A walkthrough of identifying microbial species on the International Space Station's dining table using metagenomics. DNA sequencing data from a NASA study is processed with fastp for quality trimming, then classified with kraken2, a fast k-mer-based taxonomic classifier. The analysis reveals bacteria common to human skin, hospital environments, and food production — including a kimchi-associated strain (Leuconostoc mesenteroides MSL129) that appears to have survived and thrived on the ISS. The post also explains how kraken2 achieves its speed through minimizers, compact hash codes, and exact k-mer matching rather than alignment, drawing parallels to locality-sensitive hashing techniques used in web search and plagiarism detection.
14 Impressions