CMT2A-linked mitochondrial hyperfusion-driving mutant MFN2 perturbs ER-mitochondrial associations and Ca2+ homeostasis.

BACKGROUND INFORMATION: Mitofusin2 (MFN2), an important molecular player that regulates mitochondrial fusion, also helps maintain the inter-organellar contact sites, referred as mitochondria associated membranes (MAMs) that exist between the ER and mitochondria. The study deals with a mutant of MFN2, R364W-MFN2, linked with the neuropathy, Charcot Marie Tooth (CMT) disease. Previous studies show that this mutant promotes mitochondrial hyperfusion. Here, we try to decipher the role of R364W-MFN2 in affecting the ER mitochondrial associations at the MAM junctions and inter-organellar calcium signalling between the ER and the mitochondria. RESULTS: Our results show that R364W-MFN2 altered ER-mitochondria association at the MAM junctions, predisposed mitochondria towards cellular stress with the mitochondria undergoing rapid fission upon induction of mild stress and perturbs inter-organellar calcium homeostasis. CONCLUSION: The results indicate that R364W-MFN2 not only affects mitochondrial morphology and dynamics but also modulate its interaction with the ER and Ca2+ signalling between the two organelles. SIGNIFICANCE: This study provides significant insight that presence of the R364W-MFN2 mutation makes cells susceptible towards stress, thus negatively affecting cellular health which altogether might culminate in the form of the CMT neuropathy.

MITOL-mediated DRP1 ubiquitylation and degradation promotes mitochondrial hyperfusion in a CMT2A-linked MFN2 mutant.

Mutations in mitofusin 2 (MFN2) that are associated with the pathology of the debilitating neuropathy Charcot-Marie-Tooth type 2A (CMT2A) are known to alter mitochondrial morphology. One such abundant MFN2 mutation, R364W, results in the generation of elongated, interconnected mitochondria. However, the mechanism leading to this mitochondrial aberration remains poorly understood. Here, we show that mitochondrial hyperfusion in the presence of R364W-MFN2 is due to increased degradation of DRP1 (also known as DNM1L). The E3 ubiquitin ligase MITOL (also known as MARCHF5) is known to ubiquitylate both MFN2 and DRP1. Interaction with and subsequent ubiquitylation by MITOL is stronger in the presence of wild-type MFN2 than with R364W-MFN2. This differential interaction of MITOL with MFN2 in the presence of R364W-MFN2 renders the ligase more available for DRP1 ubiquitylation. Multi-monoubiquitylation and proteasomal degradation of DRP1 in R364W-MFN2 cells in the presence of MITOL eventually leads to mitochondrial hyperfusion. Here, we provide a mechanistic insight into mitochondrial hyperfusion, while also reporting that MFN2 can indirectly modulate DRP1 - an effect not shown previously. This article has an associated First Person interview with the first author of the paper.

Corpus Callosum Atrophy in Detection of Mild and Moderate Alzheimer's Disease Using Brain Magnetic Resonance Image Processing and Machine Learning Techniques.

BACKGROUND: The total number of people with dementia is projected to reach 82 million in 2030 and 152 in 2050. Early and accurate identification of the underlying causes of dementia, such as Alzheimer's disease (AD) is of utmost importance. A large body of research has shown that imaging techniques are most promising technologies to improve subclinical and early diagnosis of dementia. Morphological changes, especially atrophy in various structures like cingulate gyri, caudate nucleus, hippocampus, frontotemporal lobe, etc., have been established as markers for AD. Being the largest white matter structure with a high demand of blood supply from several main arterial systems, anatomical alterations of the corpus callosum (CC) may serve as potential indication neurodegenerative disease. OBJECTIVE: To detect mild and moderate AD using brain magnetic resonance image (MRI) processing and machine learning techniques. METHODS: We have performed automatic detection and segmentation of the CC and calculated its morphological features to feed into a multivariate pattern analysis using support vector machine (SVM) learning techniques. RESULTS: Our results using large patients' cohort show CC atrophy-based features are capable of distinguishing healthy and mild/moderate AD patients. Our classifiers obtain more than 90%sensitivity and specificity in differentiating demented patients from healthy cohorts and importantly, achieved more than 90%sensitivity and > 80%specificity in detecting mild AD patients. CONCLUSION: Results from this analysis are encouraging and advocate development of an image analysis software package to detect dementia from brain MRI using morphological alterations of the CC.

