Dynamic Interactomics by Cross-Linking Mass Spectrometry: Mapping the Daily Cell Life in Postgenomic Era

Neuroglobin regulates autophagy through mTORC1/RAPTOR/ULK-1 pathway in human neuroblastoma cells

Neuroglobin (NGB) is a hexacoordinated hemeprotein mainly expressed in neurons. Following its upregulation and mitochondrial localization, NGB plays a pro-survival role against neuronal stress. Previously, we built a stable NGB-FLAG-overexpressing neuroblastoma cell line and showed that NGB promotes autophagy and localizes in autophagolysosomes. Here we studied the interactome of NGB-FLAG cells to identify novel autophagy-related NGB-binding partners and investigate how its upregulation could induce autophagy. LC3-II and p62 levels as well as mTORC1 activity were analyzed to evaluate autophagy in NGB-FLAG cells. NGB interactors were identified by affinity purification-mass spectrometry and protein-protein interaction network analysis and validated by immunoprecipitation. The increase of LC3-II and decrease of p62 in NGB-FLAG compared to control confirmed that NGB overexpression promotes autophagy. Interactome analysis identified the Regulatory associated protein of mTOR (RPTOR) as one of 134 putative NGB interactors, further validated by immunoprecipitation. NGB overexpression also determined a consistent increment of RPTOR phosphorylation at Ser792 which is required for mTORC1 inhibition, then confirmed by lower levels of phospho-mTOR and phospho-ULK1 in NGB-FLAG compared to control. Collectively, our data suggests that NGB is a positive regulator of autophagy. Through association with RPTOR, NGB may promote its activation and inhibit mTORC1 repressive activity on autophagy initiation.

Cross-Linking Mass Spectrometry to Capture Protein Network Dynamics of Cell Membranome

Interactions among proteins are fundamental in driving functions and activities that regulate cell biology, mechanotransduction, and cell-to-cell communication/recognition. Recently, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for interaction discovery and characterization, driving the enlightenment of novel binding partners otherwise undetected. Covalent linkages of two amino acid residues of proteins (or within complexes) in close proximity can be identified by MS, thus providing structural insights such as distance restraints or unraveling interaction dynamics.The XL-MS workflow described here is applied to map the plasma membrane protein (PMP) networks since they play important roles in the modulation of diverse molecular processes, including transport, signal transduction, endocytosis, and secretion. The strategy includes cross-linking of PMP-enriched fractions, label-free nanoLC-MS/MS, and bioinformatics data analysis. "Membranome" interconnections constitute around 30% of the mammalian proteome and 60% of all drug targets. Exploring such networks under different biological conditions is a promising and unbiased approach to depicting regulatory pathways that govern cell behavior.

Unraveling the impact of different liposomal formulations on the plasma protein corona composition might give hints on the targeting capability of nanoparticles

Nanoparticles (NPs) interact with biological fluids after being injected into the bloodstream. The interactions between NPs and plasma proteins at the nano-bio interface affect their biopharmaceutical properties and distribution in the organ and tissues due to protein corona (PrC) composition, and in turn, modification of the resulting targeting capability. Moreover, lipid and polymer NPs, at their interface, affect the composition of PrC and the relative adsorption and abundance of specific proteins. To investigate this latter aspect, we synthesized and characterized different liposomal formulations (LFs) with lipids and polymer-conjugated lipids at different molar ratios, having different sizes, size distributions and surface charges. The PrC composition of various designed LFs was evaluated ex vivo in human plasma by label-free quantitative proteomics. We also correlated the relative abundance of identified specific proteins in the coronas of the different LFs with their physicochemical properties (size, PDI, zeta potential). The evaluation of outputs from different bioinformatic tools discovered protein clusters allowing to highlight: (i) common as well as the unique species for the various formulations; (ii) correlation between each identified PrC and the physicochemical properties of LFs; (iii) some preferential binding determined by physicochemical properties of LFs; (iv) occurrence of formulation-specific protein patterns in PrC. Investigating specific clusters in PrC will help decode the multivalent roles of the protein pattern components in the drug delivery process, taking advantage of the bio-nanoscale recognition and identification for significant advances in nanomedicine.

Methylmalonic acidemia triggers lysosomal-autophagy dysfunctions

BACKGROUND

Methylmalonic acidemia (MMA) is a rare inborn error of propionate metabolism caused by deficiency of the mitochondrial methylmalonyl-CoA mutase (MUT) enzyme. As matter of fact, MMA patients manifest impairment of the primary metabolic network with profound damages that involve several cell components, many of which have not been discovered yet. We employed cellular models and patients-derived fibroblasts to refine and uncover new pathologic mechanisms connected with MUT deficiency through the combination of multi-proteomics and bioinformatics approaches.

