Composition of active bacterial communities and presence of opportunistic pathogens in disinfected and non-disinfected drinking water distribution systems in Finland.

Many factors, including microbiome structure and activity in the drinking water distribution system (DWDS), affect the colonization potential of opportunistic pathogens. The present study aims to describe the dynamics of active bacterial communities in DWDS and identify the factors that shape the community structures and activity in the selected DWDSs. Large-volume drinking water and hot water, biofilm, and water meter deposit samples were collected from five DWDSs. Total nucleic acids were extracted, and RNA was further purified and transcribed into its cDNA from a total of 181 water and biofilm samples originating from the DWDS of two surface water supplies (disinfected with UV and chlorine), two artificially recharged groundwater supplies (non-disinfected), and a groundwater supply (disinfected with UV and chlorine). In chlorinated DWDSs, concentrations of <0.02-0.97 mg/l free chlorine were measured. Bacterial communities in the RNA and DNA fractions were analysed using Illumina MiSeq sequencing with primer pair 341F-785R targeted to the 16S rRNA gene. The sequence libraries were analysed using QIIME pipeline, Program R, and MicrobiomeAnalyst. Not all bacterial cells were active based on their 16S rRNA content, and species richness was lower in the RNA fraction (Chao1 mean value 490) than in the DNA fraction (710). Species richness was higher in the two DWDSs distributing non-disinfected artificial groundwater (Chao1 mean values of 990 and 1 000) as compared to the two disinfected DWDSs using surface water (Chao1 mean values 190 and 460) and disinfected DWDS using ground water as source water (170). The difference in community structures between non-disinfected and disinfected water was clear in the beta-diversity analysis. Distance from the waterworks also affected the beta diversity of community structures, especially in disinfected distribution systems. The two most abundant bacteria in the active part of the community (RNA) and total bacterial community (DNA) belonged to the classes Alphaproteobacteria (RNA 28 %, DNA 44 %) and Gammaproteobacteria (RNA 32 %, DNA 30 %). The third most abundant and active bacteria class was Vampirovibrionia (RNA 15 %), whereas in the total community it was Paceibacteria (DNA 11 %). Class Nitrospiria was more abundant and active in both cold and hot water in DWDS that used chloramine disinfection compared to non-chlorinated or chlorine-using DWDSs. Thirty-eight operational taxonomic units (OTU) of Legionella, 30 of Mycobacterium, and 10 of Pseudomonas were detected among the sequences. The (RT)-qPCR confirmed the presence of opportunistic pathogens in the DWDSs studied as Legionella spp. was detected in 85 % (mean value 4.5 × 104 gene copies/100 ml), Mycobacterium spp. in 95 % (mean value 8.3 × 106 gene copies/100 ml), and Pseudomonas spp. in 78 % (mean value 1.6 × 105 gene copies/100 ml) of the water and biofilm samples. Sampling point inside the system (distance from the waterworks and cold/hot system) affected the active bacterial community composition. Chloramine as a chlorination method resulted in a recognizable community composition, with high abundance of bacteria that benefit from the excess presence of nitrogen. The results presented here confirm that each DWDS is unique and that opportunistic pathogens are present even in conditions when water quality is considered excellent.

Indoor green can modify the indoor dust microbial communities.

Little is known about the potential role of indoor plants in shaping the indoor microbiota. Within the ENVIRONAGE birth cohort, we collected settled dust and performed 16S and ITS amplicon sequencing and qPCR measurements to characterize the indoor microbiota, including bacterial and fungal loads and Chao1 richness, Shannon, and Simpson diversity indices. For 155 households, we obtained information on the number of indoor plants. We performed linear regression models adjusted for several a priori chosen covariables. Overall, an increase in indoor plants and density was associated with increased microbial diversity, but not load. For example, we found an increase of 64 (95%CI:3;125) and 26 (95%CI:4;48) units of bacterial and fungal taxa richness, respectively, in households with more than three plants compared to no plants. Our results support the hypothesis that indoor plants can enrich indoor microbial diversity, while impacts on microbial loads are not obvious.

