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.

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.

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.

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.

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.

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.

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.

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-β-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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02316-w.

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.

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.

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

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.

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.

Population structure of indigenous inhabitants of Arabia

Modern day Saudi Arabia occupies the majority of historical Arabia, which may have contributed to ancient waves of migration out of Africa. This ancient history has left a lasting imprint in the genetics of the region, including the diverse set of tribes that call Saudi Arabia their home. How these tribes relate to each other and to the world's major populations remains an unanswered question. In an attempt to improve our understanding of the population structure of Saudi Arabia, we conducted genomic profiling of 957 unrelated individuals who self-identify with 28 large tribes in Saudi Arabia. Consistent with the tradition of intra-tribal unions, the subjects showed strong clustering along tribal lines with the distance between clusters correlating with their geographical proximities in Arabia. However, these individuals form a unique cluster when compared to the world's major populations. The ancient origin of these tribal affiliations is supported by analyses that revealed little evidence of ancestral origin from within the 28 tribes. Our results disclose a granular map of population structure and have important implications for future genetic studies into Mendelian and common diseases in the region.

What is the right sequencing approach? Solo VS extended family analysis in consanguineous populations

Background

Testing strategies is crucial for genetics clinics and testing laboratories. In this study, we tried to compare the hit rate between solo and trio and trio plus testing and between trio and sibship testing. Finally, we studied the impact of extended family analysis, mainly in complex and unsolved cases.

Methods

Three cohorts were used for this analysis: one cohort to assess the hit rate between solo, trio and trio plus testing, another cohort to examine the impact of the testing strategy of sibship genome vs trio-based analysis, and a third cohort to test the impact of an extended family analysis of up to eight family members to lower the number of candidate variants.

Results

The hit rates in solo, trio and trio plus testing were 39, 40, and 41%, respectively. The total number of candidate variants in the sibship testing strategy was 117 variants compared to 59 variants in the trio-based analysis. We noticed that the average number of coding candidate variants in trio-based analysis was 1192 variants and 26,454 noncoding variants, and this number was lowered by 50–75% after adding additional family members, with up to two coding and 66 noncoding homozygous variants only, in families with eight family members.

Conclusion

There was no difference in the hit rate between solo and extended family members. Trio-based analysis was a better approach than sibship testing, even in a consanguineous population. Finally, each additional family member helped to narrow down the number of variants by 50–75%. Our findings could help clinicians, researchers and testing laboratories select the most cost-effective and appropriate sequencing approach for their patients. Furthermore, using extended family analysis is a very useful tool for complex cases with novel genes.

Ontology-based prediction of cancer driver genes

Identifying and distinguishing cancer driver genes among thousands of candidate mutations remains a major challenge. Accurate identification of driver genes and driver mutations is critical for advancing cancer research and personalizing treatment based on accurate stratification of patients. Due to inter-tumor genetic heterogeneity many driver mutations within a gene occur at low frequencies, which make it challenging to distinguish them from non-driver mutations. We have developed a novel method for identifying cancer driver genes. Our approach utilizes multiple complementary types of information, specifically cellular phenotypes, cellular locations, functions, and whole body physiological phenotypes as features. We demonstrate that our method can accurately identify known cancer driver genes and distinguish between their role in different types of cancer. In addition to confirming known driver genes, we identify several novel candidate driver genes. We demonstrate the utility of our method by validating its predictions in nasopharyngeal cancer and colorectal cancer using whole exome and whole genome sequencing.

Comparative genome and transcriptome analysis of diatom, Skeletonema costatum, reveals evolution of genes for harmful algal bloom

Background

Diatoms play a great role in carbon fixation with about 20% of the whole fixation in the world. However, harmful algal bloom as known as red tide is a major problem in environment and fishery industry. Even though intensive studies have been conducted so far, the molecular mechanism behind harmful algal bloom was not fully understood. There are two major diatoms have been sequenced, but more diatoms should be examined at the whole genome level, and evolutionary genome studies were required to understand the landscape of molecular mechanism of the harmful algal bloom.

Results

Here we sequenced the genome of Skeletonema costatum, which is the dominant diatom in Japan causing a harmful algal bloom, and also performed RNA-sequencing analysis for conditions where harmful algal blooms often occur. As results, we found that both evolutionary genomic and comparative transcriptomic studies revealed genes for oxidative stress response and response to cytokinin is a key for the proliferation of the diatom.

