Comparative single-cell genomics of Atribacterota JS1 in the Japan Trench hadal sedimentary biosphere.

Deep-sea and subseafloor sedimentary environments host heterotrophic microbial communities that contribute to Earth's carbon cycling. However, the potential metabolic functions of individual microorganisms and their biogeographical distributions in hadal ocean sediments remain largely unexplored. In this study, we conducted single-cell genome sequencing on sediment samples collected from six sites (7,445-8,023 m water depth) along an approximately 500 km transect of the Japan Trench during the International Ocean Discovery Program Expedition 386. A total of 1,886 single-cell amplified genomes (SAGs) were obtained, offering comprehensive genetic insights into sedimentary microbial communities in surface sediments (<1 m depth) above the sulfate-methane transition zone along the Japan Trench. Our genome data set included 269 SAGs from Atribacterota JS1, the predominant bacterial clade in these hadal environments. Phylogenetic analysis classified SAGs into nine distinct phylotypes, whereas metagenome-assembled genomes were categorized into only two phylotypes, advancing JS1 diversity coverage through a single cell-based approach. Comparative genomic analysis of JS1 lineages from different habitats revealed frequent detection of genes related to organic carbon utilization, such as extracellular enzymes like clostripain and α-amylase, and ABC transporters of oligopeptide from Japan Trench members. Furthermore, specific JS1 phylotypes exhibited a strong correlation with in situ methane concentrations and contained genes involved in glycine betaine metabolism. These findings suggest that the phylogenomically diverse and novel Atribacterota JS1 is widely distributed in Japan Trench sediment, playing crucial roles in carbon cycling within the hadal sedimentary biosphere.IMPORTANCEThe Japan Trench represents tectonically active hadal environments associated with Pacific plate subduction beneath the northeastern Japan arc. This study, for the first time, documented a large-scale single-cell and metagenomic survey along an approximately 500 km transect of the Japan Trench, obtaining high-quality genomic information on hadal sedimentary microbial communities. Single-cell genomics revealed the predominance of diverse JS1 lineages not recoverable through conventional metagenomic binning. Their metabolic potential includes genes related to the degradation of organic matter, which contributes to methanogenesis in the deeper layers. Our findings enhance understanding of sedimentary microbial communities at water depths exceeding 7,000 m and provide new insights into the ecological role of biogeochemical carbon cycling in the hadal sedimentary biosphere.

Glutamate-Sensing Genes Are Conserved among Populations Compared to Glutamate Metabolism Genes.

INTRODUCTION: Glutamate is a representative taste molecule with an umami flavor and is a major nutrient found abundantly in nature. Furthermore, it plays a significant role in the human body as a key metabolic intermediate and neurotransmitter. Therefore, the divergence of glutamate functions among populations during their evolution is of particular interest with a hypothesis that the genetic variation can lead to understanding divergence in taste perception. To elucidate variation in glutamate applications and to deepen our understanding of taste perception, we examined the nucleotide diversity of genes associated with glutamate sensing and metabolism among human populations. METHODS: We first established 67 genes related to glutamate sensing and metabolism based on the database and literature survey. Then, for those genes, we used a population genomics approach based on ten populations over 76,156 human genomes in the gnomAD database. RESULTS: Statistical tests of means and medians of the minor allele frequencies did not show any significant difference among populations. However, we observed substantial differences between two functional groups, glutamate sensing and glutamate metabolism, in populations of Latino/admixed American, Ashkenazi Jewish, and Others. Interestingly, we could find significant differences between the African population and the East Asian population at the single nucleotide polymorphism level of glutamate metabolism genes, but no clear differences were noted in glutamate-sensing genes. These suggest that glutamate-sensing genes are under the functional constraint compared to glutamate metabolism genes. CONCLUSION: Thus, glutamate-sensing genes and metabolism genes have a contrasting mode of the evolution, and glutamate-sensing genes are conservatively evolved, indicating its functional importance.

