BusyBee Web: metagenomic data analysis by bootstrapped supervised binning and annotation

Solving genomic puzzles: computational methods for metagenomic binning

Metagenomics involves the study of genetic material obtained directly from communities of microorganisms living in natural environments. The field of metagenomics has provided valuable insights into the structure, diversity and ecology of microbial communities. Once an environmental sample is sequenced and processed, metagenomic binning clusters the sequences into bins representing different taxonomic groups such as species, genera, or higher levels. Several computational tools have been developed to automate the process of metagenomic binning. These tools have enabled the recovery of novel draft genomes of microorganisms allowing us to study their behaviors and functions within microbial communities. This review classifies and analyzes different approaches of metagenomic binning and different refinement, visualization, and evaluation techniques used by these methods. Furthermore, the review highlights the current challenges and areas of improvement present within the field of research.

AFITbin: a metagenomic contig binning method using aggregate l-mer frequency based on initial and terminal nucleotides

BACKGROUND

Using next-generation sequencing technologies, scientists can sequence complex microbial communities directly from the environment. Significant insights into the structure, diversity, and ecology of microbial communities have resulted from the study of metagenomics. The assembly of reads into longer contigs, which are then binned into groups of contigs that correspond to different species in the metagenomic sample, is a crucial step in the analysis of metagenomics. It is necessary to organize these contigs into operational taxonomic units (OTUs) for further taxonomic profiling and functional analysis. For binning, which is synonymous with the clustering of OTUs, the tetra-nucleotide frequency (TNF) is typically utilized as a compositional feature for each OTU.

RESULTS

In this paper, we present AFIT, a new l-mer statistic vector for each contig, and AFITBin, a novel method for metagenomic binning based on AFIT and a matrix factorization method. To evaluate the performance of the AFIT vector, the t-SNE algorithm is used to compare species clustering based on AFIT and TNF information. In addition, the efficacy of AFITBin is demonstrated on both simulated and real datasets in comparison to state-of-the-art binning methods such as MetaBAT 2, MaxBin 2.0, CONCOT, MetaCon, SolidBin, BusyBee Web, and MetaBinner. To further analyze the performance of the purposed AFIT vector, we compare the barcodes of the AFIT vector and the TNF vector.

CONCLUSION

The results demonstrate that AFITBin shows superior performance in taxonomic identification compared to existing methods, leveraging the AFIT vector for improved results in metagenomic binning. This approach holds promise for advancing the analysis of metagenomic data, providing more reliable insights into microbial community composition and function.

AVAILABILITY

A python package is available at: https://github.com/SayehSobhani/AFITBin .

Revealing microbiota characteristics and predicting flavor-producing sub-communities in Nongxiangxing baijiu pit mud through metagenomic analysis and metabolic modeling

The microorganisms of the pit mud (PM) of Nongxiangxing baijiu (NXXB) have an important role in the synthesis of flavor substances, and they determine attributes and quality of baijiu. Herein, we utilize metagenomics and genome-scale metabolic models (GSMMs) to investigate the microbial composition, metabolic functions in PM microbiota, as well as to identify microorganisms and communities linked to flavor compounds. Metagenomic data revealed that the most prevalent assembly of bacteria and archaea was Proteiniphilum, Caproicibacterium, Petrimonas, Lactobacillus, Clostridium, Aminobacterium, Syntrophomonas, Methanobacterium, Methanoculleus, and Methanosarcina. The important enzymes ofPMwere in bothGH and GT familymetabolism. A total of 38 high-quality metagenome-assembled genomes (MAGs) were obtained, including those at the family level (n = 13), genus level (n = 17), and species level (n = 8). GSMMs of the 38 MAGs were then constructed. From the GSMMs, individual and community capabilities respectively were predicted to be able to produce 111 metabolites and 598 metabolites. Twenty-three predicted metabolites were consistent with the metabonomics detected flavors and served as targets. Twelve sub-community of were screened by cross-feeding of 38 GSMMs. Of them, Methanobacterium, Sphaerochaeta, Muricomes intestini, Methanobacteriaceae, Synergistaceae, and Caloramator were core microorganisms for targets in each sub-community. Overall, this study of metagenomic and target-community screening could help our understanding of the metabolite-microbiome association and further bioregulation of baijiu.

Microbiomes, diet flexibility, and the spread of a beetle parasite of honey bees

Invasive pests may disturb and destructively reformat the local ecosystem. The small hive beetle (SHB), Aethina tumida, originated in Africa and has expanded to America, Australia, Europe, and Asia. A key factor facilitating its fast global expansion is its ability to subsist on diverse food inside and outside honey bee colonies. SHBs feed on various plant fruits and exudates in the environment while searching for bee hives. After sneaking into a bee hive, they switch their diet to honey, pollen, and bee larvae. How SHBs survive on such a broad range of food remains unclear. In this study, we simulated the outside and within hive stages by providing banana and hive resources and quantified the SHB associated microbes adjusted by the diet. We found that SHBs fed on bananas were colonized by microbes coding more carbohydrate-active enzymes and a higher alpha diversity than communities from SHBs feeding on hive products or those collected directly from bee hives. SHBs fed on bananas and those collected from the hive showed high symbiont variance, indicated by the beta diversity. Surprisingly, we found the honey bee core symbiont Snodgrassella alvi in the guts of SHBs collected in bee hives. To determine the role of S. alvi in SHB biology, we inoculated SHBs with a genetically tagged culture of S. alvi, showing that this symbiont is a likely transient of SHBs. In contrast, the fungus Kodamaea ohmeri is the primary commensal of SHBs. Diet-based microbiome shifts are likely to play a key role in the spread and success of SHBs.

Investigation of the Microbiome of Industrial PDO Sfela Cheese and Its Artisanal Variants Using 16S rDNA Amplicon Sequencing and Shotgun Metagenomics

Sfela is a white brined Greek cheese of protected designation of origin (PDO) produced in the Peloponnese region from ovine, caprine milk, or a mixture of the two. Despite the PDO status of Sfela, very few studies have addressed its properties, including its microbiology. For this reason, we decided to investigate the microbiome of two PDO industrial Sfela cheese samples along with two non-PDO variants, namely Sfela touloumotiri and Xerosfeli. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), 16S rDNA amplicon sequencing and shotgun metagenomics analysis were used to identify the microbiome of these traditional cheeses. Cultured-based analysis showed that the most frequent species that could be isolated from Sfela cheese were Enterococcus faecium, Lactiplantibacillus plantarum, Levilactobacillus brevis, Pediococcus pentosaceus and Streptococcus thermophilus. Shotgun analysis suggested that in industrial Sfela 1, Str. thermophilus dominated, while industrial Sfela 2 contained high levels of Lactococcus lactis. The two artisanal samples, Sfela touloumotiri and Xerosfeli, were dominated by Tetragenococcus halophilus and Str. thermophilus, respectively. Debaryomyces hansenii was the only yeast species with abundance > 1% present exclusively in the Sfela touloumotiri sample. Identifying additional yeast species in the shotgun data was challenging, possibly due to their low abundance. Sfela cheese appears to contain a rather complex microbial ecosystem and thus needs to be further studied and understood. This might be crucial for improving and standardizing both its production and safety measures.

BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes

BACKGROUND

Exploring metagenomic contigs and "binning" them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure.

RESULTS

We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena's usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset.

CONCLUSIONS

BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena , together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. Video Abstract.

Genomic Assessment of the Contribution of the Wolbachia Endosymbiont of Eurosta solidaginis to Gall Induction

We explored the genome of the Wolbachia strain, wEsol, symbiotic with the plant-gall-inducing fly Eurosta solidaginis with the goal of determining if wEsol contributes to gall induction by its insect host. Gall induction by insects has been hypothesized to involve the secretion of the phytohormones cytokinin and auxin and/or proteinaceous effectors to stimulate cell division and growth in the host plant. We sequenced the metagenome of E. solidaginis and wEsol and assembled and annotated the genome of wEsol. The wEsol genome has an assembled length of 1.66 Mbp and contains 1878 protein-coding genes. The wEsol genome is replete with proteins encoded by mobile genetic elements and shows evidence of seven different prophages. We also detected evidence of multiple small insertions of wEsol genes into the genome of the host insect. Our characterization of the genome of wEsol indicates that it is compromised in the synthesis of dimethylallyl pyrophosphate (DMAPP) and S-adenosyl L-methionine (SAM), which are precursors required for the synthesis of cytokinins and methylthiolated cytokinins. wEsol is also incapable of synthesizing tryptophan, and its genome contains no enzymes in any of the known pathways for the synthesis of indole-3-acetic acid (IAA) from tryptophan. wEsol must steal DMAPP and L-methionine from its host and therefore is unlikely to provide cytokinin and auxin to its insect host for use in gall induction. Furthermore, in spite of its large repertoire of predicted Type IV secreted effector proteins, these effectors are more likely to contribute to the acquisition of nutrients and the manipulation of the host's cellular environment to contribute to growth and reproduction of wEsol than to aid E. solidaginis in manipulating its host plant. Combined with earlier work that shows that wEsol is absent from the salivary glands of E. solidaginis, our results suggest that wEsol does not contribute to gall induction by its host.

The toxins of vertically transmitted Spiroplasma

Vertically transmitted (VT) microbial symbionts play a vital role in the evolution of their insect hosts. A longstanding question in symbiont research is what genes help promote long-term stability of vertically transmitted lifestyles. Symbiont success in insect hosts is due in part to expression of beneficial or manipulative phenotypes that favor symbiont persistence in host populations. In Spiroplasma, these phenotypes have been linked to toxin and virulence domains among a few related strains. However, these domains also appear frequently in phylogenetically distant Spiroplasma, and little is known about their distribution across the Spiroplasma genus. In this study, we present the complete genome sequence of the Spiroplasma symbiont of Drosophila atripex, a non-manipulating member of the Ixodetis clade of Spiroplasma, for which genomic data are still limited. We perform a genus-wide comparative analysis of toxin domains implicated in defensive and reproductive phenotypes. From 12 VT and 31 non-VT Spiroplasma genomes, ribosome-inactivating proteins (RIPs), OTU-like cysteine proteases (OTUs), ankyrins, and ETX/MTX2 domains show high propensity for VT Spiroplasma compared to non-VT Spiroplasma. Specifically, OTU and ankyrin domains can be found only in VT-Spiroplasma, and RIP domains are found in all VT Spiroplasma and three non-VT Spiroplasma. These domains are frequently associated with Spiroplasma plasmids, suggesting a possible mechanism for dispersal and maintenance among heritable strains. Searching insect genome assemblies available on public databases uncovered uncharacterized Spiroplasma genomes from which we identified several spaid-like genes encoding RIP, OTU, and ankyrin domains, suggesting functional interactions among those domain types. Our results suggest a conserved core of symbiont domains play an important role in the evolution and persistence of VT Spiroplasma in insects.

Translational informatics for human microbiota: data resources, models and applications

With the rapid development of human intestinal microbiology and diverse microbiome-related studies and investigations, a large amount of data have been generated and accumulated. Meanwhile, different computational and bioinformatics models have been developed for pattern recognition and knowledge discovery using these data. Given the heterogeneity of these resources and models, we aimed to provide a landscape of the data resources, a comparison of the computational models and a summary of the translational informatics applied to microbiota data. We first review the existing databases, knowledge bases, knowledge graphs and standardizations of microbiome data. Then, the high-throughput sequencing techniques for the microbiome and the informatics tools for their analyses are compared. Finally, translational informatics for the microbiome, including biomarker discovery, personalized treatment and smart healthcare for complex diseases, are discussed.

Cuticle supplementation and nitrogen recycling by a dual bacterial symbiosis in a family of xylophagous beetles

Many insects engage in stable nutritional symbioses with bacteria that supplement limiting essential nutrients to their host. While several plant sap-feeding Hemipteran lineages are known to be simultaneously associated with two or more endosymbionts with complementary biosynthetic pathways to synthesize amino acids or vitamins, such co-obligate symbioses have not been functionally characterized in other insect orders. Here, we report on the characterization of a dual co-obligate, bacteriome-localized symbiosis in a family of xylophagous beetles using comparative genomics, fluorescence microscopy, and phylogenetic analyses. Across the beetle family Bostrichidae, most investigated species harbored the Bacteroidota symbiont Shikimatogenerans bostrichidophilus that encodes the shikimate pathway to produce tyrosine precursors in its severely reduced genome, likely supplementing the beetles' cuticle biosynthesis, sclerotisation, and melanisation. One clade of Bostrichid beetles additionally housed the co-obligate symbiont Bostrichicola ureolyticus that is inferred to complement the function of Shikimatogenerans by recycling urea and provisioning the essential amino acid lysine, thereby providing additional benefits on nitrogen-poor diets. Both symbionts represent ancient associations within the Bostrichidae that have subsequently experienced genome erosion and co-speciation with their hosts. While Bostrichicola was repeatedly lost, Shikimatogenerans has been retained throughout the family and exhibits a perfect pattern of co-speciation. Our results reveal that co-obligate symbioses with complementary metabolic capabilities occur beyond the well-known sap-feeding Hemiptera and highlight the importance of symbiont-mediated cuticle supplementation and nitrogen recycling for herbivorous beetles.

Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses

Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens.

Recovery and Analysis of Long-Read Metagenome-Assembled Genomes

The development of long-read nucleic acid sequencing is beginning to make very substantive impact on the conduct of metagenome analysis, particularly in relation to the problem of recovering the genomes of member species of complex microbial communities. Here we outline bioinformatics workflows for the recovery and characterization of complete genomes from long-read metagenome data and some complementary procedures for comparison of cognate draft genomes and gene quality obtained from short-read sequencing and long-read sequencing.