Structural and Drug Screening Analysis of the Non-structural Proteins of Severe Acute Respiratory Syndrome Coronavirus 2 Virus Extracted From Indian Coronavirus Disease 2019 Patients.

The novel coronavirus 2 (nCoV2) outbreaks took place in December 2019 in Wuhan City, Hubei Province, China. It continued to spread worldwide in an unprecedented manner, bringing the whole world to a lockdown and causing severe loss of life and economic stability. The coronavirus disease 2019 (COVID-19) pandemic has also affected India, infecting more than 10 million till 31st December 2020 and resulting in more than a hundred thousand deaths. In the absence of an effective vaccine, it is imperative to understand the phenotypic outcome of the genetic variants and subsequently the mode of action of its proteins with respect to human proteins and other bio-molecules. Availability of a large number of genomic and mutational data extracted from the nCoV2 virus infecting Indian patients in a public repository provided an opportunity to understand and analyze the specific variations of the virus in India and their impact in broader perspectives. Non-structural proteins (NSPs) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) virus play a major role in its survival as well as virulence power. Here, we provide a detailed overview of the SARS-CoV2 NSPs including primary and secondary structural information, mutational frequency of the Indian and Wuhan variants, phylogenetic profiles, three-dimensional (3D) structural perspectives using homology modeling and molecular dynamics analyses for wild-type and selected variants, host-interactome analysis and viral-host protein complexes, and in silico drug screening with known antivirals and other drugs against the SARS-CoV2 NSPs isolated from the variants found within Indian patients across various regions of the country. All this information is categorized in the form of a database named, Database of NSPs of India specific Novel Coronavirus (DbNSP InC), which is freely available at http://www.hpppi.iicb.res.in/covid19/index.php.

Classification and prediction of protein-protein interaction interface using machine learning algorithm.

Structural insight of the protein-protein interaction (PPI) interface can provide knowledge about the kinetics, thermodynamics and molecular functions of the complex while elucidating its role in diseases and further enabling it as a potential therapeutic target. However, owing to experimental lag in solving protein-protein complex structures, three-dimensional (3D) knowledge of the PPI interfaces can be gained via computational approaches like molecular docking and post-docking analyses. Despite development of numerous docking tools and techniques, success in identification of native like interfaces based on docking score functions is limited. Hence, we employed an in-depth investigation of the structural features of the interface that might successfully delineate native complexes from non-native ones. We identify interface properties, which show statistically significant difference between native and non-native interfaces belonging to homo and hetero, protein-protein complexes. Utilizing these properties, a support vector machine (SVM) based classification scheme has been implemented to differentiate native and non-native like complexes generated using docking decoys. Benchmarking and comparative analyses suggest very good performance of our SVM classifiers. Further, protein interactions, which are proven via experimental findings but not resolved structurally, were subjected to this approach where 3D-models of the complexes were generated and most likely interfaces were predicted. A web server called Protein Complex Prediction by Interface Properties (PCPIP) is developed to predict whether interface of a given protein-protein dimer complex resembles known protein interfaces. The server is freely available at http://www.hpppi.iicb.res.in/pcpip/ .

RETREG1/FAM134B mediated autophagosomal degradation of AMFR/GP78 and OPA1 -a dual organellar turnover mechanism.

