Tentonin 3 is a pore-forming subunit of a slow inactivation mechanosensitive channel.

Mechanically activating (MA) channels transduce numerous physiological functions. Tentonin 3/TMEM150C (TTN3) confers MA currents with slow inactivation kinetics in somato- and barosensory neurons. However, questions were raised about its role as a Piezo1 regulator and its potential as a channel pore. Here, we demonstrate that purified TTN3 proteins incorporated into the lipid bilayer displayed spontaneous and pressure-sensitive channel currents. These MA currents were conserved across vertebrates and differ from Piezo1 in activation threshold and pharmacological response. Deep neural network structure prediction programs coupled with mutagenetic analysis predicted a rectangular-shaped, tetrameric structure with six transmembrane helices and a pore at the inter-subunit center. The putative pore aligned with two helices of each subunit and had constriction sites whose mutations changed the MA currents. These findings suggest that TTN3 is a pore-forming subunit of a distinct slow inactivation MA channel, potentially possessing a tetrameric structure.

Control of artificial membrane fusion in physiological ionic solutions beyond the limits of electroformation.

Membrane fusion, merging two lipid bilayers, is crucial for fabricating artificial membrane structures. Over the past 40 years, in contrast to precise and controllable membrane fusion in-vivo through specific molecules such as SNAREs, controlling the fusion in-vitro while fabricating artificial membrane structures in physiological ionic solutions without fusion proteins has been a challenge, becoming a significant obstacle to practical applications. We present an approach consisting of an electric field and a few kPa hydraulic pressure as an additional variable to physically control the fusion, enabling tuning of the shape and size of the 3D freestanding lipid bilayers in physiological ionic solutions. Mechanical model analysis reveals that pressure-induced parallel/normal tensions enhance fusion among membranes in the microwell. In-vitro peptide-membrane assay, mimicking vesicular transport via pressure-assisted fusion, and stability of 38 days with in-chip pressure control via pore size-regulated hydrogel highlight the potential for diverse biological applications.

Ion-Induced PIP2 Clustering with Martini3: Modification of Phosphate-Ion Interactions and Comparison with CHARMM36.

Phosphatidylinositol 4,5-bisphosphate (PIP2) is a critical lipid for cellular signaling. The specific phosphorylation of the inositol ring controls protein binding as well as clustering behavior. Two popular models to describe ion-mediated clustering of PIP2 are Martini3 (M3) and CHARMM36 (C36). Molecular dynamics simulations of PIP2-containing bilayers in solutions of potassium chloride, sodium chloride, and calcium chloride, and at two different resolutions are performed to understand the aggregation and the model parameters that drive it. The average M3 clusters of PIP2 in bilayers of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine and PIP2 bilayers in the presence of K+, Na+, or Ca2+ contained 2.2, 2.6, and 6.4 times more PIP2 than C36 clusters, respectively. Indeed, the Ca2+-containing systems often formed a single large aggregate. Reparametrization of the M3 ion-phosphate Lennard-Jones interaction energies to reproduce experimental osmotic pressure of sodium dimethyl phosphate (DMP), K[DMP], and Ca[DMP]2 solutions, the same experimental target as C36, yielded comparably sized PIP2 clusters for the two models. Furthermore, C36 and the modified M3 predict similar saturation of the phosphate groups with increasing Ca2+, although the coarse-grained model does not capture the cooperativity between K+ and Ca2+. This characterization of the M3 behavior in the presence of monovalent and divalent ions lays a foundation to study cation/protein/PIP2 clustering.

CHD7 variants associated with hearing loss and enlargement of the vestibular aqueduct.