Conclusions

Diatoms causing harmful algal blooms have gained multi-copy of genes related to oxidative stress response and response to cytokinin and obtained an ability to intensive gene expression at the blooms.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5144-5) contains supplementary material, which is available to authorized users.

Finding Nemo's Genes: A chromosome-scale reference assembly of the genome of the orange clownfish Amphiprion percula

The iconic orange clownfish, Amphiprion percula, is a model organism for studying the ecology and evolution of reef fishes, including patterns of population connectivity, sex change, social organization, habitat selection and adaptation to climate change. Notably, the orange clownfish is the only reef fish for which a complete larval dispersal kernel has been established and was the first fish species for which it was demonstrated that antipredator responses of reef fishes could be impaired by ocean acidification. Despite its importance, molecular resources for this species remain scarce and until now it lacked a reference genome assembly. Here, we present a de novo chromosome-scale assembly of the genome of the orange clownfish Amphiprion percula. We utilized single-molecule real-time sequencing technology from Pacific Biosciences to produce an initial polished assembly comprised of 1,414 contigs, with a contig N50 length of 1.86 Mb. Using Hi-C-based chromatin contact maps, 98% of the genome assembly were placed into 24 chromosomes, resulting in a final assembly of 908.8 Mb in length with contig and scaffold N50s of 3.12 and 38.4 Mb, respectively. This makes it one of the most contiguous and complete fish genome assemblies currently available. The genome was annotated with 26,597 protein-coding genes and contains 96% of the core set of conserved actinopterygian orthologs. The availability of this reference genome assembly as a community resource will further strengthen the role of the orange clownfish as a model species for research on the ecology and evolution of reef fishes.

Global Ramifications of Dust and Sandstorm Microbiota

Dust and sandstorm events inject substantial quantities of foreign microorganisms into global ecosystems, with the ability to impact distant environments. The majority of these microorganisms originate from deserts and drylands where the soil is laden with highly stress-resistant microbes capable of thriving under extreme environmental conditions, and a substantial portion of them survive long journeys through the atmosphere. This large-scale transmission of highly resilient alien microbial contaminants raises concerns with regards to the invasion of sensitive and/or pristine sink environments, and to human health-concerns exacerbated by increases in the rate of desertification. Further increases in the transport of dust-associated microbiota could extend the spread of foreign microbes to new ecosystems, increase their load in present sink environments, disrupt ecosystem balance, and potentially introduce new pathogens. Our present understanding of these microorganisms, their phylogenic affiliations and functional significance, is insufficient to determine their impact. The purpose of this review is to provide an overview of available data regarding dust and sandstorm microbiota and their potential ramifications on human and ecosystem health. We conclude by discussing current gaps in dust and sandstorm microbiota research, and the need for collaborative studies involving high-resolution meta-omic approaches in conjunction with extensive ecological time-series studies to advance the field towards an improved and sufficient understanding of these invisible atmospheric travelers and their global ramifications.

Basin-scale seasonal changes in marine free-living bacterioplankton community in the Ofunato Bay

The Ofunato Bay in the northeastern Pacific Ocean area of Japan possesses the highest biodiversity of marine organisms in the world and has attracted much attention due to its economic and environmental importance. We report here a shotgun metagenomic analysis of the year-round variation in free-living bacterioplankton collected across the entire length of the bay. Phylogenetic differences among spring, summer, autumn and winter bacterioplankton suggested that members of Proteobacteria tended to decrease at high water temperatures and increase at low temperatures. It was revealed that Candidatus Pelagibacter varied seasonally, reaching as much as 60% of all sequences at the genus level in the surface waters during winter. This increase was more evident in the deeper waters, where they reached up to 75%. The relative abundance of Planktomarina also rose during winter and fell during summer. A significant component of the winter bacterioplankton community was Archaea (mainly represented by Nitrosopumilus), as their relative abundance was very low during spring and summer but high during winter. In contrast, Actinobacteria and Cyanobacteria appeared to be higher in abundance during high-temperature periods. It was also revealed that Bacteroidetes constituted a significant component of the summer bacterioplankton community, being the second largest bacterial phylum detected in the Ofunato Bay. Its members, notably Polaribacter and Flavobacterium, were found to be high in abundance during spring and summer, particularly in the surface waters. Principal component analysis and hierarchal clustering analyses showed that the bacterial communities in the Ofunato Bay changed seasonally, likely caused by the levels of organic matter, which would be deeply mixed with surface runoff in the winter.

