An Exploration of K-Mer Ranges for Megahit in the Context of Microbial Community-Wide Identification of Antimicrobial Resistance Genes and Biosynthetic Gene Clusters

With the advent of genomics and next generation sequencing, metagenomics has become a discipline in its own right, enabling for the first time the study of complex microbial ecosystems containing species that cannot be cultured in the lab. Sequencing and characterizing these microbial genomes enables the identification of novel antimicrobial resistance genes (ARGs) and biosynthetic gene clusters (BGCs), with potential applications in industry. De novo sequence assembly, as a crucial step in metagenomics, is currently being implemented with tools such as MEGAHIT, which employ a multiple <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$k$</tex>-mer approach, where several intermediate assemblies are built from k-mers from a range of sizes and merged at the end. The objective of this study was to investigate the impact that this range of k-mer sizes could have on a range of quality metrics, including the number of identified ARGs and BGCs, using a series of assembly scenarios involving 7 samples collected from the Movile Cave in Romania We found that larger k-mer sizes and more fine-grained ranges of intermediate steps were associated with increased metrics, including larger numbers of identified BGCs. Future studies are required in order to better understand the role of the range of k-mer sizes in MEGAHIT in the context of microbial communitywide identification of ARGs and BGCs.