metamage

metamage is a workflow for taxonomic classification, assembly, binning and annotation of short-read host-associated metagenomics datasets.

mermaid graph TD; reads[(Short-read paired-end metagenomics data)]-->hostread(Trimming and host read removal) hostread-->|Reads| tax(Taxonomic classification with Kaiju) hostread-->|Reads| assem(Assembly with MEGAHIT) assem-.->|Assembled contigs| metaq(MetaQuast evaluation) assem-->|Assembled contigs| func(Functional annotation) assem-->|Assembled contigs| binprep(Binning preparation) hostread-->|Reads| binprep assem-->|Assembled contigs| bin(Binning with MetaBAT2) binprep-->|Depth file| bin

It's composed of:

Read pre-processing and host read removal

• fastp for read trimming and other general pre-processing [^9]
• BowTie2 for mapping to the host genome and extracting unaligned reads [^10]

Assembly

• MEGAHIT for assembly [^1]
• MetaQuast for assembly evaluation

Functional annotation

• Macrel for predicting Antimicrobial Peptide (AMP)-like sequences from contigs [^6]
• fARGene for identifying Antimicrobial Resistance Genes (ARGs) from contigs [^7]
• Gecco for predicting biosynthetic gene clusters (BCGs) from contigs [^8]
• Prodigal for protein-coding gene prediction from contigs. [^5]

Binning

• BowTie2 and Samtools[^11] to building depth files for binning.
• MetaBAT2 for binning [^2]

Taxonomic classification of reads

• Kaiju for taxonomic classification [^3]
• KronaTools for visualizing taxonomic classification results

Output tree

• |metamage
  • |{sample_name}
  • |{samplename}_btidx - Host genome BowTie index
  • |{samplename}_btunaligned - Reads that didn't align to the host genome
  • |fastp_results - Results from trimming with fastp
  • |kaiju
  • |MEGAHIT
  • |MetaQuast - Assembly evaluation report
  • |{samplename}_assemblyidx - BowTie Index from assembly data
  • |{samplename}_assemblysorted.bam - Reads aligned to assembly contigs
  • |METABAT
  • |fargene_results
  • |gecco_results
  • |macrel_results
  • |prodigal_results

Where to get the data?

• Kaiju indexes can be generated based on a reference database but you can also find some pre-built ones in the sidebar of the Kaiju website.

• Reference host genomes can be acquired from a variety of databases, for example Ensembl.

[^1]: Li, D., Luo, R., Liu, C.M., Leung, C.M., Ting, H.F., Sadakane, K., Yamashita, H. and Lam, T.W., 2016. MEGAHIT v1.0: A Fast and Scalable Metagenome Assembler driven by Advanced Methodologies and Community Practices. Methods. [^2]: Alla Mikheenko, Vladislav Saveliev, Alexey Gurevich, MetaQUAST: evaluation of metagenome assemblies, Bioinformatics (2016) 32 (7): 1088-1090. doi: 10.1093/bioinformatics/btv697

[^3]: Kang DD, Li F, Kirton E, Thomas A, Egan R, An H, Wang Z. 2019. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ 7:e7359 https://doi.org/10.7717/peerj.7359

[^4]: Menzel, P., Ng, K. & Krogh, A. Fast and sensitive taxonomic classification for metagenomics with Kaiju. Nat Commun 7, 11257 (2016). https://doi.org/10.1038/ncomms11257

[^5]: Hyatt, D., Chen, GL., LoCascio, P.F. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11, 119 (2010). https://doi.org/10.1186/1471-2105-11-119

[^6]: Santos-Júnior CD, Pan S, Zhao X, Coelho LP. 2020. Macrel: antimicrobial peptide screening in genomes and metagenomes. PeerJ 8:e10555. DOI: 10.7717/peerj.10555

[^7]: Berglund, F., Österlund, T., Boulund, F., Marathe, N. P., Larsson, D. J., & Kristiansson, E. (2019). Identification and reconstruction of novel antibiotic resistance genes from metagenomes. Microbiome, 7(1), 52.

[^8]: Accurate de novo identification of biosynthetic gene clusters with GECCO. Laura M Carroll, Martin Larralde, Jonas Simon Fleck, Ruby Ponnudurai, Alessio Milanese, Elisa Cappio Barazzone, Georg Zeller. bioRxiv 2021.05.03.442509; doi:10.1101/2021.05.03.442509

[^9]: Shifu Chen, Yanqing Zhou, Yaru Chen, Jia Gu; fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, Volume 34, Issue 17, 1 September 2018, Pages i884–i890, https://doi.org/10.1093/bioinformatics/bty560

[^10]: Langmead B, Wilks C., Antonescu V., Charles R. Scaling read aligners to hundreds of threads on general-purpose processors. Bioinformatics. bty648.

[^11]: Twelve years of SAMtools and BCFtools Petr Danecek, James K Bonfield, Jennifer Liddle, John Marshall, Valeriu Ohan, Martin O Pollard, Andrew Whitwham, Thomas Keane, Shane A McCarthy, Robert M Davies, Heng Li GigaScience, Volume 10, Issue 2, February 2021, giab008, https://doi.org/10.1093/gigascience/giab008