Supporting data for "MOBFinder: A tool for mobilization typing of plasmid metagenomic fragments based on a language model"

Mobilization typing (MOB) is a classification scheme for plasmid genomes based on their relaxase gene. The host ranges of plasmids of different MOB categories are diverse and MOB is crucial for investigating plasmid mobilization, especially the transmission of resistance genes and virulence factors. However, MOB typing of plasmid metagenomic data is challenging due to the highly fragmented characteristics of metagenomic contigs.<br>We developed MOBFinder, an 11-class classifier, for categorizing plasmid fragments into 10 MOB types and a non-mobilizable category. We first performed MOB typing to classify complete plasmid genomes according to relaxase information and then constructed an artificial benchmark dataset of plasmid metagenomic fragments (PMFs) from those complete plasmid genomes whose MOB types are well annotated. Next, based on natural language models, we used word vectors to characterize the PMFs. Several random forest classification models were trained and integrated to predict fragments of different lengths. Evaluating the tool using the benchmark dataset, we found that MOBFinder outperforms previous tools such as MOBscan and MOB-suite, with an overall <i>accuracy</i> approximately 59% higher than that of MOB-suite. Moreover, the <i>balanced accuracy</i>, <i>harmonic mean</i>, and <i>F1-score</i> reached up to 99% for some MOB types. When applied to a cohort of patients with type II diabetes (T2D), MOBFinder offered insights suggesting that the MOBF type plasmid, which is widely present in <i>Escherichia</i> and <i>Klebsiella</i>, and the MOBQ type plasmid, might accelerate antibiotic resistance transmission in patients suffering from T2D.<br>To the best of our knowledge, MOBFinder is the first tool for MOB typing of PMFs.