The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata

Machine learning for the advancement of genome-scale metabolic modeling

Constraint-based modeling (CBM) has evolved as the core systems biology tool to map the interrelations between genotype, phenotype, and external environment. The recent advancement of high-throughput experimental approaches and multi-omics strategies has generated a plethora of new and precise information from wide-ranging biological domains. On the other hand, the continuously growing field of machine learning (ML) and its specialized branch of deep learning (DL) provide essential computational architectures for decoding complex and heterogeneous biological data. In recent years, both multi-omics and ML have assisted in the escalation of CBM. Condition-specific omics data, such as transcriptomics and proteomics, helped contextualize the model prediction while analyzing a particular phenotypic signature. At the same time, the advanced ML tools have eased the model reconstruction and analysis to increase the accuracy and prediction power. However, the development of these multi-disciplinary methodological frameworks mainly occurs independently, which limits the concatenation of biological knowledge from different domains. Hence, we have reviewed the potential of integrating multi-disciplinary tools and strategies from various fields, such as synthetic biology, CBM, omics, and ML, to explore the biochemical phenomenon beyond the conventional biological dogma. How the integrative knowledge of these intersected domains has improved bioengineering and biomedical applications has also been highlighted. We categorically explained the conventional genome-scale metabolic model (GEM) reconstruction tools and their improvement strategies through ML paradigms. Further, the crucial role of ML and DL in omics data restructuring for GEM development has also been briefly discussed. Finally, the case-study-based assessment of the state-of-the-art method for improving biomedical and metabolic engineering strategies has been elaborated. Therefore, this review demonstrates how integrating experimental and in silico strategies can help map the ever-expanding knowledge of biological systems driven by condition-specific cellular information. This multiview approach will elevate the application of ML-based CBM in the biomedical and bioengineering fields for the betterment of society and the environment.

Food and drug design for gut microbiota-directed regulation: Current experimental landscape and future innovation

Most diets and medications enhance host health via microbiota-dependent ways, but it is in the present situation of untargeted regulation. Non-targeted regulation may lead to the ineffectiveness of dietary supplements or drug treatment. Microbiota-directed food, aiming to improve diseases by targeting specific microbes without affecting other bacteria, have been proposed to deal with this problem. However, there is currently no universally applicable method to explore such foods or drugs. In this review, thirty studies on recent efforts in microbiota directed diets and medications are summarized from various databases. The methods used to find new foods and medications are primarily divided into four groups depending on the experimental models: in vivo and in vitro, as well as predictions based on bioinformatics. We also discuss their implementation, interpretation, and respective limitations, and describe the present situation. We further put forward a framework for microbiota-directed foods and medicine according to above methods and other microbiome manipulation, which will spur precision medicine.

Simultaneous Quantitation and Discovery (SQUAD) Analysis: Combining the Best of Targeted and Untargeted Mass Spectrometry-Based Metabolomics

Untargeted and targeted approaches are the traditional metabolomics workflows acquired for a wider understanding of the metabolome under focus. Both approaches have their strengths and weaknesses. The untargeted, for example, is maximizing the detection and accurate identification of thousands of metabolites, while the targeted is maximizing the linear dynamic range and quantification sensitivity. These workflows, however, are acquired separately, so researchers compromise either a low-accuracy overview of total molecular changes (i.e., untargeted analysis) or a detailed yet blinkered snapshot of a selected group of metabolites (i.e., targeted analysis) by selecting one of the workflows over the other. In this review, we present a novel single injection simultaneous quantitation and discovery (SQUAD) metabolomics that combines targeted and untargeted workflows. It is used to identify and accurately quantify a targeted set of metabolites. It also allows data retro-mining to look for global metabolic changes that were not part of the original focus. This offers a way to strike the balance between targeted and untargeted approaches in one single experiment and address the two approaches' limitations. This simultaneous acquisition of hypothesis-led and discovery-led datasets allows scientists to gain more knowledge about biological systems in a single experiment.

OrthoPhy: A Program to Construct Ortholog Data Sets Using Taxonomic Information

Species phylogenetic trees represent the evolutionary processes of organisms, and they are fundamental in evolutionary research. Therefore, new methods have been developed to obtain more reliable species phylogenetic trees. A highly reliable method is the construction of an ortholog data set based on sequence information of genes, which is then used to infer the species phylogenetic tree. However, although methods for constructing an ortholog data set for species phylogenetic analysis have been developed, they cannot remove some paralogs, which is necessary for reliable species phylogenetic inference. To address the limitations of current methods, we developed OrthoPhy, a program that excludes paralogs and constructs highly accurate ortholog data sets using taxonomic information dividing analyzed species into monophyletic groups. OrthoPhy can remove paralogs, detecting inconsistencies between taxonomic information and phylogenetic trees of candidate ortholog groups clustered by sequence similarity. Performance tests using evolutionary simulated sequences and real sequences of 40 bacteria revealed that the precision of ortholog inference by OrthoPhy is higher than that of existing programs. Additionally, the phylogenetic analysis of species was more accurate when performed using ortholog data sets constructed by OrthoPhy than that performed using data sets constructed by existing programs. Furthermore, we performed a benchmark test of the Quest for Orthologs using real sequence data and found that the concordance rate between the phylogenetic trees of orthologs inferred by OrthoPhy and those of species was higher than the rates obtained by other ortholog inference programs. Therefore, ortholog data sets constructed using OrthoPhy enabled a more accurate phylogenetic analysis of species than those constructed using the existing programs, and OrthoPhy can be used for the phylogenetic analysis of species even for distantly related species that have experienced many evolutionary events.

Genetic Evidences of Biosurfactant Production in Two Bacillus subtilis Strains MB415 and MB418 Isolated From Oil Contaminated Soil

Biosurfactants are a diverse group of amphiphilic compounds obtained from microbes. In the present study, the genomic analysis of biosurfactant-producing Bacillus subtilis MB415 and MB418 obtained from oil-contaminated soil was performed. Initially, the strains were screened for biosurfactant production by hemolytic assay, emulsification index, and oil displacement. Further FTIR analysis of extracted biosurfactants revealed the presence of lipopeptides. The sequenced genomes of MB415 and MB418 were of 4.2 Mbps with 43% GC content. Among more than 4,500 protein-coding genes, many were involved in virulence, metal/multidrug resistances, flagella assembly, chemotactic response, and aromatic ring hydroxylating dioxygenases. An annotation analysis revealed that both genomes possessed non-ribosomal synthetase gene clusters for the lipopeptide synthetases srf and fen responsible for surfactin and fengycin production. Comparative studies of both genomes highlighted variability in gene operons mainly for surfactin biosynthesis.