Contamination detection and microbiome exploration with GRIMER

BACKGROUND

Contamination detection is a important step that should be carefully considered in early stages when designing and performing microbiome studies to avoid biased outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass samples or in studies lacking proper controls. Interactive visualizations and analysis platforms are crucial to better guide this step, to help to identify and detect noisy patterns that could potentially be contamination. Additionally, external evidence, like aggregation of several contamination detection methods and the use of common contaminants reported in the literature, could help to discover and mitigate contamination.

RESULTS

We propose GRIMER, a tool that performs automated analyses and generates a portable and interactive dashboard integrating annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect contamination. GRIMER is independent of quantification methods and directly analyzes contingency tables to create an interactive and offline report. Reports can be created in seconds and are accessible for nonspecialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled and used an extensive list of possible external contaminant taxa and common contaminants with 210 genera and 627 species reported in 22 published articles.

CONCLUSION

GRIMER enables visual data exploration and analysis, supporting contamination detection in microbiome studies. The tool and data presented are open source and available at https://gitlab.com/dacs-hpi/grimer.

Non-random genetic alterations in the cyanobacterium Nostoc sp. exposed to space conditions

Understanding the impact of long-term exposure of microorganisms to space is critical in understanding how these exposures impact the evolution and adaptation of microbial life under space conditions. In this work we subjected Nostoc sp. CCCryo 231-06, a cyanobacterium capable of living under many different ecological conditions, and also surviving in extreme ones, to a 23-month stay at the International Space Station (the Biology and Mars Experiment, BIOMEX, on the EXPOSE-R2 platform) and returned it to Earth for single-cell genome analysis. We used microfluidic technology and single cell sequencing to identify the changes that occurred in the whole genome of single Nostoc cells. The variant profile showed that biofilm and photosystem associated loci were the most altered, with an increased variant rate of synonymous base pair substitutions. The cause(s) of these non-random alterations and their implications to the evolutionary potential of single bacterial cells under long-term cosmic exposure warrants further investigation.

Wolbachia causes cytoplasmic incompatibility but not male-killing in a grain pest beetle

The endosymbiotic Wolbachia is one of the most common intracellular bacteria known in arthropods and nematodes. Its ability for reproductive manipulation can cause unequal inheritance to male and female offspring, allowing the manipulator to spread, but potentially also impact the evolutionary dynamics of infected hosts. Estimated to be present in up to 66% of insect species, little is known about the phenotypic impact of Wolbachia within the order Coleoptera. Here, we describe the reproductive manipulation by the Wolbachia strain wSur harboured by the sawtoothed grain beetle Oryzaephilus surinamensis (Coleoptera, Silvanidae), through a combination of genomics approaches and bioassays. The Wolbachia strain wSur belongs to supergroup B that contains well-described reproductive manipulators of insects and encodes a pair of cytoplasmic incompatibility factor (cif) genes, as well as multiple homologues of the WO-mediated killing (wmk) gene. A phylogenetic comparison with wmk homologues of wMel of Drosophila melanogaster identified 18 wmk copies in wSur, including one that is closely related to the wMel male-killing homologue. However, further analysis of this particular wmk gene revealed an eight-nucleotide deletion leading to a stop-codon and subsequent reading frame shift midsequence, probably rendering it nonfunctional. Concordantly, utilizing a Wolbachia-deprived O. surinamensis population and controlled mating pairs of wSur-infected and noninfected partners, we found no experimental evidence for male-killing. However, a significant ~50% reduction of hatching rates in hybrid crosses of uninfected females with infected males indicates that wSur is causing cytoplasmic incompatibility. Thus, Wolbachia also represents an important determinant of host fitness in Coleoptera.

Microbial communities of stratified aquatic ecosystems of Kandalaksha Bay (White Sea) shed light on the evolutionary history of green and brown morphotypes of Chlorobiota

Anoxygenic photoautotrophic metabolism of green sulfur bacteria of the family Chlorobiaceae played a significant role in establishing the Earth's biosphere. Two known major ecological forms of these phototrophs differ in their pigment composition and, therefore, in color: the green and brown forms. The latter form often occurs in low-light environments and is specialized to harvest blue light, which can penetrate to the greatest depth in the water column. In the present work, metagenomic sequencing was used to investigate the natural population of brown Chl. phaeovibrioides ZM in a marine stratified Zeleny Mys lagoon in the Kandalaksha Bay (the White Sea) to supplement the previously obtained genomes of brown Chlorobiaceae. The genomes of brown and green Chlorobiaceae were investigated using comparative genome analysis and phylogenetic and reconciliation analysis to reconstruct the evolution of these ecological forms. Our results support the suggestion that the last common ancestor of Chlorobiaceae belonged to the brown form, i.e. it was adapted to the conditions of low illumination. However, despite the vertical inheritance of these characteristics, among modern Chlorobiaceae populations, the genes responsible for synthesizing the pigments of the brown form are subject to active horizontal transfer.

Detection of interphylum transfers of the magnetosome gene cluster in magnetotactic bacteria

Magnetosome synthesis in magnetotactic bacteria (MTB) is regarded as a very ancient evolutionary process that dates back to deep-branching phyla. Magnetotactic bacteria belonging to one of such phyla, Nitrospirota, contain the classical genes for the magnetosome synthesis (e.g., mam, mms) and man genes, which were considered to be specific for this group. However, the recent discovery of man genes in MTB from the Thermodesulfobacteriota phylum has raised several questions about the inheritance of these genes in MTB. In this work, three new man genes containing MTB genomes affiliated with Nitrospirota and Thermodesulfobacteriota, were obtained. By applying reconciliation with these and the previously published MTB genomes, we demonstrate that the last common ancestor of all Nitrospirota was most likely not magnetotactic as assumed previously. Instead, our findings suggest that the genes for magnetosome synthesis were transmitted to the phylum Nitrospirota by horizontal gene transfer (HGT), which is the first case of the interphylum transfer of magnetosome genes detected to date. Furthermore, we provide evidence for the HGT of magnetosome genes from the Magnetobacteriaceae to the Dissulfurispiraceae family within Nitrospirota. Thus, our results imply a more significant role of HGT in the MTB evolution than deemed before and challenge the hypothesis of the ancient origin of magnetosome synthesis.

Binning long reads in metagenomics datasets using composition and coverage information

Background

Advancements in metagenomics sequencing allow the study of microbial communities directly from their environments. Metagenomics binning is a key step in the species characterisation of microbial communities. Next-generation sequencing reads are usually assembled into contigs for metagenomics binning mainly due to the limited information within short reads. Third-generation sequencing provides much longer reads that have lengths similar to the contigs assembled from short reads. However, existing contig-binning tools cannot be directly applied on long reads due to the absence of coverage information and the presence of high error rates. The few existing long-read binning tools either use only composition or use composition and coverage information separately. This may ignore bins that correspond to low-abundance species or erroneously split bins that correspond to species with non-uniform coverages. Here we present a reference-free binning approach, LRBinner, that combines composition and coverage information of complete long-read datasets. LRBinner also uses a distance-histogram-based clustering algorithm to extract clusters with varying sizes.

