RBUD: A New Functional Potential Analysis Approach for Whole Microbial Genome Shotgun Sequencing.

Zhikai Xing,Shuangli Mi,Chongye Guo,Meng Li,Yunting Zhang

doi:10.3390/microorganisms8101563

Abstract

Whole metagenome shotgun sequencing is a powerful approach to detect the functional potential of microbial communities. Currently, the read-based metagenomics profiling for established database (RBED) method is one of the two kinds of conventional methods for species and functional annotations. However, the databases, which are established based on test samples or specific reference genomes or protein sequences, limit the coverage of global microbial diversity. The other assembly-based metagenomics profiling for unestablished database (ABUD) method has a low utilization rate of reads, resulting in a lot of biological information loss. In this study, we proposed a new method, read-based metagenomics profiling for unestablished database (RBUD), based on Metagenome Database of Global Microorganisms (MDGM), to solve the above problems. To evaluate the accuracy and effectiveness of our method, the intestinal bacterial composition and function analyses were performed in both avian colibacillosis chicken cases and type 2 diabetes mellitus patients. Comparing to the existing methods, RBUD is superior in detecting proteins, percentage of reads mapping and ontological similarity of intestinal microbes. The results of RBUD are in better agreement with the classical functional studies on these two diseases. RBUD also has the advantages of fast analysis speed and is not limited by the sample size.

Highlights

In recent years, with the improvement of high-throughput sequencing technology and the rapid development of microbial research methods, it has been possible to systematically analyze all microorganisms in samples, not just those that are amenable to cultivation
The published fecal shotgun metagenomic data of type 2 diabetes mellitus (T2D) and healthy controls were searched through PubMed
To fulfill the construction of Metagenome Database of Global Microorganisms (MDGM), there were several sub-steps that needed to be done as follows: firstly, whole microbial genome data (5133 bacteria, 9548 viruses and 243 fungi) and corresponding species and their taxonomic annotation information were downloaded from the National Center for Biotechnology Information (NCBI) database to construct the microbial species dataset [17]

Summary

Introduction

With the improvement of high-throughput sequencing technology and the rapid development of microbial research methods, it has been possible to systematically analyze all microorganisms in samples, not just those that are amenable to cultivation These methods were mainly applied to taxonomic studies of microorganism using phylogenetic information genes (such as ribosomal RNA) [1,2]. The former requires reads splicing, contigs assembly and prediction of open reading frame (ORF) before mapping the data to the reference database [9] In all these steps, data utilization is reduced due to the loss of low coverage areas [8]. The current methods are not sufficient to achieve the functional metagenomics studies for the lack of existing metagenomic databases and small sample size These methods cannot effectively improve the utilization of sequencing data. Our method can generate a report document containing comprehensive analysis results, including species abundance, gene abundance, gene ontology, pathways and antibiotic resistance

Animals

Raw Data Quality Control

Similarity Analysis of Bacteria Species

Statistical Analysis

Basic Workflow and Characteristics of Three Different Metagenomics Profiling