Structural insights into thermophilic chaperonin complexes.

Group I chaperonins are dual heptamer protein complexes that play significant roles in protein homeostasis. The structure and function of the Escherichia coli chaperonin are well characterized. However, the dynamic properties of chaperonins, such as large ATPase-dependent conformational changes by binding of lid-like co-chaperonin GroES, have made structural analyses challenging, and our understanding of these changes during the turnover of chaperonin complex formation is limited. In this study, we used single-particle cryogenic electron microscopy to investigate the structures of GroES-bound chaperonin complexes from the thermophilic hydrogen-oxidizing bacteria Hydrogenophilus thermoluteolus and Hydrogenobacter thermophilus in the presence of ATP and AMP-PNP. We captured the structure of an intermediate state chaperonin complex, designated as an asymmetric football-shaped complex, and performed analyses to decipher the dynamic structural variations. Our structural analyses of inter- and intra-subunit communications revealed a unique mechanism of complex formation through the binding of a second GroES to a bullet-shaped complex.

Unlocking microalgal host-exploring dark-growing microalgae transformation for sustainable high-value phytochemical production.

Microalgae have emerged as a promising, next-generation sustainable resource with versatile applications, particularly as expression platforms and green cell factories. They possess the ability to overcome the limitations of terrestrial plants, such non-arable land, water scarcity, time-intensive growth, and seasonal changes. However, the heterologous expression of interested genes in microalgae under heterotrophic cultivation (dark mode) remains a niche area within the field of engineering technologies. In this study, the green microalga, Chlorella sorokiniana AARL G015 was chosen as a potential candidate due to its remarkable capacity for rapid growth in complete darkness, its ability to utilize diverse carbon sources, and its potential for wastewater treatment in a circular bioeconomy model. The aims of this study were to advance microalgal genetic engineering via dark cultivation, thereby positioning the strain as promising dark-host for expressing heterologous genes to produce high-value phytochemicals and ingredients for food and feed. To facilitate comprehensive screening based on resistance, eleven common antibiotics were tested under heterotrophic condition. As the most effective selectable markers for this strain, G418, hygromycin, and streptomycin exhibited growth inhibition rates of 98%, 93%, and 92%, respectively, ensuring robust long-term transgenic growth. Successful transformation was achieved through microalgal cell cocultivation with Agrobacterium under complete darkness verified through the expression of green fluorescence protein and ß-glucuronidase. In summary, this study pioneers an alternative dark-host microalgal platform, using, Chlorella, under dark mode, presenting an easy protocol for heterologous gene transformation for microalgal host, devoid of the need for expensive equipment and light for industrial production. Furthermore, the developed genetic transformation methodology presents a sustainable way for production of high-value nutrients, dietary supplements, nutraceuticals, proteins and pharmaceuticals using heterotrophic microalgae as an innovative host system.

Effect of transcranial direct current stimulation on the functionality of 40 Hz auditory steady state response brain network: graph theory approach.

Introduction: Measuring whole-brain networks of the 40 Hz auditory steady state response (ASSR) is a promising approach to describe the after-effects of transcranial direct current stimulation (tDCS). The main objective of this study was to evaluate the effect of tDCS on the brain network of 40 Hz ASSR in healthy adult males using graph theory. The second objective was to identify a population in which tDCS effectively modulates the brain network of 40 Hz ASSR. Methods: This study used a randomized, sham-controlled, double-blinded crossover approach. Twenty-five adult males (20-24 years old) completed two sessions at least 1 month apart. The participants underwent cathodal or sham tDCS of the dorsolateral prefrontal cortex, after which 40 Hz ASSR was measured using magnetoencephalography. After the signal sources were mapped onto the Desikan-Killiany brain atlas, the statistical relationships between localized activities were evaluated in terms of the debiased weighted phase lag index (dbWPLI). Weighted and undirected graphs were constructed for the tDCS and sham conditions based on the dbWPLI. Weighted characteristic path lengths and clustering coefficients were then measured and compared between the tDCS and sham conditions using mixed linear models. Results: The characteristic path length was significantly lower post-tDCS simulation (p = 0.04) than after sham stimulation. This indicates that after tDCS simulation, the whole-brain networks of 40 Hz ASSR show a significant functional integration. Simple linear regression showed a higher characteristic path length at baseline, which was associated with a larger reduction in characteristic path length after tDCS. Hence, a pronounced effect of tDCS is expected for those who have a less functionally integrated network of 40 Hz ASSR. Discussion: Given that the healthy brain is functionally integrated, we conclude that tDCS could effectively normalize less functionally integrated brain networks rather than enhance functional integration.

