Additional file 6: Table S3. ARG protein families detected on toothbrushes and in the subset of H... more Additional file 6: Table S3. ARG protein families detected on toothbrushes and in the subset of HMP-II oral samples. Drug class and mechanism of resistance are in accordance with the Comprehensive Antibiotic Resistance Database [24]. Sample detection frequency, RPKM mean and standard error, and GLM p and q values are listed. ARGs enriched (q < 0.05) in toothbrush or oral samples are indicated in blue and green font, respectively.
Additional file 5: Figure S3. PCoA displaying species-level beta-diversity across microbial commu... more Additional file 5: Figure S3. PCoA displaying species-level beta-diversity across microbial communities on toothbrushes and those from specific oral sites (HMP-II). Colors/shapes corresponds to sample type.
Additional file 7: Table S4. Accession numbers and available metadata for the oral metagenomes us... more Additional file 7: Table S4. Accession numbers and available metadata for the oral metagenomes used in the resistome analysis, which correspond to the subset in Figure 3a.
Additional file 9: Figure S5. Metadata that may associate with alpha-diversity of toothbrush micr... more Additional file 9: Figure S5. Metadata that may associate with alpha-diversity of toothbrush microbiota taxonomic profiles; i.e., factors from the set of 20 variables displayed in Figure 4 that had a Mann-Whitney or Kruskal-Wallis test p < 0.1.
Additional file 8: Figure S4. Metadata that may associate with beta-diversity of toothbrush micro... more Additional file 8: Figure S4. Metadata that may associate with beta-diversity of toothbrush microbiota (left panels) and toothbrush resistomes (right panels), i.e., factors from the set of 20 variables displayed in Figure 4 that had a PERMANOVA p < 0.1.
Additional file 4: Figure S2. Relationship between genera relative abundances within toothbrush m... more Additional file 4: Figure S2. Relationship between genera relative abundances within toothbrush microbial communities predicted using the marker-gene approach (i.e., MetaPhlAn2) and genera frequencies among metagenome-assembled genomes. Genera with over 5% from either category are listed.
Additional file 2: Table S1. Frequency and relative abundance of microbial species detected in to... more Additional file 2: Table S1. Frequency and relative abundance of microbial species detected in toothbrush metagenomes. Conserved taxa (i.e., at least 50% of samples) are in bold font.
Additional file 1: Figure S1. Nonpareil curves illustrating sequencing coverage of the toothbrush... more Additional file 1: Figure S1. Nonpareil curves illustrating sequencing coverage of the toothbrush metagenomes. Solid and dotted lines correspond to observed and predicted redundancy, respectively.
<b>Plasmids reconstructed from long-read sequencing of a cultured dust isolate related to &... more <b>Plasmids reconstructed from long-read sequencing of a cultured dust isolate related to <i>S. equorum</i>.</b>We targeted staphylococcoidal culture isolates from a dust sample (AF82) with metagenomically abundant <i>Staphylococcus</i>to characterize chromosomal and plasmidic ARGs. We identified and sequenced one such strain that proved to be <i>Staphylococcus equorum</i>(100% full-length rRNA gene identity). We further isolated its plasmid DNA for Nanopore sequencing (<b>Methods</b>), resulting in 4 complete or partial plasmids assembled using CANU / Pilon (Koren et al., 2017; Walker et al., 2014).
<b>Dust contains few ARGs and mobilizable elements relative to animal gut and drinking wate... more <b>Dust contains few ARGs and mobilizable elements relative to animal gut and drinking water metagenomes.</b>We compared total MGE abundances (sum of all mobilizable gene families from HUMAnN2 {30377376} profiles and total ARG abundances (sums from ShortBRED (Kaminski et al., 2015) profiles) between dust metagenomes and two other datasets: 13 livestock stool samples from (Hu et al., 2016) and 25 drinking water metagenomes from (Ma et al., 2018). Animal guts and drinking water had significantly more total MGEs than dust, and animal stool had (as expected) significantly more total ARGs. P-values are shown from Mann-Whitney tests relative to dust distribution.
<b>Antibiotic resistance gene (ARG) class relative abundances in dust metagenomes. </b&g... more <b>Antibiotic resistance gene (ARG) class relative abundances in dust metagenomes. </b>ARGs were quantified using ShortBRED (Kaminski et al., 2015) from 166 total dust metagenomes spanning 43 buildings (Hartmann et al., 2016; Fahimipour et al., 2018). Here, the relative abundance of individual ARGs over all dust samples (normalized as reads per kilobase per million mapped reads (RPKM)) are grouped by class according to CARD (Jia et al., 2017), each circle indicating the relative abundance of one single ARG in a single sample belonging to a specific antibiotic class. The colors indicate the different antibiotic classes.