Results

The experimental results on both simulated and real datasets show that LRBinner achieves the best binning accuracy in most cases while handling the complete datasets without any sampling. Moreover, we show that binning reads using LRBinner prior to assembly reduces computational resources required for assembly while attaining satisfactory assembly qualities.

Conclusion

LRBinner shows that deep-learning techniques can be used for effective feature aggregation to support the metagenomics binning of long reads. Furthermore, accurate binning of long reads supports improvements in metagenomics assembly, especially in complex datasets. Binning also helps to reduce the resources required for assembly. Source code for LRBinner is freely available at https://github.com/anuradhawick/LRBinner.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13015-022-00221-z.

Comparison of the Microbiome of Artisanal Homemade and Industrial Feta Cheese through Amplicon Sequencing and Shotgun Metagenomics

Feta is the most renowned protected designation of origin (PDO) white brined cheese produced in Greece. The fine organoleptic characteristics and the quality of Feta rely on, among other factors, its overall microbial ecosystem. In this study, we employed 16S rDNA and internal transcribed spacer (ITS) amplicon sequencing, as well as shotgun metagenomics, to investigate the microbiome of artisanal homemade and industrial Feta cheese samples from different regions of Greece, which has very rarely been investigated. 16S rDNA data suggested the prevalence of the Lactococcus genus in the homemade samples, while Streptococcus and Lactobacillus genera prevailed in the industrial control samples. Species identification deriving from shotgun metagenomics corroborated these findings, as Lactococcus lactis dominated two homemade samples while Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus were found to be dominating one industrial sample. ITS data revealed a complex diversity of the yeast population among the samples analyzed. Debaryomyces, Kluyveromyces, Cutaneotrichosporon, Pichia, Candida, and Rhodotorula were the major genera identified, which were distributed in a rather arbitrary manner among the different samples. Furthermore, a number of potential metagenome-assembled genomes (MAGs) could be detected among assembled shotgun bins. The overall analysis of the shotgun metagenomics supported the presence of different foodborne pathogens in homemade samples (e.g., Staphylococcus aureus, Listeria monocytogenes, Enterobacter cloacae, and Streptococcus suis), but with low to very low abundances. Concluding, the combination of both amplicon sequencing and shotgun metagenomics allowed us to obtain an in-depth profile of the artisanal homemade Feta cheese microbiome.

Highly transmissible cytoplasmic incompatibility by the extracellular insect symbiont Spiroplasma

Cytoplasmic incompatibility (CI) is a form of reproductive manipulation caused by maternally inherited endosymbionts infecting arthropods, like Wolbachia, whereby matings between infected males and uninfected females produce few or no offspring. We report the discovery of a new CI symbiont, a strain of Spiroplasma causing CI in the parasitoid wasp Lariophagus distinguendus. Its extracellular occurrence enabled us to establish CI in uninfected adult insects by transferring Spiroplasma-infected hemolymph. We sequenced the CI-Spiroplasma genome and did not find any homologues of any of the cif genes discovered to cause CI in Wolbachia, suggesting independent evolution of CI. Instead, the genome contains other potential CI-causing candidate genes, such as homologues of high-mobility group (HMG) box proteins that are crucial in eukaryotic development but rare in bacterial genomes. Spiroplasma's extracellular nature and broad host range encompassing medically and agriculturally important arthropods make it a promising tool to study CI and its applications.

Whole genome sequencing of cyanobacterium Nostoc sp. CCCryo 231-06 using microfluidic single cell technology

The Nostoc sp. strain CCCryo 231-06 is a cyanobacterial strain capable of surviving under extreme conditions and thus is of great interest for the astrobiology community. The knowledge of its complete genome sequence would serve as a guide for further studies. However, a major concern has been placed on the effects of contamination on the quality of sequencing data without a reference genome. Here, we report the use of microfluidic technology combined with single cell sequencing and de novo assembly to minimize the contamination and recover the complete genome of the Nostoc strain CCCryo 231-06 with high quality. 100% of the whole genome was recovered with all contaminants removed and a strongly supported phylogenetic tree. The data reported can be useful for comparative genomics for phylogenetic and taxonomic studies. The method used in this work can be applied to studies that require high-quality assemblies of genomes of unknown microorganisms.

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This work uses a microfluidic platform for Nostoc single cell sequencing

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This technology provides minimal contamination in single cell sequencing

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Complete genome of the Nostoc strain CCCryo 231-06 was recovered with high quality

Systematic Cross-biospecimen Evaluation of DNA Extraction Kits for Long- and Short-read Multi-metagenomic Sequencing Studies

High-quality DNA extraction is a crucial step in metagenomic studies. Bias by different isolation kits impairs the comparison across datasets. A trending topic is, however, the analysis of multiple metagenomes from the same patients to draw a holistic picture of microbiota associated with diseases. We thus collected bile, stool, saliva, plaque, sputum, and conjunctival swab samples and performed DNA extraction with three commercial kits. For each combination of the specimen type and DNA extraction kit, 20-gigabase (Gb) metagenomic data were generated using short-read sequencing. While profiles of the specimen types showed close proximity to each other, we observed notable differences in the alpha diversity and composition of the microbiota depending on the DNA extraction kits. No kit outperformed all selected kits on every specimen. We reached consistently good results using the Qiagen QiAamp DNA Microbiome Kit. Depending on the specimen, our data indicate that over 10 Gb of sequencing data are required to achieve sufficient resolution, but DNA-based identification is superior to identification by mass spectrometry. Finally, long-read nanopore sequencing confirmed the results (correlation coefficient > 0.98). Our results thus suggest using a strategy with only one kit for studies aiming for a direct comparison of multiple microbiotas from the same patients.

Effects of Resistant Starch on Symptoms, Fecal Markers, and Gut Microbiota in Parkinson's Disease - The RESISTA-PD Trial

The composition of the gut microbiota is linked to multiple diseases, including Parkinson's disease (PD). Abundance of bacteria producing short-chain fatty acids (SCFAs) and fecal SCFA concentrations are reduced in PD. SCFAs exert various beneficial functions in humans. In the interventional, monocentric, open-label clinical trial "Effects of Resistant Starch on Bowel Habits, Short Chain Fatty Acids and Gut Microbiota in Parkinson'sDisease" (RESISTA-PD; ID: NCT02784145), we aimed at altering fecal SCFAs by an 8-week prebiotic intervention with resistant starch (RS). We enrolled 87 subjects in three study-arms: 32 PD patients received RS (PD + RS), 30 control subjects received RS, and 25 PD patients received solely dietary instructions. We performed paired-end 100 bp length metagenomic sequencing of fecal samples using the BGISEQ platform at an average of 9.9 GB. RS was well-tolerated. In the PD + RS group, fecal butyrate concentrations increased significantly, and fecal calprotectin concentrations dropped significantly after 8 weeks of RS intervention. Clinically, we observed a reduction in non-motor symptom load in the PD + RS group. The reference-based analysis of metagenomes highlighted stable alpha-diversity and beta-diversity across the three groups, including bacteria producing SCFAs. Reference-free analysis suggested punctual, yet pronounced differences in the metagenomic signature in the PD + RS group. RESISTA-PD highlights that a prebiotic treatment with RS is safe and well-tolerated in PD. The stable alpha-diversity and beta-diversity alongside altered fecal butyrate and calprotectin concentrations call for long-term studies, also investigating whether RS is able to modify the clinical course of PD.

