-Guan Li

Exploring antibiotic resistance genes and metal resistance genes in plasmid metagenomes from wastewater treatment plants

Plasmids operate as independent genetic elements in microorganism communities. Through horizontal gene transfer (HGT), they can provide their host microorganisms with important functions such as antibiotic resistance and heavy metal resistance. In this study, six metagenomic libraries were constructed with plasmid DNA extracted from influent, activated sludge (AS) and digested sludge (DS) of two wastewater treatment plants (WWTPs). Compared with the metagenomes of the total DNA extracted from the same sectors of the wastewater treatment plant, the plasmid metagenomes had significantly higher annotation rates, indicating that the functional genes on plasmids are commonly shared by those studied microorganisms. Meanwhile, the plasmid metagenomes also encoded many more genes related to defense mechanisms, including ARGs. Searching against an antibiotic resistance genes (ARGs) database and a metal resistance genes (MRGs) database revealed a broad-spectrum of antibiotic (323 out of a total 618 subtypes) and MRGs (23 out of a total 23 types) on these plasmid metagenomes. The influent plasmid metagenomes contained many more resistance genes (both ARGs and MRGs) than the AS and the DS metagenomes. Sixteen novel plasmids with a complete circular structure that carried these resistance genes were assembled from the plasmid metagenomes. The results of this study demonstrated that the plasmids in WWTPs could be important reservoirs for resistance genes, and may play a significant role in the horizontal transfer of these genes.

Co-occurrence of antibiotic and metal resistance genes revealed in complete genome collection

The high frequency of antibiotic resistance is a global public health concern. More seriously, widespread metal pressure in the environment may facilitate the proliferation of antibiotic resistance via coselection of antibiotic resistance genes (ARGs) and metal resistance genes (MRGs). Given the lack of comprehensive understanding of the ARG and MRG coselection, in this study both abundance relationship and genetic linkage between ARGs and MRGs were rigorously investigated by performing a genomic analysis of a large complete genome collection. Many more ARGs were enriched in human-associated bacteria compared with those subjected to less anthropogenic interference. The signatures of ARG and MRG co-occurrence were much more frequent and the distance linkages between ARGs and MRGs were much more intimate in human pathogens than those less human-associated bacteria. Moreover, the co-occurrence structures in the habitat divisions were significantly different, which could be attributed to their distinct gene transfer potentials. More exogenous ARGs and MRGs on the genomes of human pathogens indicated the importance of recent resistance acquisition in resistome development of human commensal flora. Overall, the study emphasizes the potential risk associated with ARG and MRG coselection of both environmental and medical relevance.

Exploring the Shift in Structure and Function of Microbial Communities Performing Biological Phosphorus Removal

A sequencing batch reactor fed mainly by acetate was operated to perform enhanced biological phosphorus removal (EBPR). A short-term pH shock from 7.0 to 6.0 led to a complete loss of phosphate-removing capability and a drastic change of microbial communities. 16S rRNA gene pyrosequencing showed that large proportions of glycogen accumulating organisms (GAOs) (accounted for 16% of bacteria) bloomed, including Candidatus Competibacter phosphatis and Defluviicoccus-related tetrad-forming organism, causing deteriorated EBPR performance. The EBPR performance recovered with time and the dominant Candidatus Accumulibacter (Accumulibacter) clades shifted from Clade IIC to IIA while GAOs populations shrank significantly. The Accumulibacter population variation provided a good opportunity for genome binning using a bi-dimensional coverage method, and a genome of Accumulibacter Clade IIC was well retrieved with over 90% completeness. Comparative genomic analysis demonstrated that Accumulibacter clades had different abilities in nitrogen metabolism and carbon fixation, which shed light on enriching different Accumulibacter populations selectively.

ARGs-OSP: online searching platform for antibiotic resistance genes distribution in metagenomic database and bacterial whole genome database

