BackgroundArsenic is known as a toxic metalloid, which primarily exists in inorganic form [As(III) and As(V)] and can be transformed by microbial redox processes in the natural environment. As(III) is much more toxic and mobile than As(V), hence microbial arsenic redox transformation has a major impact on arsenic toxicity and mobility which can greatly influence the human health. Our main purpose was to investigate the distribution and diversity of microbial arsenite-resistant species in three different arsenic-contaminated soils, and further study the As(III) resistance levels and related functional genes of these species.ResultsA total of 58 arsenite-resistant bacteria were identified from soils with three different arsenic-contaminated levels. Highly arsenite-resistant bacteria (MIC > 20 mM) were only isolated from the highly arsenic-contaminated site and belonged to Acinetobacter, Agrobacterium, Arthrobacter, Comamonas, Rhodococcus, Stenotrophomonas and Pseudomonas. Five arsenite-oxidizing bacteria that belonged to Achromobacter, Agrobacterium and Pseudomonas were identified and displayed a higher average arsenite resistance level than the non-arsenite oxidizers. 5 aoxB genes encoding arsenite oxidase and 51 arsenite transporter genes [18 arsB, 12 ACR3(1) and 21 ACR3(2)] were successfully amplified from these strains using PCR with degenerate primers. The aoxB genes were specific for the arsenite-oxidizing bacteria. Strains containing both an arsenite oxidase gene (aoxB) and an arsenite transporter gene (ACR3 or arsB) displayed a higher average arsenite resistance level than those possessing an arsenite transporter gene only. Horizontal transfer of ACR3(2) and arsB appeared to have occurred in strains that were primarily isolated from the highly arsenic-contaminated soil.ConclusionSoils with long-term arsenic contamination may result in the evolution of highly diverse arsenite-resistant bacteria and such diversity was probably caused in part by horizontal gene transfer events. Bacteria capable of both arsenite oxidation and arsenite efflux mechanisms had an elevated arsenite resistance level.

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Human pathogens are one of the major threats to global public health. Wastewater treatment plants (WWTPs) serve as city guts to receive and digest various human pathogens. Several techniques have been developed to detect human pathogens in WWTPs and to assess potential environmental risks. In this study, we employed 24 metagenomic DNA data sets derived from a high-throughput shotgun sequencing technique to more accurately and efficiently detect human bacterial pathogens in influent, activated sludge, and effluent of two Hong Kong WWTPs. Each data set was quality-filtered and normalized to 12,500,000 DNA sequences with a length of 150-190 bp. Then, a BLASTN search against Greengenes general 16S rRNA gene database and human pathogenic bacteria 16S rRNA gene database, a BLASTX search against human pathogenic bacteria virulence factor database, as well as MetaPhlAn analysis were conducted to survey the distribution, diversity, and abundance of human bacterial pathogens. The results revealed that (i) nine bacterial pathogens were detected; (ii) the overall pathogenic bacteria abundance was estimated as 0.06-3.20% in the total bacteria population using 16S rRNA gene fingerprinting; (iii) pathogenic bacteria detected in activated sludge and effluent shared similar profiles but were different from influent based on both 16S rRNA gene and virulence factor fingerprintings; (iv) Mycobacterium tuberculosis -like species may present potential pathogenic risks because it was detected with high abundance in both activated sludge and effluent. These findings provided a comprehensive profile of commonly concerned human pathogens in two Hong Kong WWTPs and demonstrated that the high-throughput shotgun sequencing technique is a feasible and effectual approach for environmental detection of human bacterial pathogens.

In recent years, PCR-based pyrosequencing of 16S rRNA genes has continuously increased our understanding of complex microbial communities in various environments of the Earth. However, there is always concern on the potential biases of diversity determination using different 16S rRNA gene primer sets and covered regions. Here, we first report how bacterial 16S rRNA gene pyrotags derived from a series of different primer sets resulted in the biased diversity metrics. In total, 14 types of pyrotags were obtained from two-end pyrosequencing of 7 amplicon pools generated by 7 primer sets paired by 1 of 4 forward primers (V1F, V3F, V5F, and V7F) and 1 of 4 reverse primers (V2R, V4R, V6R, and V9R), respectively. The results revealed that: i) the activated sludge exhibited a large bacterial diversity that represented a broad range of bacterial populations and served as a good sample in this methodology research; ii) diversity metrics highly depended on the selected primer sets and covered regions; iii) paired pyrotags obtained from two-end pyrosequencing of each short amplicon displayed different diversity metrics; iv) relative abundance analysis indicated the sequencing depth affected the determination of rare bacteria but not abundant bacteria; v) the primer set of V1F and V2R significantly underestimated the diversity of activated sludge; and vi) the primer set of V3F and V4R was highly recommended for future studies due to its advantages over other primer sets. All of these findings highlight the significance of this methodology research and offer a valuable reference for peer researchers working on microbial diversity determination.

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