Gradual Recovery of Building Plumbing-Associated Microbial Communities after Extended Periods of Altered Water Demand during the COVID-19 Pandemic.

COVID-19 pandemic-related building restrictions heightened drinking water microbiological safety concerns post-reopening due to the unprecedented nature of commercial building closures. Starting with phased reopening (i.e., June 2020), we sampled drinking water for 6 months from three commercial buildings with reduced water usage and four occupied residential households. Samples were analyzed using flow cytometry and full-length 16S rRNA gene sequencing along with comprehensive water chemistry characterization. Prolonged building closures resulted in 10-fold higher microbial cell counts in the commercial buildings [(2.95 ± 3.67) × 105 cells mL-1] than in residential households [(1.11 ± 0.58) × 104 cells mL-1] with majority intact cells. While flushing reduced cell counts and increased disinfection residuals, microbial communities in commercial buildings remained distinct from those in residential households on the basis of flow cytometric fingerprinting [Bray-Curtis dissimilarity (dBC) = 0.33 ± 0.07] and 16S rRNA gene sequencing (dBC = 0.72 ± 0.20). An increase in water demand post-reopening resulted in gradual convergence in microbial communities in water samples collected from commercial buildings and residential households. Overall, we find that the gradual recovery of water demand played a key role in the recovery of building plumbing-associated microbial communities as compared to short-term flushing after extended periods of reduced water demand.

Evaluating de Novo Assembly and Binning Strategies for Time Series Drinking Water Metagenomes.

Reconstructing microbial genomes from metagenomic short-read data can be challenging due to the unknown and uneven complexity of microbial communities. This complexity encompasses highly diverse populations, which often includes strain variants. Reconstructing high-quality genomes is a crucial part of the metagenomic workflow, as subsequent ecological and metabolic inferences depend on their accuracy, quality, and completeness. In contrast to microbial communities in other ecosystems, there has been no systematic assessment of genome-centric metagenomic workflows for drinking water microbiomes. In this study, we assessed the performance of a combination of assembly and binning strategies for time series drinking water metagenomes that were collected over 6 months. The goal of this study was to identify the combination of assembly and binning approaches that result in high-quality and -quantity metagenome-assembled genomes (MAGs), representing most of the sequenced metagenome. Our findings suggest that the metaSPAdes coassembly strategies had the best performance, as they resulted in larger and less fragmented assemblies, with at least 85% of the sequence data mapping to contigs greater than 1 kbp. Furthermore, a combination of metaSPAdes coassembly strategies and MetaBAT2 produced the highest number of medium-quality MAGs while capturing at least 70% of the metagenomes based on read recruitment. Utilizing different assembly/binning approaches also assists in the reconstruction of unique MAGs from closely related species that would have otherwise collapsed into a single MAG using a single workflow. Overall, our study suggests that leveraging multiple binning approaches with different metaSPAdes coassembly strategies may be required to maximize the recovery of good-quality MAGs. IMPORTANCE Drinking water contains phylogenetic diverse groups of bacteria, archaea, and eukarya that affect the esthetic quality of water, water infrastructure, and public health. Taxonomic, metabolic, and ecological inferences of the drinking water microbiome depend on the accuracy, quality, and completeness of genomes that are reconstructed through the application of genome-resolved metagenomics. Using time series metagenomic data, we present reproducible genome-centric metagenomic workflows that result in high-quality and -quantity genomes, which more accurately signifies the sequenced drinking water microbiome. These genome-centric metagenomic workflows will allow for improved taxonomic and functional potential analysis that offers enhanced insights into the stability and dynamics of drinking water microbial communities.

Spatial-temporal targeted and non-targeted surveys to assess microbiological composition of drinking water in Puerto Rico following Hurricane Maria.