A general approach to explore prokaryotic protein glycosylation reveals the unique surface layer modulation of an anammox bacterium

The enormous chemical diversity and strain variability of prokaryotic protein glycosylation makes their large-scale exploration exceptionally challenging. Therefore, despite the universal relevance of protein glycosylation across all domains of life, the understanding of their biological significance and the evolutionary forces shaping oligosaccharide structures remains highly limited. Here, we report on a newly established mass binning glycoproteomics approach that establishes the chemical identity of the carbohydrate components and performs untargeted exploration of prokaryotic oligosaccharides from large-scale proteomics data directly. We demonstrate our approach by exploring an enrichment culture of the globally relevant anaerobic ammonium-oxidizing bacterium Ca. Kuenenia stuttgartiensis. By doing so we resolve a remarkable array of oligosaccharides, which are produced by two seemingly unrelated biosynthetic routes, and which modify the same surface-layer protein simultaneously. More intriguingly, the investigated strain also accomplished modulation of highly specialized sugars, supposedly in response to its energy metabolism-the anaerobic oxidation of ammonium-which depends on the acquisition of substrates of opposite charges. Ultimately, we provide a systematic approach for the compositional exploration of prokaryotic protein glycosylation, and reveal a remarkable example for the evolution of complex oligosaccharides in bacteria.

OUP accepted manuscript

Despite recent methodology and reference database improvements for taxonomic profiling tools, metagenomic assembly and genomic binning remain important pillars of metagenomic analysis workflows. In case reference information is lacking, genomic binning is considered to be a state-of-the-art method in mixed culture metagenomic data analysis. In this light, our previously published tool BusyBee Web implements a composition-based binning method efficient enough to function as a rapid online utility. Handling assembled contigs and long nanopore generated reads alike, the webserver provides a wide range of supplementary annotations and visualizations. Half a decade after the initial publication, we revisited existing functionality, added comprehensive visualizations, and increased the number of data analysis customization options for further experimentation. The webserver now allows for visualization-supported differential analysis of samples, which is computationally expensive and typically only performed in coverage-based binning methods. Further, users may now optionally check their uploaded samples for plasmid sequences using PLSDB as a reference database. Lastly, a new application programming interface with a supporting python package was implemented, to allow power users fully automated access to the resource and integration into existing workflows. The webserver is freely available under: https://www.ccb.uni-saarland.de/busybee.

A review of the resistome within the digestive tract of livestock

Antimicrobials have been widely used to prevent and treat infectious diseases and promote growth in food-production animals. However, the occurrence of antimicrobial resistance poses a huge threat to public and animal health, especially in less developed countries where food-producing animals often intermingle with humans. To limit the spread of antimicrobial resistance from food-production animals to humans and the environment, it is essential to have a comprehensive knowledge of the role of the resistome in antimicrobial resistance (AMR), The resistome refers to the collection of all antimicrobial resistance genes associated with microbiota in a given environment. The dense microbiota in the digestive tract is known to harbour one of the most diverse resistomes in nature. Studies of the resistome in the digestive tract of humans and animals are increasing exponentially as a result of advancements in next-generation sequencing and the expansion of bioinformatic resources/tools to identify and describe the resistome. In this review, we outline the various tools/bioinformatic pipelines currently available to characterize and understand the nature of the intestinal resistome of swine, poultry, and ruminants. We then propose future research directions including analysis of resistome using long-read sequencing, investigation in the role of mobile genetic elements in the expression, function and transmission of AMR. This review outlines the current knowledge and approaches to studying the resistome in food-producing animals and sheds light on future strategies to reduce antimicrobial usage and control the spread of AMR both within and from livestock production systems.

Genome-resolved metagenomics using environmental and clinical samples

Recent advances in high-throughput sequencing technologies and computational methods have added a new dimension to metagenomic data analysis i.e. genome-resolved metagenomics. In general terms, it refers to the recovery of draft or high-quality microbial genomes and their taxonomic classification and functional annotation. In recent years, several studies have utilized the genome-resolved metagenome analysis approach and identified previously unknown microbial species from human and environmental metagenomes. In this review, we describe genome-resolved metagenome analysis as a series of four necessary steps: (i) preprocessing of the sequencing reads, (ii) de novo metagenome assembly, (iii) genome binning and (iv) taxonomic and functional analysis of the recovered genomes. For each of these four steps, we discuss the most commonly used tools and the currently available pipelines to guide the scientific community in the recovery and subsequent analyses of genomes from any metagenome sample. Furthermore, we also discuss the tools required for validation of assembly quality as well as for improving quality of the recovered genomes. We also highlight the currently available pipelines that can be used to automate the whole analysis without having advanced bioinformatics knowledge. Finally, we will highlight the most widely adapted and actively maintained tools and pipelines that can be helpful to the scientific community in decision making before they commence the analysis.

'Candidatus Chloroploca mongolica' sp. nov. a new mesophilic filamentous anoxygenic phototrophic bacterium

A mesophilic filamentous anoxygenic phototrophic bacterium, designated M50-1, was isolated from a microbial mat of the Chukhyn Nur soda lake (northeastern Mongolia) with salinity of 5-14 g/L and pH 8.0-9.3. The organism is a strictly anaerobic phototrophic bacterium, which required sulfide for phototrophic growth. The cells formed short undulate trichomes surrounded by a thin sheath and containing gas vesicles. Motility of the trichomes was not observed. The cells contained chlorosomes. The antenna pigments were bacteriochlorophyll d and β- and γ-carotenes. Analysis of the genome assembled from the metagenome of the enrichment culture revealed all the enzymes of the 3-hydroxypropionate bi-cycle for autotrophic CO2 assimilation. The genome also contained the genes encoding a type IV sulfide:quinone oxidoreductase (sqrX). The organism had no nifHDBK genes, encoding the proteins of the nitrogenase complex responsible for dinitrogen fixation. The DNA G + C content was 58.6%. The values for in silico DNA‒DNA hybridization and average nucleotide identity between M50-1 and a closely related bacterium 'Ca. Chloroploca asiatica' B7-9 containing bacteriochlorophyll c were 53.4% and 94.0%, respectively, which corresponds to interspecies differences. Classification of the filamentous anoxygenic phototrophic bacterium M50-1 as a new 'Ca. Chloroploca' species was proposed, with the species name 'Candidatus Chloroploca mongolica' sp. nov.