Feed and Host Genetics Drive Microbiome Diversity with Resultant Consequences for Production Traits in Mass-Reared Black Soldier Fly (Hermetia illucens) Larvae

Mass rearing the black soldier fly, Hermetia illucens, for waste bioremediation and valorisation is gaining traction on a global scale. While the health and productivity of this species are underpinned by associations with microbial taxa, little is known about the factors that govern gut microbiome assembly, function, and contributions towards host phenotypic development in actively feeding larvae. In the present study, a 16S rDNA gene sequencing approach applied to a study system incorporating both feed substrate and genetic variation is used to address this knowledge gap. It is determined that the alpha diversity of larval gut bacterial communities is driven primarily by features of the larval feed substrate, including the diversity of exogenous bacterial populations. Microbiome beta diversity, however, demonstrated patterns of differentiation consistent with an influence of diet, larval genetic background, and a potential interaction between these factors. Moreover, evidence for an association between microbiome structure and the rate of larval fat accumulation was uncovered. Taxonomic enrichment analysis and clustering of putative functional gut profiles further suggested that feed-dependent turnover in microbiome communities is most likely to impact larval characteristics. Taken together, these findings indicate that host-microbiome interactions in this species are complex yet relevant to larval trait emergence.

Artificial Rearing of Atlantic Salmon Juveniles for Supportive Breeding Programs Induces Long-Term Effects on Gut Microbiota after Stocking

In supportive breeding programs for wild salmon populations, stocked parr experience higher mortality rates than wild ones. Among other aspects of phenotype, the gut microbiota of artificially raised parr differs from that of wild parr before stocking. Early steps of microbiota ontogeny are tightly dependent upon environmental conditions, both of which exert long-term effects on host physiology. Therefore, our objective was to assess to what extent the resilience capacity of the microbiota of stocked salmon may prevent taxonomic convergence with that of their wild congeners after two months in the same natural environment. Using the 16S SSU rRNA marker gene, we tested the general hypothesis that environmental conditions during the very first steps of microbiota ontogeny imprint a permanent effect on later stages of microbiota recruitment. Our results first showed that gut microbiota composition of stocked and wild parr from the same genetic population, and sharing the same environment, was dependent on the early rearing environment. In contrast, skin microbiota in stocked individuals converged to that of wild individuals. Taxonomic composition and co-occurrence network analyses suggest an impairment of wild bacteria recruitment and a higher instability for the gut microbiota of stocked parr. This study is the first to demonstrate the long-term effect of early microbiota ontogeny in artificial rearing for natural population conservation programs, raising the need to implement microbial ecology.

Genome analysis of Thauera chlorobenzoica strain 3CB-1T, a halobenzoate-degrading bacterium isolated from aquatic sediment

The genus Thauera is characterized by several species and strains with the ability to degrade a variety of aromatic compounds under denitrifying conditions. Thauera chlorobenzoica strain 3CB-1^T, isolated from river sediment, has the unique ability to degrade a variety of halobenzoates, such as 3-chlorobenzoate, 3-bromobenzoate, 3-iodobenzoate, and 2-fluorobenzoate, coupled to nitrate reduction. The genome of T. chlorobenzoica strain 3CB-1^T has been sequenced, allowing us to gain insights into the molecular basis for the anaerobic degradation of (halo)aromatic compounds. The 3.77-Mb genome contains 3584 genes; 3514 are protein-coding genes of which 198 are likely associated with degradation of aromatic compounds. It has a G + C content of 67.25%. The genome contains two sets of CoA reductase gene clusters, both belonging to class I benzoate-CoA reductases (BCRs). The genes in one of the two clusters differ from the typical BCRs, with low sequence identities, suggesting they might have different substrate specificities. The genome also contains four benzoate-CoA ligase genes. One likely encodes a 3-hydroxybenzoate-CoA ligase, and two others group together with benzoate-CoA ligases from Thauera aromatica. The fourth has a 77% identity to the mbdA gene from Azoarcus sp. CIB, is absent in the T. aromatica genome, and potentially encodes a halobenzoate-CoA ligase. 3-Chlorobenzoate is reductively dechlorinated in T. chlorobenzoica by a benzoyl-CoA reductase.

Phnomibacter ginsenosidimutans gen. nov., sp. nov., a novel glycoside hydrolase positive bacterial strain with ginsenoside hydrolysing activity

The conversion of major ginsenosides into minor ginsenosides attracts a lot of interest because of their biological and pharmaceutical activities. Therefore, for the conversion of ginsenosides, finding a novel competent glycoside hydrolase-producing bacterial strain is useful for future research studies and the mass production of minor ginsenosides. Wastewater samples were collected and screened for novel glycoside hydrolase bacterial strains using Reasoner's 2A+aesculin agar medium. As a result, a novel glycoside hydrolase positive bacterial strain (SB-02^T) was identified and subjected to a polyphasic taxonomic analysis. Based on genome analysis, strain SB-02^T was found to be affiliated with the family Chitinophagaceae and have less than 92.8 % sequence similarity to other members of the same family. Functional analysis indicated that SB-02^T was able to hydrolyse the ginsenosides Rb1, Rc and Rd to F2 and C-K. Due to the conversion of ginsenosides, the strain's genome was sequenced and the genes were annotated by the NCBI. The average amino acid identity and average nucleotide identity values between SB-02^T and the available reference genomes were 65.7 and 65.9 %, respectively. The novel isolate contained MK-7 as the predominant menaquinone, the major polyamine putrescine, and iso-C_15 : 0, iso-C_15 : 1 G and iso-C_17 : 0 3-OH as major fatty acids. The major polar lipids were diphosphatidylglycerol, phosphatidylglycerol and phosphatidylethanolamine. Thus, based on the data presented here, strain SB-02^T represents a novel species within a new genus in the family Chitinophagaceae, for which the name Phnomibacter ginsenosidimutans gen. nov., sp. nov. is proposed. The type strain of Phnomibacter ginsenosidimutans is SB-02^T (=KACC 21266^T=LMG 31707^T). The genome annotation of SB-02^T shows many glycoside hydrolase genes, which may be responsible for the efficient production of many kinds of minor ginsenosides and will be very helpful for future research (target gene cloning) and mass production of either F2 or C-K.

The hunt for a yet unknown: Common molecular signature in some genetically monomorphic enterobacteria

Mark Achtman introduced the term "genetically monomorphic bacteria" (GM bacteria) for some human and plant pathogens. They displayed a great uniformity in terms of their "genetic" properties. This "uniformity" poses a challenge to microbiologists. To address these problems, we used CodonW and IslandViewer 3 as analytical tools and took Escherichia coli, Salmonella, and Shigella strains as a model organisms. We hypothesized that GM bacterium contains a common molecular signature among them. We have found a significant correlation regarding the number of protein-coding genes, predicted highly expressed genes, and the highest length of gene in this regard. On the other hand, the correspondence analysis of pathogenicity-related genes identified by IslandViewer 3 displayed a somewhat unique pattern in GM bacteria. The probable pathogenic genes are clustered into two separate groups, which is a hallmark of some pattern. Similar genes of non-monomorphic pathogenic strain clustered almost similarly, but the clusters are joined together, they are not completely separated. These features, in our considered view, may be considered as codon usages signatures of these bacteria, and E. coli in particular.