Enlargement of the endolymphatic sac, duct, and vestibular aqueduct (EVA) is the most common inner ear malformation identified in patients with sensorineural hearing loss. EVA is associated with pathogenic variants in SLC26A4. However, in European-Caucasian populations, about 50% of patients with EVA carry no pathogenic alleles of SLC26A4. We tested for the presence of variants in CHD7, a gene known to be associated with CHARGE syndrome, Kallmann syndrome, and hypogonadotropic hypogonadism, in a cohort of 34 families with EVA subjects without pathogenic alleles of SLC26A4. In two families, NM_017780.4: c.3553A > G [p.(Met1185Val)] and c.5390G > C [p.(Gly1797Ala)] were detected as monoallelic CHD7 variants in patients with EVA. At least one subject from each family had additional signs or potential signs of CHARGE syndrome but did not meet diagnostic criteria for CHARGE. In silico modeling of these two missense substitutions predicted detrimental effects upon CHD7 protein structure. Consistent with a role of CHD7 in this tissue, Chd7 transcript and protein were detected in all epithelial cells of the endolymphatic duct and sac of the developing mouse inner ear. These results suggest that some CHD7 variants can cause nonsyndromic hearing loss and EVA. CHD7 should be included in DNA sequence analyses to detect pathogenic variants in EVA patients. Chd7 expression and mutant phenotype data in mice suggest that CHD7 contributes to the formation or function of the endolymphatic sac and duct.

Amplification of olfactory signals by Anoctamin 9 is important for mammalian olfaction.

Sensing smells of foods, prey, or predators determines animal survival. Olfactory sensory neurons in the olfactory epithelium (OE) detect odorants, where cAMP and Ca2+ play a significant role in transducing odorant inputs to electrical activity. Here we show Anoctamin 9, a cation channel activated by cAMP/PKA pathway, is expressed in the OE and amplifies olfactory signals. Ano9-deficient mice had reduced olfactory behavioral sensitivity, electro-olfactogram signals, and neural activity in the olfactory bulb. In line with the difference in olfaction between birds and other vertebrates, chick ANO9 failed to respond to odorants, whereas chick CNGA2, a major transduction channel, showed greater responses to cAMP. Thus, we concluded that the signal amplification by ANO9 is important for mammalian olfactory transduction.

Neural Information Processing and Computations of Two-Input Synapses.

Information processing in artificial neural networks is largely dependent on the nature of neuron models. While commonly used models are designed for linear integration of synaptic inputs, accumulating experimental evidence suggests that biological neurons are capable of nonlinear computations for many converging synaptic inputs via homo- and heterosynaptic mechanisms. This nonlinear neuronal computation may play an important role in complex information processing at the neural circuit level. Here we characterize the dynamics and coding properties of neuron models on synaptic transmissions delivered from two hidden states. The neuronal information processing is influenced by the cooperative and competitive interactions among synapses and the coherence of the hidden states. Furthermore, we demonstrate that neuronal information processing under two-input synaptic transmission can be mapped to linearly nonseparable XOR as well as basic AND/OR operations. In particular, the mixtures of linear and nonlinear neuron models outperform the fashion-MNIST test compared to the neural networks consisting of only one type. This study provides a computational framework for assessing information processing of neuron and synapse models that may be beneficial for the design of brain-inspired artificial intelligence algorithms and neuromorphic systems.

Design principles of PI(4,5)P2 clustering under protein-free conditions: Specific cation effects and calcium-potassium synergy.

Phosphatidylinositol 4,5-bisphosphate (PIP2) clustering is a key component in cell signaling, yet little is known about the atomic-level features of this phenomenon. Network-theoretic analysis of multimicrosecond atomistic simulations of PIP2 containing asymmetric bilayers under protein-free conditions, presented here, reveals how design principles of PIP2 clustering are determined by the specific cation effects. Ca2+ generates large clusters (6% are pentamer or larger) by adding existing PIP2 dimers formed by strong O‒Ca2+‒O bridging interactions of unprotonated P4/P5 phosphates. In contrast, monovalent cations (Na+ and K+) form smaller and less-stable clusters by preferentially adding PIP2 monomers. Despite having the same net charge, the affinity to P4/P5 is higher for Na+, while affinity toward glycerol P1 is higher for K+. Consequently, a mixture of K+ and Ca2+ (as would be produced by Ca2+ influx) synergistically yields larger and more stable clusters than Ca2+ alone due to the different binding preferences of these cations.

Differentiating amnestic from non-amnestic mild cognitive impairment subtypes using graph theoretical measures of electroencephalography.