Metagenome-based diversity analyses suggest a strong locality signal for bacterial communities associated with oyster aquaculture farms in Ofunato Bay

Ofunato Bay, in Japan, is the home of buoy-and-rope-type oyster aquaculture activities. Since the oysters filter suspended materials and excrete organic matters into the seawater, bacterial communities residing in its vicinity may show dynamic changes depending on the oyster culture activities. We employed a shotgun metagenomic technique to study bacterial communities near oyster aquaculture facilities at the center of the bay (KSt. 2) and compared the results with those of two other localities far from the station, one to the northeast (innermost bay, KSt. 1) and the other to the southwest (bay entrance, KSt. 3). Seawater samples were collected every month from January to December 2015 from the surface (1 m) and deeper (8 or 10 m) layers of the three locations, and the sequentially filtered fraction on 0.2-μm membranes was sequenced on an Illumina MiSeq system. The acquired reads were uploaded to MG-RAST for KEGG functional abundance analysis, while taxonomic analyses at the phylum and genus levels were performed using MEGAN after parsing the BLAST output. Discrimination analyses were then performed using the ROC-AUC value of the cross validation, targeting the depth (shallow or deep), locality [(KSt. 1 + KSt. 2) vs. KSt 3; (KSt. 1 + KSt. 3) vs. KSt. 2 or the (KSt. 2 + KSt. 3) vs. KSt. 1] and seasonality (12 months). The matrix discrimination analysis on the adjacent 2 continuous seasons by ROC-AUC, which was based on the datasets that originated from different depths, localities and months, showed the strongest discrimination signal on the taxonomy matrix at the phylum level for the datasets from July to August compared with those from September to June, while the KEGG matrix showed the strongest signal for the datasets from March to June compared with those from July to February. Then, the locality combination was subjected to the same ROC-AUC discrimination analysis, resulting in significant differences between KSt. 2 and KSt. 1 + KSt. 3 on the KEGG matrix. These results suggest that aquaculture activities markedly affect bacterial functions.

Seasonal changes in the abundance of bacterial genes related to dimethylsulfoniopropionate catabolism in seawater from Ofunato Bay revealed by metagenomic analysis

Ofunato Bay is located in the northeastern Pacific Ocean area of Japan, and it has the highest biodiversity of marine organisms in the world, primarily due to tidal influences from the cold Oyashio and warm Kuroshio Currents. Our previous results from performing shotgun metagenomics indicated that Candidatus Pelagibacter ubique and Planktomarina temperata were the dominant bacteria (Reza et al., 2018a, 2018b). These bacteria are reportedly able to catabolize dimethylsulfoniopropionate (DMSP) produced from phytoplankton into dimethyl sulfide (DMS) or methanethiol (MeSH). This study was focused on seasonal changes in the abundances of bacterial genes (dddP, dmdA) related to DMSP catabolism in the seawater of Ofunato Bay by BLAST+ analysis using shotgun metagenomic datasets. We found seasonal changes among the Candidatus Pelagibacter ubique strains, including those of the HTCC1062 type and the Red Sea type. A good correlation was observed between the chlorophyll a concentrations and the abundances of the catabolic genes, suggesting that the bacteria directly interact with phytoplankton in the marine material cycle system and play important roles in producing DMS and MeSH from DMSP as signaling molecules for the possible formation of the scent of the tidewater or as fish attractants.

Functional interrogation of Plasmodium genus metabolism identifies species- and stage-specific differences in nutrient essentiality and drug targeting

Several antimalarial drugs exist, but differences between life cycle stages among malaria species pose challenges for developing more effective therapies. To understand the diversity among stages and species, we reconstructed genome-scale metabolic models (GeMMs) of metabolism for five life cycle stages and five species of Plasmodium spanning the blood, transmission, and mosquito stages. The stage-specific models of Plasmodium falciparum uncovered stage-dependent changes in central carbon metabolism and predicted potential targets that could affect several life cycle stages. The species-specific models further highlight differences between experimental animal models and the human-infecting species. Comparisons between human- and rodent-infecting species revealed differences in thiamine (vitamin B1), choline, and pantothenate (vitamin B5) metabolism. Thus, we show that genome-scale analysis of multiple stages and species of Plasmodium can prioritize potential drug targets that could be both anti-malarials and transmission blocking agents, in addition to guiding translation from non-human experimental disease models.

