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

Brown, C. Titus; Moritz, Dominik; O’Brien, Michael P.; Reidl, Felix; Reiter, Taylor; Sullivan, Blair D.

doi:10.1186/s13059-020-02066-4

Cited by 39 publications

(68 citation statements)

References 54 publications

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“…Taxonomy of the bins was assigned using the Genome Taxonomy Database (GTDB-Tk) on KBaseGhostKOALA v2.2 and Prokka v1.11 were used to annotate genes in the cyanobacterial bin of interest [ 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 ]. To refine the bin, spacegraphcats was used to extract additional content of the bin with a k size of 21 [ 65 ]. The code used for the analyses presented here is available at , accessed on 1 March 2021.…”

Section: Methodsmentioning

confidence: 99%

Metabolic Capacity of the Antarctic Cyanobacterium Phormidium pseudopriestleyi That Sustains Oxygenic Photosynthesis in the Presence of Hydrogen Sulfide

Lumian

Jungblut

Dillion

et al. 2021

Genes

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Sulfide inhibits oxygenic photosynthesis by blocking electron transfer between H2O and the oxygen-evolving complex in the D1 protein of Photosystem II. The ability of cyanobacteria to counter this effect has implications for understanding the productivity of benthic microbial mats in sulfidic environments throughout Earth history. In Lake Fryxell, Antarctica, the benthic, filamentous cyanobacterium Phormidium pseudopriestleyi creates a 1–2 mm thick layer of 50 µmol L−1 O2 in otherwise sulfidic water, demonstrating that it sustains oxygenic photosynthesis in the presence of sulfide. A metagenome-assembled genome of P. pseudopriestleyi indicates a genetic capacity for oxygenic photosynthesis, including multiple copies of psbA (encoding the D1 protein of Photosystem II), and anoxygenic photosynthesis with a copy of sqr (encoding the sulfide quinone reductase protein that oxidizes sulfide). The genomic content of P. pseudopriestleyi is consistent with sulfide tolerance mechanisms including increasing psbA expression or directly oxidizing sulfide with sulfide quinone reductase. However, the ability of the organism to reduce Photosystem I via sulfide quinone reductase while Photosystem II is sulfide-inhibited, thereby performing anoxygenic photosynthesis in the presence of sulfide, has yet to be demonstrated.

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Section: Methodsmentioning

confidence: 99%

Metabolic Capacity of the Antarctic Cyanobacterium Phormidium pseudopriestleyi That Sustains Oxygenic Photosynthesis in the Presence of Hydrogen Sulfide

Lumian

Jungblut

Dillion

et al. 2021

Genes

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“…To summarise, RECAST algorithm offers an improved approach for analysis of FMT experiments metagenomic data which allows researchers to gain novel biological insights. The idea of reads sorting prior to the comparison of metagenomes with the common computational approaches enables to preserve more data by presenting it unchanged from, for example, compared to the metagenomic assembly, which can cause the loss of a significant part of information [Olekhnovich et al, 2018;Brown et al, 2020]. Using the RECAST algorithm, not only FMT data such as [Draper et al, 2018] can be analyzed, but also, for example, the colonization of the organism of children by the microbiota of mothers [Ferretti et al, 2018] or others.…”

Section: Discussionmentioning

confidence: 99%

Gut microbiota alterations due to fecal transplant

Olekhnovich

Ivanov

Ulyantsev

et al. 2020

Preprint

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BackgroundFecal microbiota transplantation (FMT) is currently used to treat recurrent clostridial colitis and other diseases. However, neither the therapeutic mechanism of the FMT nor the mechanism that allows the donor bacteria to colonize the intestine of the recipient has yet been described. Moreover, FMT is a great model for studying the ecology of host-associated microbial communities. This creates the need for experimentation with approaches to metagenomic data analysis which may be useful to the interpretation of observed biological phenomena.MethodsHere the RECAST (Recipient intestinE Colonisation AnalysiS Tool) computational approach is presented, which is based on the shotgun reads sorting process in accordance with their origin in recipient metagenome. Using the RECAST algorithm, taxonomic/functional annotation, and machine learning, the shotgun metagenomic data from three FMT studies including healthy volunteers, patients with clostridial colitis and metabolic syndrome were analyzed.ResultsAccording to the analysis results, the colonizing and remaining microbial diversity in the post-FMT recipient metagenomic samples is clearly separated from the non-colonizers and lost. It is well explained by higher relative abundance in donor/pre-FMT recipient, Human Microbiome project metagenomes, and taxonomy. Moreover, the colonizing and remaining microbes are associated with lantibiotic and tetracyclines resistance genes.ConclusionBased on obtained results, the previously proposed “core” human gut microbiome concept may be elaborated. The top microbes of gut microbiota form “cores”, which, moreover, are mutually integrable between humans. Also, we assume that redistribution of microbial diversity in post-FMT recipients’ metagenomes is due to competition of donor/recipient microbes and to host immunity. The associations of top gut microbes with lantibiotic/antibiotic resistance can be related to gut microbiota colonization resistance phenomena or anthropogenic impact.

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“…Fortunately, workflow system coordination alleviates the need for a user to directly manage file interdependencies. For a larger analysis DAG, see [48]…”

Section: Workflow-based Project Managementmentioning

confidence: 99%

Streamlining Data-Intensive Biology With Workflow Systems

Reiter¹,

Brooks

Irber³

et al. 2020

Preprint

Self Cite

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AbstractAs the scale of biological data generation has increased, the bottleneck of research has shifted from data generation to analysis. Researchers commonly need to build computational workflows that include multiple analytic tools and require incremental development as experimental insights demand tool and parameter modifications. These workflows can produce hundreds to thousands of intermediate files and results that must be integrated for biological insight. The maturation of data-centric workflow systems that internally manage computational resources, software, and conditional execution of analysis steps are reshaping the landscape of biological data analysis, and empowering researchers to conduct reproducible analyses at scale. Adoption of these tools can facilitate and expedite robust data analysis, but knowledge of these techniques is still lacking. Here, we provide a series of practices and strategies for leveraging workflow systems with structured project, data, and resource management to streamline large-scale biological analysis.Author SummaryWe present a guide for workflow-enabled biological sequence data analysis, developed through our own teaching, training and analysis projects. We recognize that this is based on our own use cases and experiences, but we hope that our guide will contribute to a larger discussion within the open source and open science communities and lead to more comprehensive resources. Our main goal is to accelerate the research of scientists conducting sequence analyses by introducing them to organized workflow practices that not only benefit their own research but also facilitate open and reproducible science.

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

Cited by 39 publications

References 54 publications

Metabolic Capacity of the Antarctic Cyanobacterium Phormidium pseudopriestleyi That Sustains Oxygenic Photosynthesis in the Presence of Hydrogen Sulfide

Metabolic Capacity of the Antarctic Cyanobacterium Phormidium pseudopriestleyi That Sustains Oxygenic Photosynthesis in the Presence of Hydrogen Sulfide

Gut microbiota alterations due to fecal transplant

Streamlining Data-Intensive Biology With Workflow Systems

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