The purpose of this study was to explore different patterns of functional networks between amnestic mild cognitive impairment (aMCI) and non-aMCI (naMCI) using electroencephalography (EEG) graph theoretical analysis. The data of 197 drug-naïve individuals who complained cognitive impairment were reviewed. Resting-state EEG data was acquired. Graph analyses were performed and compared between aMCI and naMCI, as well as between early and late aMCI. Correlation analyses were conducted between the graph measures and neuropsychological test results. Machine learning algorithms were applied to determine whether the EEG graph measures could be used to distinguish aMCI from naMCI. Compared to naMCI, aMCI showed higher modularity in the beta band and lower radius in the gamma band. Modularity was negatively correlated with scores on the semantic fluency test, and the radius in the gamma band was positively correlated with visual memory, phonemic, and semantic fluency tests. The naïve Bayes algorithm classified aMCI and naMCI with 89% accuracy. Late aMCI showed inefficient and segregated network properties compared to early aMCI. Graph measures could differentiate aMCI from naMCI, suggesting that these measures might be considered as predictive markers for progression to Alzheimer's dementia in patients with MCI.

Lotus Seed Green Embryo Extract and a Purified Glycosyloxyflavone Constituent, Narcissoside, Activate TRPV1 Channels in Dorsal Root Ganglion Sensory Neurons.

Several studies have documented the broad-spectrum bioactivities of a lotus seed (Plumula nelumbinis [PN]) green embryo extract. However, the specific bioactive components and associated molecular mechanisms remain largely unknown. This study aimed to identify the ion channel-activating mechanisms of PN extracts. Using fluorometric imaging and patch-clamp recordings, PN extracts were screened for calcium channel activation in dorsal root ganglion (DRG) neurons. The TRPV1 channels in DRG neurons were strongly activated by the PN extract (mean amplitude of 131 ± 45 pA at 200 µg/mL) and its purified glycosyloxyflavone narcissoside (401 ± 271 pA at 100 µM). Serial treatment with a 200 µg/mL PN extract in TRPV1-overexpressing HEK293T cells induced robust desensitization to 10 ± 10% of the initial current amplitude. Thus, we propose that the PN extract and narcissoside function as TRPV1 agonists. This new finding may advance our knowledge regarding the traditional and scientific functions of PN in human health and disease.

The structural aspects of neural dynamics and information flow.

BACKGROUND: Neurons have specialized structures that facilitate information transfer using electrical and chemical signals. Within the perspective of neural computation, the neuronal structure is an important prerequisite for the versatile computational capabilities of neurons resulting from the integration of diverse synaptic input patterns, complex interactions among the passive and active dendritic local currents, and the interplay between dendrite and soma to generate action potential output. For this, characterization of the relationship between the structure and neuronal spike dynamics could provide essential information about the cellular-level mechanism supporting neural computations. RESULTS: This work describes simulations and an information-theoretic analysis to investigate how specific neuronal structure affects neural dynamics and information processing. Correlation analysis on the Allen Cell Types Database reveals biologically relevant structural features that determine neural dynamics-eight highly correlated structural features are selected as the primary set for characterizing neuronal structures. These features are used to characterize biophysically realistic multi-compartment mathematical models for primary neurons in the direct and indirect hippocampal pathways consisting of the pyramidal cells of Cornu Ammonis 1 (CA1) and CA3 and the granule cell in the dentate gyrus (DG). Simulations reveal that the dynamics of these neurons vary depending on their specialized structures and are highly sensitive to structural modifications. Information-theoretic analysis confirms that structural factors are critical for versatile neural information processing at a single-cell and a neural circuit level; not only basic AND/OR but also linearly non-separable XOR functions can be explained within the information-theoretic framework. CONCLUSIONS: Providing quantitative information on the relationship between the structure and the dynamics/information flow of neurons, this work would help us understand the design and coding principles of biological neurons and may be beneficial for designing biologically plausible neuron models for artificial intelligence (AI) systems.

Characterization of multiscale logic operations in the neural circuits.