Current trends in RNA virus detection through metatranscriptome sequencing data.

With advances in sequencing technology, metatranscriptome sequencing from a variety of environmental and biological sources has revealed the existence of various previously unknown RNA viruses. This review presents recent major RNA virome studies sampled from invertebrate and vertebrate species as well as aquatic environments. In particular, we focus on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and related RNA virus identification through metatranscriptome sequencing analyses. Recently developed bioinformatics software and databases for RNA virus identification are introduced. A relationship between newly identified RNA viruses and endogenous viral elements in host genomes is also discussed.

Computational network analysis of host genetic risk variants of severe COVID-19.

BACKGROUND: Genome-wide association studies have identified numerous human host genetic risk variants that play a substantial role in the host immune response to SARS-CoV-2. Although these genetic risk variants significantly increase the severity of COVID-19, their influence on body systems is poorly understood. Therefore, we aim to interpret the biological mechanisms and pathways associated with the genetic risk factors and immune responses in severe COVID-19. We perform a deep analysis of previously identified risk variants and infer the hidden interactions between their molecular networks through disease mapping and the similarity of the molecular functions between constructed networks. RESULTS: We designed a four-stage computational workflow for systematic genetic analysis of the risk variants. We integrated the molecular profiles of the risk factors with associated diseases, then constructed protein-protein interaction networks. We identified 24 protein-protein interaction networks with 939 interactions derived from 109 filtered risk variants in 60 risk genes and 56 proteins. The majority of molecular functions, interactions and pathways are involved in immune responses; several interactions and pathways are related to the metabolic and cardiovascular systems, which could lead to multi-organ complications and dysfunction. CONCLUSIONS: This study highlights the importance of analyzing molecular interactions and pathways to understand the heterogeneous susceptibility of the host immune response to SARS-CoV-2. We propose new insights into pathogenicity analysis of infections by including genetic risk information as essential factors to predict future complications during and after infection. This approach may assist more precise clinical decisions and accurate treatment plans to reduce COVID-19 complications.

Lactate-mediated neural plasticity genes emerged during the evolution of memory systems.

The ability to record experiences and learning is present to different degrees in several species; however, the complexity and diversity of memory processes are cognitive function features that differentiate humans from other species. Lactate has recently been discovered to act as a signaling molecule for neuronal plasticity linked to long-term memory. Because lactate is not only an energy substrate for neurons but also a signaling molecule for plasticity (Magistretti and Allaman in Nat Rev Neurosci 19:235-249, 2018. https://doi.org/10.1038/nrn.2018.19 ), it is of particular interest to understand how and when memory-related genes and lactate-mediated neural plasticity (LMNP) genes emerged and evolved in humans. To understand the evolutionary origin and processes of memory and LMNP genes, we first collected information on genes related to memory and LMNP from the literature and then conducted a comparative analysis of these genes. We found that the memory and LMNP genes have different origins, suggesting that these genes may have become established gradually in evolutionarily and functional terms and not at the same time. We also found that memory and LMNP systems have a similar evolutionary history, having been formed with the gradual participation of newly emerging genes throughout their evolution. We propose that the function of LMNP as a signaling process may be evolutionarily associated with memory systems through an unidentified system that is linked by 13 common genes between memory and LMNP gene sets. This study provides evolutionary insight into the possible relationship between memory and the LMNP systems that deepens our understanding of the evolution of memory systems.

Comprehensive evolutionary analysis and nomenclature of plant G3BPs.

