Evidence map›Paper›PMID 39436938›Full record

ArticlePLoS computational biology2024

Simulation of 69 microbial communities indicates sequencing depth and false positives are major drivers of bias in prokaryotic metagenome-assembled genome recovery.

Ulisses Rocha, Jonas Coelho Kasmanas, Rodolfo Toscan, Danilo S Sanches, Stefania Magnusdottir, Joao Pedro Saraiva

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Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ulisses RochaDepartment of Applied Microbial Ecology, Helmholtz Center for Environmental Research-UFZ, Leipzig, Germany.ORCID 0000-0001-6972-6692
Jonas Coelho KasmanasDepartment of Applied Microbial Ecology, Helmholtz Center for Environmental Research-UFZ, Leipzig, Germany.
Rodolfo ToscanDepartment of Applied Microbial Ecology, Helmholtz Center for Environmental Research-UFZ, Leipzig, Germany.
Danilo S SanchesDepartment of Computer Science, Federal University of Technology-Paraná, UTFPR, Cornélio Procópio, Brazil.
Stefania MagnusdottirDepartment of Applied Microbial Ecology, Helmholtz Center for Environmental Research-UFZ, Leipzig, Germany.
Joao Pedro SaraivaDepartment of Applied Microbial Ecology, Helmholtz Center for Environmental Research-UFZ, Leipzig, Germany.ORCID 0000-0001-8251-1960

Funding

Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) 460129525Helmholtz Young Investigator grant VH-NG-1248São Paulo Research Foundation (FAPESP) 2019/03396-9São Paulo Research Foundation (FAPESP) 2022/03534-5
6 · The paper itself

Abstract

We hypothesize that sample species abundance, sequencing depth, and taxonomic relatedness influence the recovery of metagenome-assembled genomes (MAGs). To test this hypothesis, we assessed MAG recovery in three in silico microbial communities composed of 42 species with the same richness but different sample species abundance, sequencing depth, and taxonomic distribution profiles using three different pipelines for MAG recovery. The pipeline developed by Parks and colleagues (8K) generated the highest number of MAGs and the lowest number of true positives per community profile. The pipeline by Karst and colleagues (DT) showed the most accurate results (~ 92%), outperforming the 8K and Multi-Metagenome pipeline (MM) developed by Albertsen and collaborators. Sequencing depth influenced the accurate recovery of genomes when using the 8K and MM, even with contrasting patterns: the MM pipeline recovered more MAGs found in the original communities when employing sequencing depths up to 60 million reads, while the 8K recovered more true positives in communities sequenced above 60 million reads. DT showed the best species recovery from the same genus, even though close-related species have a low recovery rate in all pipelines. Our results highlight that more bins do not translate to the actual community composition and that sequencing depth plays a role in MAG recovery and increased community resolution. Even low MAG recovery error rates can significantly impact biological inferences. Our data indicates that the scientific community should curate their findings from MAG recovery, especially when asserting novel species or metabolic traits.

Indexed as

Computer SimulationMetagenomeMicrobiotaBacteriaComputational BiologyGenome, BacterialHigh-Throughput Nucleotide SequencingMetagenomicsSequence Analysis, DNA

Identifiers

PMID39436938
PMCPMC11530072

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.