Malaria kills nearly one-half million people a year and over 1 billion people are at risk of becoming infected by the parasite. Plasmodial infections are difficult to treat for a myriad of reasons, but the ability of the organism to remain latent in hosts and the complex life cycles greatly contributed to the difficulty in treat malaria. Genome-scale metabolic models (GeMMs) enable hierarchical integration of disparate data types into a framework amenable to computational simulations enabling deeper mechanistic insights from high-throughput data measurements. In this study, GeMMs of multiple Plasmodium species are used to study metabolic similarities and differences across the Plasmodium genus. In silico gene-knock out simulations across species and stages uncovered functional metabolic differences between human- and rodent-infecting species as well as across the parasite’s life-cycle stages. These findings may help identify drug regimens that are more effective in targeting human-infecting species across multiple stages of the organism.

Low Concentrations of Vitamin C Reduce the Synthesis of Extracellular Polymers and Destabilize Bacterial Biofilms

Extracellular polymeric substances (EPS) produced by bacteria form a matrix supporting the complex three-dimensional architecture of biofilms. This EPS matrix is primarily composed of polysaccharides, proteins and extracellular DNA. In addition to supporting the community structure, the EPS matrix protects bacterial biofilms from the environment. Specifically, it shields the bacterial cells inside the biofilm, by preventing antimicrobial agents from getting in contact with them, thereby reducing their killing effect. New strategies for disrupting the formation of the EPS matrix can therefore lead to a more efficient use of existing antimicrobials. Here we examined the mechanism of the known effect of vitamin C (sodium ascorbate) on enhancing the activity of various antibacterial agents. Our quantitative proteomics analysis shows that non-lethal concentrations of vitamin C inhibit bacterial quorum sensing and other regulatory mechanisms underpinning biofilm development. As a result, the EPS biosynthesis in reduced, and especially the polysaccharide component of the matrix is depleted. Once the EPS content is reduced beyond a critical point, bacterial cells get fully exposed to the medium. At this stage, the cells are more susceptible to killing, either by vitamin C-induced oxidative stress as reported here, or by other antimicrobials or treatments.

FARNA: knowledgebase of inferred functions of non-coding RNA transcripts

Non-coding RNA (ncRNA) genes play a major role in control of heterogeneous cellular behavior. Yet, their functions are largely uncharacterized. Current available databases lack in-depth information of ncRNA functions across spectrum of various cells/tissues. Here, we present FARNA, a knowledgebase of inferred functions of 10,289 human ncRNA transcripts (2,734 microRNA and 7,555 long ncRNA) in 119 tissues and 177 primary cells of human. Since transcription factors (TFs) and TF co-factors (TcoFs) are crucial components of regulatory machinery for activation of gene transcription, cellular processes and diseases in which TFs and TcoFs are involved suggest functions of the transcripts they regulate. In FARNA, functions of a transcript are inferred from TFs and TcoFs whose genes co-express with the transcript controlled by these TFs and TcoFs in a considered cell/tissue. Transcripts were annotated using statistically enriched GO terms, pathways and diseases across cells/tissues based on guilt-by-association principle. Expression profiles across cells/tissues based on Cap Analysis of Gene Expression (CAGE) are provided. FARNA, having the most comprehensive function annotation of considered ncRNAs across widest spectrum of human cells/tissues, has a potential to greatly contribute to our understanding of ncRNA roles and their regulatory mechanisms in human. FARNA can be accessed at: http://cbrc.kaust.edu.sa/farna

Co-ordinated Regulations of mRNA Synthesis and Decay during Cold Acclimation in Arabidopsis Cells

Plants possess a cold acclimation system to acquire freezing tolerance through pre-exposure to non-freezing low temperatures. The transcriptional cascade of C-repeat-binding factors (CBFs)/dehydration response element-binding factors (DREBs) is considered a major transcriptional regulatory pathway during cold acclimation. However, little is known regarding the functional significance of mRNA stability regulation in the response of gene expression to cold stress. The actual level of individual mRNAs is determined by a balance between mRNA synthesis and degradation. Therefore, it is important to assess the regulatory steps to increase our understanding of gene regulation. Here, we analyzed temporal changes in mRNA amounts and half-lives in response to cold stress in Arabidopsis cell cultures based on genome-wide analysis. In this mRNA decay array method, mRNA half-life measurements and microarray analyses were combined. In addition, temporal changes in the integrated value of transcription rates were estimated from the above two parameters using a mathematical approach. Our results showed that several cold-responsive genes, including Cold-regulated 15a, were relatively destabilized, whereas the mRNA amounts were increased during cold treatment by accelerating the transcription rate to overcome the destabilization. Considering the kinetics of mRNA synthesis and degradation, this apparently contradictory result supports that mRNA destabilization is advantageous for the swift increase in CBF-responsive genes in response to cold stress.