Background: Ever since the seminal work by McCulloch and Pitts, the theory of neural computation and its philosophical foundation known as 'computationalism' have been central to brain-inspired artificial intelligence (AI) technologies. The present study describes neural dynamics and neural coding approaches to understand the mechanisms of neural computation. The primary focus is to characterize the multiscale nature of logic computations in the brain, which might occur at a single neuron level, between neighboring neurons via synaptic transmission, and at the neural circuit level. Results: For this, we begin the analysis with simple neuron models to account for basic Boolean logic operations at a single neuron level and then move on to the phenomenological neuron models to explain the neural computation from the viewpoints of neural dynamics and neural coding. The roles of synaptic transmission in neural computation are investigated using biologically realistic multi-compartment neuron models: two representative computational entities, CA1 pyramidal neuron in the hippocampus and Purkinje fiber in the cerebellum, are analyzed in the information-theoretic framework. We then construct two-dimensional mutual information maps, which demonstrate that the synaptic transmission can process not only basic AND/OR Boolean logic operations but also the linearly non-separable XOR function. Finally, we provide an overview of the evolutionary algorithm and discuss its benefits in automated neural circuit design for logic operations. Conclusions: This study provides a comprehensive perspective on the multiscale logic operations in the brain from both neural dynamics and neural coding viewpoints. It should thus be beneficial for understanding computational principles of the brain and may help design biologically plausible neuron models for AI devices.

Drinking coffee enhances neurocognitive function by reorganizing brain functional connectivity.

The purpose of this study was to identify the mechanisms underlying effects of coffee on cognition in the context of brain networks. Here we investigated functional connectivity before and after drinking coffee using graph-theoretic analysis of electroencephalography (EEG). Twenty-one healthy adults voluntarily participated in this study. The resting-state EEG data and results of neuropsychological tests were consecutively acquired before and 30 min after coffee consumption. Graph analyses were performed and compared before and after coffee consumption. Correlation analyses were conducted to assess the relationship between changes in graph measures and those in cognitive function tests. Functional connectivity (FC) was reorganized toward more efficient network properties after coffee consumption. Performance in Digit Span tests and Trail Making Test Part B improved after coffee consumption, and the improved performance in executive function was correlated with changes in graph measures, reflecting a shift toward efficient network properties. The beneficial effects of coffee on cognitive function might be attributed to the reorganization of FC toward more efficient network properties. Based on our findings, the patterns of network reorganization could be used as quantitative markers to elucidate the mechanisms underlying the beneficial effects of coffee on cognition, especially executive function.

Lysosomal SLC46A3 modulates hepatic cytosolic copper homeostasis.

The environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) causes hepatic toxicity associated with prominent lipid accumulation in humans. Here, the authors report that the lysosomal copper transporter SLC46A3 is induced by TCDD and underlies the hepatic lipid accumulation in mice, potentially via effects on mitochondrial function. SLC46A3 was localized to the lysosome where it modulated intracellular copper levels. Forced expression of hepatic SLC46A3 resulted in decreased mitochondrial membrane potential and abnormal mitochondria morphology consistent with lower copper levels. SLC46A3 expression increased hepatic lipid accumulation similar to the known effects of TCDD exposure in mice and humans. The TCDD-induced hepatic triglyceride accumulation was significantly decreased in Slc46a3-/- mice and was more pronounced when these mice were fed a high-fat diet, as compared to wild-type mice. These data are consistent with a model where lysosomal SLC46A3 induction by TCDD leads to cytosolic copper deficiency resulting in mitochondrial dysfunction leading to lower lipid catabolism, thus linking copper status to mitochondrial function, lipid metabolism and TCDD-induced liver toxicity.

PLD2-PI(4,5)P2 interactions in fluid phase membranes: Structural modeling and molecular dynamics simulations.

Interaction of phospholipase D2 (PLD2) with phosphatidylinositol (4,5)-bisphosphate (PIP2) is regarded as the critical step of numerous physiological processes. Here we build a full-length model of human PLD2 (hPLD2) combining template-based and ab initio modeling techniques and use microsecond all-atom molecular dynamics (MD) simulations of the protein in contact with a complex membrane to determine hPLD2-PIP2 interactions. MD simulations reveal that the intermolecular interactions preferentially occur between specific PIP2 phosphate groups and hPLD2 residues; the most strongly interacting residues are arginine at the pbox consensus sequence (PX) and pleckstrin homology (PH) domain. Interaction networks indicate formation of clusters at the protein-membrane interface consisting of amino acids, PIP2, and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidic acid (POPA); the largest cluster was in the PH domain.

