Analysis of rhizosphere fungal community of agricultural crops cultivated in laboratory experiments on Chernevaya taiga soil.

Chernevaya taiga of Western Siberia, Russia, is a unique ecosystem characterized by fertile soil, exceptionally large herbaceous plant sizes, and extraordinarily rapid rates of plant residue degradation. We expected that growing crops on soil collected from Chernevaya taiga, which has never been used for agricultural purposes before, would result in a distinct rhizospheric fungal community. This community could potentially yield novel, potent biostimulators and biocontrol fungi for modern agriculture. To check this idea, we used high-throughput ITS sequencing to examine the microbial communities in the rhizosphere of spring wheat and radish grown in greenhouse experiments on Chernevaya and control soils. Additionally, representative fungal strains were isolated and assessed for their ability to promote growth in wheat seedlings. The study revealed that the most abundant phyla in the rhizospheric fungal community were Mortierellomycota, primarily consisting of Mortierella species, and Ascomycota. Mucor and Umbelopsis comprised the majority of Mucoromycota in the control soils. Fusarium and Oidiodendron, two potentially plant-pathogenic fungi, were only found in the rhizosphere of crops grown in the control soil. Conversely, Chernevaya soil contained a diverse range of potential biocontrol fungi for plants. Tested novel fungal isolates showed a stimulating effect on the development of wheat seedlings and positively affected their rate of biomass accumulation. The results of the study demonstrate that the soil of Chernevaya taiga do indeed contain fungi with prominent potential to stimulate agricultural plants growth.

Protocol for refining metagenomic binning with BinSPreader.

The analysis of metagenomic data obtained via high-throughput DNA sequencing is primarily carried out by a dedicated binning process involving clustering contigs, presumably belonging to the same species. Here, we present a protocol for improving the quality of binning using BinSPreader. We describe steps for typical metagenome assembly and binning workflow. We then detail binning refining, its variants, output, and possible caveats. This protocol optimizes the process of reconstructing more complete genomes of microorganisms that make up the metagenome. For complete details on the use and execution of this protocol, please refer to Tolstoganov et al.1.

Chromosome-Length Assembly of the Baikal Seal (Pusa sibirica) Genome Reveals a Historically Large Population Prior to Isolation in Lake Baikal.

Pusa sibirica, the Baikal seal, is the only extant, exclusively freshwater, pinniped species. The pending issue is, how and when they reached their current habitat-the rift lake Baikal, more than three thousand kilometers away from the Arctic Ocean. To explore the demographic history and genetic diversity of this species, we generated a de novo chromosome-length assembly, and compared it with three closely related marine pinniped species. Multiple whole genome alignment of the four species compared with their karyotypes showed high conservation of chromosomal features, except for three large inversions on chromosome VI. We found the mean heterozygosity of the studied Baikal seal individuals was relatively low (0.61 SNPs/kbp), but comparable to other analyzed pinniped samples. Demographic reconstruction of seals revealed differing trajectories, yet remarkable variations in Ne occurred during approximately the same time periods. The Baikal seal showed a significantly more severe decline relative to other species. This could be due to the difference in environmental conditions encountered by the earlier populations of Baikal seals, as ice sheets changed during glacial-interglacial cycles. We connect this period to the time of migration to Lake Baikal, which occurred ~3-0.3 Mya, after which the population stabilized, indicating balanced habitat conditions.

Accurate isoform discovery with IsoQuant using long reads.

Annotating newly sequenced genomes and determining alternative isoforms from long-read RNA data are complex and incompletely solved problems. Here we present IsoQuant-a computational tool using intron graphs that accurately reconstructs transcripts both with and without reference genome annotation. For novel transcript discovery, IsoQuant reduces the false-positive rate fivefold and 2.5-fold for Oxford Nanopore reference-based or reference-free mode, respectively. IsoQuant also improves performance for Pacific Biosciences data.

Agricultural Crops Grown in Laboratory Conditions on Chernevaya Taiga Soil Demonstrate Unique Composition of the Rhizosphere Microbiota.

