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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.

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.

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., Here, Bajaffer et al. reviewed the evolution of a memory system and its related genes. As memory is a function that is highly characteristic of humans, how it was established is of great interest. Mechanisms and genes among species were overviewed. This review also discussed possible approaches to study the evolution of memory systems in the future.

Droplet microfluidics techniques have shown promising results to study single-cells at high throughput. However, their adoption in laboratories studying “-omics” sciences is still irrelevant because of the field’s complex and multidisciplinary nature. 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 fluorescent activated droplet sorting (FADS) systems to integrate the use of 4 independent fluorescence-exciting lasers (e.g., 405, 488, 561, 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 was also integrated into our method 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 (> 50,000 cells/day) capabilities to mining and bioprospecting metagenomic data.

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.

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

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.

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.

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.

MotivationStructural 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.ResultsWe 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 celltypes, 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.Availabilityhttps://github.com/bio-ontology-research-group/DeepSVPContactrobert.hoehndorf@kaust.edu.sa

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., Author summary Arabian Peninsula has been home to ancient civilizations and elucidating its population structure can add to our understanding of human history. We conducted genomic profiling of 957 unrelated individuals who self-identify with 28 large tribes in Saudi Arabia. We found that genomic structure of Saudis is more clustered than previously thought, suggesting that tribal linages have been maintained for a long time in Arabian Peninsula in spite of admixture. The population structure revealed by our study has important implications for both Mendelian and complex genetics work in the study population.

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.

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.

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 Cnidaria1. Thus, Cnidarian representative species, Hydra, is considered to be a living fossil and 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-1762,3 function as motor neurons 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) expression4 are excited simultaneously, which is then followed by longitudinal contraction. This indicates not only that these neuron subsets are motor neurons but also that a single molecularly defined neuron subset forms a single coactive motor 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 timings5. 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. We propose that this simple feature (one subset, one circuit, one function) found in Hydra is a fundamental trait of the primitive nervous system.

Most studies proposing new strategies to manage and treat infections have been largely focused on identifying druggable targets that can inhibit a pathogen's growth when it is the single cause of infection. In vivo, however, infections can be caused by multiple species. This is important to take into account when attempting to develop or use current antibacterials since their efficacy can change significantly between single infections and coinfections. In this study, we used genome-scale metabolic models (GEMs) to interrogate the growth capabilities of Vibrio cholerae in single infections and coinfections with enterotoxigenic E. coli (ETEC), which cooccur in a large fraction of diarrheagenic patients. Coinfection model predictions showed that V. cholerae growth capabilities are enhanced in the presence of ETEC relative to V. cholerae single infection, through cross-fed metabolites made available to V. cholerae by ETEC. In vitro, cocultures of the two enteric pathogens further confirmed model predictions showing an increased growth of V. cholerae in coculture relative to V. cholerae single cultures while ETEC growth was suppressed. Dual RNAseq analysis of the cocultures also confirmed that the transcriptome of V. cholerae was distinct during coinfection compared to single-infection scenarios where processes related to metabolism were significantly perturbed. Further, in silico gene-knockout simulations uncovered discrepancies in gene essentiality for V. cholerae growth between single infections and coinfections. Integrative model-guided analysis thus identified druggable targets that would be critical for V. cholerae growth in both single infections and coinfections; thus, designing inhibitors against those targets would provide a broader spectrum of coverage against cholera infections., Gene essentiality is altered during polymicrobial infections. Nevertheless, most studies rely on single-species infections to assess pathogen gene essentiality. Here, we use genome-scale metabolic models (GEMs) to explore the effect of coinfection of the diarrheagenic pathogen Vibrio cholerae with another enteric pathogen, enterotoxigenic Escherichia coli (ETEC). Model predictions showed that V. cholerae metabolic capabilities were increased due to ample cross-feeding opportunities enabled by ETEC. This is in line with increased severity of cholera symptoms known to occur in patients with dual infections by the two pathogens. In vitro coculture systems confirmed that V. cholerae growth is enhanced in cocultures relative to single cultures. Further, expression levels of several V. cholerae metabolic genes were significantly perturbed as shown by dual RNA sequencing (RNAseq) analysis of its cocultures with different ETEC strains. A decrease in ETEC growth was also observed, probably mediated by nonmetabolic factors. Single gene essentiality analysis predicted conditionally independent genes that are essential for the pathogen’s growth in both single-infection and coinfection scenarios. Our results reveal growth differences that are of relevance to drug targeting and efficiency in polymicrobial infections. IMPORTANCE Most studies proposing new strategies to manage and treat infections have been largely focused on identifying druggable targets that can inhibit a pathogen's growth when it is the single cause of infection. In vivo, however, infections can be caused by multiple species. This is important to take into account when attempting to develop or use current antibacterials since their efficacy can change significantly between single infections and coinfections. In this study, we used genome-scale metabolic models (GEMs) to interrogate the growth capabilities of Vibrio cholerae in single infections and coinfections with enterotoxigenic E. coli (ETEC), which cooccur in a large fraction of diarrheagenic patients. Coinfection model predictions showed that V. cholerae growth capabilities are enhanced in the presence of ETEC relative to V. cholerae single infection, through cross-fed metabolites made available to V. cholerae by ETEC. In vitro, cocultures of the two enteric pathogens further confirmed model predictions showing an increased growth of V. cholerae in coculture relative to V. cholerae single cultures while ETEC growth was suppressed. Dual RNAseq analysis of the cocultures also confirmed that the transcriptome of V. cholerae was distinct during coinfection compared to single-infection scenarios where processes related to metabolism were significantly perturbed. Further, in silico gene-knockout simulations uncovered discrepancies in gene essentiality for V. cholerae growth between single infections and coinfections. Integrative model-guided analysis thus identified druggable targets that would be critical for V. cholerae growth in both single infections and coinfections; thus, designing inhibitors against those targets would provide a broader spectrum of coverage against cholera infections.