Stress induces extensive reprogramming of mRNA metabolism, which includes the transcription and translation of stress-related genes and the formation of stress granules. RasGAP SH3 domain-binding proteins (G3BPs, also called Rasputins) form a highly conserved family of proteins found throughout eukaryotic evolution, which coordinate signal transduction and posttranscriptional gene regulation and play a key role in the formation of stress granules. G3BPs play a role in osmotic, oxidative, and biotic stress in mammals, and recent results revealed that they play similar functions in higher plants. Although simple eukaryotes such as yeast have only one G3BP gene, higher plants show a massive expansion of their G3BP genes into distinct subfamilies. However, because this family of genes has not been well-characterized in plants, functions that have evolved during this expansion remain unidentified. Therefore, we carried out a phylogenetic analysis of G3BPs in different eukaryotes, particularly focusing on the green lineage. On the basis of this evolutionary analysis of G3BPs in eukaryotes, we propose a uniform nomenclature for plant G3BPs that should help predict the evolutionary and functional diversification in this family.

Identification of lipolytic enzymes using high-throughput single-cell screening and sorting of a metagenomic library.

The demand for novel, robust microbial biocatalysts for use in industrial and pharmaceutical applications continues to increase rapidly. As a result, there is a need to develop advanced tools and technologies to exploit the vast metabolic potential of unculturable microorganisms found in various environments. Single-cell and functional metagenomics studies can explore the enzymatic potential of entire microbial communities in a given environment without the need to culture the microorganisms. This approach has contributed substantially to the discovery of unique microbial genes for industrial and medical applications. Functional metagenomics involves the extraction of microbial DNA directly from environmental samples, constructing expression libraries comprising the entire microbial genome, and screening of the libraries for the presence of desired phenotypes. In this study, lipolytic enzymes from the Red Sea were targeted. A high-throughput single-cell microfluidic platform combined with a laser-based fluorescent screening bioassay was employed to discover new genes encoding lipolytic enzymes. Analysis of the metagenomic library led to the identification of three microbial genes encoding lipases based on their functional similarity and sequence homology to known lipases. The results demonstrated that microfluidics is a robust technology that can be used for screening in functional metagenomics. The results also indicate that the Red Sea is a promising, under-investigated source of new genes and gene products.

A cautionary signal from the Red Sea on the impact of increased dust activity on marine microbiota.

BACKGROUND: Global climate change together with growing desertification is leading to increased dust emissions to the atmosphere, drawing attention to possible impacts on marine ecosystems receiving dust deposition. Since microorganisms play important roles in maintaining marine homeostasis through nutrient cycling and carbon flow, detrimental changes in the composition of marine microbiota in response to increased dust input could negatively impact marine health, particularly so in seas located within the Global Dust Belt. Due to its strategic location between two deserts and unique characteristics, the Red Sea provides an attractive semi-enclosed "megacosm" to examine the impacts of large dust deposition on the vastly diverse microbiota in its exceptionally warm oligotrophic waters. RESULTS: We used culture-independent metagenomic approaches to assess temporal changes in the Red Sea microbiota in response to two severe sandstorms, one originated in the Nubian Desert in the summer 2016 and a second one originated in the Libyan Desert in the spring 2017. Despite differences in sandstorm origin and meteorological conditions, both sandstorms shifted bacterial and Archaeal groups in a similar mode. In particular, the relative abundance of autotrophic bacteria declined while those of heterotrophic bacteria, particularly Bacteroidetes, and Archaea increased. The changes peaked within six days from the start of sandstorms, and the community recovered the original assemblage within one month. CONCLUSION: Our results suggest that increased dust emission with expanding desertification could lead to undesirable impacts in ocean function, enhancing heterotrophic processes while reducing autotrophic ones, thereby affecting the marine food web in seas receiving dust deposition.

Validation of the application of gel beads-based single-cell genome sequencing platform to soil and seawater.

