Integrative meta-omics in Galaxy and beyond

Valerie C. Schiml, Francesco Delogu, Praveen Kumar, Benoit Kunath, Bérénice Batut, Subina Mehta, James E. Johnson, Björn Grüning, Phillip B. Pope, Pratik D. Jagtap, Timothy J. Griffin, Magnus Arntzen

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Background: ‘Omics methods have empowered scientists to tackle the complexity of microbial communities on a scale not attainable before. Individually, omics analyses can provide great insight; while combined as “meta-omics”, they enhance the understanding of which organisms occupy specific metabolic niches, how they interact, and how they utilize environmental nutrients. Here we present three integrative meta-omics workflows, developed in Galaxy, for enhanced analysis and integration of metagenomics, metatranscriptomics, and metaproteomics, combined with our newly developed web-application, ViMO (Visualizer for Meta-Omics) to analyse metabolisms in complex microbial communities. Results: In this study, we applied the workflows on a highly efficient cellulose-degrading minimal consortium enriched from a biogas reactor to analyse the key roles of uncultured microorganisms in complex biomass degradation processes. Metagenomic analysis recovered metagenome-assembled genomes (MAGs) for several constituent populations including Hungateiclostridium thermocellum , Thermoclostridium stercorarium and multiple heterogenic strains affiliated to Coprothermobacter proteolyticus. The metagenomics workflow was developed as two modules, one standard, and one optimized for improving the MAG quality in complex samples by implementing a combination of single- and co-assembly, and dereplication after binning. The exploration of the active pathways within the recovered MAGs can be visualized in ViMO, which also provides an overview of the MAG taxonomy and quality (contamination and completeness), and information about carbohydrate-active enzymes (CAZymes), as well as KEGG annotations and pathways, with counts and abundances at both mRNA and protein level. To achieve this, the metatranscriptomic reads and metaproteomic mass-spectrometry spectra are mapped onto predicted genes from the metagenome to analyse the functional potential of MAGs, as well as the actual expressed proteins and functions of the microbiome, all visualized in ViMO. Conclusion: Our three workflows for integrative meta-omics in combination with ViMO presents a progression in the analysis of ‘omics data, particularly within Galaxy, but also beyond. The optimized metagenomics workflow allows for detailed reconstruction of microbial community consisting of MAGs with high quality, and thus improves analyses of the metabolism of the microbiome, using the metatranscriptomics and metaproteomics workflows.

Original languageEnglish (US)
Article number56
JournalEnvironmental Microbiome
Volume18
Issue number1
DOIs
StatePublished - Dec 2023

Bibliographical note

Funding Information:
This research was supported by the Novo Nordisk Foundation through Grant NNF20OC0061313, and by the Research Council of Norway INFRASTRUKTUR-program Grant No. 295910, and through the joint University of Minnesota-NMBU Norwegian Centennial Chair program. The Galaxy server that was used for some calculations is in part funded by Collaborative Research Centre 992 Medical Epigenetics (DFG Grant SFB 992/1 2012) and German Federal Ministry of Education and Research (BMBF Grants 031 A538A/A538C RBC, 031L0101B/031L0101C de.NBI-epi, 031L0106 de.STAIR (de.NBI)).

Funding Information:
The authors would like to thank Live H. Hagen, Norwegian University of Life Sciences for valuable discussions regarding the implementation of the optimized metagenomics workflow.

Publisher Copyright:
© 2023, The Author(s).

Keywords

  • Bioinformatics
  • Galaxy
  • Integrated meta-omics
  • Metagenomics
  • Metaproteomics
  • Metatrascriptomics

PubMed: MeSH publication types

  • Journal Article

Fingerprint

Dive into the research topics of 'Integrative meta-omics in Galaxy and beyond'. Together they form a unique fingerprint.

Cite this