Mara Zilocchi

Amyotrophic lateral sclerosis (ALS) is characterized by progressive motor neuron degeneration associated with genomic instability and mitochondrial dysfunction, although the mechanistic relationship between these hallmarks remains unclear. To determine whether nuclear DNA damage alone induces mitochondrial dysfunction, we exploited the AID-DIvA system, selectively generating DNA double-strand breaks (DSBs) in nuclear DNA. DSB induction caused early impairment of mitochondrial bioenergetics, including reduced basal respiration, ATP-linked respiration, and maximal respiratory capacity, preceding more pronounced mitochondrial alterations, after prolonged damage. Resolution of DSBs restored mitochondrial function, demonstrating a direct and reversible link between nuclear genome instability and mitochondrial dysfunction. Mechanistically, persistent activation of the DNA damage response (DDR) triggered PARP1-dependent NAD□ depletion, while PARP1 inhibition rescued mitochondrial respiration and ATP synthesis. We next investigated the consequences of DDR activation triggered by the expression of 102 (G4C2) repeats in an inducible cell model of C9ORF72-linked ALS. In these cells, DDR activation preceded mitochondrial dysfunction, recapitulating the sequence observed in AID-DIvA cells. Mitochondrial defects included impaired oxidative phosphorylation and reduced ATP production without increased mitochondrial ROS, suggesting that DNA damage signalling acts upstream of mitochondrial dysfunction. In support of this hypothesis, inhibition of ATM as well as nicotinamide riboside-mediated replenishment of cellular NAD ⁺ significantly restored mitochondrial functions. Collectively, our findings identify nuclear DNA damage as a trigger of mitochondrial dysfunction and uncover a pathogenic DDR–mitochondria crosstalk mediated by persistent DNA damage signalling. These results support a bidirectional relationship between genome instability and mitochondrial dysfunction and highlight mitochondrial and DNA damage response modulators as potential therapeutic targets for ALS and related neurodegenerative disorders.

Understanding SARS-CoV-2 human protein-protein interactions (PPIs) and the host response to infection is essential for developing effective COVID-19 antivirals. However, how the ancestral virus and its variants remodel virus-host protein assemblies in various organ-specific cells and bodily fluids remains unclear. Here, we conduct 639 affinity-purifications by tagging and expressing 28 SARS-CoV-2 and spike proteins from the ancestral virus and four variants in eight cell lines representing five mammalian organs and the immune system. Using mass spectrometry (MS), we identify both known and previously unreported SARS-CoV-2-human PPIs, highlighting similarities and differences across organ- or immune-derived cell lines and virus strains. Besides verifying the cell- and variant-specific PPIs, co-fractionation-MS analysis of COVID-19 patients’ saliva confirm host PPI changes between SARS-CoV-2 strains. We discover that the NSP3 papain-like protease, a secreted protein, binds fibrinogen to induce abnormal blood clotting and interferon-induced proteins to evade host innate immune responses. Leveraging deep learning, we design peptide inhibitors that successfully blocked SARS-CoV-2 and variant replication in human liver cells, reversing virus-induced PPI alterations. Together, these findings provide molecular insights into SARS-CoV-2 biology, uncover reorganized viral-host protein assemblies during infection, and identify potential host therapeutic targets and inhibitors for developing antivirals against SARS-CoV-2 strains.

Human mitochondrial (mt) protein assemblies are vital for neuronal and brain function, and their alteration contributes to many human disorders, e.g., neurodegenerative diseases resulting from abnormal protein–protein interactions (PPIs). Knowledge of the composition of mt protein complexes is, however, still limited. Affinity purification mass spectrometry (MS) and proximity-dependent biotinylation MS have defined protein partners of some mt proteins, but are too technically challenging and laborious to be practical for analyzing large numbers of samples at the proteome level, e.g., for the study of neuronal or brain-specific mt assemblies, as well as altered mtPPIs on a proteome-wide scale for a disease of interest in brain regions, disease tissues or neurons derived from patients. To address this challenge, we adapted a co-fractionation–MS platform to survey native mt assemblies in adult mouse brain and in human NTERA-2 embryonal carcinoma stem cells or differentiated neuronal-like cells. The workflow consists of orthogonal separations of mt extracts isolated from chemically cross-linked samples to stabilize PPIs, data-dependent acquisition MS to identify co-eluted mt protein profiles from collected fractions and a computational scoring pipeline to predict mtPPIs, followed by network partitioning to define complexes linked to mt functions as well as those essential for neuronal and brain physiological homeostasis. We developed an R/CRAN software package, Macromolecular Assemblies from Co-elution Profiles for automated scoring of co-fractionation–MS data to define complexes from mtPPI networks. Presently, the co-fractionation–MS procedure takes 1.5–3.5 d of proteomic sample preparation, 31 d of MS data acquisition and 8.5 d of data analyses to produce meaningful biological insights.