Biodiversity-based development and evolution: the emerging research systems in model and non-model organisms

Evolutionary developmental biology, or Evo-Devo for short, has become an established field that, broadly speaking, seeks to understand how changes in development drive major transitions and innovation in organismal evolution. It does so via integrating the principles and methods of many subdisciplines of biology. Although we have gained unprecedented knowledge from the studies on model organisms in the past decades, many fundamental and crucially essential processes remain a mystery. Considering the tremendous biodiversity of our planet, the current model organisms seem insufficient for us to understand the evolutionary and physiological processes of life and its adaptation to exterior environments. The currently increasing genomic data and the recently available gene-editing tools make it possible to extend our studies to non-model organisms. In this review, we review the recent work on the regulatory signaling of developmental and regeneration processes, environmental adaptation, and evolutionary mechanisms using both the existing model animals such as zebrafish and Drosophila, and the emerging nonstandard model organisms including amphioxus, ascidian, ciliates, single-celled phytoplankton, and marine nematode. In addition, the challenging questions and new directions in these systems are outlined as well.

Omics-Driven Biotechnology for Industrial Applications

Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on "omics" driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in "omics" technologies, compare the pros and cons of the different "omics" technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of "omics" technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of "omics" technologies to agricultural and food biotechnology, and review the impact of "omics" on current COVID-19 research.

Scaffolding Contigs Using Multiple Reference Genomes

Scaffolding is an important step of the genome assembly and its function is to order and orient the contigs in the assembly of a draft genome into larger scaffolds. Several single reference-based scaffolders have currently been proposed. However, a single reference genome may not be sufficient alone for a scaffolder to correctly scaffold a target draft genome, especially when the target genome and the reference genome have distant evolutionary relationship or some rearrangements. This motivates researchers to develop the so-called multiple reference-based scaffolders that can utilize multiple reference genomes, which may provide different but complementary types of scaffolding information, to scaffold the target draft genome. In this chapter, we will review some of the state-of-the-art multiple reference-based scaffolders, such as Ragout, MeDuSa and Multi-CAR, and give a complete introduction to Multi-CSAR, an improved extension of Multi-CAR.

Microalgae with artificial intelligence: A digitalized perspective on genetics, systems and products

With recent advances in novel gene-editing tools such as RNAi, ZFNs, TALENs, and CRISPR-Cas9, the possibility of altering microalgae toward designed properties for various application is becoming a reality. Alteration of microalgae genomes can modify metabolic pathways to give elevated yields in lipids, biomass, and other components. The potential of such genetically optimized microalgae can give a "domino effect" in further providing optimization leverages down the supply chain, in aspects such as cultivation, processing, system design, process integration, and revolutionary products. However, the current level of understanding the functional information of various microalgae gene sequences is still primitive and insufficient as microalgae genome sequences are long and complex. From this perspective, this work proposes to link up this knowledge gap between microalgae genetic information and optimized bioproducts using Artificial Intelligence (AI). With the recent acceleration of AI research, large and complex data from microalgae research can be properly analyzed by combining the cutting-edge of both fields. In this work, the most suitable class of AI algorithms (such as active learning, semi-supervised learning, and meta-learning) are discussed for different cases of microalgae applications. This work concisely reviews the current state of the research milestones and highlight some of the state-of-art that has been carried out, providing insightful future pathways. The utilization of AI algorithms in microalgae cultivation, system optimization, and other aspects of the supply chain is also discussed. This work opens the pathway to a digitalized future for microalgae research and applications.

The role of the microbiota in periodontal disease

The last decade has witnessed unparalleled advances in our understanding of the complexity of the oral microbiome and the compositional changes that occur in subgingival biofilms in the transition from health to gingivitis and to destructive periodontal disease. The traditional view, which has held sway for the last 2 decades, that disease is characterized by the outgrowth of a consortium, or consortia, of a limited number of potentially pathogenic organisms, has given way to an alternative paradigm. In this new view, the microbiological changes associated with disease represent whole-scale alterations to the overall microbial population structure and to the functional properties of the entire community. Thus, and in common with other microbially mediated diseases of the gastrointestinal tract, the normally balanced, symbiotic, and generally benign commensal microbiome of the tooth-associated biofilm undergoes dysbiosis to a potentially deleterious microbiota. Coincident with progress in defining the microbiology of these diseases, there have been equally important advances in our understanding of the inflammatory systems of the periodontal tissues, their control, and how inflammation may contribute both to the development of dysbiosis and, in a deregulated state, the destructive disease process. One can therefore speculate that the inflammatory response and the periodontal microbiome are in a bidirectional balance in oral health and a bidirectional imbalance in periodontitis. However, despite these clear insights into both sides of the host/microbe balance in periodontal disease, there remain several unresolved issues concerning the role of the microbiota in disease. These include, but are not limited to, the factors which determine progression from gingivitis to periodontitis in a proportion of the population, whether dysbiosis causes disease or results from disease, and the molecular details of the microbial stimulus responsible for driving the destructive inflammatory response. Further progress in resolving these issues may provide significant benefit to diagnosis, treatment, and prevention.

Discovery of Three 22-Membered Macrolides by Deciphering the Streamlined Genome of Mangrove-Derived Streptomyces sp. HM190

Strain HM190, a moderate halophile, was isolated from rhizosphere soil of the mangrove Kandelia obovata in Fugong village, China. The 16S ribosomal RNA (rRNA) gene sequence and the results of phylogenetic analysis revealed that strain HM190 belonged to the genus Streptomyces and had the highest sequence similarity of 99.79% to Streptomyces heilongjiangensis NEAU-W2^T. The complete genome of strain HM190 comprised 7,762,826 bp in a linear chromosome with 71.97% G + C content. According to antiSMASH analysis, a total of 30 biosynthetic gene clusters (BGCs) were predicted to be involved in secondary metabolism, 12 of which were responsible for the production of polyketide- and non-ribosomal peptide-derived secondary metabolites. Gene cluster 5 was responsible for macrolide biosynthesis in a strain-specific 126,331-bp genomic island belonging to the left-arm region. Combined genomics–metabolomics analysis led to the discovery of three 22-membered macrolides (compounds 1–3). Their structures were elucidated by using spectroscopic techniques including high-resolution electrospray ionization mass spectroscopy (HRESIMS) and nuclear magnetic resonance (NMR). The absolute configurations of compounds 1–3 were determined by the X-ray single crystal diffraction and NMR data analysis. All three compounds displayed moderate cytotoxic activities toward tumor cell lines HepG2, A549, and HCT116.

GenCoF: a graphical user interface to rapidly remove human genome contaminants from metagenomic datasets

Summary

The removal of human genomic reads from shotgun metagenomic sequencing is a critical step in protecting subject privacy. Freely available tools addressing this issue require advanced programing knowledge or are limited by analytical time and data load due to their server-based nature. Here, we compared the most cited tools for host-DNA removal using synthetic and real metagenomic datasets. Then, we integrated the most efficient pipeline in a graphical user interface to make these tools available without command line use. This interface, GenCoF, rapidly removes human genome contaminants from metagenomic datasets. Additionally, the tool offers quality-filtering, data reduction and interactive modification of any parameter in order to customize the analysis. GenCoF offers both quality and host-associated filtering in a non-commercial, freely available tool in a local, interactive and easy-to-use interface.