Inhibition of a nutritional endosymbiont by glyphosate abolishes mutualistic benefit on cuticle synthesis in Oryzaephilus surinamensis

Glyphosate is widely used as a herbicide, but recent studies begin to reveal its detrimental side effects on animals by targeting the shikimate pathway of associated gut microorganisms. However, its impact on nutritional endosymbionts in insects remains poorly understood. Here, we sequenced the tiny, shikimate pathway encoding symbiont genome of the sawtoothed grain beetle Oryzaephilus surinamensis. Decreased titers of the aromatic amino acid tyrosine in symbiont-depleted beetles underscore the symbionts' ability to synthesize prephenate as the precursor for host tyrosine synthesis and its importance for cuticle sclerotization and melanization. Glyphosate exposure inhibited symbiont establishment during host development and abolished the mutualistic benefit on cuticle synthesis in adults, which could be partially rescued by dietary tyrosine supplementation. Furthermore, phylogenetic analyses indicate that the shikimate pathways of many nutritional endosymbionts likewise contain a glyphosate sensitive 5-enolpyruvylshikimate-3-phosphate synthase. These findings highlight the importance of symbiont-mediated tyrosine supplementation for cuticle biosynthesis in insects, but also paint an alarming scenario regarding the use of glyphosate in light of recent declines in insect populations.

Improving metagenomic binning results with overlapped bins using assembly graphs

Background

Metagenomic sequencing allows us to study the structure, diversity and ecology in microbial communities without the necessity of obtaining pure cultures. In many metagenomics studies, the reads obtained from metagenomics sequencing are first assembled into longer contigs and these contigs are then binned into clusters of contigs where contigs in a cluster are expected to come from the same species. As different species may share common sequences in their genomes, one assembled contig may belong to multiple species. However, existing tools for binning contigs only support non-overlapped binning, i.e., each contig is assigned to at most one bin (species).

Results

In this paper, we introduce GraphBin2 which refines the binning results obtained from existing tools and, more importantly, is able to assign contigs to multiple bins. GraphBin2 uses the connectivity and coverage information from assembly graphs to adjust existing binning results on contigs and to infer contigs shared by multiple species. Experimental results on both simulated and real datasets demonstrate that GraphBin2 not only improves binning results of existing tools but also supports to assign contigs to multiple bins.

Conclusion

GraphBin2 incorporates the coverage information into the assembly graph to refine the binning results obtained from existing binning tools. GraphBin2 also enables the detection of contigs that may belong to multiple species. We show that GraphBin2 outperforms its predecessor GraphBin on both simulated and real datasets. GraphBin2 is freely available at https://github.com/Vini2/GraphBin2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13015-021-00185-6.

Recovery of complete genomes and non-chromosomal replicons from activated sludge enrichment microbial communities with long read metagenome sequencing

New long read sequencing technologies offer huge potential for effective recovery of complete, closed genomes from complex microbial communities. Using long read data (ONT MinION) obtained from an ensemble of activated sludge enrichment bioreactors we recover 22 closed or complete genomes of community members, including several species known to play key functional roles in wastewater bioprocesses, specifically microbes known to exhibit the polyphosphate- and glycogen-accumulating organism phenotypes (namely Candidatus Accumulibacter and Dechloromonas, and Micropruina, Defluviicoccus and Candidatus Contendobacter, respectively), and filamentous bacteria (Thiothrix) associated with the formation and stability of activated sludge flocs. Additionally we demonstrate the recovery of close to 100 circularised plasmids, phages and small microbial genomes from these microbial communities using long read assembled sequence. We describe methods for validating long read assembled genomes using their counterpart short read metagenome-assembled genomes, and assess the influence of different correction procedures on genome quality and predicted gene quality. Our findings establish the feasibility of performing long read metagenome-assembled genome recovery for both chromosomal and non-chromosomal replicons, and demonstrate the value of parallel sampling of moderately complex enrichment communities to obtaining high quality reference genomes of key functional species relevant for wastewater bioprocesses.

Antibiotic resistance: Global health crisis and metagenomics

Antibiotic resistance is a global problem which affects human health. The imprudent use of antibiotics (medicine, agriculture, aquaculture, and food industry) has resulted in the broader dissemination of resistance. Urban wastewater & sewage treatment plants act as the hotspot for the widespread of antimicrobial resistance. Natural environment also plays an important role in the dissemination of resistance. Mapping of antibiotic resistance genes (ARGS) in environment is essential for mitigating antimicrobial resistance (AMR) widespread. Therefore, the review article emphasizes on the application of metagenomics for the surveillance of antimicrobial resistance. Metagenomics is the next generation tool which is being used for cataloging the resistome of diverse environments. We summarize the different metagenomic tools that can be used for mining of ARGs and acquired AMR present in the metagenomic data. Also, we recommend application of targeted sequencing/ capture platform for mapping of resistome with higher specificity and selectivity.

Current challenges and best-practice protocols for microbiome analysis

Analyzing the microbiome of diverse species and environments using next-generation sequencing techniques has significantly enhanced our understanding on metabolic, physiological and ecological roles of environmental microorganisms. However, the analysis of the microbiome is affected by experimental conditions (e.g. sequencing errors and genomic repeats) and computationally intensive and cumbersome downstream analysis (e.g. quality control, assembly, binning and statistical analyses). Moreover, the introduction of new sequencing technologies and protocols led to a flood of new methodologies, which also have an immediate effect on the results of the analyses. The aim of this work is to review the most important workflows for 16S rRNA sequencing and shotgun and long-read metagenomics, as well as to provide best-practice protocols on experimental design, sample processing, sequencing, assembly, binning, annotation and visualization. To simplify and standardize the computational analysis, we provide a set of best-practice workflows for 16S rRNA and metagenomic sequencing data (available at https://github.com/grimmlab/MicrobiomeBestPracticeReview).

GraphBin: refined binning of metagenomic contigs using assembly graphs

MOTIVATION

The field of metagenomics has provided valuable insights into the structure, diversity and ecology within microbial communities. One key step in metagenomics analysis is to assemble reads into longer contigs which are then binned into groups of contigs that belong to different species present in the metagenomic sample. Binning of contigs plays an important role in metagenomics and most available binning algorithms bin contigs using genomic features such as oligonucleotide/k-mer composition and contig coverage. As metagenomic contigs are derived from the assembly process, they are output from the underlying assembly graph which contains valuable connectivity information between contigs that can be used for binning.

RESULTS

We propose GraphBin, a new binning method that makes use of the assembly graph and applies a label propagation algorithm to refine the binning result of existing tools. We show that GraphBin can make use of the assembly graphs constructed from both the de Bruijn graph and the overlap-layout-consensus approach. Moreover, we demonstrate improved experimental results from GraphBin in terms of identifying mis-binned contigs and binning of contigs discarded by existing binning tools. To the best of our knowledge, this is the first time that the information from the assembly graph has been used in a tool for the binning of metagenomic contigs.