The genome of Chenopodium quinoa

Chenopodium quinoa (quinoa) is a highly nutritious grain identified as an important crop to improve world food security. Unfortunately, few resources are available to facilitate its genetic improvement. Here we report the assembly of a high-quality, chromosome-scale reference genome sequence for quinoa, which was produced using single-molecule real-time sequencing in combination with optical, chromosome-contact and genetic maps. We also report the sequencing of two diploids from the ancestral gene pools of quinoa, which enables the identification of sub-genomes in quinoa, and reduced-coverage genome sequences for 22 other samples of the allotetraploid goosefoot complex. The genome sequence facilitated the identification of the transcription factor likely to control the production of anti-nutritional triterpenoid saponins found in quinoa seeds, including a mutation that appears to cause alternative splicing and a premature stop codon in sweet quinoa strains. These genomic resources are an important first step towards the genetic improvement of quinoa.

CT-based morphological assessment of the hip joint in Japanese patients: association with radiographic predictors of femoroacetabular impingement

AIMS

Femoroacetabular impingement (FAI) has been highlighted and well documented primarily in Western countries and there are few large studies focused on FAI-related morphological assessment in Asian patients. We chose to investigate this subject.

PATIENTS AND METHODS

We assessed the morphology of the hip and the prevalence of radiographic FAI in Japanese patients by measuring predictors of FAI. We reviewed a total of 1178 hips in 695 men and 483 women with a mean age of 58.2 years (20 to 89) using CT images that had been obtained for reasons unrelated to symptoms from the hip. We measured the lateral centre edge angle, acetabular index, crossover sign, alpha angle and anterior femoral head-neck offset ratio.

RESULTS

A total of 441 hips (37.4%) had pincer-type deformity (41.7% men, 31.3% women) and 534 (45.3%) had cam-type deformity (54.4% men, 32.3% women). Moreover, 773 hips (65.6%) had at least one parameter that predisposes to FAI (74.0% men, 53.6% women) and 424 hips (36.0%) had two or more parameters (43.6% men, 25.0% women).

CONCLUSION

The prevalence of radiographic FAI was common in Japanese patients who are generally considered to have dysplastic hips. Cite this article: Bone Joint J 2016;98-B:1167-74.

In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria

BACKGROUND

Finding a source from which high-energy-density biofuels can be derived at an industrial scale has become an urgent challenge for renewable energy production. Some microorganisms can produce free fatty acids (FFA) as precursors towards such high-energy-density biofuels. In particular, photosynthetic cyanobacteria are capable of directly converting carbon dioxide into FFA. However, current engineered strains need several rounds of engineering to reach the level of production of FFA to be commercially viable; thus new chassis strains that require less engineering are needed. Although more than 120 cyanobacterial genomes are sequenced, the natural potential of these strains for FFA production and excretion has not been systematically estimated.

RESULTS

Here we present the FFA SC (FFASC), an in silico screening method that evaluates the potential for FFA production and excretion of cyanobacterial strains based on their proteomes. A literature search allowed for the compilation of 64 proteins, most of which influence FFA production and a few of which affect FFA excretion. The proteins are classified into 49 orthologous groups (OGs) that helped create rules used in the scoring/ranking of algorithms developed to estimate the potential for FFA production and excretion of an organism. Among 125 cyanobacterial strains, FFASC identified 20 candidate chassis strains that rank in their FFA producing and excreting potential above the specifically engineered reference strain, Synechococcus sp. PCC 7002. We further show that the top ranked cyanobacterial strains are unicellular and primarily include Prochlorococcus (order Prochlorales) and marine Synechococcus (order Chroococcales) that cluster phylogenetically. Moreover, two principal categories of enzymes were shown to influence FFA production the most: those ensuring precursor availability for the biosynthesis of lipids, and those involved in handling the oxidative stress associated to FFA synthesis.