Availability and implementation

GenCoF is freely available (under a GPL license) for Mac OS and Linux at https://github.com/MattCzajkowski/GenCoF.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Nexus Between Periodontal Inflammation and Dysbiosis

The nexus between periodontal inflammation and the polymicrobial biofilm in the gingival sulcus is critical to understanding the pathobiology of periodontitis. Both play a major role in the etiology and pathogenesis of periodontal diseases and each reinforces the other. However, this nexus is also at the center of a significant conundrum for periodontology. For all mucosal polymicrobial biofilms, the most confounding issue is the paradoxical relationship between inflammation, infection, and disease. Despite significant advances made in both periodontal microbiology and periodontal pathobiology, the issue of which comes first, the inflammatory response or the change to a dysbiotic subgingival microbiota, is still debated. In this paper, we present a model for the pathogenesis of periodontitis based on the central role of inflammation and how this modulates the polymicrobial biofilm within the context of the continuum of health, gingivitis, and periodontitis. We propose a new model termed “Inflammation-Mediated Polymicrobial-Emergence and Dysbiotic-Exacerbation” (IMPEDE), which is designed to integrate into and complement the 2017 World Workshop Classification of Periodontitis.

A genome-wide identification, characterization and functional analysis of salt-related long non-coding RNAs in non-model plant Pistacia vera L. using transcriptome high throughput sequencing

Long non-coding RNAs (lncRNAs) play crucial roles in regulating gene expression in response to plant stresses. Given the importance regulatory roles of lncRNAs, providing methods for predicting the function of these molecules, especially in non-model plants, is strongly demanded by researchers. Here, we constructed a reference sequence for lncRNAs in P. vera (Pistacia vera L.) with 53220 transcripts. In total, we identified 1909 and 2802 salt responsive lncRNAs in Ghazvini, a salt tolerant cultivar, after 6 and 24 h salt treatment, respectively and 1820 lncRNAs in Sarakhs, a salt sensitive cultivar, after 6 h salt treatment. Functional analysis of these lncRNAs by several hybrid methods, revealed that salt responsive NAT-related lncRNAs associated with transcription factors, CERK1, LEA, Laccase genes and several genes involved in the hormone signaling pathways. Moreover, gene ontology (GO) enrichment analysis of salt responsive target genes related to top five selected lncRNAs showed their involvement in the regulation of ATPase, cation transporter, kinase and UDP-glycosyltransferases genes. Quantitative real-time PCR (qRT-PCR) experiment results of lncRNAs, pre-miRNAs and mature miRNAs were in accordance with our RNA-seq analysis. In the present study, a comparative analysis of differentially expressed lncRNAs and microRNA precursors between salt tolerant and sensitive pistachio cultivars provides valuable knowledge on gene expression regulation under salt stress condition.

fusionDB: assessing microbial diversity and environmental preferences via functional similarity networks

Microbial functional diversification is driven by environmental factors, i.e. microorganisms inhabiting the same environmental niche tend to be more functionally similar than those from different environments. In some cases, even closely phylogenetically related microbes differ more across environments than across taxa. While microbial similarities are often reported in terms of taxonomic relationships, no existing databases directly link microbial functions to the environment. We previously developed a method for comparing microbial functional similarities on the basis of proteins translated from their sequenced genomes. Here, we describe fusionDB, a novel database that uses our functional data to represent 1374 taxonomically distinct bacteria annotated with available metadata: habitat/niche, preferred temperature, and oxygen use. Each microbe is encoded as a set of functions represented by its proteome and individual microbes are connected via common functions. Users can search fusionDB via combinations of organism names and metadata. Moreover, the web interface allows mapping new microbial genomes to the functional spectrum of reference bacteria, rendering interactive similarity networks that highlight shared functionality. fusionDB provides a fast means of comparing microbes, identifying potential horizontal gene transfer events, and highlighting key environment-specific functionality.

OMA standalone: orthology inference among public and custom genomes and transcriptomes

Genomes and transcriptomes are now typically sequenced by individual laboratories but analyzing them often remains challenging. One essential step in many analyses lies in identifying orthologs—corresponding genes across multiple species—but this is far from trivial. The Orthologous MAtrix (OMA) database is a leading resource for identifying orthologs among publicly available, complete genomes. Here, we describe the OMA pipeline available as a standalone program for Linux and Mac. When run on a cluster, it has native support for the LSF, SGE, PBS Pro, and Slurm job schedulers and can scale up to thousands of parallel processes. Another key feature of OMA standalone is that users can combine their own data with existing public data by exporting genomes and precomputed alignments from the OMA database, which currently contains over 2100 complete genomes. We compare OMA standalone to other methods in the context of phylogenetic tree inference, by inferring a phylogeny of Lophotrochozoa, a challenging clade within the protostomes. We also discuss other potential applications of OMA standalone, including identifying gene families having undergone duplications/losses in specific clades, and identifying potential drug targets in nonmodel organisms. OMA standalone is available under the permissive open source Mozilla Public License Version 2.0.

Metagenomic assessment of body surface bacterial communities of the sea urchin, Tripneustes gratilla

Sea urchins, including Tripneustes gratilla, are susceptible to a disease known as bald sea urchin disease, which has the potential to lead to economic losses in this emerging aquaculture industry in South Africa. This disease is characterized by lesions that form on sea urchin exoskeletal surfaces. This study aimed to characterize the body surface bacterial communities associated with T. gratilla, using a 16S rDNA gene metagenomics approach, to provide insight into the bacterial agents associated with this aquaculture species, as well as with this balding disease. Bacterial samples were collected from non-lesioned healthy animals obtained from natural locations along the eastern coast of South Africa, as well as from different cultured cohorts: non-lesioned healthy-, lesioned diseased- and non-lesioned stressed animals. A total of 1,067,515 individual bacterial operational taxonomic units (OTUs) were identified, belonging to 133 family-, 123 genus- and 113 species level OTU groups. Alpha diversity analyses, based on Chao1, Shannon and Simpson indices, showed that there were no statistically significant differences (ANOVA; P > 0.05) between the respective cohorts, as all cohorts displayed a high degree of bacterial diversity. Similarly, beta diversity analyses (Non-metric multidimensional scaling) showed a large degree of overlapping OTUs across the four cohorts. Within each cohort, various OTUs commonly associated with marine environments were found, predominantly belonging to the families Vibrionaceae, Saprospiraceae, Flavobacteriaceae and Sphingomonadaceae. Differential abundance analysis (DESeq2) revealed that OTUs that are differentially abundant across cohorts were likely not responsible for this balding disease, suggesting that complex bacterial agents, rather than a specific pathogenic agent, are likely causing this disease. Furthermore, the putative metabolic functions assigned to the bacterial communities showed that heterotrophic bacteria appear to be responsible for tissue lysis of degrading animal matter. The results from this study, obtained through univariate and multivariate-based approaches, contributes to future management strategies of this emerging aquaculture species by providing insight into the bacterial communities associated with both natural and cultured environments.

