MAGNETO: An Automated Workflow for Genome-Resolved Metagenomics

Churcheward, Benjamin; Millet, Maxime; Bihouée, Audrey; Fertin, Guillaume; Chaffron, Samuel

doi:10.1128/msystems.00432-22

Cited by 12 publications

(11 citation statements)

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“…The Chaetoceros genus was notably the best represented of all diatom genera (11 out of 52 diatom MAGs) [ 46 ], in agreement with its broad distribution and abundance patterns [ 13 ]. Future studies involving increased sequencing effort coupled with innovative assembly strategies, such as automated MAG recovery workflows [ 80 ], will likely improve the access to new resources for this genus and other diatoms in the near future. The genomes we considered for the present study displayed the same magnitude in size, number of protein-coding genes and G+C content as the newly published Chaetoceros tenuissimus genome [ 81 ], pointing out the accuracy of the MAG reconstruction methods.…”

Section: Discussionmentioning

confidence: 99%

Whole-genome scanning reveals environmental selection mechanisms that shape diversity in populations of the epipelagic diatom Chaetoceros

et al. 2022

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Diatoms form a diverse and abundant group of photosynthetic protists that are essential players in marine ecosystems. However, the microevolutionary structure of their populations remains poorly understood, particularly in polar regions. Exploring how closely related diatoms adapt to different environments is essential given their short generation times, which may allow rapid adaptations, and their prevalence in marine regions dramatically impacted by climate change, such as the Arctic and Southern Oceans. Here, we address genetic diversity patterns in Chaetoceros, the most abundant diatom genus and one of the most diverse, using 11 metagenome-assembled genomes (MAGs) reconstructed from Tara Oceans metagenomes. Genome-resolved metagenomics on these MAGs confirmed a prevalent distribution of Chaetoceros in the Arctic Ocean with lower dispersal in the Pacific and Southern Oceans as well as in the Mediterranean Sea. Single-nucleotide variants identified within the different MAG populations allowed us to draw a landscape of Chaetoceros genetic diversity and revealed an elevated genetic structure in some Arctic Ocean populations. Gene flow patterns of closely related Chaetoceros populations seemed to correlate with distinct abiotic factors rather than with geographic distance. We found clear positive selection of genes involved in nutrient availability responses, in particular for iron (e.g., ISIP2a, flavodoxin), silicate, and phosphate (e.g., polyamine synthase), that were further supported by analysis of Chaetoceros transcriptomes. Altogether, these results highlight the importance of environmental selection in shaping diatom diversity patterns and provide new insights into their metapopulation genomics through the integration of metagenomic and environmental data.

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Section: Discussionmentioning

confidence: 99%

Whole-genome scanning reveals environmental selection mechanisms that shape diversity in populations of the epipelagic diatom Chaetoceros

et al. 2022

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“…Lastly, the postprocessing module renders runtime and memory usage Table 1. Comparison of features between Metaphor and state-of-the-art GRM workflows as listed by [29]. Data adapted to include Metaphor.…”

Section: Design and Implementationmentioning

confidence: 99%

“…A simplified version of the flow of data between the different modules of the workflow is show on Fig 1 . Table 1. Comparison of features between Metaphor and state-of-the-art GRM workflows as listed by [29]. Data adapted to include Metaphor.…”

Section: Design and Implementationmentioning

confidence: 99%

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Metaphor - A workflow for streamlined assembly and binning of metagenomes

Salazar

Shabban

Quiroga

et al. 2023

Preprint

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Recent advances in bioinformatics and high-throughput sequencing have enabled the large-scale recovery of genomes from metagenomes. This has the potential to bring important insights as researchers can bypass cultivation and analyse genomes sourced directly from environmental samples. There are, however, technical challenges associated with this process, most notably the complexity of computational workflows required to process metagenomic data, which include dozens of bioinformatics software tools, each with their own set of customisable parameters that affect the final output of the workflow. At the core of these workflows are the processes of assembly - combining the short input reads into longer, contiguous fragments (contigs), and binning - clustering these contigs into individual genome bins. Both processes can be done for each sample separately or by pooling together multiple samples to leverage information from a combination of samples. Here we present Metaphor, a fully-automated workflow for genome-resolved metagenomics (GRM). Metaphor differs from existing GRM workflows by offering flexible approaches for the assembly and binning of the input data, and by combining multiple binning algorithms with a bin refinement step to achieve high quality genome bins. Moreover, Metaphor generates reports to evaluate the performance of the workflow. We showcase the functionality of Metaphor on different synthetic datasets, and the impact of available assembly and binning strategies on the final results. The workflow is freely available at https://github.com/vinisalazar/metaphor.

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“…Although the use of MAGs in microbial ecology is becoming a common practice nowadays, processing raw metagenomic reads up to genome reconstruction involves various steps and software which can represent a major technical obstacle, especially for non-specialists. To face this problem, several workflows such as MetaWRAP, 12 its Snakemake version called SnakeWRAP, 13 ATLAS 14 and more recently MAGNETO, 15 have been developed to automatically reconstruct genomes from metagenomes. However, these workflows contain various modules and perform more tasks than only generating MAGs.…”

Section: Introductionmentioning

confidence: 99%

SnakeMAGs: a simple, efficient, flexible and scalable workflow to reconstruct prokaryotic genomes from metagenomes

Tadrent

Dedeine²

2023

F1000Res

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Background: Over the last decade, we have observed in microbial ecology a transition from gene-centric to genome-centric analyses. Indeed, the advent of metagenomics combined with binning methods, single-cell genome sequencing as well as high-throughput cultivation methods have contributed to the continuing and exponential increase of available prokaryotic genomes, which in turn has favored the exploration of microbial metabolisms. In the case of metagenomics, data processing, from raw reads to genome reconstruction, involves various steps and software which can represent a major technical obstacle. Methods: To overcome this challenge, we developed SnakeMAGs, a simple workflow that can process Illumina data, from raw reads to metagenome-assembled genomes (MAGs) classification and relative abundance estimate. It integrates state-of-the-art bioinformatic tools to sequentially perform: quality control of the reads (illumina-utils, Trimmomatic), host sequence removal (optional step, using Bowtie2), assembly (MEGAHIT), binning (MetaBAT2), quality filtering of the bins (CheckM, GUNC), classification of the MAGs (GTDB-Tk) and estimate of their relative abundance (CoverM). Developed with the popular Snakemake workflow management system, it can be deployed on various architectures, from single to multicore and from workstation to computer clusters and grids. It is also flexible since users can easily change parameters and/or add new rules. Results: Using termite gut metagenomic datasets, we showed that SnakeMAGs is slower but allowed the recovery of more MAGs encompassing more diverse phyla compared to another similar workflow named ATLAS. Importantly, these additional MAGs showed no significant difference compared to the other ones in terms of completeness, contamination, genome size nor relative abundance. Conclusions: Overall, it should make the reconstruction of MAGs more accessible to microbiologists. SnakeMAGs as well as test files and an extended tutorial are available at https://github.com/Nachida08/SnakeMAGs.

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MAGNETO: An Automated Workflow for Genome-Resolved Metagenomics

Cited by 12 publications

References 73 publications

Whole-genome scanning reveals environmental selection mechanisms that shape diversity in populations of the epipelagic diatom Chaetoceros

Whole-genome scanning reveals environmental selection mechanisms that shape diversity in populations of the epipelagic diatom Chaetoceros

Metaphor - A workflow for streamlined assembly and binning of metagenomes

SnakeMAGs: a simple, efficient, flexible and scalable workflow to reconstruct prokaryotic genomes from metagenomes

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