CONCLUSION

To our knowledge FFASC is the first in silico method to screen cyanobacteria proteomes for their potential to produce and excrete FFA, as well as the first attempt to parameterize the criteria derived from genetic characteristics that are favorable/non-favorable for this purpose. Thus, FFASC helps focus experimental evaluation only on the most promising cyanobacteria.

The Emerging Facets of Non-Cancerous Warburg Effect

The Warburg effect (WE), or aerobic glycolysis, is commonly recognized as a hallmark of cancer and has been extensively studied for potential anti-cancer therapeutics development. Beyond cancer, the WE plays an important role in many other cell types involved in immunity, angiogenesis, pluripotency, and infection by pathogens (e.g., malaria). Here, we review the WE in non-cancerous context as a "hallmark of rapid proliferation." We observe that the WE operates in rapidly dividing cells in normal and pathological states that are triggered by internal and external cues. Aerobic glycolysis is also the preferred metabolic program in the cases when robust transient responses are needed. We aim to draw attention to the potential of computational modeling approaches in systematic characterization of common metabolic features beyond the WE across physiological and pathological conditions. Identification of metabolic commonalities across various diseases may lead to successful repurposing of drugs and biomarkers.

An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as “modifier genes,” but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic models.

Marine Metagenome as A Resource for Novel Enzymes

More than 99% of identified prokaryotes, including many from the marine environment, cannot be cultured in the laboratory. This lack of capability restricts our knowledge of microbial genetics and community ecology. Metagenomics, the culture-independent cloning of environmental DNAs that are isolated directly from an environmental sample, has already provided a wealth of information about the uncultured microbial world. It has also facilitated the discovery of novel biocatalysts by allowing researchers to probe directly into a huge diversity of enzymes within natural microbial communities. Recent advances in these studies have led to a great interest in recruiting microbial enzymes for the development of environmentally-friendly industry. Although the metagenomics approach has many limitations, it is expected to provide not only scientific insights but also economic benefits, especially in industry. This review highlights the importance of metagenomics in mining microbial lipases, as an example, by using high-throughput techniques. In addition, we discuss challenges in the metagenomics as an important part of bioinformatics analysis in big data.

DESM: portal for microbial knowledge exploration systems

Microorganisms produce an enormous variety of chemical compounds. It is of general interest for microbiology and biotechnology researchers to have means to explore information about molecular and genetic basis of functioning of different microorganisms and their ability for bioproduction. To enable such exploration, we compiled 45 topic-specific knowledgebases (KBs) accessible through DESM portal (www.cbrc.kaust.edu.sa/desm). The KBs contain information derived through text-mining of PubMed information and complemented by information data-mined from various other resources (e.g. ChEBI, Entrez Gene, GO, KOBAS, KEGG, UniPathways, BioGrid). All PubMed records were indexed using 4 538 278 concepts from 29 dictionaries, with 1 638 986 records utilized in KBs. Concepts used are normalized whenever possible. Most of the KBs focus on a particular type of microbial activity, such as production of biocatalysts or nutraceuticals. Others are focused on specific categories of microorganisms, e.g. streptomyces or cyanobacteria. KBs are all structured in a uniform manner and have a standardized user interface. Information exploration is enabled through various searches. Users can explore statistically most significant concepts or pairs of concepts, generate hypotheses, create interactive networks of associated concepts and export results. We believe DESM will be a useful complement to the existing resources to benefit microbiology and biotechnology research.

Metagenomic studies of the Red Sea

Metagenomics has significantly advanced the field of marine microbial ecology, revealing the vast diversity of previously unknown microbial life forms in different marine niches. The tremendous amount of data generated has enabled identification of a large number of microbial genes (metagenomes), their community interactions, adaptation mechanisms, and their potential applications in pharmaceutical and biotechnology-based industries. Comparative metagenomics reveals that microbial diversity is a function of the local environment, meaning that unique or unusual environments typically harbor novel microbial species with unique genes and metabolic pathways. The Red Sea has an abundance of unique characteristics; however, its microbiota is one of the least studied among marine environments. The Red Sea harbors approximately 25 hot anoxic brine pools, plus a vibrant coral reef ecosystem. Physiochemical studies describe the Red Sea as an oligotrophic environment that contains one of the warmest and saltiest waters in the world with year-round high UV radiations. These characteristics are believed to have shaped the evolution of microbial communities in the Red Sea. Over-representation of genes involved in DNA repair, high-intensity light responses, and osmoregulation were found in the Red Sea metagenomic databases suggesting acquisition of specific environmental adaptation by the Red Sea microbiota. The Red Sea brine pools harbor a diverse range of halophilic and thermophilic bacterial and archaeal communities, which are potential sources of enzymes for pharmaceutical and biotechnology-based application. Understanding the mechanisms of these adaptations and their function within the larger ecosystem could also prove useful in light of predicted global warming scenarios where global ocean temperatures are expected to rise by 1-3°C in the next few decades. In this review, we provide an overview of the published metagenomic studies that were conducted in the Red Sea, and the bio-prospecting potential of the Red Sea microbiota. Furthermore, we discuss the limitations of the previous studies and the need for generating a large and representative metagenomic database of the Red Sea to help establish a dynamic model of the Red Sea microbiota.

