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Klai, N.

Publications and source records attributed to Klai, N..

2 recordsLinked to original sources

Multiplexed Amplicon Sequencing Reveals High Sequence Diversity of Antibiotic Resistance Genes in Quebec Sewers

The United Nations Environment Assembly (UNEA-3) have recognised the importance of the environment in the development, spread and transmission of antimicrobial resistance (AMR) to humans and animals. Such recognition calls for wider surveillance of antimicrobial resistance genes (ARG) in wastewater and other environmental reservoirs. For ARG surveillance to be valuable to regulators, it must enable source tracking and risk assessment. Adequate surveillance also requires the processing of a large number of samples at a relatively low cost, and a low detection limit to allow quantification of the riskiest ARGs. However, current methods for tracking ARGs have various limitations. The current study presents a multiplexed targeted amplicon sequencing approach for the detection of sequence variants of ARGs in environmental samples. To demonstrate the application of this technique, wastewater samples collected from the inlet to 16 treatment plants located along a 440-km transect of the St-Lawrence river in the province of Quebec (Canada) were analysed. Among the ARGs examined, between 3 and 45 nucleic acid sequence variants were detected demonstrating the high sequence diversity that occurs within genes originating from a single sample type and the information that is missed using traditional techniques. Using the PLSDB and Comprehensive Antibiotic Resistance Database (CARD), the risk of ARG sequence variants was inferred based upon their reported mobility and detection in pathogens. Results suggest that sequence variants within a single ARG class present different risks to public health. In the future, targeted amplicon sequencing could be a valuable tool in environmental studies for both risk assessment purposes and in AMR source tracking.

microbiology↗

Wastewater Influent Microbial Immigration and Contribution to Resource Consumption in Activated Sludge Using Taxon-Specific Mass-Flow Immigration Model

Wastewater influent microorganisms are part of the total chemical oxygen demand (COD) and affect the activated sludge (AS) microbial community. Precise modeling of AS processes requires accurate quantification of influent microorganisms, which is missing in many AS models (ASMs). In this study, influent microorganisms in COD unit were determined using a fast quantification method based on DNA yield and was compared with conventional respirometry method. The actively growing influent microorganisms were identified. A mass-flow immigration model was developed to quantify the influent-to-AS immigration efficiency (mi) of specific taxon i using mass balance and 16S rRNA gene high-throughput sequencing data. The modelled average m was 0.121-0.257 in site 1 (LaPrairie), and 0.050-0.126 in site 2 (Pincourt), which were corrected to 0.111-0.186 and 0.048-0.109 respectively using a constrain of mi [&le;] 1. The model was further developed to calculate contributions to organic substrate consumption by specific taxa. Those genera with zero or negative net growth rates were not completely immigration dependent (mi < 1) and contributed to 2.4% - 5.4% of the substrate consumption. These results suggest that influent microbiome may be important contributors to AS microbiome assembly and system performance (substrate consumption), which may help to improve future AS process modelling and design. SynopsisInfluent microbial immigration lacks detailed taxon-specific quantification. This study presents quantitative methods and models for influent biomass, mass-flow immigration model, and resource consumption in activated sludge. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/504022v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1d6b43forg.highwire.dtl.DTLVardef@d3b7eborg.highwire.dtl.DTLVardef@1cfaef5org.highwire.dtl.DTLVardef@1e75bdb_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