Summary: Mitochondria have been the focus of extensive research for decades since their dysfunction is linked to more than 150 distinct human disorders. Despite considerable efforts, researchers have only been able to skim the surface of the mitochondrial social complexity and the impact of inter-organelle and inter-organ communication alterations on human health. While some progress has been made in deciphering connections among mitochondria and other cytoplasmic organelles through direct (i.e., contact sites) or indirect (i.e., inter-organelle trafficking) crosstalk, most of these efforts have been restricted to a limited number of proteins involved in specific physiological pathways or disease states. This research bottleneck is further narrowed by our incomplete understanding of the cellular alteration timeline in a specific pathology, which prevents the distinction between a primary organelle dysfunction and the defects occurring due to the disruption of the organelle’s interconnectivity. In this perspective, we will (i) summarize the current knowledge on the mitochondrial crosstalk within cell(s) or tissue(s) in health and disease, with a particular focus on neurodegenerative disorders, (ii) discuss how different large-scale and targeted approaches could be used to characterize the different levels of mitochondrial social complexity, and (iii) consider how investigating the different expression patterns of mitochondrial proteins in different cell types/tissues could represent an important step forward in depicting the distinctive architecture of inter-organelle communication.

Bacterial transcription factors (TFs) are widely studied inEscherichia coli. Yet it remains unclear how individual genes in the underlying pathways of TF machinery operate together during environmental challenge. Here, we address this by applying an unbiased, quantitative synthetic genetic interaction (GI) approach to measure pairwise GIs among all TF genes inE. coliunder auxotrophic (rich medium) and prototrophic (minimal medium) static growth conditions. The resulting static and differential GI networks reveal condition-dependent GIs, widespread changes among TF genes in metabolism, and new roles for uncharacterized TFs (yjdC,yneJ,ydiP) as regulators of cell division, putrescine utilization pathway, and cold shock adaptation. Pan-bacterial conservation suggests TF genes with GIs are co-conserved in evolution. Together, our results illuminate the global organization ofE. coliTFs, and remodeling of genetic backup systems for TFs under environmental change, which is essential for controlling the bacterial transcriptional regulatory circuits.

Neuropsychiatric disorders (NPDs) such as bipolar disorder (BD), schizophrenia (SZ) and mood disorder (MD) are hard to manage due to overlapping symptoms and lack of biomarkers. Risk alleles of BD/SZ/MD are emerging, with evidence suggesting mitochondrial (mt) dysfunction as a critical factor for disease onset and progression. Mood stabilizing treatments for these disorders are scarce, revealing the need for biomarker discovery and artificial intelligence approaches to design synthetically accessible novel therapeutics. Here, we show mt involvement in NPDs by associating 245 mt proteins to BD/SZ/MD, with 7 common players in these disease categories. Analysis of over 650 publications suggests that 245 NPD-linked mt proteins are associated with 800 other mt proteins, with mt impairment likely to rewire these interactions. High dosage of mood stabilizers is known to alleviate manic episodes, but which compounds target mt pathways is another gap in the field that we address through mood stabilizer-gene interaction analysis of 37 prescriptions and over-the-counter psychotropic treatments, which we have refined to 15 mood-stabilizing agents. We show 26 of the 245 NPD-linked mt proteins are uniquely or commonly targeted by one or more of these mood stabilizers. Further, induced pluripotent stem cell-derived patient neurons and three-dimensional human brain organoids as reliable BD/SZ/MD models are outlined, along with multiomics methods and machine learning-based decision making tools for biomarker discovery, which remains a bottleneck for precision psychiatry medicine.