Residential green space can shape the indoor microbial environment.

BACKGROUND: The influence of outdoor green space on microbial communities indoors has scarcely been investigated. Here, we study the associations between nearby residential green space and residential indoor microbiota. METHODS: We collected settled dust from 176 living rooms of participants of the ENVIRONAGE birth cohort. We performed 16S and ITS amplicon sequencing, and quantitative PCR measurements of total bacterial and fungal loads to calculate bacterial and fungal diversity measures (Chao1 richness, Shannon and Simpson diversity indices) and relative abundance of individual taxa. Green spaces were estimated within 50m and 100m buffers around the residential address. We defined total residential green space using high-resolution land-cover data, further stratified in low-growing (height<3m) and high-growing green (height>3m). We used land-use data to calculate the residential nature. We ran linear regression models, adjusting for confounders and other potential determinants. Results are expressed as units change for an interquartile range (IQR) increase in residential green space and their 95% confidence intervals (CI). RESULTS: After adjustment, we observed statistically significant associations between the indoor microbial diversity indices and nearby residential green space. For bacteria, the Shannon index was directly associated with residential nature (e.g. 0.08 units increase (CI:0.02,0.13) per IQR increase in nature within a 50m buffer). Fungal diversity was directly associated with high-growing residential green and inversely with low-growing green. For example, an IQR increase in high-growing green within a 50m buffer was associated with increases in 0.14 (CI:0.01,0.27) and 0.02 (CI:0.008,0.04) units in the Shannon and Simpson indices, respectively. CONCLUSIONS: Nearby green space determines the diversity of indoor environment microbiota, and the type of green differently impacts bacterial and fungal diversity. Further research is needed to investigate in more detail possible microbial taxa compositions underlying the observed changes in indoor microbiota diversity and to explore their contribution to beneficial health effects associated with green space exposure.

Diverse and active archaea communities occur in non-disinfected drinking water systems-Less activity revealed in disinfected and hot water systems.

The knowledge about the members of active archaea communities in DWDS is limited. The current understanding is based on high-throughput 16S ribosomal RNA gene (DNA-based) amplicon sequencing that reveals the diversity of active, dormant, and dead members of the prokaryote (bacteria, archaea) communities. The sequencing primers optimized for bacteria community analysis may underestimate the share of the archaea community. This study characterized archaea communities at five full-scale drinking water distribution systems (DWDS), representing a variety of drinking water production units (A-E); A&B use artificially recharged non-disinfected groundwater (ARG), the other DWDS's supplied water disinfected by using ultraviolet (UV) light and chlorine compounds, C&D were surface waterworks and E was a ground waterworks. For the first time for archaea community analyses, this study employed the archaea-specific high-throughput sequencing primers for 16S ribosomal RNA (rRNA) as a target (reverse-transcribed cDNA; an RNA-based approach) in addition to the previously used 16S rRNA gene target (rDNA; a DNA-based approach) to reveal the active fraction of the archaea present in DWDS. The archaea community structure in varying environmental conditions in the water and biofilm of the five DWDSs were investigated by taking into consideration the system properties (cold or hot water system) and water age (distance from the treatment plants) in samples from each season of one year. The RNA-based archaea amplicon reads were obtained mostly from cold water samples from DWDSs (A-B) distributing water without disinfection where the DNA-based and RNA-based analysis created separate clusters in a weighted beta-diversity analysis. The season and location in DWDS A further affected the diversity of these archaea communities as was seen by different clusters in beta-diversity plots. The recovery of archaea reads was not adequate for analysis in any of the disinfected samples in DWDSs C-E or non-disinfected hot water in DWDSs A-B when utilizing RNA-based template. The metabolically active archaea community of DWDSs thus seemed to be effectively controlled by disinfection of water and in the hot water systems by the temperature. All biofilms regardless of DWDS showed lower species richness values (mainly Nitrososphaeria class) than non-disinfected water from DWDSs A-B where several archaea classes occurred (e.g. Woesearchaeia, Nitrososphaeria, Micrarchaeia, Methanomicrobia, Iairchaeia, Bathyarchaeia) indicating only part of the archaea members were able to survive in biofilms. Thus, Archaea has been shown as a significant part of normal DWDS biota, and their role especially in non-disinfected DWDS may be more important than previously considered.