Alterations in brain networks in children with sub-threshold autism spectrum disorder: A magnetoencephalography study.

Individuals with sub-threshold autism spectrum disorder (ASD) are those who have social communication difficulties but do not meet the full ASD diagnostic criteria. ASD is associated with an atypical brain network; however, no studies have focused on sub-threshold ASD. Here, we used the graph approach to investigate alterations in the brain networks of children with sub-threshold ASD, independent of a clinical diagnosis. Graph theory is an effective approach for characterizing the properties of complex networks on a large scale. Forty-six children with ASD and 31 typically developing children were divided into three groups (i.e., ASD-Unlikely, ASD-Possible, and ASD-Probable groups) according to their Social Responsiveness Scale scores. We quantified magnetoencephalographic signals using a graph-theoretic index, the phase lag index, for every frequency band. Resultantly, the ASD-Probable group had significantly lower small-worldness (SW) in the delta, theta, and beta bands than the ASD-Unlikely group. Notably, the ASD-Possible group exhibited significantly higher SW than the ASD-Probable group and significantly lower SW than the ASD-Unlikely group in the delta band only. To our knowledge, this was the first report of the atypical brain network associated with sub-threshold ASD. Our findings indicate that magnetoencephalographic signals using graph theory may be useful in detecting sub-threshold ASD.

Atypical Resting State Functional Neural Network in Children With Autism Spectrum Disorder: Graph Theory Approach.

Measuring whole brain networks is a promising approach to extract features of autism spectrum disorder (ASD), a brain disorder of widespread regions. Objectives of this study were to evaluate properties of resting-state functional brain networks in children with and without ASD and to evaluate their relation with social impairment severity. Magnetoencephalographic (MEG) data were recorded for 21 children with ASD (7 girls, 60-89 months old) and for 25 typically developing (TD) control children (10 girls, 60-91 months old) in a resting state while gazing at a fixation cross. After signal sources were localized onto the Desikan-Killiany brain atlas, statistical relations between localized activities were found and evaluated in terms of the phase lag index. After brain networks were constructed and after matching with intelligence using a coarsened exact matching algorithm, ASD and TD graph theoretical measures were compared. We measured autism symptoms severity using the Social Responsiveness Scale and investigated its relation with altered small-worldness using linear regression models. Children with ASD were found to have significantly lower small-worldness in the beta band (p = 0.007) than TD children had. Lower small-worldness in the beta band of children with ASD was associated with higher Social Responsiveness Scale total t-scores (p = 0.047). Significant relations were also inferred for the Social Awareness (p = 0.008) and Social Cognition (p = 0.015) sub-scales. Results obtained using graph theory demonstrate a difference between children with and without ASD in MEG-derived resting-state functional brain networks, and the relation of that difference with social impairment. Combining graph theory and MEG might be a promising approach to establish a biological marker for ASD.

Epileptiform discharges relate to altered functional brain networks in autism spectrum disorders.