Challenges and opportunities of airborne metagenomics

Recent metagenomic studies of environments, such as marine and soil, have significantly enhanced our understanding of the diverse microbial communities living in these habitats and their essential roles in sustaining vast ecosystems. The increase in the number of publications related to soil and marine metagenomics is in sharp contrast to those of air, yet airborne microbes are thought to have significant impacts on many aspects of our lives from their potential roles in atmospheric events such as cloud formation, precipitation, and atmospheric chemistry to their major impact on human health. In this review, we will discuss the current progress in airborne metagenomics, with a special focus on exploring the challenges and opportunities of undertaking such studies. The main challenges of conducting metagenomic studies of airborne microbes are as follows: 1) Low density of microorganisms in the air, 2) efficient retrieval of microorganisms from the air, 3) variability in airborne microbial community composition, 4) the lack of standardized protocols and methodologies, and 5) DNA sequencing and bioinformatics-related challenges. Overcoming these challenges could provide the groundwork for comprehensive analysis of airborne microbes and their potential impact on the atmosphere, global climate, and our health. Metagenomic studies offer a unique opportunity to examine viral and bacterial diversity in the air and monitor their spread locally or across the globe, including threats from pathogenic microorganisms. Airborne metagenomic studies could also lead to discoveries of novel genes and metabolic pathways relevant to meteorological and industrial applications, environmental bioremediation, and biogeochemical cycles.

Evolutionary Divergence of Plant Borate Exporters and Critical Amino Acid Residues for the Polar Localization and Boron-Dependent Vacuolar Sorting of AtBOR1

Boron (B) is an essential micronutrient for plants but is toxic when accumulated in excess. The plant BOR family encodes plasma membrane-localized borate exporters (BORs) that control translocation and homeostasis of B under a wide range of conditions. In this study, we examined the evolutionary divergence of BORs among terrestrial plants and showed that the lycophyte Selaginella moellendorffii and angiosperms have evolved two types of BOR (clades I and II). Clade I includes AtBOR1 and homologs previously shown to be involved in efficient transport of B under conditions of limited B availability. AtBOR1 shows polar localization in the plasma membrane and high-B-induced vacuolar sorting, important features for efficient B transport under low-B conditions, and rapid down-regulation to avoid B toxicity. Clade II includes AtBOR4 and barley Bot1 involved in B exclusion for high-B tolerance. We showed, using yeast complementation and B transport assays, that three genes in S. moellendorffii, SmBOR1 in clade I and SmBOR3 and SmBOR4 in clade II, encode functional BORs. Furthermore, amino acid sequence alignments identified an acidic di-leucine motif unique in clade I BORs. Mutational analysis of AtBOR1 revealed that the acidic di-leucine motif is required for the polarity and high-B-induced vacuolar sorting of AtBOR1. Our data clearly indicated that the common ancestor of vascular plants had already acquired two types of BOR for low- and high-B tolerance, and that the BOR family evolved to establish B tolerance in each lineage by adapting to their environments.

The four-transmembrane protein IP39 of Euglena forms strands by a trimeric unit repeat

Euglenoid flagellates have striped surface structures comprising pellicles, which allow the cell shape to vary from rigid to flexible during the characteristic movement of the flagellates. In Euglena gracilis, the pellicular strip membranes are covered with paracrystalline arrays of a major integral membrane protein, IP39, a putative four-membrane-spanning protein with the conserved sequence motif of the PMP-22/EMP/MP20/Claudin superfamily. Here we report the three-dimensional structure of Euglena IP39 determined by electron crystallography. Two-dimensional crystals of IP39 appear to form a striated pattern of antiparallel double-rows in which trimeric IP39 units are longitudinally polymerised, resulting in continuously extending zigzag-shaped lines. Structural analysis revealed an asymmetric molecular arrangement in the trimer, and suggested that at least four different interactions between neighbouring protomers are involved. A combination of such multiple interactions would be important for linear strand formation of membrane proteins in a lipid bilayer.