Bacterial diversity and predicted enzymatic function in a multipurpose surface water system - from wastewater effluent discharges to drinking water production.

BACKGROUND: Rivers and lakes are used for multiple purposes such as for drinking water (DW) production, recreation, and as recipients of wastewater from various sources. The deterioration of surface water quality with wastewater is well-known, but less is known about the bacterial community dynamics in the affected surface waters. Understanding the bacterial community characteristics -from the source of contamination, through the watershed to the DW production process-may help safeguard human health and the environment. RESULTS: The spatial and seasonal dynamics of bacterial communities, their predicted functions, and potential health-related bacterial (PHRB) reads within the Kokemäenjoki River watershed in southwest Finland were analyzed with the 16S rRNA-gene amplicon sequencing method. Water samples were collected from various sampling points of the watershed, from its major pollution sources (sewage influent and effluent, industrial effluent, mine runoff) and different stages of the DW treatment process (pre-treatment, groundwater observation well, DW production well) by using the river water as raw water with an artificial groundwater recharge (AGR). The beta-diversity analysis revealed that bacterial communities were highly varied among sample groups (R = 0.92, p <  0.001, ANOSIM). The species richness and evenness indices were highest in surface water (Chao1; 920 ± 10) among sample groups and gradually decreased during the DW treatment process (DW production well; Chao1: 320 ± 20). Although the phylum Proteobacteria was omnipresent, its relative abundance was higher in sewage and industrial effluents (66-80%) than in surface water (55%). Phyla Firmicutes and Fusobacteria were only detected in sewage samples. Actinobacteria was more abundant in the surface water (≥13%) than in other groups (≤3%). Acidobacteria was more abundant in the DW treatment process (≥13%) than in others (≤2%). In total, the share of PHRB reads was higher in sewage and surface water than in the DW treatment samples. The seasonal effect in bacterial communities was observed only on surface water samples, with the lowest diversity during summer. CONCLUSIONS: The low bacterial diversity and absence of PHRB read in the DW samples indicate AGR can produce biologically stable and microbiologically safe drinking water. Furthermore, the significantly different bacterial communities at the pollution sources compared to surface water and DW samples highlight the importance of effective wastewater treatment for protecting the environment and human health.

Associations between dog keeping and indoor dust microbiota.

Living with dogs appears to protect against allergic diseases and airway infections, an effect possibly linked with immunomodulation by microbial exposures associated with dogs. The aim of this study was to characterize the influence of dog ownership on house dust microbiota composition. The bacterial and fungal microbiota was characterized with Illumina MiSeq sequencing from floor dust samples collected from homes in a Finnish rural-suburban (LUKAS2, N = 182) birth cohort, and the results were replicated in a German urban (LISA, N = 284) birth cohort. Human associated bacteria variable was created by summing up the relative abundances of five bacterial taxa. Bacterial richness, Shannon index and the relative abundances of seven bacterial genera, mostly within the phyla Proteobacteria and Firmicutes, were significantly higher in the dog than in the non-dog homes, whereas the relative abundance of human associated bacteria was lower. The results were largely replicated in LISA. Fungal microbiota richness and abundance of Leucosporidiella genus were higher in dog homes in LUKAS2 and the latter association replicated in LISA. Our study confirms that dog ownership is reproducibly associated with increased bacterial richness and diversity in house dust and identifies specific dog ownership-associated genera. Dogs appeared to have more limited influence on the fungal than bacterial indoor microbiota.

