LEMON: a method to construct the local strains at horizontal gene transfer sites in gut metagenomics

Chen Li,Yiqi Jiang,Shuaicheng Li

doi:10.1186/s12859-019-3301-8

Abstract

BackgroundHorizontal Gene Transfer (HGT) refers to the transfer of genetic materials between organisms through mechanisms other than parent-offspring inheritance. HGTs may affect human health through a large number of microorganisms, especially the gut microbiomes which the human body harbors. The transferred segments may lead to complicated local genome structural variations. Details of the local genome structure can elucidate the effects of the HGTs.ResultsIn this work, we propose a graph-based method to reconstruct the local strains from the gut metagenomics data at the HGT sites. The method is implemented in a package named LEMON. The simulated results indicate that the method can identify transferred segments accurately on reference sequences of the microbiome. Simulation results illustrate that LEMON could recover local strains with complicated structure variation. Furthermore, the gene fusion points detected in real data near HGT breakpoints validate the accuracy of LEMON. Some strains reconstructed by LEMON have a replication time profile with lower standard error, which demonstrates HGT events recovered by LEMON is reliable.ConclusionsThrough LEMON we could reconstruct the sequence structure of bacteria, which harbors HGT events. This helps us to study gene flow among different microbial species.

Highlights

Horizontal Gene Transfer (HGT) refers to the transfer of genetic materials between organisms through mechanisms other than parent-offspring inheritance
Horizontal Gene Transfer [1, 2] is the movement of genetic materials between organisms other than by the vertical transmission of DNA from parent to offspring [3]
In this paper we present LEMON, a novel HGT discovery software that can detect HGT events and reconstruct strains containing multiple HGT events with complicated structural variation

Summary

Results

HGT events detection in simulated human gut microbiomes To simulate human gut microbiome with different complexity as mentioned in “Local strains” section, we constructed 5 simulated microbiomes containing 160, 320, 640, 1280, 2560 species, respectively. At 30X, LEMON detects all transferred segment and the RA is 1.0, which means LEMON has reconstructed the same structure as the true local strain, while LUMPY fails to detect Red +D1 and the RA is 0.9565. LEMON could detect more transferred segments than LUMPY and reconstruct more accurate strains across different coverage levels. It is reasonable to find only 3 matching breakpoints in 17 pairs of data

Background

Evaluation metrics

Conclusions and discussion