RESULTS

Our data show that MUT deficiency is connected with profound proteome dysregulations, revealing molecular actors involved in lysosome and autophagy functioning. To elucidate the effects of defective MUT on lysosomal and autophagy regulation, we analyzed the morphology and functionality of MMA-lysosomes that showed deep alterations, thus corroborating omics data. Lysosomes of MMA cells present as enlarged vacuoles with low degradative capabilities. Notwithstanding, treatment with an anti-propionigenic drug is capable of totally rescuing lysosomal morphology and functional activity in MUT-deficient cells. These results indicate a strict connection between MUT deficiency and lysosomal-autophagy dysfunction, providing promising therapeutic perspectives for MMA.

CONCLUSIONS

Defective homeostatic mechanisms in the regulation of autophagy and lysosome functions have been demonstrated in MUT-deficient cells. Our data prove that MMA triggers such dysfunctions impacting on autophagosome-lysosome fusion and lysosomal activity.

Metabolic rewiring and autophagy inhibition correct lysosomal storage disease in mucopolysaccharidosis IIIB

Mucopolysaccharidoses (MPSs) are lysosomal disorders with neurological involvement for which no cure exists. Here, we show that recombinant NK1 fragment of hepatocyte growth factor rescues substrate accumulation and lysosomal defects in MPS I, IIIA and IIIB patient fibroblasts. We investigated PI3K/Akt pathway, which is of crucial importance for neuronal function and survival, and demonstrate that PI3K inhibition abolishes NK1 therapeutic effects. We identified that autophagy inhibition, by Beclin1 silencing, reduces MPS IIIB phenotype and that NK1 downregulates autophagic-lysosome (ALP) gene expression, suggesting a possible contribution of autophagosome biogenesis in MPS. Indeed, metabolomic analyses revealed defects of mitochondrial activity accompanied by anaerobic metabolism and inhibition of AMP-activated protein kinase (AMPK), which acts on metabolism and autophagy, rescues lysosomal defects. These results provide insights into the molecular mechanisms of MPS IIIB physiopathology, supporting the development of new promising approaches based on autophagy inhibition and metabolic rewiring to correct lysosomal pathology in MPSs.

Progress, Challenges and Opportunities of NMR and XL-MS for Cellular Structural Biology

The validity of protein structures and interactions, whether determined under ideal laboratory conditions or predicted by AI tools such as Alphafold2, to precisely reflect those found in living cells remains to be examined. Moreover, understanding the changes in protein structures and interactions in response to stimuli within living cells, under both normal and disease conditions, is key to grasping proteins' functionality and cellular processes. Nevertheless, achieving high-resolution identification of these protein structures and interactions within living cells presents a technical challenge. In this Perspective, we summarize the recent advancements in in-cell nuclear magnetic resonance (NMR) and in vivo cross-linking mass spectrometry (XL-MS) for studying protein structures and interactions within a cellular context. Additionally, we discuss the challenges, opportunities, and potential benefits of integrating in-cell NMR and in vivo XL-MS in future research to offer an exhaustive approach to studying proteins in their natural habitat.

Developmental Impacts of Epigenetics and Metabolism in COVID-19

Developmental biology is intricately regulated by epigenetics and metabolism but the mechanisms are not completely understood. The situation becomes even more complicated during diseases where all three phenomena are dysregulated. A salient example is COVID-19, where the death toll exceeded 6.96 million in 4 years, while the virus continues to mutate into different variants and infect people. Early evidence during the pandemic showed that the host's immune and inflammatory responses to COVID-19 (like the cytokine storm) impacted the host's metabolism, causing damage to the host's organs and overall physiology. The involvement of angiotensin-converting enzyme 2 (ACE2), the pivotal host receptor for the SARS-CoV-2 virus, was identified and linked to epigenetic abnormalities along with other contributing factors. Recently, studies have revealed stronger connections between epigenetics and metabolism in COVID-19 that impact development and accelerate aging. Patients manifest systemic toxicity, immune dysfunction and multi-organ failure. Single-cell multiomics and other state-of-the-art high-throughput studies are only just beginning to demonstrate the extent of dysregulation and damage. As epigenetics and metabolism directly impact development, there is a crucial need for research implementing cutting-edge technology, next-generation sequencing, bioinformatics analysis, the identification of biomarkers and clinical trials to help with prevention and therapeutic interventions against similar threats in the future.