Loss of basic utilities, such as drinking water and electricity distribution, were sustained for months in the aftermath of Hurricane Maria's (HM) landfall in Puerto Rico (PR) in September 2017. The goal of this study was to assess if there was deterioration in biological quality of drinking water due to these disruptions. This study characterized the microbial composition of drinking water following HM across nine drinking water systems (DWSs) in PR and utilized an extended temporal sampling campaign to determine if changes in the drinking water microbiome were indicative of HM associated disturbance followed by recovery. In addition to monitoring water chemistry, the samples were subjected to culture independent targeted and non-targeted microbial analysis including quantitative PCR (qPCR) and genome-resolved metagenomics. The qPCR results showed that residual disinfectant was the major driver of bacterial concentrations in tap water with marked decrease in concentrations from early to late sampling timepoints. While Mycobacterium avium and Pseudomonas aeruginosa were not detected in any sampling locations and timepoints, genetic material from Leptospira and Legionella pneumophila were transiently detected in a few sampling locations. The majority of metagenome assembled genomes (MAGs) recovered from these samples were not associated with pathogens and were consistent with bacterial community members routinely detected in DWSs. Further, whole metagenome-level comparisons between drinking water samples collected in this study with samples from other full-scale DWS indicated no significant deviation from expected community membership of the drinking water microbiome. Overall, our results suggest that disruptions due to HM did not result in significant and sustained deterioration of biological quality of drinking water at our study sites.

Impact of Hurricane Maria on Drinking Water Quality in Puerto Rico.

This study performed a comprehensive assessment of the impact of Hurricane Maria (HM) on drinking water quality in Puerto Rico (PR) by integrating targeted chemical analysis of both inorganic (18 trace elements) and organic trace pollutants (200 micropollutants) with high-throughput quantitative toxicogenomics and in vitro biomarkers-based toxicity assays. Average concentrations of 14 detected trace elements and 20 organic micropollutants showed elevation after HM. Arsenic, sucralose, perfluorooctanoic acid (PFOA), atrazine-2-hydroxy, benzotriazole, acesulfame, and prometon were at significantly (p < 0.05) higher levels in the post-HM than in the pre-HM samples. Thirteen micropollutants, including four pesticides, were only detected in posthurricane samples. Spatial comparison showed higher pollutant and toxicity levels in the samples from northern PR (where eight Superfund sites are located) than in those from southern PR. Distinctive pathway-specific molecular toxicity fingerprints for water extracts before and after HM and at different locations revealed changes in toxicity nature that likely resulted from the impact of HM on drinking water composition. Correlation analysis and Maximum Cumulative Ratio assessment suggested that metals (i.e., arsenic) and PFOA were the top ranked pollutants that have the potential to cause increased risk after HM, providing a possible direction for future water resource management and epidemiological studies.

The lung microbiome in children with HIV-bronchiectasis: a cross-sectional pilot study.

BACKGROUND: Data on the lung microbiome in HIV-infected children is limited. The current study sought to determine the lung microbiome in HIV-associated bronchiectasis and to assess its association with pulmonary exacerbations. METHODS: A cross-sectional pilot study of 22 children (68% male; mean age 10.8 years) with HIV-associated bronchiectasis and a control group of 5 children with cystic fibrosis (CF). Thirty-one samples were collected, with 11 during exacerbations. Sputum samples were processed with 16S rRNA pyrosequencing. RESULTS: The average number of operational taxonomy units (OTUs) was 298 ± 67 vs. 434 ± 90, for HIV-bronchiectasis and CF, respectively. The relative abundance of Proteobacteria was higher in HIV-bronchiectasis (72.3%), with only 22.2% Firmicutes. There was no correlation between lung functions (FEV1% and FEF25/75%) and bacterial community (r = 0.154; p = 0.470 and r = 0.178; p = 0.403), respectively. Bacterial assemblage of exacerbation and non-exacerbation samples in HIV-bronchiectasis was not significantly different (ANOSIM, RHIV-bronchiectasis = 0.08; p = 0.14 and RCF = 0.08, p = 0.50). Higher within-community heterogeneity and lower evenness was associated with CF (Shannon-Weiner (H') = 5.39 ± 0.38 and Pielou's evenness (J) 0.79 ± 0.10 vs. HIV-bronchiectasis (Shannon-Weiner (H') = 4.45 ± 0.49 and Pielou's (J) 0.89 ± 0.03. CONCLUSION: The microbiome in children with HIV-associated bronchiectasis seems to be less rich, diverse and heterogeneous with predominance of Proteobacteria when compared to cystic fibrosis.