Legionella pneumophila was quantified during the COVID-19 pandemic in 26 buildings in three countries to identify factors that influenced positivity.

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.

Understanding whether the spatial-temporal dynamics of the drinking water microbiome are reproducible in full-scale drinking water systems is an important step towards devising engineering strategies to manipulate it. Yet, direct comparisons across full-scale drinking water systems are challenging because multiple factors, from source water to treatment process choice and configuration, can be unique to each system. This study compared the spatial-temporal dynamics of the drinking water microbiome in two drinking water treatment plants (DWTPs) with identical sequence of treatment strategies treating source waters from the same river system and with treated drinking water distributed in same large-scale (but independent) distribution system (DWDS) with similar disinfectant residual regiment. Dissimilarities in source water communities were tempered by the pre-disinfection treatments, resulting in highly similar post-filtration microbial communities between the two systems. However, high community turnover due to disinfection resulted in highly dissimilar microbial communities in the finished water between the two systems. Interestingly however, the microbial communities in the two systems increased in similarity during transit through the DWDS despite presence of a disinfectant residual. Overall our study finds that the drinking water microbiome demonstrated reproducible spatial and temporal dynamics within both independent but nearly identical DWTPs and their corresponding DWDSs. Graphical abstract

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.

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 a period of 6 months. The goal of this study was to identify the combination of assembly and binning approaches that results in high quality and quantity metagenome-assembled genomes (MAGs), representing most of the sequenced metagenome. Our findings suggest that the metaSPAdes co-assembly 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 1kbp. Furthermore, a combination of metaSPAdes co-assembly 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 assist 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 co-assembly strategies may be required to maximize the recovery of good-quality MAGs, which more accurately capture the microbial diversity of drinking water samples.

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.

DNA-extractions from drinking water samples are essential for a range of subsequent microbial community quantitation and characterization methods, i.e., quantitative polymerase chain reaction (qPCR) assays targeting specific genes and the characterization of compositional and functional profiles using high throughout sequencing technologies (e.g. amplicon sequencing and shotgun metagenomic sequencing). Despite advances in the specificity and sensitivity of molecular techniques, efficient recovery of DNA from drinking water samples, particularly those with low cell counts, remains challenging. Drinking water samples, in which microbial concentrations range between 103and 105 cells.ml-1, generally requires the collection of large volume of sample and subsequent processing by filtration to concentrate microbial cells. Here we document a modified version of the DNeasy PowerWater Kit® protocol that utilizes enzymatic, chemical, and mechanical lysis strategies to enhance recovery of DNA from drinking water samples. The DNA quantities recovered using this protocol are typically at least two to three-fold higher when compared to the routine DNeasy PowerWater Kit® protocol. In our hands, this protocol consistently provides sufficient DNA of high quality from as little as 1.5 liters of filtered drinking water with cell counts in the range of 103-104 cells.ml-1, while maintaining the 16S rRNA qPCR counts at least 100-1000 times higher compared to DNA extracts from negative controls (i.e., blank unused filters, filters with autoclaved deionized water filtered, and reagent blanks) processed identically as the drinking water samples.

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.