Background The antibiotic resistant genes (ARGs) have been emerging as one of the top global issue s in both medical and environmental fields. The metagenomic analysis has been widely adopted in ARG-related studies, revealing a universal presence of ARGs in diverse environments from medical settings to natural habitats, even in drinking water and ancient permafrost. With the tremendous resources of accessible metagenomic datasets, it would be feasible and beneficial to construct a global profile of antibiotic resistome as a guidance of its phylogenetic and ecological distribution. And such information should be shared by an open webpage to avoid the unnecessary repeat of data processing and the bias caused by incompatible search method. Results Two dataset collections, the Whole Genome Database (WGD, 54,718 complete and draft bacterial genomes) and the Metagenomic Database (MGD, 854 metagenomic datasets of 7 eco-types), were downloaded and analyzed using a standard method of ARG online analysis platform (ARGs-OAP v1.0). The representativeness of WGD and MGD was evaluated to have a comprehensive coverage of ARGs in bacterial genomes and metagenomes. Besides, an ARGs online searching platform (ARGs-OSP, http://args-osp.herokuapp.com/) was developed in this study to make the data accessible to other researchers via the search and download functionality. Finally, flexible usage of the ARGs-OAP was demonstrated by evaluating the co-occurrence of class 1 integrases and total ARGs across different environments. Conclusions The ARGs-OSP is presented in this study as the valuable sources and references for future studies with versatile research interests, meanwhile avoiding unnecessary re-computations and re-analysis.

Conserved phylogenetic distribution and limited antibiotic resistance of class 1 integrons revealed by assessing the bacterial genome and plasmid collection

BackgroundIntegrons, especially the class 1 integrons, are major contributors to the acquisition and dissemination of antibiotic resistance genes (ARGs). However, comprehensive knowledge of the types, content, and distribution of integrons in bacterial taxa is lacking to evaluate their contribution.ResultsWe have constructed a new integrase database and developed a pipeline that provides comprehensive recovery of class 1 integrons. Previous PCR-based techniques might only detect one fourth of the integron-integrases and integrons recovered in this study. By exploring the class 1 integrons in over 73,000 currently available complete and draft bacterial genomes, the contribution of class 1 integrons in spreading and acquiring ARGs was evaluated. Firstly, the host species of class 1 integrons are highly conserved within (96%) in class Gammaproteobacteria, dominated by four pathogenic species of “ESKAPE.” Secondly, more than half of class 1 integrons are embedded in chromosomes with less potential for horizontal gene transfer. Finally, ARGs that have been acquired by these integrons only cover 11% of all the ARG genotypes detected in bacterial genomes.ConclusionsThe above observations indicated that there are both biological and ecological limitations to class 1 integrons in acquiring and spreading ARGs across different classes of the domain Bacteria.

Tracking antibiotic resistance gene pollution from different sources using machine-learning classification

BackgroundAntimicrobial resistance (AMR) has been a worldwide public health concern. Current widespread AMR pollution has posed a big challenge in accurately disentangling source-sink relationship, which has been further confounded by point and non-point sources, as well as endogenous and exogenous cross-reactivity under complicated environmental conditions. Because of insufficient capability in identifying source-sink relationship within a quantitative framework, traditional antibiotic resistance gene (ARG) signatures-based source-tracking methods would hardly be a practical solution.ResultsBy combining broad-spectrum ARG profiling with machine-learning classification SourceTracker, here we present a novel way to address the question in the era of high-throughput sequencing. Its potential in extensive application was firstly validated by 656 global-scale samples covering diverse environmental types (e.g., human/animal gut, wastewater, soil, ocean) and broad geographical regions (e.g., China, USA, Europe, Peru). Its potential and limitations in source prediction as well as effect of parameter adjustment were then rigorously evaluated by artificial configurations with representative source proportions. When applying SourceTracker in region-specific analysis, excellent performance was achieved by ARG profiles in two sample types with obvious different source compositions, i.e., influent and effluent of wastewater treatment plant. Two environmental metagenomic datasets of anthropogenic interference gradient further supported its potential in practical application. To complement general-profile-based source tracking in distinguishing continuous gradient pollution, a few generalist and specialist indicator ARGs across ecotypes were identified in this study.ConclusionWe demonstrated for the first time that the developed source-tracking platform when coupling with proper experiment design and efficient metagenomic analysis tools will have significant implications for assessing AMR pollution. Following predicted source contribution status, risk ranking of different sources in ARG dissemination will be possible, thereby paving the way for establishing priority in mitigating ARG spread and designing effective control strategies.