Single-cell genomics is applied to environmental samples as a method to solve the problems of current metagenomics. However, in the fluorescence-activated cell sorting-based cell isolation and subsequent whole genome amplification, the sorting efficiency and the sequence quality are greatly affected by the type of target environment, limiting its adaptability. Here, we developed an improved single-cell genomics platform, named SAG-gel, which utilizes gel beads for single-cell isolation, lysis, and whole genome amplification. To validate the versatility of SAG-gel, single-cell genome sequencing was performed with model bacteria and microbial samples collected from eight environmental sites, including soil and seawater. Gel beads enabled multiple lysis treatments. The genome coverage with model bacteria was improved by 9.1-25%. A total of 734 single amplified genomes were collected from the diverse environmental samples, and almost full-length 16S rRNA genes were recovered from 57.8% of them. We also revealed two marine Rhodobacter strains harboring nearly identical 16S rRNA genes but having different genome contents. In addition, searching for viral sequences elucidated the virus-host linkage over the sampling sites, revealing the geographic distribution and diverse host range of viruses.

DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning.

MOTIVATION: Structural genomic variants account for much of human variability and are involved in several diseases. Structural variants are complex and may affect coding regions of multiple genes, or affect the functions of genomic regions in different ways from single nucleotide variants. Interpreting the phenotypic consequences of structural variants relies on information about gene functions, haploinsufficiency or triplosensitivity and other genomic features. Phenotype-based methods to identifying variants that are involved in genetic diseases combine molecular features with prior knowledge about the phenotypic consequences of altering gene functions. While phenotype-based methods have been applied successfully to single nucleotide variants as well as short insertions and deletions, the complexity of structural variants makes it more challenging to link them to phenotypes. Furthermore, structural variants can affect a large number of coding regions, and phenotype information may not be available for all of them. RESULTS: We developed DeepSVP, a computational method to prioritize structural variants involved in genetic diseases by combining genomic and gene functions information. We incorporate phenotypes linked to genes, functions of gene products, gene expression in individual cell types and anatomical sites of expression, and systematically relate them to their phenotypic consequences through ontologies and machine learning. DeepSVP significantly improves the success rate of finding causative variants in several benchmarks and can identify novel pathogenic structural variants in consanguineous families. AVAILABILITY AND IMPLEMENTATION: https://github.com/bio-ontology-research-group/DeepSVP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Seawater desalination based drinking water: Microbial characterization during distribution with and without residual chlorine.

Monitoring the changes that occur to water during distribution is vital to ensure water safety. In this study, the biological stability of reverse osmosis (RO) produced drinking water, characterized by low cell concentration and low assimilable organic carbon, in combination with chlorine disinfection was investigated. Water quality at several locations throughout the existing distribution network was monitored to investigate whether microbial water quality changes can be identified. Results revealed that the water leaving the plant had an average bacterial cell concentration of 103 cells/mL. A 0.5-1.5 log increase in bacterial cell concentration was observed at locations in the network. The residual disinfectant was largely dissipated in the network from 0.5 mg/L at the treatment plant to less than 0.1 mg/L in the network locations. The simulative study involving miniature distribution networks, mimicking the dynamics of a distribution network, fed with the RO produced chlorinated and non-chlorinated drinking water revealed that distributing RO produced water without residual disinfection, especially at high water temperatures (25-30 °C), poses a higher chance for water quality change. Within six months of operation of the miniature network fed with unchlorinated RO produced water, the adenosine triphosphate (ATP) and total cell concentration (TCC) in the pipe biofilm were 4 × 102 pg ATP/cm2 and 1 × 107 cells/ cm2. The low bacterial cell concentration and organic carbon concentration in the RO-produced water did not prevent biofilm development inside the network with and without residual chlorine. The bacterial community analysis using 16S ribosomal RNA (rRNA) gene sequencing revealed that mesophilic bacteria with higher temperature tolerance and bacteria associated with oligotrophic, nutrient-poor conditions dominated the biofilm, with no indication of the existence of opportunistic pathogenic species. However, chlorination selected against most bacterial groups and the bacterial community that remained was mainly the bacteria capable of surviving disinfection regimes. Biofilms that developed in the presence of chlorine contained species classified as opportunistic pathogens. These biofilms have an impact on shaping the water quality received at the consumer tap. The presence of these bacteria on its own is not a health risk indicator; viability assessment and qPCRs targeting genes specific to the opportunistic pathogens as well as quantitative microbiological risk assessment (QMRA) should be included to assess the risk. The results from this study highlight the importance of implementing multiple barriers to ensure water safety. Changes in water quality detected even when high-quality disinfected RO-produced water is distributed highlight microbiological challenges that chlorinated systems endure, especially at high water temperatures.

