AFS: identification and quantification of species composition by metagenomic sequencing

Bioinformatics. 2017 May 1;33(9):1396-1398. doi: 10.1093/bioinformatics/btw822.

Abstract

Summary: DNA-based methods to detect and quantify taxon composition in biological materials are often based on species-specific polymerase chain reaction, limited to detecting species targeted by the assay. Next-generation sequencing overcomes this drawback by untargeted shotgun sequencing of whole metagenomes at affordable cost. Here we present AFS, a software pipeline for quantification of species composition in food. AFS uses metagenomic shotgun sequencing and sequence read counting to infer species proportions. Using Illumina data from a reference sausage comprising four species, we reveal that AFS is independent of the sequencing assay and library preparation protocol. Cost-saving short (50-bp) single-end reads and Nextera ® library preparation yield reliable results.

Availability and implementation: Datasets, binaries and usage instructions are available under http://all-food-seq.sourceforge.net. Raw data is available at NCBI's SRA with accession number PRJNA271645.

Contact: hankeln@uni-mainz.de.

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

  • Food Microbiology / methods*
  • High-Throughput Nucleotide Sequencing / methods
  • Metagenomics / methods*
  • Sequence Analysis, DNA / methods*
  • Software*