Potential and limitations of a pilot-scale drinking water distribution system for bacterial community predictive modelling.

Waterborne disease outbreaks are a persistent and serious threat to public health according to reported incidents across the globe. Online drinking water quality monitoring technologies have evolved substantially and have become more accurate and accessible. However, using online measurements alone is unsuitable for detecting microbial regrowth, potentially including harmful species, ahead of time in the distribution systems. Alternatively, observational data could be collected periodically, e.g. once per week or once per month and it could include a representative set of variables: physicochemical water characteristics, disinfectant concentrations, and bacterial abundances, which would be a valuable source of knowledge for predictive modelling that aims to reveal pathogen-related threats. In this study, we utilised data collected from a pilot-scale drinking water distribution system. A data-driven random forest model was used for predictive modelling and was trained for nowcasting and forecasting abundances of bacterial groups. In all the experiments, we followed the realistic crossline scenario, which means that when training and testing the models the data is collected from different pipelines. In spite of the more accurate results of the nowcasting, the 1-week forecasting still provided accurate predictions of the most abundant bacteria, their rapid increase and decrease. In the future predictive modelling might be used as a tool in designing control measures for opportunistic pathogens which are able to multiply in the favourable conditions in drinking water distribution systems (DWDS). Eventually, the forecasting information will be able to produce practically helpful data for controlling the DWDS regrowth.

Early life home microbiome and hyperactivity/inattention in school-age children.

This study evaluates the association between indoor microbial diversity early in life and hyperactivity/inattention symptoms in children at ages 10 and 15 years.A random sample enriched with subjects with hyperactivity/inattention at age 15 years was selected from the German LISA birth cohort. Bedroom floor dust was collected at age 3 months and 4 bacterial and fungal diversity measures [number of observed operational taxonomic units (OTUs), Chao1, Shannon and Simpson indices] were calculated from Illumina MiSeq sequencing data. Hyperactivity/inattention was based on the Strengths and Difficulties Questionnaire at ages 10 and 15 (cut-off ≥7). Adjusted associations between 4 diversity measures in tertiles and hyperactivity/inattention were investigated with weighted and survey logistic regression models. We included 226 individuals with information on microbial diversity and hyperactivity/inattention. Early life bacterial diversity was inversely associated with hyperactivity/inattention at age 10 [bacterial OTUs (medium vs low: aOR = 0.4, 95%CI = (0.2-0.8)) and Chao1 (medium vs low: 0.3 (0.1-0.5); high vs low: 0.3 (0.2-0.6)], whereas fungal diversity was directly associated [Chao1 (high vs low: 2.1 (1.1-4.0)), Shannon (medium vs low: 2.8 (1.3-5.8)), and Simpson (medium vs low: 4.7 (2.4-9.3))]. At age 15, only Shannon index was significantly associated with hyperactivity/inattention [bacteria (medium vs low: 2.3 (1.2-4.2); fungi (high vs low: 0.5 (0.3-0.9))]. In conclusion, early life exposure to microbial diversity may play a role in the psychobehavioural development. We observe heterogeneity in the direction of the associations encouraging further longitudinal studies to deepen our understanding of the characteristics of the microbial community underlying the observed associations.

Indoor bacterial microbiota and development of asthma by 10.5 years of age.