Online Interactive Microbial Classification and Geospatial Distributional Analysis Using BioAtlas

In recent decades, the accumulation of data on 16s ribosomal RNA genes has yielded free and public databases such as SILVA, GreenGenes, The Ribosomal Database Project, and IMG, handling massive amounts of raw data and meta information. 16s rRNA gene contains hypervariable regions with great classification power. As a result, numerous classification tools have emerged including state-of-the-art tools such as Mothur, Qiime, and the 16s classifier. However, there is a gap between the sequence databases, the taxonomy profiling tools and available meta information such as geo/body-location information. Here, we present BioAtlas, and interactive web tool for searching, exploring, and analyzing prokaryotic distributions by integration of various resources of metagenomics databases. In the following section we show how to use BioAtlas to (1) search and explore prokaryote occurrences across the geospatial map of the world, (2) investigate and hunt for occurrences across generic user-generated surface-specific maps, with an example map of a human female, with data from Bouslimani et al., and (3) classify a user-given sequences dataset through our online platform for visual exploration of the spatial abundances of the identified microbes.

Collinsella vaginalis sp. nov. strain Marseille-P2666T, a new member of the Collinsella genus isolated from the genital tract of a patient suffering from bacterial vaginosis

A strictly anaerobic, Gram-stain-positive, non motile and non-spore-forming rod-shaped bacterium, strain Marseille-P2666^T, was isolated using the culturomics approach from a vaginal sample of a French patient suffering from bacterial vaginosis. Cells were saccharolytic and were negative for catalase, oxidase, urease, nitrate reduction, indole production, hydrolysis of aesculin and gelatin. Strain Marseille-P2666^T exhibited 97.04 % 16S rRNA sequence similarity to Collinsella tanakaei type strain YIT 12063^T, the phylogenetically closest species with standing in nomenclature. The major fatty acids were C18:1ω9 (38 %), C16 : 0 (24 %) and C18 : 0 (19 %). The G+C content of the genome sequence of strain Marseille-P2666^T is 64.6 mol%. On the basis of its phenotypic, phylogenetic and genomic features, strain Marseille-P2666^T (=CSUR 2666^T=DSM103342^T) was classified as type strain of a novel species within the genus Collinsella for which the name Collinsella vaginalis sp. nov. is proposed.

Misprediction of Structural Disorder in Halophiles

Whereas the concept of intrinsic disorder derives from biophysical observations of the lack of structure of proteins or protein regions under native conditions, many of our respective concepts rest on proteome-scale bioinformatics predictions. It is established that most predictors work reliably on proteins commonly encountered, but it is often neglected that we know very little about their performance on proteins of microorganisms that thrive in environments of extreme temperature, pH, or salt concentration, which may cause adaptive sequence composition bias. To address this issue, we predicted structural disorder for the complete proteomes of different extremophile groups by popular prediction methods and compared them to those of the reference mesophilic group. While significant deviations from mesophiles could be explained by a lack or gain of disordered regions in hyperthermophiles and radiotolerants, respectively, we found systematic overprediction in the case of halophiles. Additionally, examples were collected from the Protein Data Bank (PDB) to demonstrate misprediction and to help understand the underlying biophysical principles, i.e., halophilic proteins maintain a highly acidic and hydrophilic surface to avoid aggregation in high salt conditions. Although sparseness of data on disordered proteins from extremophiles precludes the development of dedicated general predictors, we do formulate recommendations for how to address their disorder with current bioinformatics tools.

Multi-CSAR: a multiple reference-based contig scaffolder using algebraic rearrangements

Background

One of the important steps in the process of assembling a genome sequence from short reads is scaffolding, in which the contigs in a draft genome are ordered and oriented into scaffolds. Currently, several scaffolding tools based on a single reference genome have been developed. However, a single reference genome may not be sufficient alone for a scaffolder to generate correct scaffolds of a target draft genome, especially when the evolutionary relationship between the target and reference genomes is distant or some rearrangements occur between them. This motivates the need to develop scaffolding tools that can order and orient the contigs of the target genome using multiple reference genomes.

Results

In this work, we utilize a heuristic method to develop a new scaffolder called Multi-CSAR that is able to accurately scaffold a target draft genome based on multiple reference genomes, each of which does not need to be complete. Our experimental results on real datasets show that Multi-CSAR outperforms other two multiple reference-based scaffolding tools, Ragout and MeDuSa, in terms of many average metrics, such as sensitivity, precision, F-score, genome coverage, NGA50, scaffold number and running time.

Conclusions

Multi-CSAR is a multiple reference-based scaffolder that can efficiently produce more accurate scaffolds of a target draft genome by referring to multiple complete and/or incomplete genomes of related organisms. Its stand-alone program is available for download at https://github.com/ablab-nthu/Multi-CSAR.

Metagenomic analysis of uncultured microorganisms and their enzymatic attributes

Although second generation biofuel technology is a sustainable route for bioethanol production it is not currently a robust technology because of certain hindrances viz., unavailability of potential enzyme resources, low efficiency of enzymes and restricted availability of potent enzymes that work under harsh conditions in industrial processes. Therefore, bioprospecting of extremophilic microorganisms using metagenomics is a promising alternative to discover novel microbes and enzymes with efficient tolerance to unfavourable conditions and thus could revolutionize the energy sector. Metagenomics a recent field in "omics" technology enables the genomic study of uncultured microorganisms with the goal of better understanding microbial dynamics. Metagenomics in conjunction with NextGen Sequencing technology facilitates the sequencing of microbial DNA directly from environmental samples and has expanded, and transformed our knowledge of the microbial world. However, filtering the meaningful information from the millions of genomic sequences offers a serious challenge to bioinformaticians. The current review holds the opinion tool 'know- how' to unravel the secrets of nature while expediting the bio-industrial world. We also discuss the novel biocatalytic agents discovered through metagenomics and how bioengineering plays a pivotal role to enhance their efficiency.

Complete genome sequence of Planococcus sp. PAMC21323 isolated from Antarctica and its metabolic potential to detoxify pollutants

The Planococcus sp. PAMC21323 is a yellow pigment-producing bacterium isolated from King George Island in Antarctica; it has a broad growth temperature range of 5-40 °C. Herein, we describe the complete genome sequence information of the genus Planococcus with its annotated sequence, genetic features for bioremediation, and oxidative stress capacity. The Planococcus sp. PAMC21323 possesses chromosomal DNA (3,196,500-bp) with plasmid DNA (3364-bp). The complete 3,199,864-bp of the genome consists of 3171 genes including 60 transfer RNAs and 24 ribosomal RNAs. Strain PAMC21323 encodes various genes associated with detoxification of heavy metal ions and aromatic hydrocarbons. Moreover, it is equipped with diverse stress response systems, which can be used to sense the internal and oxidative stresses caused by detoxification. This is the first report highlighting the genetic potential of Planococcus sp. PAMC21323 in bioremediation, suggesting application of this psychrotrophic strain in bioremediation in harsh environments.