Changes in mRNA stability associated with cold stress in Arabidopsis cells

Control of mRNA half-life is a powerful strategy to adjust individual mRNA levels to various stress conditions, because the mRNA degradation rate controls not only the steady-state mRNA level but also the transition speed of mRNA levels. Here, we analyzed mRNA half-life changes in response to cold stress in Arabidopsis cells using genome-wide analysis, in which mRNA half-life measurements and transcriptome analysis were combined. Half-lives of average transcripts were determined to be elongated under cold conditions. Taking this general shift into account, we identified more than a thousand transcripts that were classified as relatively stabilized or relatively destabilized. The relatively stabilized class was predominantly observed in functional categories that included various regulators involved in transcriptional, post-transcriptional and post-translational processes. On the other hand, the relatively destabilized class was enriched in categories related to stress and hormonal response proteins, supporting the idea that rapid decay of mRNA is advantageous for swift responses to stress. In addition, pentatricopeptide repeat, cyclin-like F-box and Myb transcription factor protein families were significantly over-represented in the relatively destabilized class. The global analysis presented here demonstrates not only the importance of mRNA turnover control in the cold stress response but also several structural characteristics that might be important in the control of mRNA stability.

Exploring functionally related enzymes using radially distributed properties of active sites around the reacting points of bound ligands

BACKGROUND

Structural genomics approaches, particularly those solving the 3D structures of many proteins with unknown functions, have increased the desire for structure-based function predictions. However, prediction of enzyme function is difficult because one member of a superfamily may catalyze a different reaction than other members, whereas members of different superfamilies can catalyze the same reaction. In addition, conformational changes, mutations or the absence of a particular catalytic residue can prevent inference of the mechanism by which catalytic residues stabilize and promote the elementary reaction. A major hurdle for alignment-based methods for prediction of function is the absence (despite its importance) of a measure of similarity of the physicochemical properties of catalytic sites. To solve this problem, the physicochemical features radially distributed around catalytic sites should be considered in addition to structural and sequence similarities.

RESULTS

We showed that radial distribution functions (RDFs), which are associated with the local structural and physicochemical properties of catalytic active sites, are capable of clustering oxidoreductases and transferases by function. The catalytic sites of these enzymes were also characterized using the RDFs. The RDFs provided a measure of the similarity among the catalytic sites, detecting conformational changes caused by mutation of catalytic residues. Furthermore, the RDFs reinforced the classification of enzyme functions based on conventional sequence and structural alignments.

CONCLUSIONS

Our results demonstrate that the application of RDFs provides advantages in the functional classification of enzymes by providing information about catalytic sites.

CIPRO 2.5: Ciona intestinalis protein database, a unique integrated repository of large-scale omics data, bioinformatic analyses and curated annotation, with user rating and reviewing functionality

The Ciona intestinalis protein database (CIPRO) is an integrated protein database for the tunicate species C. intestinalis. The database is unique in two respects: first, because of its phylogenetic position, Ciona is suitable model for understanding vertebrate evolution; and second, the database includes original large-scale transcriptomic and proteomic data. Ciona intestinalis has also been a favorite of developmental biologists. Therefore, large amounts of data exist on its development and morphology, along with a recent genome sequence and gene expression data. The CIPRO database is aimed at collecting those published data as well as providing unique information from unpublished experimental data, such as 3D expression profiling, 2D-PAGE and mass spectrometry-based large-scale analyses at various developmental stages, curated annotation data and various bioinformatic data, to facilitate research in diverse areas, including developmental, comparative and evolutionary biology. For medical and evolutionary research, homologs in humans and major model organisms are intentionally included. The current database is based on a recently developed KH model containing 36 034 unique sequences, but for higher usability it covers 89 683 all known and predicted proteins from all gene models for this species. Of these sequences, more than 10 000 proteins have been manually annotated. Furthermore, to establish a community-supported protein database, these annotations are open to evaluation by users through the CIPRO website. CIPRO 2.5 is freely accessible at http://cipro.ibio.jp/2.5.