Chernevaya taiga in West Siberia is a unique environment, with gigantism of grasses and shrubs. Exceptionally high productivity of plants is determined by the synergistic interaction of various factors, with a special role belonging to microorganisms colonizing the plant roots. This research explored whether agricultural plants can recruit specific microorganisms from within virgin Chernevaya Umbrisol and thus increase their productivity. Radish and wheat plants were grown on the Umbrisol (T1) and control Retisol of Scotch pine forest stand (T3) soils in the phytotron, and then a bacterial community analysis of the rhizosphere was performed using high-throughput sequencing of the 16S rRNA genes. In laboratory experiments, the plant physiological parameters were significantly higher when growing on the Umbrisol as compared to the Retisol. Bacterial diversity in T1 soil was considerably higher than in the control sample, and the principal coordinate analysis demonstrated apparent differences in the bacterial communities associated with the plants. Agricultural plants growing in the T1 soil form specific prokaryotic communities, with dominant genera Chthoniobacter, Pseudomonas, Burkholderia, and Massilia. These communities also include less abundant but essential for plant growth nitrifiers Cand. Nitrosocosmius and Nitrospira, and representatives of Proteobacteria, Bacilli, and Actinobacteria, known to be gibberellin-producers.

MetaGT: A pipeline for de novo assembly of metatranscriptomes with the aid of metagenomic data.

While metagenome sequencing may provide insights on the genome sequences and composition of microbial communities, metatranscriptome analysis can be useful for studying the functional activity of a microbiome. RNA-Seq data provides the possibility to determine active genes in the community and how their expression levels depend on external conditions. Although the field of metatranscriptomics is relatively young, the number of projects related to metatranscriptome analysis increases every year and the scope of its applications expands. However, there are several problems that complicate metatranscriptome analysis: complexity of microbial communities, wide dynamic range of transcriptome expression and importantly, the lack of high-quality computational methods for assembling meta-RNA sequencing data. These factors deteriorate the contiguity and completeness of metatranscriptome assemblies, therefore affecting further downstream analysis. Here we present MetaGT, a pipeline for de novo assembly of metatranscriptomes, which is based on the idea of combining both metatranscriptomic and metagenomic data sequenced from the same sample. MetaGT assembles metatranscriptomic contigs and fills in missing regions based on their alignments to metagenome assembly. This approach allows to overcome described complexities and obtain complete RNA sequences, and additionally estimate their abundances. Using various publicly available real and simulated datasets, we demonstrate that MetaGT yields significant improvement in coverage and completeness of metatranscriptome assemblies compared to existing methods that do not exploit metagenomic data. The pipeline is implemented in NextFlow and is freely available from https://github.com/ablab/metaGT.

Fungal Metagenome of Chernevaya Taiga Soils: Taxonomic Composition, Differential Abundance and Factors Related to Plant Gigantism.

The Chernevaya taiga of Western Siberia is a unique and complex ecosystem, distinguished by the unusually large sizes of herbaceous plants, the reasons for which are poorly understood. Here, we explored the fungal diversity of the Chernevaya taiga soils in the Tomsk regions of Western Siberia in comparison with other soil types. The soil biomes of Chernevaya taiga and the control regions were investigated using Illumina ITS rRNA sequencing, and taxonomic analysis revealed a predominance of fungal phyla in the different soils. These results demonstrate that the fungi of the Chernevaya taiga regions have a higher species diversity (Faith's PD) vs. the control soils, and the diversity is due more to the sampling sites rather than to the seasons (Bray-Curtis distance). We studied most of the differentially abundant taxa among the soil types, and we annotated the taxa with their ecological guilds and trophic types. Some of the abundant fungal taxa in the summer- and fall-Chernevaya taiga samples belong to the phylum Glomeromycota-arbuscular mycorrhizal symbiotrophs, which are known to establish symbiotic relationships and enhance plant growth. Additionally, several OTUs were assigned to novel genera in the Glomeraceae and Claroideoglomeraceae families. Our findings add a potential explanation of the high productivity and plant gigantism in Chernevaya taiga and expand our knowledge of fungal biodiversity.

Metagenomic Data Assembly - The Way of Decoding Unknown Microorganisms.

Metagenomics is a segment of conventional microbial genomics dedicated to the sequencing and analysis of combined genomic DNA of entire environmental samples. The most critical step of the metagenomic data analysis is the reconstruction of individual genes and genomes of the microorganisms in the communities using metagenomic assemblers - computational programs that put together small fragments of sequenced DNA generated by sequencing instruments. Here, we describe the challenges of metagenomic assembly, a wide spectrum of applications in which metagenomic assemblies were used to better understand the ecology and evolution of microbial ecosystems, and present one of the most efficient microbial assemblers, SPAdes that was upgraded to become applicable for metagenomics.

