CHCHD2 mutant mice display mitochondrial protein accumulation and disrupted energy metabolism.

Mutations in the mitochondrial cristae protein CHCHD2 lead to a late-onset autosomal dominant form of Parkinson's disease (PD) which closely resembles idiopathic PD, providing the opportunity to gain new insights into the mechanisms of mitochondrial dysfunction contributing to PD. To begin to address this, we used CRISPR genome-editing to generate CHCHD2 T61I point mutant mice. CHCHD2 T61I mice had normal viability, and had only subtle motor deficits with no signs of premature dopaminergic (DA) neuron degeneration. Nonetheless, CHCHD2 T61I mice exhibited robust molecular changes in the brain including increased CHCHD2 insolubility, accumulation of CHCHD2 protein preferentially in the substantia nigra (SN), and elevated levels of α-synuclein. Metabolic analyses revealed an increase in glucose metabolism through glycolysis relative to the TCA cycle with increased respiratory exchange ratio, and immune-electron microscopy revelated disrupted mitochondria in DA neurons. Moreover, spatial genomics revealed decreased expression of mitochondrial complex I and III respiratory chain proteins, while proteomics revealed increased respiratory chain and other mitochondrial protein-protein interactions. As such, the CHCHD2 T61I point-mutation mice exhibit robust mitochondrial disruption and a consequent metabolic shift towards glycolysis. These findings thus establish CHCHD2 T61I mice as a new model for mitochondrial-based PD, and implicate disrupted respiratory chain function as a likely causative driver.

Improved Imaging Surface for Quantitative Single-Molecule Microscopy.

Preventing nonspecific binding is essential for sensitive surface-based quantitative single-molecule microscopy. Here we report a much-simplified RainX-F127 (RF-127) surface with improved passivation. This surface achieves up to 100-fold less nonspecific binding from protein aggregates compared to commonly used polyethylene glycol (PEG) surfaces. The method is compatible with common single-molecule techniques including single-molecule pull-down (SiMPull), super-resolution imaging, antibody-binding screening and single exosome visualization. This method is also able to specifically detect alpha-synuclein (α-syn) and tau aggregates from a wide range of biofluids including human serum, brain extracts, cerebrospinal fluid (CSF) and saliva. The simplicity of this method further allows the functionalization of microplates for robot-assisted high-throughput single-molecule experiments. Overall, this simple but improved surface offers a versatile platform for quantitative single-molecule microscopy without the need for specialized equipment or personnel.

Single-molecule dynamics of DNA gyrase in evolutionarily distant bacteria Mycobacterium tuberculosis and Escherichia coli.

DNA gyrase is an essential nucleoprotein motor present in all bacteria and is a major target for antibiotic treatment of Mycobacterium tuberculosis (MTB) infection. Gyrase hydrolyzes ATP to add negative supercoils to DNA using a strand passage mechanism that has been investigated using biophysical and biochemical approaches. To analyze the dynamics of substeps leading to strand passage, single-molecule rotor bead tracking (RBT) has been used previously to follow real-time supercoiling and conformational transitions in Escherichia coli (EC) gyrase. However, RBT has not yet been applied to gyrase from other pathogenically relevant bacteria, and it is not known whether substeps are conserved across evolutionarily distant species. Here, we compare gyrase supercoiling dynamics between two evolutionarily distant bacterial species, MTB and EC. We used RBT to measure supercoiling rates, processivities, and the geometries and transition kinetics of conformational states of purified gyrase proteins in complex with DNA. Our results show that E. coli and MTB gyrases are both processive, with the MTB enzyme displaying velocities ∼5.5× slower than the EC enzyme. Compared with EC gyrase, MTB gyrase also more readily populates an intermediate state with DNA chirally wrapped around the enzyme, in both the presence and absence of ATP. Our substep measurements reveal common features in conformational states of EC and MTB gyrases interacting with DNA but also suggest differences in populations and transition rates that may reflect distinct cellular needs between these two species.

Hyperphosphorylated tau self-assembles into amorphous aggregates eliciting TLR4-dependent responses.

Soluble aggregates of the microtubule-associated protein tau have been challenging to assemble and characterize, despite their important role in the development of tauopathies. We found that sequential hyperphosphorylation by protein kinase A in conjugation with either glycogen synthase kinase 3ß or stress activated protein kinase 4 enabled recombinant wild-type tau of isoform 0N4R to spontaneously polymerize into small amorphous aggregates in vitro. We employed tandem mass spectrometry to determine the phosphorylation sites, high-resolution native mass spectrometry to measure the degree of phosphorylation, and super-resolution microscopy and electron microscopy to characterize the morphology of aggregates formed. Functionally, compared with the unmodified aggregates, which require heparin induction to assemble, these self-assembled hyperphosphorylated tau aggregates more efficiently disrupt membrane bilayers and induce Toll-like receptor 4-dependent responses in human macrophages. Together, our results demonstrate that hyperphosphorylated tau aggregates are potentially damaging to cells, suggesting a mechanism for how hyperphosphorylation could drive neuroinflammation in tauopathies.

Understanding gambling behaviour and risk attitudes using cryptocurrency-based casino blockchain data.

The statistical concept of gambler's ruin suggests that gambling has a large amount of risk. Nevertheless, gambling at casinos and gambling on the Internet are both hugely popular activities. In recent years, both prospect theory and laboratory-controlled experiments have been used to improve our understanding of risk attitudes associated with gambling. Despite theoretical progress, collecting real-life gambling data, which is essential to validate predictions and experimental findings, remains a challenge. To address this issue, we collect publicly available betting data from a DApp (decentralized application) on the Ethereum blockchain, which instantly publishes the outcome of every single bet (consisting of each bet's timestamp, wager, probability of winning, userID and profit). This online casino is a simple dice game that allows gamblers to tune their own winning probabilities. Thus the dataset is well suited for studying gambling strategies and the complex dynamic of risk attitudes involved in betting decisions. We analyse the dataset through the lens of current probability-theoretic models and discover empirical examples of gambling systems. Our results shed light on understanding the role of risk preferences in human financial behaviour and decision-makings beyond gambling.