Gene essentiality is altered during polymicrobial infections. Nevertheless, most studies rely on single-species infections to assess pathogen gene essentiality. Here, we use genome-scale metabolic models (GEMs) to explore the effect of coinfection of the diarrheagenic pathogen Vibrio cholerae with another enteric pathogen, enterotoxigenic Escherichia coli (ETEC). Model predictions showed that V. cholerae metabolic capabilities were increased due to ample cross-feeding opportunities enabled by ETEC. This is in line with increased severity of cholera symptoms known to occur in patients with dual infections by the two pathogens. In vitro coculture systems confirmed that V. cholerae growth is enhanced in cocultures relative to single cultures. Further, expression levels of several V. cholerae metabolic genes were significantly perturbed as shown by dual RNA sequencing (RNAseq) analysis of its cocultures with different ETEC strains. A decrease in ETEC growth was also observed, probably mediated by nonmetabolic factors. Single gene essentiality analysis predicted conditionally independent genes that are essential for the pathogen’s growth in both single-infection and coinfection scenarios. Our results reveal growth differences that are of relevance to drug targeting and efficiency in polymicrobial infections. IMPORTANCE Most studies proposing new strategies to manage and treat infections have been largely focused on identifying druggable targets that can inhibit a pathogen's growth when it is the single cause of infection. In vivo, however, infections can be caused by multiple species. This is important to take into account when attempting to develop or use current antibacterials since their efficacy can change significantly between single infections and coinfections. In this study, we used genome-scale metabolic models (GEMs) to interrogate the growth capabilities of Vibrio cholerae in single infections and coinfections with enterotoxigenic E. coli (ETEC), which cooccur in a large fraction of diarrheagenic patients. Coinfection model predictions showed that V. cholerae growth capabilities are enhanced in the presence of ETEC relative to V. cholerae single infection, through cross-fed metabolites made available to V. cholerae by ETEC. In vitro, cocultures of the two enteric pathogens further confirmed model predictions showing an increased growth of V. cholerae in coculture relative to V. cholerae single cultures while ETEC growth was suppressed. Dual RNAseq analysis of the cocultures also confirmed that the transcriptome of V. cholerae was distinct during coinfection compared to single-infection scenarios where processes related to metabolism were significantly perturbed. Further, in silico gene-knockout simulations uncovered discrepancies in gene essentiality for V. cholerae growth between single infections and coinfections. Integrative model-guided analysis thus identified druggable targets that would be critical for V. cholerae growth in both single infections and coinfections; thus, designing inhibitors against those targets would provide a broader spectrum of coverage against cholera infections.

To improve our understanding of the environmental microbiome, we developed a single-cell genome sequencing platform, named SAG-gel, which utilizes gel beads for single-cell isolation, cell lysis, and whole genome amplification (WGA) for sequencing. SAG-gel enables serial, parallel and independent reactions of > 100,000 single cells in a single tube, delivering high-quality genome recovery with storable randomized single-cell genome libraries. From soil and marine environmental sources, we acquired 734 partial genomes that are recapitulated in 231 species, 35% of which were assigned as high-to-medium qualities. We found that each genome to be almost unique and 98.7% of them were newly identified, implying the complex genetic diversities across 44 phyla. The various metabolic capabilities including virulence factors and biosynthetic gene clusters were found across the lineages at single-cell resolution. This technology will accelerate the accumulation of reference genomes of uncharacterized environmental microbes and provide us new insights for their roles.

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 anti-predator 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.

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.

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.

Small photosynthetic eukaryotes play important roles in oceanic food webs in coastal regions. We investigated seasonal changes in the communities of photosynthetic picoeukaryotes (PPEs) of the class Mamiellophyceae, including the genera Bathycoccus, Micromonas and Ostreococcus, in Ofunato Bay, which is located in northeastern Japan and faces the Pacific Ocean. The abundances of PPEs were assessed over a period of one year in 2015 at three sampling stations, KSt. 1 (innermost bay area), KSt. 2 (middle bay area) and KSt. 3 (bay entrance area) at depths of 1 m (KSt. 1, KSt. 2 and KSt. 3), 8 m (KSt. 1) or 10 m (KSt. 2 and KSt. 3) by employing MiSeq shotgun metagenomic sequencing. The total abundances of Bathycoccus, Ostreococcus and Micromonas were in the ranges of 42–49%, 35–49% and 13–17%, respectively. Considering all assayed sampling stations and depths, seasonal changes revealed high abundances of PPEs during the winter and summer and low abundances during late winter to early spring and late summer to early autumn. Bathycoccus was most abundant in the winter, and Ostreococcus showed a high abundance during the summer. Another genus, Micromonas, was relatively low in abundance throughout the study period. Taken together with previously suggested blooming periods of phytoplankton, as revealed by chlorophyll a concentrations in Ofunato Bay during spring and autumn, these results for PPEs suggest that greater phytoplankton blooming has a negative influence on the seasonal occurrences of PPEs in the bay.

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.