BACKGROUND: Early-life indoor bacterial exposure is associated with the risk of asthma, but the roles of specific bacterial genera are poorly understood. OBJECTIVE: We sought to determine whether individual bacterial genera in indoor microbiota predict the development of asthma. METHODS: Dust samples from living rooms were collected at 2 months of age. The dust microbiota was characterized by using Illumina MiSeq sequencing amplicons of the bacterial 16S ribosomal RNA gene. Children (n = 373) were followed up for ever asthma until the age of 10.5 years. RESULTS: Richness was inversely associated with asthma after adjustments (P = .03). The phylogenetic microbiota composition in asthmatics patients' homes was characteristically different from that in nonasthmatic subjects' homes (P = .02, weighted UniFrac, adjusted association, permutational multivariate analysis of variance, PERMANOVA-S). The first 2 axis scores of principal coordinate analysis of the weighted UniFrac distance matrix were inversely associated with asthma. Of 658 genera detected in the dust samples, the relative abundances of 41 genera correlated (r > |0.4|) with one of these axes. Lactococcus genus was a risk factor for asthma (adjusted odds ratio, 1.36 [95% CI, 1.13-1.63] per interquartile range change). The abundance of 12 bacterial genera (mostly from the Actinomycetales order) was associated with lower asthma risk (P < .10), although not independently of each other. The sum relative abundance of these 12 intercorrelated genera was significantly protective and explained the majority of the association of richness with less asthma. CONCLUSION: Our data confirm that phylogenetic differences in the microbiota of infants' homes are associated with subsequent asthma risk and suggest that communities of selected bacteria are more strongly linked to asthma protection than individual bacterial taxa or mere richness.

Author Correction: Farm-like indoor microbiota in non-farm homes protects children from asthma development.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Active eukaryotes in drinking water distribution systems of ground and surface waterworks.

BACKGROUND: Eukaryotes are ubiquitous in natural environments such as soil and freshwater. Little is known of their presence in drinking water distribution systems (DWDSs) or of the environmental conditions that affect their activity and survival. METHODS: Eukaryotes were characterized by Illumina high-throughput sequencing targeting 18S rRNA gene (DNA) that estimates the total community and the 18S rRNA gene transcript (RNA) that is more representative of the active part of the community. DWDS cold water (N = 124), hot water (N = 40), and biofilm (N = 16) samples were collected from four cities in Finland. The sampled DWDSs were from two waterworks A-B with non-disinfected, recharged groundwater as source water and from three waterworks utilizing chlorinated water (two DWDSs of surface waterworks C-D and one of ground waterworks E). In each DWDS, samples were collected from three locations during four seasons of 1 year. RESULTS: A beta-diversity analysis revealed that the main driver shaping the eukaryotic communities was the DWDS (A-E) (R = 0.73, P < 0.001, ANOSIM). The kingdoms Chloroplastida (green plants and algae), Metazoa (animals: rotifers, nematodes), Fungi (e.g., Cryptomycota), Alveolata (ciliates, dinoflagellates), and Stramenopiles (algae Ochrophyta) were well represented and active-judging based on the rRNA gene transcripts-depending on the surrounding conditions. The unchlorinated cold water of systems (A-B) contained a higher estimated total number of taxa (Chao1, average 380-480) than chlorinated cold water in systems C-E (Chao1 ≤ 210). Within each DWDS, unique eukaryotic communities were identified at different locations as was the case also for cold water, hot water, and biofilms. A season did not have a consistent impact on the eukaryotic community among DWDSs. CONCLUSIONS: This study comprehensively characterized the eukaryotic community members within the DWDS of well-maintained ground and surface waterworks providing good quality water. The study gives an indication that each DWDS houses a unique eukaryotic community, mainly dependent on the raw water source and water treatment processes in place at the corresponding waterworks. In particular, disinfection as well as hot water temperature seemed to represent a strong selection pressure that controlled the number of active eukaryotic species.

Farm-like indoor microbiota in non-farm homes protects children from asthma development.

