Draft genome sequence of multidrug-resistant Bradyrhizobium sp. BL isolated from a sewage treatment plant in China

The genus Bradyrhizobium is considered to be widespread and abundant group of symbiotic bacteria in many plant-soil ecosystems. However, the ecological versatility of this phylogenetic group remains highly understudied in man-made ecosystems, mainly due to the lack of pure cultures and genomic data. To further expand our understanding of this genus for human health, we analyzed the high quality draft genome of Bradyrhizobium strain BL, isolated from a municipal wastewater treatment plant in Ningbo, China. The Bradyrhizobium sp. BL draft genome has a total size of 7,718,431 bp with an overall G + C content of 46.43%. From a total of 7236 predicted sequences, 7176 and 60 are protein and RNA coding sequences, respectively. Moreover, 63.51% of the predicted genes were assigned into to Clusters of Orthologous Groups (COG) functional categories. The Bradyrhizobium sp. BL genome contains various defense mechanisms against antibiotics that up to predicted 60 antibiotic resistance coding genes. The Bradyrhizobium sp. BL genome contains 237 termed virulence factors coding genes which show its potential pathogenicity. This study provides important insights into the genomic diversity of the genus Bradyrhizobium and provides a foundation for future comparative genomic studies that will generate a better understanding of the antibiotic resistance process.


Introduction
Antibiotics are hailed as the greatest harvest of the medical profession in the 20th century. They have been widely used in medical, agricultural and animal husbandry since they were discovered. However, long-term excessive use of antibiotics or abuse of antibiotics will make a huge difference to ourselves and our living environment. The threat also leads to the widespread spread of antibiotic-resistant bacteria [1]. At present, a large number of studies have found that resistant microorganisms are widely spread in water, soil, air and other media and in animals and plants [2,3].
The sewage treatment plant is a gathering place for urban sewage and wastewater. The antibiotic pollutants discharged from various pollution sources are collected into urban sewage treatment plants through different channels [4,5], some of the resistant bacteria in the sewage are removed by the treatment technology, and the other part of the resistant bacteria are discharged into the environment through the water outlet of the sewage treatment plant, causing secondary impact on the urban environment such as natural water. Therefore, understanding and studying the resistant microorganisms in the effluent of sewage treatment plants is particularly important for the biological risk assessment and control of wastewater treatment and reuse [4].
In this experiment, we carried out water sampling research from the effluent of Beilun Yandong Wastewater Treatment Plant in Ningbo, and isolated and identified a kind of resistance microorganisms of sulfamethoxazole, trimethoprim and erythromycin. We performed the whole genome sequencing of this resistant microorganism isolated from the sewage treatment plant and determined that the resistant microorganism belongs to Bradyrhizobium. The dataset has been submitted to the European Nucleotide Archive (ENA) and is reported here.

Materials And Methods
Isolation of the bacterial strain.
Sewage sample was diluted 30 times and pipetted 100 µL diluent in YEP-Agar medium (Yeast extract 5.0 g/L, peptone 10.0 g/L, NaCL 5.0 g/L, and agar 15.0 g/L) for 72 hours at 30 o C. The growing bacterial colonies were sub-cultured. Here, we selected and isolated sulfamethoxazole (8.0 mg/L), trimethoprim (4.0 mg/L) and erythromycin (4.0 mg/L) resistant bacteria. After three generation purifications, a purified isolate BL was obtained.
Genome sequencing and assembly.
We got water samples containing resistant microorganisms from a sewage treatment plant outlet, then extracted strains and genomic DNA from water samples. Genomic DNA was isolated by using a commercial kit (Thermo Fisher). The quality of isolated DNA was checked using a Qubit fluorimeter (Thermo Fisher). Genomic DNA sequencing were performed using Illumina Hiseq™ to obtain raw image data, which were then converted to the original sequencing reads by CASAVA Base Calling analysis. The raw data quality value and other information were statistically analyzed, and the quality of the sampled data was visually evaluated using FastQC, then the data was processed by Trimmomatic to obtain clean data [6]. For the clean data that have been obtained, the SPAdes was used to splice [7], and the contigs complement GAP obtained by splicing were used by GapFiller [8]. We used PrInSeS-G for sequence correction, correcting clipping errors during splicing and insertion of small fragments [9].
Prokka is a collection of genetic element prediction tools that call Prodigal to predict coding genes, Aragorn predicts tRNA, RNAmmer predicts rRNA, and Infernal predicts miscRNA [10]. The predicted gene elements are eventually aggregated and completed the preliminary note. Meanwhile, we used RepeatModerler to perform the repeated sequence prediction of the assembly results, and then used RepeatMasker to find the position and frequency of each type of repeat sequence on the genome segment.
Genome annotation and protein classification.
We used NCBI Blast to compare gene protein sequences with multiple databases to obtain functional annotation information [11]. These databases are VFDB, CARD, PHI-base and other virulence factors and drug resistance databases as well as CDD, KOG, COG, NR, NT, PFAM, Swissprot, TrEMBL, KEGG. At the same time, we used HMMER3 to compare the gene protein sequence with the CAZy database to obtain functional annotation information [12].
In addition, we used TMHMM for transmembrane protein prediction analysis [13], SignalP for signal peptide prediction analysis [14], LipoP for lipoprotein prediction analysis [15], ProtCamp for protein subcellular localization analysis, IslandPath-DIOMB for genomic island prediction analysis, and PhiSpy for prophage prediction analysis.
Comparative genomics and phylogenetic analysis.
We used NCBI Blast to compare the predicted 16S rRNA gene sequence with the NCBI database [11], obtained the information of the homologous strain, and constructed the phylogenetic tree. The phylogenetic tree was built using neighbor-joining method [16] and the evolutionary distances were computed using the Maximum Composite Likelihood method [17] available on MEGA7 phylogenetic suite [18]. The PGAP was used to perform pan-genome analysis and homologous gene cluster analysis based on the homologous strain gene information [19], and a phylogenetic tree was constructed based on the homologous gene.

Results And Discussion
Genome sequencing information Genome project history.
The genus Bradyrhizobium within the Alphaproteobacteria is traditionally associated with legumes and was proposed by Jordan [20] for all slow-growing strains from the genus Rhizobium. Bradyrhizobium species are symbiotic bacteria inducing the formation of nitrogen-fixing nodules on the roots of plants [21], and could be resistance to different  (Figure 2).

Genome properties.
The Bradyrhizobium sp. BL draft genome consists of 61,051,394 reads and has a total size of 7,718,431 bp with an overall G + C content of 46.43% (Table 1). From a total of 7236 predicted sequences, 7176 and 60 are proteins and RNA coding sequences, respectively.
Moreover, 63.51% of the predicted genes were assigned into to Clusters of Orthologous Groups (COG) functional categories ( Table 2).
Insights from the genome sequence.

Conclusions
In this study, the genome of Bradyrhizobium sp. BL was analyzed, demonstrating that

Abbreviations
Mdt: multidrug resistance proteins; Acr: multidrug efflux pump subunit; Bep: efflux pump membrane transporter. the draft of manuscript. Guo-Xiang Li, Yu-Qin He and Yi Dai did the assembly and annotation. Peng Bao supervised the study. All authors discussed, revised and approved the final manuscript.

Funding
This research was financially supported by Ningbo Science and Technology People-Benefit Project (No. 2017C50009), Ningbo Leading Talent Program.

Competing interests
The authors declare that they have no competing interests. The data used to support the findings of this study are included within the article and the supplementary information file.