Many individuals with autism spectrum disorders have comorbid epilepsy. Even in the absence of observable seizures, interictal epileptiform discharges are common in individuals with autism spectrum disorders. However, how these interictal epileptiform discharges are related to autistic symptomatology remains unclear. This study used magnetoencephalography to investigate the relation between interictal epileptiform discharges and altered functional brain networks in children with autism spectrum disorders. Instead of particularly addressing individual brain regions, we specifically examine network properties. For this case-control study, we analysed 70 children with autism spectrum disorders (52 boys, 18 girls, 38-92 months old) and 19 typically developing children (16 boys, 3 girls, 48-88 months old). After assessing the participants' social reciprocity using the Social Responsiveness Scale, we constructed graphs of functional brain networks from frequency band separated task-free magnetoencephalography recordings. Nodes corresponded to Desikan-Killiany atlas-based 68 brain regions. Edges corresponded to phase lag index values between pairs of brain regions. To elucidate the effects of the existence of interictal epileptiform discharges on graph metrics, we matched each of three pairs from three groups (typically developing children, children with autism spectrum disorders who had interictal epileptiform discharges and those who did not) in terms of age and sex. We used a coarsened exact matching algorithm and applied adjusted regression analysis. We also investigated the relation between social reciprocity and the graph metric. Results show that, in children with autism spectrum disorders, the average clustering coefficient in the theta band was significantly higher in children who had interictal epileptiform discharges. Moreover, children with autism spectrum disorders who had no interictal epileptiform discharges had a significantly lower average clustering coefficient in the theta band than typically developing children had. However, the difference between typically developing children and children with autism spectrum disorder who had interictal epileptiform discharges was not significant. Furthermore, the higher average clustering coefficient in the theta band corresponded to severe autistic symptoms in children with autism spectrum disorder who had interictal epileptiform discharges. However, the association was not significant in children with autism spectrum disorders who had no interictal epileptiform discharge. In conclusion, results demonstrate that alteration of functional brain networks in children with autism spectrum disorders depends on the existence of interictal epileptiform discharges. Interictal epileptiform discharges might 'normalize' the deviation of altered brain networks in autism spectrum disorders, increasing the clustering coefficient. However, when the effect exceeds tolerance, it actually exacerbates autistic symptoms.

Japanese local government management of compulsory hospitalization for patients with mental disorders and comorbid COVID-19.

Administering medical treatment or managing quarantine for a patient is particularly difficult when a patient harming others or causing self-harm because of severe depression, a manic state, or psychomotor agitation is also infected with COVID-19. Kanazawa University Hospital is the only facility able to manage such difficult cases occurring in Ishikawa prefecture, a local administrative area in Japan. The hospital has arranged a negative pressure apparatus in a psychiatric ward with two protection rooms. This report describes an urgently established but viable system in one prefecture of Japan for treating COVID-19-infected patients with severe psychiatric symptoms during the COVID-19 pandemic.

Decomposed Temporal Complexity Analysis of Neural Oscillations and Machine Learning Applied to Alzheimer's Disease Diagnosis.

Despite growing evidence of aberrant neuronal complexity in Alzheimer's disease (AD), it remains unclear how this variation arises. Neural oscillations reportedly comprise different functions depending on their own properties. Therefore, in this study, we investigated details of the complexity of neural oscillations by decomposing the oscillations into frequency, amplitude, and phase for AD patients. We applied resting-state magnetoencephalography (MEG) to 17 AD patients and 21 healthy control subjects. We first decomposed the source time series of the MEG signal into five intrinsic mode functions using ensemble empirical mode decomposition. We then analyzed the temporal complexities of these time series using multiscale entropy. Results demonstrated that AD patients had lower complexity on short time scales and higher complexity on long time scales in the alpha band in temporal regions of the brain. We evaluated the alpha band complexity further by decomposing it into amplitude and phase using Hilbert spectral analysis. Consequently, we found lower amplitude complexity and higher phase complexity in AD patients. Correlation analyses between spectral complexity and decomposed complexities revealed scale-dependency. Specifically, amplitude complexity was positively correlated with spectral complexity on short time scales, whereas phase complexity was positively correlated with spectral complexity on long time scales. Regarding the relevance of cognitive function to the complexity measures, the phase complexity on the long time scale was found to be correlated significantly with the Mini-Mental State Examination score. Additionally, we examined the diagnostic utility of the complexity characteristics using machine learning (ML) methods. We prepared a feature pool using multiple sparse autoencoders (SAEs), chose some discriminating features, and applied them to a support vector machine (SVM). Compared to the simple SVM and the SVM after feature selection (FS + SVM), the SVM with multiple SAEs (SAE + FS + SVM) had improved diagnostic accuracy. Through this study, we 1) advanced the understanding of neuronal complexity in AD patients using decomposed temporal complexity analysis and 2) demonstrated the effectiveness of combining ML methods with information about signal complexity for the diagnosis of AD.

Complete Genome Sequence of the Acetic Acid Bacterium Acetobacter aceti NBRC 14818.