<b>ARG class relative abundances in drinking water and livestock stool metagenomes.</b&g... more <b>ARG class relative abundances in drinking water and livestock stool metagenomes.</b>ARGs were quantified as for dust in <b>Fig. 1</b>(average per gene across samples) from 25 drinking water and 13 animal stool metagenomes (Ma et al., 2017; Hu et al., 2017). ARG levels per class in <b>A)</b>drinking water were similar to those in dust, as were overall ARG levels (<b>Fig. 4</b>), while <b>B) </b>in livestock most classes and particularly tetracycline, streptothricin, macrolide, and lincosamide resistance were much more abundant.
Fig S4 Genome of the <i>S. equorum</i>dust isolate reconstructed from whole genome se... more Fig S4 Genome of the <i>S. equorum</i>dust isolate reconstructed from whole genome sequencing (Illumina technology). The genome was reconstructed using SPades and represented using DNAPlotter (Carver et al., 2009). Red dashes on the second circle indicate annotated antibiotic resistance genes on the forward DNA strand while the third circle shows the ones detected on the reverse strand; orange dashes on the first circle: other annotated genes, light grey: repeat regions, long turquoise dashes: mobile genetic element genes, dark green and dark purple: GC plot, light green and purple: GC skew.
Background While indoor microbiomes impact our health and well-being, much remains unknown about ... more Background While indoor microbiomes impact our health and well-being, much remains unknown about taxonomic and functional transitions that occur in human-derived microbial communities once they are transferred away from human hosts. Toothbrushes are a model to investigate the potential response of oral-derived microbiota to conditions of the built environment. Here, we characterize metagenomes of toothbrushes from 34 subjects to define the toothbrush microbiome and resistome and possible influential factors. Results Toothbrush microbiomes often comprised a dominant subset of human oral taxa and less abundant or site-specific environmental strains. Although toothbrushes contained lower taxonomic diversity than oral-associated counterparts (determined by comparison with the Human Microbiome Project), they had relatively broader antimicrobial resistance gene (ARG) profiles. Toothbrush resistomes were enriched with a variety of ARGs, notably those conferring multidrug efflux and putativ...
The decades-long global trend of urbanization has led to a population that spends increasing amou... more The decades-long global trend of urbanization has led to a population that spends increasing amounts of time indoors. Exposure to microbes in buildings, and specifically in dust, is thus also increasing, and has been linked to various health outcomes and to antibiotic resistance genes (ARGs). These are most efficiently screened using DNA sequencing, but this method does not determine which microbes are viable, nor does it reveal whether their ARGs can actually disseminate to other microbes. We have thus performed the first study to: 1) examine the potential for ARG dissemination in indoor dust microbial communities, and 2) validate the presence of detected mobile ARGs in viable dust bacteria. Specifically, we integrated 166 dust metagenomes from 43 different buildings. Sequences were assembled, annotated, and screened for potential integrons, transposons, plasmids, and associated ARGs. The same dust samples were further investigated using cultivation and isolate genome and plasmid sequencing. Potential ARGs were detected in dust isolate genomes, and we confirmed their placement on mobile genetic elements using long-read sequencing. We found 183 ARGs, of which 52 were potentially mobile (associated with a putative plasmid, transposon or integron). One dust isolate related to Staphylococcus equorum proved to contain a plasmid carrying an ARG that was detected metagenomically and confirmed through whole genome and plasmid sequencing. This study thus highlights the power of combining cultivation with metagenomics to assess the risk of potentially mobile ARGs for public health.
Journal of Exposure Science & Environmental Epidemiology, 2019
The indoor environment is an important source of microbial exposures for its human occupants. Whi... more The indoor environment is an important source of microbial exposures for its human occupants. While we naturally want to favor positive health outcomes, built environment design and operation may counter-intuitively favor negative health outcomes, particularly with regard to antibiotic resistance. Indoor environments contain microbes from both human and non-human origins, providing a unique venue for microbial interactions, including horizontal gene transfer. Furthermore, stressors present in the built environment could favor the exchange of genetic material in general and the retention of antibiotic resistance genes in particular. Intrinsic and acquired antibiotic resistance both pose a potential threat to human health; these phenomena need to be considered and controlled separately. The presence of both environmental and human-associated microbes, along with their associated antibiotic resistance genes, in the face of stressors, including antimicrobial chemicals, creates a unique ...
Wastewater treatment plants (WWTPs) contain high density and diversity of viruses which can signi... more Wastewater treatment plants (WWTPs) contain high density and diversity of viruses which can significantly impact microbial communities in aquatic systems. While previous studies have investigated viruses in WWTP samples that have been specifically concentrated for viruses and filtered to exclude bacteria, little is known about viral communities associated with bacterial communities throughout wastewater treatment systems. Additionally, differences in viral composition between attached and suspended growth wastewater treatment bioprocesses are not well characterized. Here, shotgun metagenomics was used to analyse wastewater and biomass from transects through two full-scale WWTPs for viral composition and associations with bacterial hosts. One WWTP used a suspended growth activated sludge bioreactor and the other used a biofilm reactor (trickling filter). Myoviridae, Podoviridae and Siphoviridae were the dominant viral families throughout both WWTPs, which are all from the order Caudovirales. Beta diversity analysis of viral sequences showed that samples clustered significantly both by plant and by specific sampling location. For each WWTP, the overall bacterial community structure was significantly different than community structure of bacterial taxa associated with viral sequences. These findings highlight viral community composition in transects through different WWTPs and provide context for dsDNA viral sequences in bacterial communities from these systems.