Draft Genome Sequence of Bordetella sp. Strain FB-8, Isolated from a Former Uranium Mining Area in Germany.

Here, we present the draft genome sequence of Bordetella sp. strain FB-8, a mixotrophic iron-oxidizing bacterium isolated from creek sediment in the former uranium-mining district of Ronneburg, Germany. To date, iron oxidation has not been reported in Bordetella species, indicating that FB-8 may be an environmentally important Bordetella sp.

Mixotrophic Iron-Oxidizing Thiomonas Isolates from an Acid Mine Drainage-Affected Creek.

Natural attenuation of heavy metals occurs via coupled microbial iron cycling and metal precipitation in creeks impacted by acid mine drainage (AMD). Here, we describe the isolation, characterization, and genomic sequencing of two iron-oxidizing bacteria (FeOB) species: Thiomonas ferrovorans FB-6 and Thiomonas metallidurans FB-Cd, isolated from slightly acidic (pH 6.3), Fe-rich, AMD-impacted creek sediments. These strains precipitated amorphous iron oxides, lepidocrocite, goethite, and magnetite or maghemite and grew at a pH optimum of 5.5. While Thiomonas spp. are known as mixotrophic sulfur oxidizers and As oxidizers, the FB strains oxidized Fe, which suggests they can efficiently remove Fe and other metals via coprecipitation. Previous evidence for Thiomonas sp. Fe oxidation is largely ambiguous, possibly because of difficulty demonstrating Fe oxidation in heterotrophic/mixotrophic organisms. Therefore, we also conducted a genomic analysis to identify genetic mechanisms of Fe oxidation, other metal transformations, and additional adaptations, comparing the two FB strain genomes with 12 other Thiomonas genomes. The FB strains fall within a relatively novel group of Thiomonas strains that includes another strain (b6) with solid evidence of Fe oxidation. Most Thiomonas isolates, including the FB strains, have the putative iron oxidation gene cyc2, but only the two FB strains possess the putative Fe oxidase genes mtoAB The two FB strain genomes contain the highest numbers of strain-specific gene clusters, greatly increasing the known Thiomonas genetic potential. Our results revealed that the FB strains are two distinct novel species of Thiomonas with the genetic potential for bioremediation of AMD via iron oxidation.IMPORTANCE As AMD moves through the environment, it impacts aquatic ecosystems, but at the same time, these ecosystems can naturally attenuate contaminated waters via acid neutralization and catalyzing metal precipitation. This is the case in the former Ronneburg uranium-mining district, where AMD impacts creek sediments. We isolated and characterized two iron-oxidizing Thiomonas species that are mildly acidophilic to neutrophilic and that have two genetic pathways for iron oxidation. These Thiomonas species are well positioned to naturally attenuate AMD as it discharges across the landscape.

Correction to: CDSnake: Snakemake pipeline for retrieval of annotated OTUs from paired-end reads using CD-HIT utilities.

An amendment to this paper has been published and can be accessed via the original article.

Extending rnaSPAdes functionality for hybrid transcriptome assembly.

BACKGROUND: De novo RNA-Seq assembly is a powerful method for analysing transcriptomes when the reference genome is not available or poorly annotated. However, due to the short length of Illumina reads it is usually impossible to reconstruct complete sequences of complex genes and alternative isoforms. Recently emerged possibility to generate long RNA reads, such as PacBio and Oxford Nanopores, may dramatically improve the assembly quality, and thus the consecutive analysis. While reference-based tools for analysing long RNA reads were recently developed, there is no established pipeline for de novo assembly of such data. RESULTS: In this work we present a novel method that allows to perform high-quality de novo transcriptome assemblies by combining accuracy and reliability of short reads with exon structure information carried out from long error-prone reads. The algorithm is designed by incorporating existing hybridSPAdes approach into rnaSPAdes pipeline and adapting it for transcriptomic data. CONCLUSION: To evaluate the benefit of using long RNA reads we selected several datasets containing both Illumina and Iso-seq or Oxford Nanopore Technologies (ONT) reads. Using an existing quality assessment software, we show that hybrid assemblies performed with rnaSPAdes contain more full-length genes and alternative isoforms comparing to the case when only short-read data is used.