Genome sequence and description of Gracilibacillus timonensis sp. nov. strain Marseille-P2481T , a moderate halophilic bacterium isolated from the human gut microflora

Microbial culturomics represents an ongoing revolution in the characterization of the human gut microbiota. By using three culture media containing high salt concentrations (10, 15, and 20% [w/v] NaCl), we attempted an exhaustive exploration of the halophilic microbial diversity of the human gut and isolated strain Marseille‐P2481 (= CSUR P2481 =  DSM 103076), a new moderately halophilic bacterium. This bacterium is a Gram‐positive, strictly aerobic, spore‐forming rod that is motile by use of a flagellum and exhibits catalase, but not oxidase activity. Strain Marseille‐P2481 was cultivated in media containing up to 20% (w/v) NaCl, with optimal growth being obtained at 37°C, pH 7.0–8.0, and 7.5% [w/v] NaCl). The major fatty acids were 12‐methyl‐tetradecanoic acid and hexadecanoic acid. Its draft genome is 4,548,390 bp long, composed of 11 scaffolds, with a G+C content of 39.8%. It contains 4,335 predicted genes (4,266 protein coding including 89 pseudogenes and 69 RNA genes). Strain Marseille‐P2481 showed 96.57% 16S rRNA sequence similarity with Gracilibacillus alcaliphilus strain SG103^T, the phylogenetically closest species with standing in nomenclature. On the basis of its specific features, strain Marseille‐P2481^T was classified as type strain of a new species within the genus Gracilibacillus for which the name Gracilibacillus timonensis sp. nov. is formally proposed.

Genome sequence of Planktotalea frisia type strain (SH6-1T), a representative of the Roseobacter group isolated from the North Sea during a phytoplankton bloom

Planktotalea frisia SH6-1^T Hahnke et al. (Int J Syst Evol Microbiol 62:1619-24, 2012) is a planktonic marine bacterium isolated during a phytoplankton bloom from the southern North Sea. It belongs to the Roseobacter group within the alphaproteobacterial family Rhodobacteraceae. Here we describe the draft genome sequence and annotation of the type strain SH6-1^T. The genome comprises 4,106,736 bp and contains 4128 protein-coding and 38 RNA genes. The draft genome sequence provides evidence for at least three extrachromosomal elements, encodes genes for DMSP utilization, quorum sensing, photoheterotrophy and a type IV secretion system. This indicates not only adaptation to a free-living lifestyle of P. frisia but points also to interactions with prokaryotic or eukaryotic organisms.

Noncontiguous finished genome sequence and description of Mediterranea massiliensis gen. nov., sp. nov., a new member of the Bacteroidaceae family isolated from human colon

Strain Marseille-P2645T was isolated in a colon sample from a Frenchwoman who underwent a colonoscopy. Bacterial cells were Gram negative, non-spore forming, mobile and strictly anaerobic. The genome of strain Marseille-P2645T is 3 950 441 bp long and contains 3374 protein-coding genes. The DNA G+C content is of 51.66 mol%. Strain Marseille-P2645T exhibited a 92.9% sequence similarity with Bacteroides helcogenes strain P36-108T (GenBank accession no. CP002352), the phylogenetically closest species with standing in nomenclature. Strain Marseille-P2645T (= CSUR P2645 = DSM 103034) is therefore a candidate as a type species of a new genus belonging to the Bacteroidaceae family, for which the name of Mediterranea massiliensis gen. nov., sp. nov., is proposed.

Studies on lipid A isolated from Phyllobacterium trifolii PETP02T lipopolysaccharide

The structure of lipid A from lipopolysaccharide of Phyllobacterium trifolii PETP02T, a nitrogen-fixing symbiotic bacterium, was studied. It was found that the lipid A backbone was composed of two 2,3-diamino-2,3-dideoxy-D-glucose (GlcpN3N) residues connected by a β-(1 → 6) glycosidic linkage, substituted by galacturonic acid (GalpA) at position C-1 and partly decorated by a phosphate residue at C-4' of the non-reducing GlcpN3N. Both diaminosugars were symmetrically substituted by 3-hydroxy fatty acids (14:0(3-OH) and 16:0(3-OH)). Ester-linked secondary acyl residues [i.e. 19:0cyc and 28:0(27-OH) or 28:0(27-4:0(3-OMe))] were located in the distal part of lipid A. A high similarity between the lipid A of P. trifolii and Mesorhizobium was observed and discussed from the perspective of the genetic context of both genomes.

Response of the bacterial community in an on-farm biopurification system, to which diverse pesticides are introduced over an agricultural season

A biopurification system (BPS) is used on-farm to clean pesticide-contaminated wastewater. Due to high pesticide loads, a BPS represents a hot spot for the proliferation and selection as well as the genetic adaptation of discrete pesticide degrading microorganisms. However, while considerable knowledge exists on the biodegradation of specific pesticides in BPSs, the bacterial community composition of these systems has hardly been explored. In this work, the Shannon diversity, the richness and the composition of the bacterial community within an operational BPS receiving wastewater contaminated with various pesticides was, for the first time, elucidated over the course of an agricultural season, using DGGE profiling and pyrosequencing of 16S rRNA gene fragments amplified from total community DNA. During the agricultural season, an increase in the concentration of pesticides in the BPS was observed along with the detection of significant community changes including a decrease in microbial diversity. Additionally, a significant increase in the relative abundance of Proteobacteria, mainly the Gammaproteobacteria, was found, and OTUs (operational taxonomic units) affiliated to Pseudomonas responded positively during the course of the season. Furthermore, a banding-pattern analysis of 16S rRNA gene-based DGGE fingerprinting, targeting the Alpha- and Betaproteobacteria as well as the Actinobacteria, indicated that the Betaproteobacteria might play an important role. Interestingly, a decrease of Firmicutes and Bacteroidetes was observed, indicating their selective disadvantage in a BPS, to which pesticides have been introduced.

Capturing the genetic makeup of the active microbiome in situ

More than any other technology, nucleic acid sequencing has enabled microbial ecology studies to be complemented with the data volumes necessary to capture the extent of microbial diversity and dynamics in a wide range of environments. In order to truly understand and predict environmental processes, however, the distinction between active, inactive and dead microbial cells is critical. Also, experimental designs need to be sensitive toward varying population complexity and activity, and temporal as well as spatial scales of process rates. There are a number of approaches, including single-cell techniques, which were designed to study in situ microbial activity and that have been successively coupled to nucleic acid sequencing. The exciting new discoveries regarding in situ microbial activity provide evidence that future microbial ecology studies will indispensably rely on techniques that specifically capture members of the microbiome active in the environment. Herein, we review those currently used activity-based approaches that can be directly linked to shotgun nucleic acid sequencing, evaluate their relevance to ecology studies, and discuss future directions.