Integration of Droplet Microfluidic Tools for Single-Cell Functional Metagenomics: An Engineering Head Start.

Droplet microfluidic techniques have shown promising outcome to study single cells at high throughput. However, their adoption in laboratories studying "-omics" sciences is still irrelevant due to the complex and multidisciplinary nature of the field. To facilitate their use, here we provide engineering details and organized protocols for integrating three droplet-based microfluidic technologies into the metagenomic pipeline to enable functional screening of bioproducts at high throughput. First, a device encapsulating single cells in droplets at a rate of ∼250 Hz is described considering droplet size and cell growth. Then, we expand on previously reported fluorescence-activated droplet sorting systems to integrate the use of 4 independent fluorescence-exciting lasers (i.e., 405, 488, 561, and 637 nm) in a single platform to make it compatible with different fluorescence-emitting biosensors. For this sorter, both hardware and software are provided and optimized for effortlessly sorting droplets at 60 Hz. Then, a passive droplet merger is also integrated into our pipeline to enable adding new reagents to already-made droplets at a rate of 200 Hz. Finally, we provide an optimized recipe for manufacturing these chips using silicon dry-etching tools. Because of the overall integration and the technical details presented here, our approach allows biologists to quickly use microfluidic technologies and achieve both single-cell resolution and high-throughput capability (>50,000 cells/day) for mining and bioprospecting metagenomic data.

Comparative Analysis of Mitochondrial Genomes in Gryllidea (Insecta: Orthoptera): Implications for Adaptive Evolution in Ant-Loving Crickets.

Species of infraorder Gryllidea, or crickets, are useful invertebrate models for studying developmental biology and neuroscience. They have also attracted attention as alternative protein sources for human food and animal feed. Mitochondrial genomic information on related invertebrates, such as katydids, and locusts, has recently become available in attempt to clarify the controversial classification schemes, although robust phylogenetic relationships with emphasis on crickets remain elusive. Here, we report newly sequenced complete mitochondrial genomes of crickets to study their phylogeny, genomic rearrangements, and adaptive evolution. First, we conducted de novo assembly of mitochondrial genomes from eight cricket species and annotated protein-coding genes and transfer and ribosomal RNAs using automatic annotations and manual curation. Next, by combining newly described protein-coding genes with public data of the complete Gryllidea genomes and gene annotations, we performed phylogenetic analysis and found gene order rearrangements in several branches. We further analyzed genetic signatures of selection in ant-loving crickets (Myrmecophilidae), which are small wingless crickets that inhabit ant nests. Three distinct approaches revealed two positively selected sites in the cox1 gene in these crickets. Protein 3D structural analyses suggested that these selected sites could influence the interaction of respiratory complex proteins, conferring benefits to ant-loving crickets with a unique ecological niche and morphology. These findings enhance our understanding of the genetic basis of cricket evolution without relying on estimates based on a limited number of molecular markers.

Genome sequencing and identification of cellulase genes in Bacillus paralicheniformis strains from the Red Sea.