We report here the complete genome sequence of the acetic acid bacterium Acetobacter aceti type strain NBRC 14818. The genome comprises a chromosome of 3,596,270 bp with 57.1% GC content and four plasmids/phages of 63,279 bp, 25,755 bp, 4,858 bp, and 2,964 bp, with an average GC content of 57.0%.

Different associations between intelligence and social cognition in children with and without autism spectrum disorders.

Autism spectrum disorders (ASD) are characterized by impaired social cognition and communication. In addition to social impairment, individuals with ASD often have intellectual disability. Intelligence is known to influence the phenotypic presentation of ASD. Nevertheless, the relation between intelligence and social reciprocity in people with ASD remains unclear, especially in childhood. To elucidate this relation, we analyzed 56 typically developing children (35 male, 21 female, aged 60-91 months) and 46 children with ASD (35 male, 11 female, aged 60-98 months) from university and affiliated hospitals. Their cognitive function was evaluated using the Kaufman Assessment Battery for Children. Their social cognition was assessed using the Social Responsiveness Scale. We used linear regression models to ascertain whether the associations between intelligence and social cognition of typically developing children and children with ASD are significantly different. Among the children with ASD, scores on the Kaufman Assessment Battery for Children correlated significantly with social cognition, indicating that higher intelligence is associated with better social cognition. For typically developing children, however, no significant correlation was found. One explanation might be that children with ASD fully use general intelligence for successful learning in social cognition, although extensive use of intelligence might not be necessary for TD children. Alternatively, autistic impairment in social cognition can be compensated by intelligence despite a persistent deficit in social cognition. In either case, when using the SRS as a quantitative phenotype measure for ASD, the influence of intelligence must be considered.

Spontaneous MEG activity of the cerebral cortex during eyes closed and open discriminates Alzheimer's disease from cognitively normal older adults.

This study aimed to examine whether magnetoencephalography (MEG) is useful to detect early stage Alzheimer's disease (AD). We analyzed MEG data from the early stage AD group (n = 20; 6 with mild cognitive impairment due to AD and 14 with AD dementia) and cognitively normal control group (NC, n = 27). MEG was recorded during resting eyes closed (EC) and eyes open (EO), and the following 6 values for each of 5 bands (θ1: 4-6, θ2: 6-8, α1: 8-10, α2: 10-13, ß: 13-20 Hz) in the cerebral 68 regions were compared between the groups: (1) absolute power during EC and (2) EO, (3) whole cerebral normalization (WCN) power during EC and (4) EO, (5) difference of the absolute powers between the EC and EO conditions (the EC-EO difference), and (6) WCN value of the EC-EO difference. We found significant differences between the groups in the WCN powers during the EO condition, and the EC-EO differences. Using a Support Vector Machine classifier, a discrimination accuracy of 83% was obtained and an AUC in an ROC analysis was 0.91. This study demonstrates that MEG during resting EC and EO is useful in discriminating between early stage AD and NC.

Discovery and analysis of a novel type of the serine biosynthetic enzyme phosphoserine phosphatase in Thermus thermophilus.

Studying the diversity of extant metabolisms and enzymes, especially those involved in the biosynthesis of primary metabolites including amino acids, is important to shed light on the evolution of life. Many organisms synthesize serine from phosphoserine via a reaction catalyzed by phosphoserine phosphatase (PSP). Two types of PSP, belonging to distinct protein superfamilies, have been reported. Genomic analyses have revealed that the thermophilic bacterium Thermus thermophilus lacks both homologs while still having the ability to synthesize serine. Here, we purified a protein from T. thermophilus which we biochemically identified as a PSP. A knockout mutant of the responsible gene (TT_C1695) was constructed, which showed serine auxotrophy. These results indicated the involvement of this gene in serine biosynthesis in T. thermophilus. TT_C1695 was originally annotated as a protein with unknown function belonging to the haloacid dehalogenase-like hydrolase (HAD) superfamily. The HAD superfamily, which comprises phosphatases against a variety of substrates, includes also the classical PSP as a member. However, the amino acid sequence of the TT_C1695 was more similar to phosphatases acting on non-phosphoserine substrates than classical PSP; therefore, a BLASTP search and phylogenetic analysis failed to predict TT_C1695 as a PSP. Our results strongly suggest that the T. thermophilus PSP and classical PSP evolved specificity for phosphoserine independently. ENZYMES: Phosphoserine phosphatase (PSP; EC 3.1.3.3); serine hydroxymethyltransferase (EC 2.1.2.1); 3-phosphoglycerate dehydrogenase (EC 1.1.1.95); 3-phosphoserine aminotransferase (EC 2.6.1.52).