CDSnake: Snakemake pipeline for retrieval of annotated OTUs from paired-end reads using CD-HIT utilities.

BACKGROUND: Illumina paired-end reads are often used for 16S analysis in metagenomic studies. Since DNA fragment size is usually smaller than the sum of lengths of paired reads, reads can be merged for downstream analysis. In spite of development of several tools for merging of paired-end reads, poor quality at the 3' ends within the overlapping region prevents the accurate combining of significant portion of read pairs. Recently CD-HIT-OTU-Miseq was presented as a new approach for 16S analysis using the paired-end reads, it completely avoids the reads merging process due to separate clustering of paired reads. CD-HIT-OTU-Miseq is a set of tools which are supposed to be successively launched by auxiliary shell scripts. This launch mode is not suitable for processing of big amounts of data generated in modern omics experiments. To solve this issue we created CDSnake - Snakemake pipeline utilizing CD-HIT tools for easier consecutive launch of CD-HIT-OTU-Miseq tools for complete processing of paired end reads in metagenomic studies. Usage of pipeline make 16S analysis easier due to one-command launch and helps to yield reproducible results. RESULTS: We benchmarked our pipeline against two commonly used pipelines for OTU retrieval, incorporated into popular workflow for microbiome analysis, QIIME2 - DADA2 and deblur. Three mock datasets having highly overlapping paired-end 2 × 250 bp reads were used for benchmarking - Balanced, HMP, and Extreme. CDSnake outputted less OTUs than DADA2 and deblur. However, on Balanced and HMP datasets number of OTUs outputted by CDSnake was closer to real number of strains which were used for mock community generation, than those outputted by DADA2 and deblur. Though generally slower than other pipelines, CDSnake outputted higher total counts, preserving more information from raw data. Inheriting this properties from original CD-HIT-OTU-MiSeq utilities, CDSnake made their usage handier due to simple scalability, easier automated runs and other Snakemake benefits. CONCLUSIONS: We developed Snakemake pipeline for OTU-MiSeq utilities, which simplified and automated data analysis. Benchmarking showed that this approach is capable to outperform popular tools in certain conditions.

Using SPAdes De Novo Assembler.

SPAdes-St. Petersburg genome Assembler-was originally developed for de novo assembly of genome sequencing data produced for cultivated microbial isolates and for single-cell genomic DNA sequencing. With time, the functionality of SPAdes was extended to enable assembly of IonTorrent data, as well as hybrid assembly from short and long reads (PacBio and Oxford Nanopore). In this article we present protocols for five different assembly pipelines that comprise the SPAdes package and that are used for assembly of metagenomes and transcriptomes as well as assembly of putative plasmids and biosynthetic gene clusters from whole-genome sequencing and metagenomic datasets. In addition, we present guidelines for understanding results with use cases for each pipeline, and several additional support protocols that help in using SPAdes properly. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Assembling isolate bacterial datasets Basic Protocol 2: Assembling metagenomic datasets Basic Protocol 3: Assembling sets of putative plasmids Basic Protocol 4: Assembling transcriptomes Basic Protocol 5: Assembling putative biosynthetic gene clusters Support Protocol 1: Installing SPAdes Support Protocol 2: Providing input via command line Support Protocol 3: Providing input data via YAML format Support Protocol 4: Restarting previous run Support Protocol 5: Determining strand-specificity of RNA-seq data.

Metaviral SPAdes: assembly of viruses from metagenomic data.

MOTIVATION: Although the set of currently known viruses has been steadily expanding, only a tiny fraction of the Earth's virome has been sequenced so far. Shotgun metagenomic sequencing provides an opportunity to reveal novel viruses but faces the computational challenge of identifying viral genomes that are often difficult to detect in metagenomic assemblies. RESULTS: We describe a MetaviralSPAdes tool for identifying viral genomes in metagenomic assembly graphs that is based on analyzing variations in the coverage depth between viruses and bacterial chromosomes. We benchmarked MetaviralSPAdes on diverse metagenomic datasets, verified our predictions using a set of virus-specific Hidden Markov Models and demonstrated that it improves on the state-of-the-art viral identification pipelines. AVAILABILITY AND IMPLEMENTATION: Metaviral SPAdes includes ViralAssembly, ViralVerify and ViralComplete modules that are available as standalone packages: https://github.com/ablab/spades/tree/metaviral_publication, https://github.com/ablab/viralVerify/ and https://github.com/ablab/viralComplete/. CONTACT: d.antipov@spbu.ru. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MGnify: the microbiome analysis resource in 2020.