BACKGROUND: Cellulolytic microorganisms are considered a key player in the degradation of plant biomass in various environments. These microorganisms can be isolated from various environments, such as soils, the insect gut, the mammalian rumen and oceans. The Red Sea exhibits a unique environment in terms of presenting a high seawater temperature, high salinity, low nutrient levels and high biodiversity. However, there is little information regarding cellulase genes in the Red Sea environment. This study aimed to examine whether the Red Sea can be a resource for the bioprospecting of microbial cellulases by isolating cellulase-producing microorganisms from the Red Sea environment and characterizing cellulase genes. RESULTS: Three bacterial strains were successfully isolated from the plankton fraction and the surface of seagrass. The isolated strains were identified as Bacillus paralicheniformis and showed strong cellulase activity. These results suggested that these three isolates secreted active cellulases. By whole genome sequencing, we found 10 cellulase genes from the three isolates. We compared the expression of these cellulase genes under cellulase-inducing and non-inducing conditions and found that most of the cellulase genes were generally upregulated during cellulolysis in the isolates. Our operon structure analysis also showed that cellulase genes form operons with genes involved in various kinds of cellular reactions, such as protein metabolism, which suggests the existence of crosstalk between cellulolysis and other metabolic pathways in the bacterial isolates. These results suggest that multiple cellulases are playing important roles in cellulolysis. CONCLUSIONS: Our study reports the isolation and characterization of cellulase-producing bacteria from the Red Sea. Our whole-genome sequencing classified our three isolates as Bacillus paralicheniformis, and we revealed the presence of ten cellulase orthologues in each of three isolates' genomes. Our comparative expression analysis also identified that most of the cellulase genes were upregulated under the inducing conditions in general. Although cellulases have been roughly classified into three enzyme groups of beta-glucosidase, endo-ß-1,4-glucanase and exoglucanase, these findings suggest the importance to consider microbial cellulolysis as a more complex reaction with various kinds of cellulase enzymes.

Seasonal and annual changes in the microbial communities of Ofunato Bay, Japan, based on metagenomics.

Five years of datasets from 2015 to 2019 of whole genome shotgun sequencing for cells trapped on 0.2-µm filters of seawater collected monthly from Ofunato Bay, an enclosed bay in Japan, were analysed, which included the 2015 data that we had reported previously. Nucleotide sequences were determined for extracted DNA from three locations for both the upper (1 m) and deeper (8 or 10 m) depths. The biotic communities analysed at the domain level comprised bacteria, eukaryotes, archaea and viruses. The relative abundance of bacteria was over 60% in most months for the five years. The relative abundance of the SAR86 cluster was highest in the bacterial group, followed by Candidatus Pelagibacter and Planktomarina. The relative abundance of Ca. Pelagibacter showed no relationship with environmental factors, and those of SAR86 and Planktomarina showed positive correlations with salinity and dissolved oxygen, respectively. The bacterial community diversity showed seasonal changes, with high diversity around September and low diversity around January for all five years. Nonmetric multidimensional scaling analysis also revealed that the bacterial communities in the bay were grouped in a season-dependent manner and linked with environmental variables such as seawater temperature, salinity and dissolved oxygen.

Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan.

Although numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data ( http://marine-meta.healthscience.sci.waseda.ac.jp/omd/ ), which provides a three-dimensional bird's-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

Evolution of memory system-related genes.

Memory has an essential function in human life as it helps individuals remember and recognize their surroundings. It is also the major form of cognition that controls behavior. As memory is a function that is highly characteristic of humans, how it was established is of particular interest. Recent progress in the field of neurosciences, together with the technological advancement of genome-wide approaches, has led to the accumulation of evidence regarding the presence and similar/distinct mechanisms of memory among species. However, the understanding of the evolution of memory obtained utilizing these genome-wide approaches remains unclear. The purpose of this review was to provide an overview of the literature on the evolution of the memory system among species and the genes involved in this process. This review also discusses possible approaches to study the evolution of memory systems to guide future research.

A single neuron subset governs a single coactive neuron circuit in Hydra vulgaris, representing a possible ancestral feature of neural evolution.