Computational modeling of the effects of autophagy on amyloid-ß peptide levels.

BACKGROUND: Autophagy is an evolutionarily conserved intracellular process that is used for delivering proteins and organelles to the lysosome for degradation. For decades, autophagy has been speculated to regulate amyloid-ß peptide (Aß) accumulation, which is involved in Alzheimer's disease (AD); however, specific autophagic effects on the Aß kinetics only have begun to be explored. RESULTS: We develop a mathematical model for autophagy with respect to Aß kinetics and perform simulations to understand the quantitative relationship between Aß levels and autophagy activity. In the case of an abnormal increase in the Aß generation, the degradation, secretion, and clearance rates of Aß are significantly changed, leading to increased levels of Aß. When the autophagic Aß degradation is defective in addition to the increased Aß generation, the Aß-regulation failure is accompanied by elevated concentrations of autophagosome and autolysosome, which may further clog neurons. CONCLUSIONS: The model predicts that modulations of different steps of the autophagy pathway (i.e., Aß sequestration, autophagosome maturation, and intralysosomal hydrolysis) have significant step-specific and combined effects on the Aß levels and thus suggests therapeutic and preventive implications of autophagy in AD.

Characterization of Specific Ion Effects on PI(4,5)P2 Clustering: Molecular Dynamics Simulations and Graph-Theoretic Analysis.

Numerous cellular functions mediated by phosphatidylinositol (4,5)-bisphosphate (PI(4,5)P2; PIP2) involve clustering of the lipid as well as colocalization with other lipids. Although the cation-mediated electrostatic interaction is regarded as the primary clustering mechanism, the ion-specific nature of the intermolecular network formation makes it challenging to characterize the clusters. Here we use all-atom molecular dynamics (MD) simulations of PIP2 monolayers and graph-theoretic analysis to gain insight into the phenomenon. MD simulations reveal that the intermolecular interactions preferentially occur between specific cations and phosphate groups (P1, P4, and P5) of the inositol headgroup with better-matched kosmotropic/chaotropic characters consistent with the law of matching water affinities (LMWA). Ca2+ is strongly attracted to P4/P5, while K+ preferentially binds to P1; Na+ interacts with both P4/P5 and P1. These specific interactions lead to the characteristic clustering patterns. Specificially, the size distributions and structures of PIP2 clusters generated by kosmotropic cations Ca2+ and Na+ are bimodal, with a combination of small and large clusters, while there is little clustering in the presence of only chaotropic K+; the largest clusters are obtained in systems with all three cations. The small-world network (a model with both local and long-range connections) best characterizes the clusters, followed by the random and the scale-free networks. More generally, the present results interpreted within the LMWA are consistent with the relative eukaryotic intracellular concentrations Ca2+ ≪ Na+ < Mg2+ < K+; that is, concentrations of Ca2+ and Na+ must be low to prevent damaging aggregation of lipids, DNA, RNA and phosphate-containing proteins.

Comparison of the umbrella sampling and the double decoupling method in binding free energy predictions for SAMPL6 octa-acid host-guest challenges.

We calculate the absolute binding free energies of tetra-methylated octa-acids host-guest systems as a part of the SAMPL6 blind challenge (receipt ID vq30p). We employed two different free energy simulation methods, i.e., the umbrella sampling (US) and double decoupling method (DDM). The US method was used with the weighted histogram analysis method (WHAM) (US-WHAM scheme). In the DDM scheme, Hamiltonian replica-exchange method (HREM) was combined with the Bennett acceptance ratio (BAR) (HREM-BAR scheme). We obtained initial binding poses via molecular docking using GalaxyDock-HG program, which is developed for the SAMPL challenge. The root mean square deviation (RMSD) and the mean absolute deviations (MAD) using US-WHAM scheme were 1.33 and 1.02 kcal/mol, respectively. The MAD was the top among all submissions, however the correlation with respect to experiment was unexceptional. While the RMSD and MAD via HREM-BAR scheme were greater than US-WHAM scheme, (i.e., 2.09 and 1.76 kcal/mol), their correlations were slightly better than US-WHAM. The correlation between the two methods was high. Further discussion on the DDM method can be found in a companion paper by Han et al. (receipt ID 3z83m) in the same issue.