Protein engineering for improving the thermostability of tryptophan oxidase and insights from structural analysis.

l-Tryptophan oxidase, VioA from Chromobacterium violaceum, which has a high substrate specificity for tryptophan, is useful for quantitative assay of tryptophan. However, stability of wild type VioA is not enough for its application in clinical or industrial use. To improve the thermal stability of the enzyme, we developed a VioA (C395A) mutant, with higher stability than wild type VioA. The VioA (C395A) exhibited similar specificity and kinetic parameter for tryptophan to wild type. Conventionally, the quantity of tryptophan is determined by instrumental methods, such as high-performance liquid chromatography (HPLC) after pre-column-derivatization. Using the mutant enzyme, we succeeded in the tryptophan quantification in human plasma samples, to an accuracy of <2.9% when compared to the instrumental method, and to a precision of CV <3.2%. To analyse the improvement in storage stability and substrate specificity, we further determined the crystal structures of VioA (C395A) complexed with FAD, and with FAD and tryptophan at 1.8 Å resolution.

Earth Without Life: A Systems Model of a Global Abiotic Nitrogen Cycle.

Nitrogen is the major component of Earth's atmosphere and plays important roles in biochemistry. Biological systems have evolved a variety of mechanisms for fixing and recycling environmental nitrogen sources, which links them tightly with terrestrial nitrogen reservoirs. However, prior to the emergence of biology, all nitrogen cycling was abiological, and this cycling may have set the stage for the origin of life. It is of interest to understand how nitrogen cycling would proceed on terrestrial planets with comparable geodynamic activity to Earth, but on which life does not arise. We constructed a kinetic mass-flux model of nitrogen cycling in its various major chemical forms (e.g., N2, reduced (NHx) and oxidized (NOx) species) between major planetary reservoirs (the atmosphere, oceans, crust, and mantle) and included inputs from space. The total amount of nitrogen species that can be accommodated in each reservoir, and the ways in which fluxes and reservoir sizes may have changed over time in the absence of biology, are explored. Given a partition of volcanism between arc and hotspot types similar to the modern ones, our global nitrogen cycling model predicts a significant increase in oceanic nitrogen content over time, mostly as NHx, while atmospheric N2 content could be lower than today. The transport timescales between reservoirs are fast compared to the evolution of the environment; thus atmospheric composition is tightly linked to surface and interior processes. Key Words: Nitrogen cycle-Abiotic-Planetology-Astrobiology. Astrobiology 18, 897-914.

Nitrate reductases in Hydrogenobacter thermophilus with evolutionarily ancient features: distinctive localization and electron transfer.

Dissimilatory nitrate reductase (NAR) and assimilatory nitrate reductase (NAS) serve as key enzymes for nitrogen catabolism and anabolism in many organisms. We purified NAR and NAS from H. thermophilus, a hydrogen-oxidizing chemolithoautotroph belonging to the phylogenetically deepest branch in the Bacteria domain. Physiological contribution of these enzymes to nitrate respiration and assimilation was clarified by transcriptomic analysis and gene disruption experiments. These enzymes showed several features unreported in bacteria, such as the periplasmic orientation of NAR anchored with a putative transmembrane subunit and the specific electron transfer from a [4Fe-4S]-type ferredoxin to NAS. While some of their enzymatic properties are shared with NARs from archaea and with NASs from phototrophs, phylogenetic analysis indicated that H. thermophilus NAR and NAS have deep evolutionary origins that cannot be explained by a recent horizontal gene transfer event from archaea and phototrophs. These findings revealed the diversity of NAR and NAS in nonphotosynthetic bacteria, and they also implied that the outward orientation of NAR and the ferredoxin-dependent electron transfer of NAS are evolutionarily ancient features preserved in H. thermophilus.

Translation-dependent bioassay for amino acid quantification using auxotrophic microbes as biocatalysts of protein synthesis.