The last common ancestor of Bilateria and Cnidaria is believed to be one of the first animals to develop a nervous system over 500 million years ago. Many of the genes involved in the neural function of the advanced nervous system in Bilateria are well conserved in Cnidaria. Thus, the cnidarian Hydra vulgaris is a good model organism for the study of the putative primitive nervous system in its last common ancestor. The diffuse nervous system of Hydra consists of several peptidergic neuron subsets. However, the specific functions of these subsets remain unclear. Using calcium imaging, here we show that the neuron subsets that express neuropeptide, Hym-176, function as motor circuits to evoke longitudinal contraction. We found that all neurons in a subset defined by the Hym-176 gene (Hym-176A) or its paralogs (Hym-176B) expression are excited simultaneously, followed by longitudinal contraction. This indicates not only that these neuron subsets have a motor function but also that a single molecularly defined neuron subset forms a single coactive circuit. This is in contrast with the bilaterian nervous system, where a single molecularly defined neuron subset harbors multiple coactive circuits, showing a mixture of neurons firing with different timings. Furthermore, we found that the two motor circuits, one expressing Hym-176B in the body column and the other expressing Hym-176A in the foot, are coordinately regulated to exert region-specific contraction. Our results demonstrate that one neuron subset is likely to form a monofunctional circuit as a minimum functional unit to build a more complex behavior in Hydra. This simple feature (one subset, one circuit, one function) found in Hydra may represent the simple ancestral condition of neural evolution.

Significant variants of type 2 diabetes in the Arabian Region through an Integration of exome databases.

Type 2 diabetes (T2D) is a major global health issue, and it has also become one of the major diseases in Arab countries. In addition to the exome databases that have already been established, whole exome sequencing data for the Greater Middle East are now available. To elucidate the genetic features of T2D in the Arabian Peninsula, we integrated two exome databases (gnomAD exome and the Greater Middle East Variome Project) with clinical information from the ClinVar. After the integration, we obtained 18 single nucleotide polymorphisms and found two statistically and clinically significant variants in two genes, SLC30A8 rs13266634 and KCNJ11 rs5219. Interestingly, the two genes are linked to the uptake of the metals, Zn and K respectively, which indicating the regional features of the genetic variants. The frequency of the risk allele of rs13266634 among individuals in the Arabian Peninsula was higher than among individuals in other regions. On the other hand, the frequency of the risk allele of rs5219 in the Arabian Peninsula was lower than that in other regions. We identified and characterized T2D-related variants that show unique tendencies in the Arabian Peninsula. Our analyses contribute to and provide guidance for the clinical research of T2D in the Arabian Peninsula.

Characterization of microbiologically influenced corrosion by comprehensive metagenomic analysis of an inland oil field.

Corrosion in pipelines and reservoir tanks in oil plants is a serious problem in the global energy industry because it causes substantial economic losses associated with frequent part replacement and can lead to potential damage to entire crude oil fields. Previous studies revealed that corrosion is mainly caused by microbial activities in a process currently termed microbiologically influenced corrosion or biocorrosion. Identifying the bacteria responsible for biocorrosion is crucial for its suppression. In this study, we analyzed the microbial communities present at corrosion sites in oil plant pipelines using comparative metagenomic analysis along with bioinformatics and statistics. We analyzed the microbial communities in pipelines in an oil field in which groundwater is used as injection water. We collected samples from four different facilities in the oil field. Metagenomic analysis revealed that the microbial community structures greatly differed even among samples from the same facility. Treatments such as biocide administration and demineralization at each location in the pipeline may have independently affected the microbial community structure. The results indicated that microbial inspection throughout the pipeline network is essential to prevent biocorrosion at industrial plants. By identifying the bacterial species responsible for biocorrosion, this study provides bacterial indicators to detect and classify biocorrosion. Furthermore, these species may serve as biomarkers to detect biocorrosion at an early stage. Then, appropriate management such as treatment with suitable biocides can be performed immediately and appropriately. Thus, our study will serve as a platform for obtaining microbial information related to biocorrosion to enable the development of a practical approach to prevent its occurrence.