A Robust Framework for Microbial Archaeology

Microbial archaeology is flourishing in the era of high-throughput sequencing, revealing the agents behind devastating historical plagues, identifying the cryptic movements of pathogens in prehistory, and reconstructing the ancestral microbiota of humans. Here, we introduce the fundamental concepts and theoretical framework of the discipline, then discuss applied methodologies for pathogen identification and microbiome characterization from archaeological samples. We give special attention to the process of identifying, validating, and authenticating ancient microbes using high-throughput DNA sequencing data. Finally, we outline standards and precautions to guide future research in the field.

Draft genome sequences of strains Salinicola socius SMB35T, Salinicola sp. MH3R3-1 and Chromohalobacter sp. SMB17 from the Verkhnekamsk potash mining region of Russia

Halomonads are moderately halophilic bacteria that are studied as models of prokaryotic osmoadaptation and sources of enzymes and chemicals for biotechnological applications. Despite the progress in understanding the diversity of these organisms, our ability to explain ecological, metabolic, and biochemical traits of halomonads at the genomic sequence level remains limited. This study addresses this gap by presenting draft genomes of Salinicola socius SMB35^T, Salinicola sp. MH3R3–1 and Chromohalobacter sp. SMB17, which were isolated from potash mine tailings in the Verkhnekamsk salt deposit area of Russia. The analysis of these genomes confirmed the importance of ectoines and quaternary amines to the capacity of halomonads to tolerate osmotic stress and adapt to hypersaline environments. The study also revealed that Chromohalobacter and Salinicola share 75–90% of the predicted proteome, but also harbor a set of genus-specific genes, which in Salinicola amounted to approximately 0.5 Mbp. These genus-specific genome segments may contribute to the phenotypic diversity of the Halomonadaceae and the ability of these organisms to adapt to changing environmental conditions and colonize new ecological niches.

High-quality draft genome sequence of a biofilm forming lignocellulolytic Aspergillus niger strain ATCC 10864

Filamentous fungus Aspergillus niger has high industrial value due to their lignocellulolytic enzyme activities and ATCC 10864 is one of the few type strains of A. niger which has a unique biofilm forming capability. Here we report the first draft genome sequence of A. niger ATCC 10864 strain. The genome of A. niger ATCC 10864 is 36,172,237 bp long and comprise of 310 scaffolds with 49.5% average GC content. A total of 10,804 protein-coding genes were predicted among which 10,761 genes were with putative functions. A. niger ATCC 10864 genome coded for 709 putative carbohydrate active enzyme families distributed in six functional categories and among them glycoside hydrolases (GHs) represent the most number of families (279). Genes that include pepA, brlA, exgA, LaeA, rodA, GCN have also been identified in this study, which may play a role in biofilm formation. This high-quality draft genome sequence will facilitate our understanding of the mechanisms behind fungal biofilm formation and higher lignocellulolytic enzyme production.

An Efficient Approach to Explore and Discriminate Anomalous Regions in Bacterial Genomes Based on Maximum Entropy

Recently, there has been an increase in the number of whole bacterial genomes sequenced, mainly due to the advancing of next-generation sequencing technologies. In face of this, there is a need to provide new analytical alternatives that can follow this advance. Given our current knowledge about the genomic plasticity of bacteria and that those genomic regions can uncover important features about this microorganism, our goal was to develop a fast methodology based on maximum entropy (ME) to guide the researcher to regions that could be prioritized during the analysis. This methodology was compared with other available methods. In addition, ME was applied to eight different bacterial genera. The methodology consists of two main steps: processing the nucleotide sequence and ME calculation. We applied ME to Xanthomonas axonopodis pv. citri 306 (XAC) and Xanthomonas campestris pv. campestris ATCC 33913 (XCC), both of which have their anomalous regions well documented. We then compared our results against those from Alien Hunter, HGT-DB, Islander, IslandPath, and SIGI-HMM. ME was shown to be superior in terms of efficiency and analysis duration. Besides, ME only needs the genome sequence in FASTA format as input. The proposed strategy based on ME is able to help in bacterial genome exploration. This is a simple and fast strategy for individual genomes in comparison with other available methods, without relying on previous annotation and alignments. This methodology can also be a new option in the early stages of analysis of newly sequenced bacterial genomes.

Pro-resolving mediators in the regulation of periodontal disease

Periodontitis is an inflammatory disease of the supporting structures of the dentition that is initiated by bacteria that form a biofilm on the surface of the teeth. The pathogenesis of the disease is a result of complex interactions between the biofilm and the host response that results in dysbiosis of the microbiome and dysregulation of the inflammatory response. Current data suggest that the excess inflammation associated with periodontitis is due to a failure of resolution of inflammation pathways. In this review, the relationship between inflammation and microbial dysbiosis is examined in the context of pro-inflammation and pro-resolution mediators and their ability to modify the course of disease. The impact of local oral inflammation on systemic inflammation and the relationship of periodontitis to other inflammatory diseases, including type 2 diabetes and cardiovascular disease is reviewed. Active resolvers of inflammation, including the lipoxins and resolvins, show great promise as therapeutics for the treatment of periodontitis and other inflammatory diseases.

Permanent Draft Genome Sequence of Desulfurococcus amylolyticus Strain Z-533T, a Peptide and Starch Degrader Isolated from Thermal Springs in the Kamchatka Peninsula and Kunashir Island, Russia

Desulfurococcus amylolyticus Z-533^T, a hyperthermophilic crenarcheon, ferments peptide and starch, generating acetate, isobutyrate, isovalerate, CO₂, and hydrogen. Unlike D. amylolyticus Z-1312, it cannot use cellulose and is inhibited by hydrogen. The reported draft genome sequence of D. amylolyticus Z-533^T will help to understand the molecular basis for these differences.

Fluxomics links cellular functional analyses to whole-plant phenotyping

Fluxes through metabolic pathways reflect the integration of genetic and metabolic regulations. While it is attractive to measure all the mRNAs (transcriptome), all the proteins (proteome), and a large number of the metabolites (metabolome) in a given cellular system, linking and integrating this information remains difficult. Measurement of metabolome-wide fluxes (termed the fluxome) provides an integrated functional output of the cell machinery and a better tool to link functional analyses to plant phenotyping. This review presents and discusses sets of methodologies that have been developed to measure the fluxome. First, the principles of metabolic flux analysis (MFA), its 'short time interval' version Inst-MFA, and of constraints-based methods, such as flux balance analysis and kinetic analysis, are briefly described. The use of these powerful methods for flux characterization at the cellular scale up to the organ (fruits, seeds) and whole-plant level is illustrated. The added value given by fluxomics methods for unravelling how the abiotic environment affects flux, the process, and key metabolic steps are also described. Challenges associated with the development of fluxomics and its integration with 'omics' for thorough plant and organ functional phenotyping are discussed. Taken together, these will ultimately provide crucial clues for identifying appropriate target plant phenotypes for breeding.