MGnify (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the assembly, analysis and archiving of microbiome data derived from sequencing microbial populations that are present in particular environments. Over the past 2 years, MGnify (formerly EBI Metagenomics) has more than doubled the number of publicly available analysed datasets held within the resource. Recently, an updated approach to data analysis has been unveiled (version 5.0), replacing the previous single pipeline with multiple analysis pipelines that are tailored according to the input data, and that are formally described using the Common Workflow Language, enabling greater provenance, reusability, and reproducibility. MGnify's new analysis pipelines offer additional approaches for taxonomic assertions based on ribosomal internal transcribed spacer regions (ITS1/2) and expanded protein functional annotations. Biochemical pathways and systems predictions have also been added for assembled contigs. MGnify's growing focus on the assembly of metagenomic data has also seen the number of datasets it has assembled and analysed increase six-fold. The non-redundant protein database constructed from the proteins encoded by these assemblies now exceeds 1 billion sequences. Meanwhile, a newly developed contig viewer provides fine-grained visualisation of the assembled contigs and their enriched annotations.

Genomic Variations in Drug Resistant Mycobacterium tuberculosis Strains Collected from Patients with Different Localization of Infection.

Mycobacterium tuberculosis is a highly studied pathogen due to public health importance. Despite this, problems like early drug resistance, diagnostics and treatment success prediction are still not fully resolved. Here, we analyze the incidence of point mutations widely used for drug resistance detection in laboratory practice and conduct comparative analysis of whole-genome sequence (WGS) for clinical M. tuberculosis strains collected from patients with pulmonary tuberculosis (PTB) and extra-pulmonary tuberculosis (XPTB) localization. A total of 72 pulmonary and 73 extrapulmonary microbiologically characterized M. tuberculosis isolates were collected from patients from 2007 to 2014 in Russia. Genomic DNA was used for WGS and obtained data allowed identifying major mutations known to be associated with drug resistance to first-line and second-line antituberculous drugs. In some cases previously described mutations were not identified. Using genome-based phylogenetic analysis we identified M. tuberculosis substrains associated with distinctions in the occurrence in PTB vs. XPTB cases. Phylogenetic analyses did reveal M. tuberculosis genetic substrains associated with TB localization. XPTB was associated with Beijing sublineages Central Asia (Beijing CAO), Central Asia Clade A (Beijing A) and 4.8 groups, while PTB localization was associated with group LAM (4.3). Further, the XPTB strain in some cases showed elevated drug resistance patterns relative to PTB isolates. HIV was significantly associated with the development of XPTB in the Beijing B0/W148 group and among unclustered Beijing isolates.

Draft Genome Sequence of Mn(II)-Oxidizing Bacterium Oxalobacteraceae sp. Strain AB_14.

Biological Mn(II) oxidation produces reactive manganese oxides that help to mitigate metal contamination in the environment. Here, we present the genome of Oxalobacteraceae sp. strain AB_14, a species of Mn(II)-oxidizing bacteria (MOB) that is notable for its ability to catalyze Mn oxidation at low pH (5.5).

rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data.

BACKGROUND: The possibility of generating large RNA-sequencing datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the organisms with finished and well-annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing, and paralogous genes. RESULTS: Herein we describe the novel transcriptome assembler rnaSPAdes, which has been developed on top of the SPAdes genome assembler and explores computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-sequencing datasets, and briefly highlight strong and weak points of different assemblers. CONCLUSIONS: Based on the performed comparison between different assembly methods, we infer that it is not possible to detect the absolute leader according to all quality metrics and all used datasets. However, rnaSPAdes typically outperforms other assemblers by such important property as the number of assembled genes and isoforms, and at the same time has higher accuracy statistics on average comparing to the closest competitors.