Force matching as a stepping stone to QM/MM CB[8] host/guest binding free energies: a SAMPL6 cautionary tale.

Use of quantum mechanical/molecular mechanical (QM/MM) methods in binding free energy calculations, particularly in the SAMPL challenge, often fail to achieve improvement over standard additive (MM) force fields. Frequently, the implementation is through use of reference potentials, or the so-called "indirect approach", and inherently relies on sufficient overlap existing between MM and QM/MM configurational spaces. This overlap is generally poor, particularly for the use of free energy perturbation to perform the MM to QM/MM free energy correction at the end states of interest (e.g., bound and unbound states). However, by utilizing MM parameters that best reproduce forces obtained at the desired QM level of theory, it is possible to lessen the configurational disparity between MM and QM/MM. To this end, we sought to use force matching to generate MM parameters for the SAMPL6 CB[8] host-guest binding challenge, classically compute binding free energies, and apply energetic end state corrections to obtain QM/MM binding free energy differences. For the standard set of 11 molecules and the bonus set (including three additional challenge molecules), error statistics, such as the root mean square deviation (RMSE) were moderately poor (5.5 and 5.4 kcal/mol). Correlation statistics, however, were in the top two for both standard and bonus set submissions ([Formula: see text] of 0.42 and 0.26, [Formula: see text] of 0.64 and 0.47 respectively). High RMSE and moderate correlation strongly indicated the presence of systematic error. Identifiable issues were ameliorated for two of the guest molecules, resulting in a reduction of error and pointing to strong prospects for the future use of this methodology.

Prediction of CB[8] host-guest binding free energies in SAMPL6 using the double-decoupling method.

This study reports the results of binding free energy calculations for CB[8] host-guest systems in the SAMPL6 blind challenge (receipt ID 3z83m). Force-field parameters were developed specific for each of host and guest molecules to improve configurational sampling. We used quantum mechanical (QM) implicit solvent calculations and QM force matching to determine non-bonded (partial atomic charges) and bonded terms, respectively. Free energy calculations were carried out using the double-decoupling method (DDM) combined with Hamiltonian replica exchange method (HREM) and Bennett acceptance ratio (BAR) method. The root mean square error (RMSE) of the predicted values using DDM with respect to the experimental results was 4.32 kcal/mol. The coefficient of determination (R2) and Kendall rank coefficient (τ) were 0.49 and 0.52, respectively, highest of all submissions. In addition, these were compared to the results obtained by umbrella sampling (US) and weighted histogram analysis method (WHAM). Overall, DDM achieved a higher prediction accuracy than the US method. Results are discussed in terms of parameterization and free energy simulations.

Numerical study of entrainment of the human circadian system and recovery by light treatment.

BACKGROUND: While the effects of light as a zeitgeber are well known, the way the effects are modulated by features of the sleep-wake system still remains to be studied in detail. METHODS: A mathematical model for disturbance and recovery of the human circadian system is presented. The model combines a circadian oscillator and a sleep-wake switch that includes the effects of orexin. By means of simulations, we characterize the period-locking zone of the model, where a stable 24-hour circadian rhythm exists, and the occurrence of circadian disruption due to both insufficient light and imbalance in orexin. We also investigate how daily bright light treatments of short duration can recover the normal circadian rhythm. RESULTS: It is found that the system exhibits continuous phase advance/delay at lower/higher orexin levels. Bright light treatment simulations disclose two optimal time windows, corresponding to morning and evening light treatments. Among the two, the morning light treatment is found effective in a wider range of parameter values, with shorter recovery time. CONCLUSIONS: This approach offers a systematic way to determine the conditions under which circadian disruption occurs, and to evaluate the effects of light treatment. In particular, it could potentially offer a way to optimize light treatments for patients with circadian disruption, e.g., sleep and mood disorders, in clinical settings.