Revolutionizing Biological Science: The Synergy of Genomics in Health, Bioinformatics, Agriculture, and Artificial Intelligence

With climate emergency, COVID-19, and the rise of planetary health scholarship, the binary of human and ecosystem health has been deeply challenged. The interdependence of human and nonhuman animal health is increasingly acknowledged and paving the way for new frontiers in integrative biology. The convergence of genomics in health, bioinformatics, agriculture, and artificial intelligence (AI) has ushered in a new era of possibilities and applications. However, the sheer volume of genomic/multiomics big data generated also presents formidable sociotechnical challenges in extracting meaningful biological, planetary health and ecological insights. Over the past few years, AI-guided bioinformatics has emerged as a powerful tool for managing, analyzing, and interpreting complex biological datasets. The advances in AI, particularly in machine learning and deep learning, have been transforming the fields of genomics, planetary health, and agriculture. This article aims to unpack and explore the formidable range of possibilities and challenges that result from such transdisciplinary integration, and emphasizes its radically transformative potential for human and ecosystem health. The integration of these disciplines is also driving significant advancements in precision medicine and personalized health care. This presents an unprecedented opportunity to deepen our understanding of complex biological systems and advance the well-being of all life in planetary ecosystems. Notwithstanding in mind its sociotechnical, ethical, and critical policy challenges, the integration of genomics, multiomics, planetary health, and agriculture with AI-guided bioinformatics opens up vast opportunities for transnational collaborative efforts, data sharing, analysis, valorization, and interdisciplinary innovations in life sciences and integrative biology.

Proteomics and Metabolomics in Biomedicine

The technological advances of recent years have significantly enhanced medical discoveries [...].

Deciphering the Relationship between SARS-CoV-2 and Cancer

Some viruses are known to be associated with the onset of specific cancers. These microorganisms, oncogenic viruses or oncoviruses, can convert normal cells into cancer cells by modulating the central metabolic pathways or hampering genomic integrity mechanisms, consequently inhibiting the apoptotic machinery and/or enhancing cell proliferation. Seven oncogenic viruses are known to promote tumorigenesis in humans: human papillomavirus (HPV), hepatitis B and C viruses (HBV, HCV), Epstein-Barr virus (EBV), human T-cell leukemia virus 1 (HTLV-1), Kaposi sarcoma-associated herpesvirus (KSHV), and Merkel cell polyomavirus (MCPyV). Recent research indicates that SARS-CoV-2 infection and COVID-19 progression may predispose recovered patients to cancer onset and accelerate cancer development. This hypothesis is based on the growing evidence regarding the ability of SARS-CoV-2 to modulate oncogenic pathways, promoting chronic low-grade inflammation and causing tissue damage. Herein, we summarize the main relationships known to date between virus infection and cancer, providing a summary of the proposed biochemical mechanisms behind the cellular transformation. Mechanistically, DNA viruses (such as HPV, HBV, EBV, and MCPyV) encode their virus oncogenes. In contrast, RNA viruses (like HCV, HTLV-1) may encode oncogenes or trigger host oncogenes through cis-/-trans activation leading to different types of cancer. As for SARS-CoV-2, its role as an oncogenic virus seems to occur through the inhibition of oncosuppressors or controlling the metabolic and autophagy pathways in the infected cells. However, these effects could be significant in particular scenarios like those linked to severe COVID-19 or long COVID. On the other hand, looking at the SARS-CoV-2─cancer relationship from an opposite perspective, oncolytic effects and anti-tumor immune response were triggered by SARS-CoV-2 infection in some cases. In summary, our work aims to recall comprehensive attention from the scientific community to elucidate the effects of SARS-CoV-2 and, more in general, β-coronavirus infection on cancer susceptibility for cancer prevention or supporting therapeutic approaches.

Sex-Gender-Based Differences in Metabolic Diseases

Sexual dimorphism creates different biological and cellular activities and selective regulation mechanisms in males and females, thus generating differential responses in health and disease. In this scenario, the sex itself is a source of physiologic metabolic disparities that depend on constitutive genetic and epigenetic features that characterize in a specific manner one sex or the other. This has as a direct consequence a huge impact on the metabolic routes that drive the phenotype of an individual. The impact of sex is being clearly recognized also in disease, whereas male and females are more prone to the development of some disorders, or have selective responses to drugs and therapeutic treatments. Actually, very less is known regarding the probable differences guided by sex in the context of inherited metabolic disorders, owing to the scarce consideration of sex in such restricted field, accompanied by an intrinsic bias connected with the rarity of such diseases. Metabolomics technologies have been ultimately developed and adopted for being excellent tools for the investigation of metabolic mechanisms, for marker discovery or monitoring, and for supporting diagnostic procedures of metabolic disorders. Hence, metabolomic approaches can excellently embrace the discovery of sex differences, especially when associated to the outcome or the management of certain inborn errors of the metabolism.