Asthma prevalence has increased in epidemic proportions with urbanization, but growing up on traditional farms offers protection even today1. The asthma-protective effect of farms appears to be associated with rich home dust microbiota2,3, which could be used to model a health-promoting indoor microbiome. Here we show by modeling differences in house dust microbiota composition between farm and non-farm homes of Finnish birth cohorts4 that in children who grow up in non-farm homes, asthma risk decreases as the similarity of their home bacterial microbiota composition to that of farm homes increases. The protective microbiota had a low abundance of Streptococcaceae relative to outdoor-associated bacterial taxa. The protective effect was independent of richness and total bacterial load and was associated with reduced proinflammatory cytokine responses against bacterial cell wall components ex vivo. We were able to reproduce these findings in a study among rural German children2 and showed that children living in German non-farm homes with an indoor microbiota more similar to Finnish farm homes have decreased asthma risk. The indoor dust microbiota composition appears to be a definable, reproducible predictor of asthma risk and a potential modifiable target for asthma prevention.

Categorical performance characteristics of method ISO 7899-2 and indicator value of intestinal enterococci for bathing water quality monitoring.

Intestinal enterococci indicate the fecal contamination of bathing waters. This study defines the performance characteristics of the reference method ISO 7899-2:2000 with water samples collected from inland and coastal bathing areas in Finland. From a total of 341 bacterial isolates grown on Slanetz and Bartley medium, 63.6% were confirmed as intestinal enterococci on bile aesculin agar. The partial 16S rRNA gene sequences showed that Enterococcus faecium and Enterococcus faecalis clades accounted for 93.1% of the confirmed isolates. The range of the false positive and false negative rate of the ISO 7899-2 was 0.0-18.5% and 5.6-57.1%, respectively, being affected by the presumptive colony count on the membrane. The analysis of multiple sample volumes is proposed to reach 10-100 colonies per membrane when 47 mm diameter membranes are used to prevent overestimation of low counts and underestimation of the high counts.

Crawling-induced floor dust resuspension affects the microbiota of the infant breathing zone.

BACKGROUND: Floor dust is commonly used for microbial determinations in epidemiological studies to estimate early-life indoor microbial exposures. Resuspension of floor dust and its impact on infant microbial exposure is, however, little explored. The aim of our study was to investigate how floor dust resuspension induced by an infant's crawling motion and an adult walking affects infant inhalation exposure to microbes. RESULTS: We conducted controlled chamber experiments with a simplified mechanical crawling infant robot and an adult volunteer walking over carpeted flooring. We applied bacterial 16S rRNA gene sequencing and quantitative PCR to monitor the infant breathing zone microbial content and compared that to the adult breathing zone and the carpet dust as the source. During crawling, fungal and bacterial levels were, on average, 8- to 21-fold higher in the infant breathing zone compared to measurements from the adult breathing zone. During walking experiments, the increase in microbial levels in the infant breathing zone was far less pronounced. The correlation in rank orders of microbial levels in the carpet dust and the corresponding infant breathing zone sample varied between different microbial groups but was mostly moderate. The relative abundance of bacterial taxa was characteristically distinct in carpet dust and infant and adult breathing zones during the infant crawling experiments. Bacterial diversity in carpet dust and the infant breathing zone did not correlate significantly. CONCLUSIONS: The microbiota in the infant breathing zone differ in absolute quantitative and compositional terms from that of the adult breathing zone and of floor dust. Crawling induces resuspension of floor dust from carpeted flooring, creating a concentrated and localized cloud of microbial content around the infant. Thus, the microbial exposure of infants following dust resuspension is difficult to predict based on common house dust or bulk air measurements. Improved approaches for the assessment of infant microbial exposure, such as sampling at the infant breathing zone level, are needed.

Quantitative assessment of microbes from samples of indoor air and dust.

