Drinking Water Microbiome Sequence Data Set
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The fasta file (BM_OTU.fasta) contain the sequences of the bacterial 16S rRNA-encoding V4 region gene (≈250 nt) for each Operational Taxonomic Unit (OTU). This dataset is associated with the following publication: Gomez-Alvarez, V., and R. Revetta. Monitoring of Nitrification in Chloraminated Drinking Water Distribution Systems With Microbiome Bioindicators Using Supervised Machine Learning. Frontiers in Microbiology. Frontiers, Lausanne, SWITZERLAND, 11: 2254-2267, (2020).
Drinking Water Microbiome OTU Abundance Data Set
공공데이터포털
An abundance matrix (BM_OTU.xlsx) contains rows as OTU, columns as samples, and entries representing the abundance of each OTU as a ratio of all sequences obtained for each individual sample. This dataset is associated with the following publication: Gomez-Alvarez, V., and R. Revetta. Monitoring of Nitrification in Chloraminated Drinking Water Distribution Systems With Microbiome Bioindicators Using Supervised Machine Learning. Frontiers in Microbiology. Frontiers, Lausanne, SWITZERLAND, 11: 2254-2267, (2020).
Resilience of Microbial Communities Sequence Data Set
공공데이터포털
The EX_Genome_Assemblies.zip file contain the contig sequences (i.e. assembly) of fifteen isolates used for genomic and antibiotic resistance genes (ARG) analysis. EX_OTU.fasta file contain the sequences of the bacterial 16S rRNA-encoding V4 region gene (≈250 nt) for each Operational Taxonomic Unit (OTU). This dataset is associated with the following publication: Gomez-Alvarez, V., S. Pfaller, J. Pressman, D. Wahman, and R. Revetta. Resilience of microbial communities in a simulated drinking water distribution system subjected to disturbances: role of conditionally rare taxa and potential implications for antibiotic-resistant bacteria. Environmental Science: Water Research & Technology. Royal Society of Chemistry, Cambridge, UK, 2: 645-657, (2016).
Microbial Community Analysis based on 16S rRNA gene of Sediment Layers
공공데이터포털
A table (DP_OTU.xlsx) contains rows as OTUs, columns as samples, and entries representing the abundance of each OTU. This dataset is associated with the following publication: Gomez-Alvarez, V., H. Liu, J. Pressman, and D. Wahman. Metagenomic Profile of Microbial Communities in a Drinking Water Storage Tank Sediment after Sequential Exposure to Monochloramine, Free Chlorine, and Monochloramine. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 1(5): 1283-1294, (2021).
Metropolitan DWDS Sequence Data Set
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PS_GenBank.fasta file contain the sequences of the bacterial 16S rRNA-encoding gene for each representative sequence. The sequence containing four hypervariable regions was amplified using the primer set Eub-8f and 787. PS_GenBank.xlsx file contains rows as sample and columns as entries representing the accession number (NCBI) deposited in GenBank for each representative sequence (i.e. unique sequences). PS_OTU.fasta file contain the sequences of the bacterial 16S rRNA-encoding gene for each Operational Taxonomic Unit (OTU). The sequence containing four hypervariable regions was amplified using the primer set Eub-8f and 787. This dataset is associated with the following publication: Revetta , R., V. Gomez-Alvarez, T. Gerke, J. Santodomingo , and N. Ashbolt. CHANGES IN BACTERIAL COMPOSITION OF BIOFILM IN A METROPOLITAN DRINKING WATER DISTRIBUTION SYSTEM. JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 121(1): 294-305, (2016).
Drinking Water Microbiome Taxonomic Lineage Abundance Data Set
공공데이터포털
An abundance matrix (BM_taxonomic_lineage.xlsx) contains rows as taxonomic lineage, columns as samples, and entries representing the abundance of each lineage as a ratio of all sequences obtained for each individual sample. This dataset is associated with the following publication: Gomez-Alvarez, V., and R. Revetta. Monitoring of Nitrification in Chloraminated Drinking Water Distribution Systems With Microbiome Bioindicators Using Supervised Machine Learning. Frontiers in Microbiology. Frontiers, Lausanne, SWITZERLAND, 11: 2254-2267, (2020).
Resilience of Microbial Communities OTU Abundance Data Set
공공데이터포털
An abundance matrix (EX_OTU.xlsx) contains rows as OTU, columns as samples, and entries representing the abundance of each OTU as a ratio of all sequences obtained for each individual sample. This dataset is associated with the following publication: Gomez-Alvarez, V., S. Pfaller, J. Pressman, D. Wahman, and R. Revetta. Resilience of microbial communities in a simulated drinking water distribution system subjected to disturbances: role of conditionally rare taxa and potential implications for antibiotic-resistant bacteria. Environmental Science: Water Research & Technology. Royal Society of Chemistry, Cambridge, UK, 2: 645-657, (2016).
Identification of bacteria in drinking and purified water during the monitoring of a typical water purification system
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Background A typical purification system that provides purified water which meets ionic and organic chemical standards, must be protected from microbial proliferation to minimize cross-contamination for use in cleaning and preparations in pharmaceutical industries and in health environments. Methodology Samples of water were taken directly from the public distribution water tank at twelve different stages of a typical purification system were analyzed for the identification of isolated bacteria. Two miniature kits were used: (i) identification system (api 20 NE, Bio-Mérieux) for non-enteric and non-fermenting gram-negative rods; and (ii) identification system (BBL crystal, Becton and Dickson) for enteric and non-fermenting gram-negative rods. The efficiency of the chemical sanitizers used in the stages of the system, over the isolated and identified bacteria in the sampling water, was evaluated by the minimum inhibitory concentration (MIC) method. Results The 78 isolated colonies were identified as the following bacteria genera: Pseudomonas, Flavobacterium and Acinetobacter. According to the miniature kits used in the identification, there was a prevalence of isolation of P. aeruginosa 32.05%, P. picketti (Ralstonia picketti) 23.08%, P. vesiculares 12.82%,P. diminuta 11.54%, F. aureum 6.42%, P. fluorescens 5.13%, A. lwoffi 2.56%, P. putida 2.56%, P. alcaligenes 1.28%, P. paucimobilis 1.28%, and F. multivorum 1.28%. Conclusions We found that research was required for the identification of gram-negative non-fermenting bacteria, which were isolated from drinking water and water purification systems, since Pseudomonas genera represents opportunistic pathogens which disperse and adhere easily to surfaces, forming a biofilm which interferes with the cleaning and disinfection procedures in hospital and industrial environments.