ARGs-OAP v2.0 with an expanded SARG database and Hidden Markov Models for enhancement characterization and quantification of antibiotic resistance genes in environmental metagenomes

Motivation Much global attention has been paid to antibiotic resistance in monitoring its emergence, accumulation and dissemination. For rapid characterization and quantification of antibiotic resistance genes (ARGs) in metagenomic datasets, an online analysis pipeline, ARGs‐OAP has been developed consisting of a database termed Structured Antibiotic Resistance Genes (the SARG) with a hierarchical structure (ARGs type‐subtype‐reference sequence). Results The new release of the database, termed SARG version 2.0, contains sequences not only from CARD and ARDB databases, but also carefully selected and curated sequences from the latest protein collection of the NCBI‐NR database, to keep up to date with the increasing number of ARG deposited sequences. SARG v2.0 has tripled the sequences of the first version and demonstrated improved coverage of ARGs detection in metagenomes from various environmental samples. In addition to annotation of high‐throughput raw reads using a similarity search strategy, ARGs‐OAP v2.0 now provides model‐based identification of assembled sequences using SARGfam, a high‐quality profile Hidden Markov Model (HMM), containing profiles of ARG subtypes. Additionally, ARGs‐OAP v2.0 improves cell number quantification by using the average coverage of essential single copy marker genes, as an option in addition to the previous method based on the 16S rRNA gene. Availability and implementation ARGs‐OAP can be accessed through http://smile.hku.hk/SARGs. The database could be downloaded from the same site. Source codes for this study can be downloaded from https://github.com/xiaole99/ARGs‐OAP‐v2.0.

AQMM: Enabling Absolute Quantification of Metagenome and Metatranscriptome

Metatranscriptome has become increasingly important along with the application of next generation sequencing in the studies of microbial functional gene activity in environmental samples. However, the quantification of target active gene is hindered by the current relative quantification methods, especially when tracking the sharp environmental change. Great needs are here for an easy-to-perform method to obtain the absolute quantification. By borrowing information from the parallel metagenome, an absolute quantification method for both metagenomic and metatranscriptomic data to per gene/cell/volume/gram level was developed. The effectiveness of AQMM was validated by simulated experiments and was demonstrated with a real experimental design of comparing activated sludge with and without foaming. Our method provides a novel bioinformatic approach to fast and accurately conduct absolute quantification of metagenome and metatranscriptome in environmental samples. The AQMM can be accessed from https://github.com/biofuture/aqmm.

MinION Nanopore Sequencing Enables Correlation between Resistome Phenotype and Genotype of Coliform Bacteria in Municipal Sewage

Wastewater treatment plants (WWTPs) functioned as the intersection between the human society and nature environment, are receiving increasingly more attention on risk assessment of the acquisition of environmental antibiotic resistance genes (ARGs) by pathogenetic populations during treatment. However, because of the general lack of robust resistome profiling methods, genotype, and resistance phenotype is still poorly correlated in human pathogens of sewage samples. Here we applied MinION sequencing to quantify the resistance genes of multiple antibiotic resistant (MAR) coliform bacteria, a common indicator for human enteric pathogens in sewage samples. Our pipeline could deliver the results within 30 h from sample collection and the resistome quantification was consistent to that based on the Illumina platform. Additionally, the long nanopore reads not only enabled a simultaneous identification of the carrier populations of ARGs detected, but also facilitated the genome reconstruction of a representative MAR strain, from which we identified an instance of chromosomal integration of environmental resistance gene obtained by plasmid exchange with a porcine pathogen. This study demonstrated the utilization of MinION sequencing in quick monitoring and simultaneous phylogenetic tracking of environmental ARGs to address potential health risk associated with them.

Bioprospecting for β-lactam resistance genes using a metagenomics-guided strategy

Emergence of new antibiotic resistance bacteria poses a serious threat to human health, which is largely attributed to the evolution and spread of antibiotic resistance genes (ARGs). In this work, a metagenomics-guided strategy consisting of metagenomic analysis and function validation was proposed for rapidly identifying novel ARGs from hot spots of ARG dissemination, such as wastewater treatment plants (WWTPs) and animal feces. We used an antibiotic resistance gene database to annotate 76 putative β-lactam resistance genes from the metagenomes of sludge and chicken feces. Among these 76 candidate genes, 25 target genes that shared 40~70% amino acid identity to known β-lactamases were cloned by PCR from the metagenomes. Their resistances to four β-lactam antibiotics were further demonstrated. Furthermore, the validated ARGs were used as the reference sequences to identify novel ARGs in eight environmental samples, suggesting the necessity of re-examining the profiles of ARGs in environmental samples using the validated novel ARG sequences. This metagenomics-guided pipeline does not rely on the activity of ARGs during the initial screening process and may specifically select novel ARG sequences for function validation, which make it suitable for the high-throughput screening of novel ARGs from environmental metagenomes.