Turnover of cellular organelles, including endoplasmic reticulum (ER) and mitochondria, is orchestrated by an efficient cellular surveillance system. We have identified a mechanism for dual regulation of ER and mitochondria under stress. It is known that AMFR, an ER E3 ligase and ER-associated degradation (ERAD) regulator, degrades outer mitochondrial membrane (OMM) proteins, MFNs (mitofusins), via the proteasome and triggers mitophagy. We show that destabilized mitochondria are almost devoid of the OMM and generate "mitoplasts". This brings the inner mitochondrial membrane (IMM) in the proximity of the ER. When AMFR levels are high and the mitochondria are stressed, the reticulophagy regulatory protein RETREG1 participates in the formation of the mitophagophore by interacting with OPA1. Interestingly, OPA1 and other IMM proteins exhibit similar RETREG1-dependent autophagosomal degradation as AMFR, unlike most of the OMM proteins. The "mitoplasts" generated are degraded by reticulo-mito-phagy - simultaneously affecting dual organelle turnover.Abbreviations: AMFR/GP78: autocrine motility factor receptor; BAPTA: 1,2-bis(o-aminophenoxy)ethane-N,N,N',N'-tetraacetic acid; BFP: blue fluorescent protein; CCCP: carbonyl cyanide m-chlorophenyl hydrazone; CNBr: cyanogen bromide; ER: endoplasmic reticulum; ERAD: endoplasmic-reticulum-associated protein degradation; FL: fluorescence, GFP: green fluorescent protein; HA: hemagglutinin; HEPES: 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid; IMM: inner mitochondrial membrane; LIR: LC3-interacting region; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MFN: mitofusin, MGRN1: mahogunin ring finger 1; NA: numerical aperature; OMM: outer mitochondrial membrane; OPA1: OPA1 mitochondrial dynamin like GTPase; PRNP/PrP: prion protein; RER: rough endoplasmic reticulum; RETREG1/FAM134B: reticulophagy regulator 1; RFP: red fluorescent protein; RING: really interesting new gene; ROI: region of interest; RTN: reticulon; SEM: standard error of the mean; SER: smooth endoplasmic reticulum; SIM: structured illumination microscopy; SQSTM1/p62: sequestosome 1; STED: stimulated emission depletion; STOML2: stomatin like 2; TOMM20: translocase of outer mitochondrial membrane 20; UPR: unfolded protein response.

Loss of tumor susceptibility gene 101 (TSG101) perturbs endoplasmic reticulum structure and function.

Tumor susceptibility gene 101 (TSG101), an ESCRT-I protein, is implicated in multiple cellular processes and its functional depletion can lead to blocked lysosomal degradation, cell cycle arrest, demyelination and neurodegeneration. Here, we show that loss of TSG101 results in endoplasmic reticulum (ER) stress and this causes ER membrane remodelling (EMR). This correlates with an expansion of ER, increased vacuolation, altered relative distribution of the rough and smooth ER and disruption of three-way junctions. Blocked lysosomal degradation due to TSG101 depletion leads to ER stress and Ca2+ leakage from ER stores, causing destabilization of actin cytoskeleton. Inhibiting Ca2+ release from the ER by blocking ryanodine receptors (RYRs) with Dantrolene partially rescues the ER stress phenotypes. Hence, in this study we have identified the involvement of TSG101 in modulating ER stress mediated remodelling by engaging the actin cytoskeleton. This is significant because functional depletion of TSG101 effectuates ER-stress, perturbs the structure, mobility and function of the ER, all aspects closely associated with neurodegenerative diseases. SUMMARY STATEMENT: We show that tumor susceptibility gene (TSG) 101 regulates endoplasmic reticulum (ER) stress and its membrane remodelling. Loss of TSG101 perturbs structure, mobility and function of the ER as a consequence of actin destabilization.

Cytosolic aggregates in presence of non-translocated proteins perturb endoplasmic reticulum structure and dynamics.

Presence of cytosolic protein aggregates and membrane damage are two common attributes of neurodegenerative diseases. These aggregates delay degradation of non-translocated protein precursors leading to their persistence and accumulation in the cytosol. Here, we find that cells with intracellular protein aggregates (of cytosolic prion protein or huntingtin) destabilize the endoplasmic reticulum (ER) morphology and dynamics when non-translocated protein load is high. This affects trafficking of proteins out from the ER, relative distribution of the rough and smooth ER and three-way junctions that are essential for the structural integrity of the membrane network. The changes in ER membranes may be due to high aggregation tendency of the ER structural proteins-reticulons, and altered distribution of those associated with the three-way ER junctions-Lunapark. Reticulon4 is seen to be enriched in the aggregate fractions in presence of non-translocated protein precursors. This could be mitigated by improving signal sequence efficiencies of the proteins targeted to the ER. These were observed using PrP variants and the seven-pass transmembrane protein (CRFR1) with different signal sequences that led to diverse translocation efficiencies. This identifies a previously unappreciated consequence of cytosolic aggregates on non-translocated precursor proteins-their persistent presence affects ER morphology and dynamics. This may be one of the ways in which cytosolic aggregates can affect endomembranes during neurodegenerative disease.