Bioassay for amino acid quantification is an important technology for a variety of fields, which allows for easy, inexpensive, and high-throughput analyses. Here, we describe a novel translation-dependent bioassay for the quantification of amino acids. For this, the gene encoding firefly luciferase was introduced into Lactococcus lactis auxotrophic to Glu, His, Ile, Leu, Pro, Val, and Arg. After a preculture where luciferase expression was repressed, the cells were mixed with analytes, synthetic medium, and an inducer for luciferase expression. Luminescence response to the target amino acid appeared just after mixing, and linear standard curves for these amino acids were obtained during 15-60-min incubation periods. The rapid quantification of amino acids has neither been reported in previous works on bioassays nor is it theoretically feasible with conventional methods, which require incubation times of more than 4 h to allow for the growth of the microbe used. In contrast, our assay was shown to depend on protein translation, rather than on cell growth. Furthermore, replacement of the luciferase gene with that of the green fluorescent protein (GFP) or ß-galactosidase allowed for fluorescent and colorimetric detection of the amino acids, respectively. Significantly, when a Gln-auxotrophic Escherichia coli mutant was created and transformed by a luciferase expression plasmid, a linear standard curve for Gln was observed in 15 min. These results demonstrate that this methodology can provide versatile bioassays by adopting various combinations of marker genes and host strains according to the analytes and experimental circumstances.

An HTRF based high-throughput screening for discovering chemical compounds that inhibit the interaction between Trypanosoma brucei Pex5p and Pex14p.

The glycosome, a peroxisome-related organelle, is essential for the growth and survival of trypanosomatid protozoa. In glycosome biogenesis, Pex5p recognizes newly synthesized glycosomal matrix proteins via peroxisome-targeting signal type-1 (PTS-1) and transports them into glycosomes through an interaction with Pex14p, a component of the matrix protein import machinery on the glycosomal membrane. Knockdown of the PEX5 or PEX14 with RNAi has been shown to inhibit the growth of Trypanosoma brucei. Thus, compounds that inhibit the interaction of TbPex5p-TbPex14p are expected to become lead compounds in the development of anti-trypanosomal drugs. Here, we report a homogenous time-resolved fluorescence (HTRF) assay for the screening of compounds that inhibit the TbPex5p-TbPex14p interaction. The binding of GST-TbPex14p and TbPex5p-His with or without additional compounds was evaluated by measuring the energy transfer of the HTRF pair, using a terbium-labeled anti GST antibody as the donor and an FITC-labeled anti His antibody as the acceptor. The assay was performed in a 384-well plate platform and exhibits a Z'-factor of 0.85-0.91, while the coefficiency of variation is 1.1-7.7%, suggesting it can be readily adapted to a high-throughput format for the automated screening of chemical libraries. We screened 20,800 compounds and found 11 compounds that inhibited energy transfer. Among them, in a pull-down assay one compound exhibited selective inhibition of TbPex5p-TbPex14p without any HsPex5p-HsPex14p interaction.

Rapid enzymatic assays for L-citrulline and L-arginine based on the platform of pyrophosphate detection.

Rapid determination of L-citrulline and L-arginine, physiologically important amino acids, is a beneficial technique from the scientific and medical viewpoints. In this study, enzymatic assays for L-citrulline and L-arginine were established and evaluated. L-Citrulline assay was constructed by coupling argininosuccinate synthetase to a pyrophosphate detection system, in which pyruvate phosphate dikinase was employed, so that the citrulline-dependent production of pyrophosphate could be determined. Furthermore, the L-arginine assay was developed by coupling arginine deiminase to the L-citrulline assay. Both assays exhibited high selectivity to L-citrulline and L-arginine without any significant reactivity to other proteinaceous amino acids. These assays were also resistant to various contaminants that interfered with the conventional L-citrulline and L-arginine assays. The high accuracy of these assays was demonstrated by measurements in the presence of human plasma. Because these assays can be conducted under the neutral pH without terminating the reaction progress, they allow not only measurements in static analyte solutions, but also real-time monitoring of L-citrulline and L-arginine synthesis in the reaction mixture. The features of these assays also demonstrated that the pyrophosphate detection system served as a useful platform to develop selective and robust enzymatic assays by being coupled to a pyrophosphate-producing enzyme.