Different types of house dust samples are widely used as surrogates of airborne inhalation exposure in studies assessing health effects of indoor microbes. Here we studied-in a quantitative assessment-the representativeness of different house dust samples of indoor air (IA) and investigated seasonality and reproducibility of indoor samples. Microbial exposure was measured five times over 1 year in four rural and five urban Finnish homes. Six sampling methods were used: button inhalable aerosol sampler (actively collected personal and indoor air sampling), settled dust, floor dust, mattress dust and vacuum cleaner dust bag dust; the latter three referred to herein as "reservoir dust samples". Using quantitative PCR, we quantified the fungal species Cladosporium herbarum, the fungal group Penicillium/Aspergillus/Paecilomyces variotii, total fungal DNA, and Gram-positive and Gram-negative bacteria. We observed significant differences in microbial levels between rural and urban homes, most pronounced for personal air samples. Fungal species and groups but not total fungal DNA in indoor air correlated moderately to well with reservoir dust and with personal air samples. For bacterial groups, the correlations between air and dust were generally lower. Samples of indoor air and settled dust reflected similarly seasonal variation in microbial levels and were also similar compositionally, as assessed by ratios of qPCR markers. In general, determinations from mattress dust and other reservoir samples were better reproducible in repeated assessments over time than from indoor air or settled dust. This study indicates that settled dust reflects the microbial composition of indoor air and responds similarly to environmental determinants. Reservoir dusts tend to predict better microbial levels in indoor air and are more reproducible. Sampling strategies in indoor studies need to be developed based on the study questions and may need to rely on more than one type of sample.

Indoor microbiota in severely moisture damaged homes and the impact of interventions.

BACKGROUND: The limited understanding of microbial characteristics in moisture-damaged buildings impedes efforts to clarify which adverse health effects in the occupants are associated with the damage and to develop effective building intervention strategies. The objectives of this current study were (i) to characterize fungal and bacterial microbiota in house dust of severely moisture-damaged residences, (ii) to identify microbial taxa associated with moisture damage renovations, and (iii) to test whether the associations between the identified taxa and moisture damage are replicable in another cohort of homes. We applied bacterial 16S rRNA gene and fungal ITS amplicon sequencing complemented with quantitative PCR and chemical-analytical approaches to samples of house dust, and also performed traditional cultivation of bacteria and fungi from building material samples. RESULTS: Active microbial growth on building materials had significant though small influence on the house dust bacterial and fungal communities. Moisture damage interventions-including actual renovation of damaged homes and cases where families moved to another home-had only a subtle effect on bacterial community structure, seen as shifts in abundance weighted bacterial profiles after intervention. While bacterial and fungal species richness were reduced in homes that were renovated, they were not reduced for families that moved houses. Using different discriminant analysis tools, we were able identify taxa that were significantly reduced in relative abundance during renovation of moisture damage. For bacteria, the majority of candidates belonged to different families within the Actinomycetales order. Results for fungi were overall less consistent. A replication study in approximately 400 homes highlighted some of the identified taxa, confirming associations with observations of moisture damage and mold. CONCLUSIONS: The present study is one of the first studies to analyze changes in microbiota due to moisture damage interventions using high-throughput sequencing. Our results suggest that effects of moisture damage and moisture damage interventions may appear as changes in the abundance of individual, less common, and especially bacterial taxa, rather than in overall community structure.

Genome sequencing and population genomic analyses provide insights into the adaptive landscape of silver birch.

Silver birch (Betula pendula) is a pioneer boreal tree that can be induced to flower within 1 year. Its rapid life cycle, small (440-Mb) genome, and advanced germplasm resources make birch an attractive model for forest biotechnology. We assembled and chromosomally anchored the nuclear genome of an inbred B. pendula individual. Gene duplicates from the paleohexaploid event were enriched for transcriptional regulation, whereas tandem duplicates were overrepresented by environmental responses. Population resequencing of 80 individuals showed effective population size crashes at major points of climatic upheaval. Selective sweeps were enriched among polyploid duplicates encoding key developmental and physiological triggering functions, suggesting that local adaptation has tuned the timing of and cross-talk between fundamental plant processes. Variation around the tightly-linked light response genes PHYC and FRS10 correlated with latitude and longitude and temperature, and with precipitation for PHYC. Similar associations characterized the growth-promoting cytokinin response regulator ARR1, and the wood development genes KAK and MED5A.