AVAILABILITY AND IMPLEMENTATION

The source code of GraphBin is available at https://github.com/Vini2/GraphBin.

CONTACT

vijini.mallawaarachchi@anu.edu.au or yu.lin@anu.edu.au.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

‘Candidatus Oscillochloris kuznetsovii’ a novel mesophilic filamentous anoxygenic phototrophic Chloroflexales bacterium from Arctic coastal environments

Chloroflexales bacteria are mostly known as filamentous anoxygenic phototrophs that thrive as members of the microbial communities of hot spring cyanobacterial mats. Recently, we described many new Chloroflexales species from non-thermal environments and showed that mesophilic Chloroflexales are more diverse than previously expected. Most of these species were isolated from aquatic environments of mid-latitudes. Here, we present the comprehensive characterization of a new filamentous multicellular anoxygenic phototrophic Chloroflexales bacterium from an Arctic coastal environment (Kandalaksha Gulf, the White Sea). Phylogenomic analysis and 16S rRNA phylogeny indicated that this bacterium belongs to the Oscillochloridaceae family as a new species. We propose that this species be named ‘Candidatus Oscillochloris kuznetsovii’. The genomes of this species possessed genes encoding sulfide:quinone reductase, the nitrogenase complex and the Calvin cycle, which indicate potential for photoautotrophic metabolism. We observed only mesophilic anaerobic anoxygenic phototrophic growth of this novel bacterium. Electron microphotography showed the presence of chlorosomes, polyhydroxyalkanoate-like granules and polyphosphate-like granules in the cells. High-performance liquid chromatography also revealed the presence of bacteriochlorophylls a, c and d as well as carotenoids. In addition, we found that this bacterium is present in benthic microbial communities of various coastal environments of the Kandalaksha Gulf.

Unravelling the diversity of magnetotactic bacteria through analysis of open genomic databases

Magnetotactic bacteria (MTB) are prokaryotes that possess genes for the synthesis of membrane-bounded crystals of magnetite or greigite, called magnetosomes. Despite over half a century of studying MTB, only about 60 genomes have been sequenced. Most belong to Proteobacteria, with a minority affiliated with the Nitrospirae, Omnitrophica, Planctomycetes, and Latescibacteria. Due to the scanty information available regarding MTB phylogenetic diversity, little is known about their ecology, evolution and about the magnetosome biomineralization process. This study presents a large-scale search of magnetosome biomineralization genes and reveals 38 new MTB genomes. Several of these genomes were detected in the phyla Elusimicrobia, Candidatus Hydrogenedentes, and Nitrospinae, where magnetotactic representatives have not previously been reported. Analysis of the obtained putative magnetosome biomineralization genes revealed a monophyletic origin capable of putative greigite magnetosome synthesis. The ecological distributions of the reconstructed MTB genomes were also analyzed and several patterns were identified. These data suggest that open databases are an excellent source for obtaining new information of interest.

Exploring neighborhoods in large metagenome assembly graphs using spacegraphcats reveals hidden sequence diversity

Genomes computationally inferred from large metagenomic data sets are often incomplete and may be missing functionally important content and strain variation. We introduce an information retrieval system for large metagenomic data sets that exploits the sparsity of DNA assembly graphs to efficiently extract subgraphs surrounding an inferred genome. We apply this system to recover missing content from genome bins and show that substantial genomic sequence variation is present in a real metagenome. Our software implementation is available at https://github.com/spacegraphcats/spacegraphcats under the 3-Clause BSD License.

MetaBCC-LR: metagenomics binning by coverage and composition for long reads

MOTIVATION

Metagenomics studies have provided key insights into the composition and structure of microbial communities found in different environments. Among the techniques used to analyse metagenomic data, binning is considered a crucial step to characterize the different species of micro-organisms present. The use of short-read data in most binning tools poses several limitations, such as insufficient species-specific signal, and the emergence of long-read sequencing technologies offers us opportunities to surmount them. However, most current metagenomic binning tools have been developed for short reads. The few tools that can process long reads either do not scale with increasing input size or require a database with reference genomes that are often unknown. In this article, we present MetaBCC-LR, a scalable reference-free binning method which clusters long reads directly based on their k-mer coverage histograms and oligonucleotide composition.

RESULTS

We evaluate MetaBCC-LR on multiple simulated and real metagenomic long-read datasets with varying coverages and error rates. Our experiments demonstrate that MetaBCC-LR substantially outperforms state-of-the-art reference-free binning tools, achieving ∼13% improvement in F1-score and ∼30% improvement in ARI compared to the best previous tools. Moreover, we show that using MetaBCC-LR before long-read assembly helps to enhance the assembly quality while significantly reducing the assembly cost in terms of time and memory usage. The efficiency and accuracy of MetaBCC-LR pave the way for more effective long-read-based metagenomics analyses to support a wide range of applications.

AVAILABILITY AND IMPLEMENTATION

The source code is freely available at: https://github.com/anuradhawick/MetaBCC-LR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Bacterial symbionts support larval sap feeding and adult folivory in (semi-)aquatic reed beetles

Symbiotic microbes can enable their host to access untapped nutritional resources but may also constrain niche space by promoting specialization. Here, we reconstruct functional changes in the evolutionary history of the symbiosis between a group of (semi-)aquatic herbivorous insects and mutualistic bacteria. Sequencing the symbiont genomes across 26 species of reed beetles (Chrysomelidae, Donaciinae) spanning four genera indicates that the genome-eroded mutualists provide life stage-specific benefits to larvae and adults, respectively. In the plant sap-feeding larvae, the symbionts are inferred to synthesize most of the essential amino acids as well as the B vitamin riboflavin. The adult reed beetles’ folivory is likely supported by symbiont-encoded pectinases that complement the host-encoded set of cellulases, as revealed by transcriptome sequencing. However, mapping the occurrence of the symbionts’ pectinase genes and the hosts’ food plant preferences onto the beetles’ phylogeny reveals multiple independent losses of pectinase genes in lineages that switched to feeding on pectin-poor plants, presumably constraining their hosts’ subsequent adaptive potential.

Symbiotic microbes in insects can enable their hosts to access untapped nutritional resources. Here, the authors show that symbiotic bacteria in reed beetles can provide essential amino acids to sap-feeding larvae and help leaf-feeding adults to degrade pectin, respectively.

Exploration of activated sludge resistome using metagenomics

Antibiotic resistance is a global problem. In India poor waste management and inadequate sanitary are key factors which encourage the dissemination of antimicrobial resistance. Microbial biodiversity serves as an invaluable source for diverse types of bioactive compounds that encompass most of the pharmaceuticals to date. Therefore, in this study, we used the metagenomic approach for the surveillance of antibiotic resistance genes, drug resistant microbes and mobile-genetic elements in two activated sludge metagenome samples collected from Ankleshwar, Gujarat, India. Proteobacteria were found to be the most abundant bacteria among the metagenome analyzed. Twenty-four genes conferring resistance to antibiotics and heavy metals were found. Multidrug resistant "ESKAPE pathogens" were also abundant in the sludge metagenome. Mobile genetic elements like IncP-1 plasmid pKJK5, IncP-1beta multi resistance plasmid and pB8 were also noticed in the higher abundance. These plasmids play an important role in the spread of antibiotic resistance by the horizontal gene transfer. Statistical analysis of both metagenome using STAMP software confirmed presence of mobile genetic elements such as gene transfer agents, phages, Prophages etc. which also play important role in the dissemination of antibiotic resistant genes.