High-quality permanent draft genome sequence of the Bradyrhizobium elkanii type strain USDA 76T, isolated from Glycine max (L.) Merr

Bradyrhizobium elkanii USDA 76^T (INSCD = ARAG00000000), the type strain for Bradyrhizobium elkanii, is an aerobic, motile, Gram-negative, non-spore-forming rod that was isolated from an effective nitrogen-fixing root nodule of Glycine max (L. Merr) grown in the USA. Because of its significance as a microsymbiont of this economically important legume, B. elkanii USDA 76^T was selected as part of the DOE Joint Genome Institute 2010 Genomic Encyclopedia for Bacteria and Archaea-Root Nodule Bacteria sequencing project. Here the symbiotic abilities of B. elkanii USDA 76^T are described, together with its genome sequence information and annotation. The 9,484,767 bp high-quality draft genome is arranged in 2 scaffolds of 25 contigs, containing 9060 protein-coding genes and 91 RNA-only encoding genes. The B. elkanii USDA 76^T genome contains a low GC content region with symbiotic nod and fix genes, indicating the presence of a symbiotic island integration. A comparison of five B. elkanii genomes that formed a clique revealed that 356 of the 9060 protein coding genes of USDA 76^T were unique, including 22 genes of an intact resident prophage. A conserved set of 7556 genes were also identified for this species, including genes encoding a general secretion pathway as well as type II, III, IV and VI secretion system proteins. The type III secretion system has previously been characterized as a host determinant for Rj and/or rj soybean cultivars. Here we show that the USDA 76^T genome contains genes encoding all the type III secretion system components, including a translocon complex protein NopX required for the introduction of effector proteins into host cells. While many bradyrhizobial strains are unable to nodulate the soybean cultivar Clark (rj1), USDA 76^T was able to elicit nodules on Clark (rj1), although in reduced numbers, when plants were grown in Leonard jars containing sand or vermiculite. In these conditions, we postulate that the presence of NopX allows USDA 76^T to introduce various effector molecules into this host to enable nodulation.

High quality draft genome sequence of an extremely halophilic archaeon Natrinema altunense strain AJ2T

Natrinema altunense strain AJ2T, a halophilic archaeal strain, was isolated from a high-altitude (3884 m) salt lake in Xinjiang, China. This strain requires at least 1.7 M NaCl to grow and can grow anaerobically in the presence of nitrate. To understand the genetics underlying its extreme phenotype, we de novo assembled the entire genome sequence of AJ2T (=CGMCC 1.3731T=JCM 12890T). We assembled 3,774,135 bp of a total of 4.4 Mb genome in only 20 contigs and noted its high GC content (64.6%). Subsequently we predicted the gene content and generated genome annotation to identify the relationship between the epigenetic characteristics and genomic features. The genome sequence contains 52 tRNA genes, 3 rRNA genes and 4,462 protein-coding genes, 3792 assigned as functional or hypothetical proteins in nr database. This Whole Genome Shotgun project was deposited in DDBJ/EMBL/GenBank under the accession JNCS00000000. We performed a Bayesian (Maximum-Likelihood) phylogenetic analysis using 16S rRNA sequence and obtained its relationship to other strains in the Natrinema and Haloterrigena genera. We also confirmed the ANI value between every two species of Natrinema and Haloterrigena genera. In conclusion, our analysis furthered our understanding of the extreme-environment adapted strain AJ2T by characterizing its genome structure, gene content and phylogenetic placement. Our detailed case study will contribute to our overall understanding of why Natrinema strains can survive in such a high-altitude salt lake.

Analytical Biases Associated with GC-Content in Molecular Evolution

Molecular evolution is being revolutionized by high-throughput sequencing allowing an increased amount of genome-wide data available for multiple species. While base composition summarized by GC-content is one of the first metrics measured in genomes, its genomic distribution is a frequently neglected feature in downstream analyses based on DNA sequence comparisons. Here, we show how base composition heterogeneity among loci and taxa can bias common molecular evolution analyses such as phylogenetic tree reconstruction, detection of natural selection and estimation of codon usage. We then discuss the biological, technical and methodological causes of these GC-associated biases and suggest approaches to overcome them.

Accessing the genomic information of unculturable oceanic picoeukaryotes by combining multiple single cells

Pico-sized eukaryotes play key roles in the functioning of marine ecosystems, but we still have a limited knowledge on their ecology and evolution. The MAST-4 lineage is of particular interest, since it is widespread in surface oceans, presents ecotypic differentiation and has defied culturing efforts so far. Single cell genomics (SCG) are promising tools to retrieve genomic information from these uncultured organisms. However, SCG are based on whole genome amplification, which normally introduces amplification biases that limit the amount of genomic data retrieved from a single cell. Here, we increase the recovery of genomic information from two MAST-4 lineages by co-assembling short reads from multiple Single Amplified Genomes (SAGs) belonging to evolutionary closely related cells. We found that complementary genomic information is retrieved from different SAGs, generating co-assembly that features >74% of genome recovery, against about 20% when assembled individually. Even though this approach is not aimed at generating high-quality draft genomes, it allows accessing to the genomic information of microbes that would otherwise remain unreachable. Since most of the picoeukaryotes still remain uncultured, our work serves as a proof-of-concept that can be applied to other taxa in order to extract genomic data and address new ecological and evolutionary questions.

Permanent draft genome of Thiobacillus thioparus DSM 505T, an obligately chemolithoautotrophic member of the Betaproteobacteria

Thiobacillus thioparus DSM 505^T is one of first two isolated strains of inorganic sulfur-oxidising Bacteria. The original strain of T. thioparus was lost almost 100 years ago and the working type strain is Culture C^T (=DSM 505^T = ATCC 8158^T) isolated by Starkey in 1934 from agricultural soil at Rutgers University, New Jersey, USA. It is an obligate chemolithoautotroph that conserves energy from the oxidation of reduced inorganic sulfur compounds using the Kelly-Trudinger pathway and uses it to fix carbon dioxide It is not capable of heterotrophic or mixotrophic growth. The strain has a genome size of 3,201,518 bp. Here we report the genome sequence, annotation and characteristics. The genome contains 3,135 protein coding and 62 RNA coding genes. Genes encoding the transaldolase variant of the Calvin-Benson-Bassham cycle were also identified and an operon encoding carboxysomes, along with Smith’s biosynthetic horseshoe in lieu of Krebs’ cycle sensu stricto. Terminal oxidases were identified, viz. cytochrome c oxidase (cbb3, EC 1.9.3.1) and ubiquinol oxidase (bd, EC 1.10.3.10). There is a partial sox operon of the Kelly-Friedrich pathway of inorganic sulfur-oxidation that contains soxXYZAB genes but lacking soxCDEF, there is also a lack of the DUF302 gene previously noted in the sox operon of other members of the ‘Proteobacteria’ that can use trithionate as an energy source. In spite of apparently not growing anaerobically with denitrification, the nar, nir, nor and nos operons encoding enzymes of denitrification are found in the T. thioparus genome, in the same arrangements as in the true denitrifier T. denitrificans.