxia resistance can be achieved. Such knowledge may eventually inspire novel strategies to circumvent the consequences of hypoxic-damage in humans.

physiology↗

bioRxiv2022

DAXX adds a de novo H3.3K9me3 deposition pathway to the histone chaperone network

A multitude of histone chaperones are required to protect histones after their biosynthesis until DNA deposition. They cooperate through the formation of co-chaperone complexes, but the crosstalk between nucleosome assembly pathways remains enigmatic. Using explorative interactomics approaches, we characterize the organization of the histone H3-H4 chaperones network and define the interplay between histone chaperone systems. We identify and validate several novel histone dependent complexes and predict the structure of the ASF1 and SPT2 co-chaperone complex, expanding the role of ASF1 in histone dynamics. We show that DAXX acts separately from the rest of the network, recruiting heterochromatin factors and promoting lysine 9 tri-methylation of new histone H3.3 prior to deposition onto DNA. With its functionality, DAXX provides a molecular mechanism for de novo heterochromatin assembly. Collectively, our findings provide a new framework for understanding how cells orchestrate histone supply and comply with chromatin dynamics throughout the cell cycle.

molecular biology↗

bioRxiv2021

NASP maintains histone H3-H4 homeostasis through two distinct H3 binding modes

Histone chaperones regulate all aspects of histone metabolism. NASP is a major histone chaperone for H3-H4 dimers critical for preventing histone degradation. Here, we identify two distinct histone binding modes of NASP and reveal how they cooperate to ensure histone H3-H4 supply. We determine the structures of a sNASP dimer, a complex of sNASP with an H3 3 peptide, and the sNASP-H3-H4-ASF1b co-chaperone complex. This captures distinct functionalities of NASP and identifies two distinct binding modes involving the H3 3 helix and the H3 N region, respectively. Functional studies demonstrate the H3 N-interaction represents the major binding mode of NASP in cells and shielding of the H3 N region by NASP is essential in maintaining the H3-H4 histone soluble pool. In conclusion, our studies uncover the molecular basis of NASP as a major H3-H4 chaperone in guarding histone homeostasis.

biochemistry↗

bioRxiv2019

Characterization of Intellectual disability and Autism comorbidity through gene panel sequencing

Intellectual disability (ID) and autism spectrum disorder (ASD) are clinically and genetically heterogeneous diseases. Recent whole exome sequencing studies indicated that genes associated with different neurological diseases are shared across disorders and converge on common functional pathways. Using the Ion Torrent platform, we developed a low-cost next generation sequencing (NGS) gene panel that has been transferred into clinical practice, replacing single disease gene analyses for the early diagnosis of individuals with ID/ASD. The gene panel was designed using an innovative in silico approach based on disease networks and mining data from public resources to score disease-gene associations. We analyzed 150 unrelated individuals with ID and/or ASD and a confident diagnosis has been reached in 26 cases (17%). Likely pathogenic mutations have been identified in another 15 patients, reaching a total diagnostic yield of 27%. Our data also support the pathogenic role of genes recently proposed to be involved in ASD. Although many of the identified variants need further investigation to be considered disease-causing, our results indicate the efficiency of the targeted gene panel on the identification of novel and rare variants in patients with ID and ASD.

genetics↗

bioRxiv2018

In silico prediction of blood cholesterol levels from genotype data

In this work we present a framework for blood cholesterol levels prediction from genotype data. The predictor is based on an algorithm for cholesterol metabolism simulation available in literature, implemented and optimized by our group in R language. Main weakness of the former simulation algorithm was the need of experimental data to simulate mutations in genes altering the cholesterol metabolism. This caveat strongly limited the application of the model in the clinical practice. In this work we present how this limitation could be bypassed thanks to an optimization of model parameters based on patients cholesterol levels retrieved from literature. Prediction performance has been assessed taking in consideration several scoring indices currently used for performance evaluation of machine learning methods. Our assessment shows how the optimization phase improved model performance, compared to the original version available in literature.

systems biology↗