SeqDeχ: A Sequence Deconvolution Tool for Genome Separation of Endosymbionts From Mixed Sequencing Samples

In recent years, the advent of NGS technology has made genome sequencing much cheaper than in the past; the high parallelization capability and the possibility to sequence more than one organism at once have opened the door to processing whole symbiotic consortia. However, this approach needs the development of specific bioinformatics tools able to analyze these data. In this work, we describe SeqDex, a tool that starts from a preliminary assembly obtained from sequencing a mixture of DNA from different organisms, to identify the contigs coming from one organism of interest. SeqDex is a fully automated machine learning–based tool exploiting partial taxonomic affiliations and compositional analysis to predict the taxonomic affiliations of contigs in an assembly. In literature, there are few methods able to deconvolve host–symbiont datasets, and most of them heavily rely on user curation and are therefore time consuming. The problem has strong similarities with metagenomic studies, where mixed samples are sequenced and the bioinformatics challenge is trying to separate contigs on the basis of their source organism; however, in symbiotic systems, additional information can be exploited to improve the output. To assess the ability of SeqDex to deconvolve host–symbiont datasets, we compared it to state-of-the-art methods for metagenomic binning and for host–symbiont deconvolution on three study cases. The results point out the good performances of the presented tool that, in addition to the ease of use and customization potential, make SeqDex a useful tool for rapid identification of endosymbiont sequences.

Genome-Based Metabolic Reconstruction of a Novel Uncultivated Freshwater Magnetotactic coccus "Ca. Magnetaquicoccus inordinatus" UR-1, and Proposal of a Candidate Family "Ca. Magnetaquicoccaceae"

Magnetotactic bacteria are widely represented microorganisms that have the ability to synthesize magnetosomes. The magnetotactic cocci of the order Magnetococcales are the most frequently identified, but their classification remains unclear due to the low number of cultivated representatives. This paper reports the analysis of an uncultivated magnetotactic coccus UR-1 collected from the Uda River (in eastern Siberia). Genome analyses of this bacterium and comparison to the available Magnetococcales genomes identified a novel species called "Ca. Magnetaquicoccus inordinatus," and a delineated candidate family "Ca. Magnetaquicoccaceae" within the order Magnetococcales is proposed. We used average amino acid identity values <55-56% and <64-65% as thresholds for the separation of families and genera, respectively, within the order Magnetococcales. Analyses of the genome sequence of UR-1 revealed a potential ability for a chemolithoautotrophic lifestyle, with the oxidation of a reduced sulfur compound and carbon assimilation by rTCA. A nearly complete magnetosome genome island, containing a set of mam and mms genes, was also identified. Further comparative analyses of the magnetosome genes showed vertical inheritance as well as horizontal gene transfer as the evolutionary drivers of magnetosome biomineralization genes in strains of the order Magnetococcales.

MetaTOR: A Computational Pipeline to Recover High-Quality Metagenomic Bins From Mammalian Gut Proximity-Ligation (meta3C) Libraries

Characterizing the complete genomic structure of complex microbial communities would represent a key step toward the understanding of their diversity, dynamics, and evolution. Current metagenomics approaches aiming at this goal are typically done by analyzing millions of short DNA sequences directly extracted from the environment. New experimental and computational approaches are constantly sought for to improve the analysis and interpretation of such data. We developed MetaTOR, an open-source computational solution that bins DNA contigs into individual genomes according to their 3D contact frequencies. Those contacts are quantified by chromosome conformation capture experiments (3C, Hi-C), also known as proximity-ligation approaches, applied to metagenomics samples (meta3C). MetaTOR was applied on 20 meta3C libraries of mice gut microbiota. We quantified the program ability to recover high-quality metagenome-assembled genomes (MAGs) from metagenomic assemblies generated directly from the meta3C libraries. Whereas nine high-quality MAGs are identified in the 148-Mb assembly generated using a single meta3C library, MetaTOR identifies 82 high-quality MAGs in the 763-Mb assembly generated from the merged 20 meta3C libraries, corresponding to nearly a third of the total assembly. Compared to the hybrid binning softwares MetaBAT or CONCOCT, MetaTOR recovered three times more high-quality MAGs. These results underline the potential of 3C-/Hi-C-based approaches in metagenomic projects.

Autometa: automated extraction of microbial genomes from individual shotgun metagenomes

Shotgun metagenomics is a powerful, high-resolution technique enabling the study of microbial communities in situ. However, species-level resolution is only achieved after a process of 'binning' where contigs predicted to originate from the same genome are clustered. Such culture-independent sequencing frequently unearths novel microbes, and so various methods have been devised for reference-free binning. As novel microbiomes of increasing complexity are explored, sometimes associated with non-model hosts, robust automated binning methods are required. Existing methods struggle with eukaryotic contamination and cannot handle highly complex single metagenomes. We therefore developed an automated binning pipeline, termed 'Autometa', to address these issues. This command-line application integrates sequence homology, nucleotide composition, coverage and the presence of single-copy marker genes to separate microbial genomes from non-model host genomes and other eukaryotic contaminants, before deconvoluting individual genomes from single metagenomes. The method is able to effectively separate over 1000 genomes from a metagenome, allowing the study of previously intractably complex environments at the level of single species. Autometa is freely available at https://bitbucket.org/jason_c_kwan/autometa and as a docker image at https://hub.docker.com/r/jasonkwan/autometa under the GNU Affero General Public License 3 (AGPL 3).

Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates

Emerging antibiotic resistance is a major global health threat. The analysis of nucleic acid sequences linked to susceptibility phenotypes facilitates the study of genetic antibiotic resistance determinants to inform molecular diagnostics and drug development. We collected genetic data (11,087 newly-sequenced whole genomes) and culture-based resistance profiles (10,991 out of the 11,087 isolates comprehensively tested against 22 antibiotics in total) of clinical isolates including 18 main species spanning a time period of 30 years. Species and drug specific resistance patterns were observed including increased resistance rates for Acinetobacter baumannii to carbapenems and for Escherichia coli to fluoroquinolones. Species-level pan-genomes were constructed to reflect the genetic repertoire of the respective species, including conserved essential genes and known resistance factors. Integrating phenotypes and genotypes through species-level pan-genomes allowed to infer gene-drug resistance associations using statistical testing. The isolate collection and the analysis results have been integrated into GEAR-base, a resource available for academic research use free of charge at https://gear-base.com.