This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmer... more This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Additional file 6: Table S3. ARG protein families detected on toothbrushes and in the subset of H... more Additional file 6: Table S3. ARG protein families detected on toothbrushes and in the subset of HMP-II oral samples. Drug class and mechanism of resistance are in accordance with the Comprehensive Antibiotic Resistance Database [24]. Sample detection frequency, RPKM mean and standard error, and GLM p and q values are listed. ARGs enriched (q < 0.05) in toothbrush or oral samples are indicated in blue and green font, respectively.
Additional file 5: Figure S3. PCoA displaying species-level beta-diversity across microbial commu... more Additional file 5: Figure S3. PCoA displaying species-level beta-diversity across microbial communities on toothbrushes and those from specific oral sites (HMP-II). Colors/shapes corresponds to sample type.
Additional file 7: Table S4. Accession numbers and available metadata for the oral metagenomes us... more Additional file 7: Table S4. Accession numbers and available metadata for the oral metagenomes used in the resistome analysis, which correspond to the subset in Figure 3a.
Additional file 9: Figure S5. Metadata that may associate with alpha-diversity of toothbrush micr... more Additional file 9: Figure S5. Metadata that may associate with alpha-diversity of toothbrush microbiota taxonomic profiles; i.e., factors from the set of 20 variables displayed in Figure 4 that had a Mann-Whitney or Kruskal-Wallis test p < 0.1.
Additional file 8: Figure S4. Metadata that may associate with beta-diversity of toothbrush micro... more Additional file 8: Figure S4. Metadata that may associate with beta-diversity of toothbrush microbiota (left panels) and toothbrush resistomes (right panels), i.e., factors from the set of 20 variables displayed in Figure 4 that had a PERMANOVA p < 0.1.
Additional file 4: Figure S2. Relationship between genera relative abundances within toothbrush m... more Additional file 4: Figure S2. Relationship between genera relative abundances within toothbrush microbial communities predicted using the marker-gene approach (i.e., MetaPhlAn2) and genera frequencies among metagenome-assembled genomes. Genera with over 5% from either category are listed.
Additional file 2: Table S1. Frequency and relative abundance of microbial species detected in to... more Additional file 2: Table S1. Frequency and relative abundance of microbial species detected in toothbrush metagenomes. Conserved taxa (i.e., at least 50% of samples) are in bold font.
Additional file 1: Figure S1. Nonpareil curves illustrating sequencing coverage of the toothbrush... more Additional file 1: Figure S1. Nonpareil curves illustrating sequencing coverage of the toothbrush metagenomes. Solid and dotted lines correspond to observed and predicted redundancy, respectively.
<b>Plasmids reconstructed from long-read sequencing of a cultured dust isolate related to &... more <b>Plasmids reconstructed from long-read sequencing of a cultured dust isolate related to <i>S. equorum</i>.</b>We targeted staphylococcoidal culture isolates from a dust sample (AF82) with metagenomically abundant <i>Staphylococcus</i>to characterize chromosomal and plasmidic ARGs. We identified and sequenced one such strain that proved to be <i>Staphylococcus equorum</i>(100% full-length rRNA gene identity). We further isolated its plasmid DNA for Nanopore sequencing (<b>Methods</b>), resulting in 4 complete or partial plasmids assembled using CANU / Pilon (Koren et al., 2017; Walker et al., 2014).
<b>Dust contains few ARGs and mobilizable elements relative to animal gut and drinking wate... more <b>Dust contains few ARGs and mobilizable elements relative to animal gut and drinking water metagenomes.</b>We compared total MGE abundances (sum of all mobilizable gene families from HUMAnN2 {30377376} profiles and total ARG abundances (sums from ShortBRED (Kaminski et al., 2015) profiles) between dust metagenomes and two other datasets: 13 livestock stool samples from (Hu et al., 2016) and 25 drinking water metagenomes from (Ma et al., 2018). Animal guts and drinking water had significantly more total MGEs than dust, and animal stool had (as expected) significantly more total ARGs. P-values are shown from Mann-Whitney tests relative to dust distribution.
<b>Antibiotic resistance gene (ARG) class relative abundances in dust metagenomes. </b&g... more <b>Antibiotic resistance gene (ARG) class relative abundances in dust metagenomes. </b>ARGs were quantified using ShortBRED (Kaminski et al., 2015) from 166 total dust metagenomes spanning 43 buildings (Hartmann et al., 2016; Fahimipour et al., 2018). Here, the relative abundance of individual ARGs over all dust samples (normalized as reads per kilobase per million mapped reads (RPKM)) are grouped by class according to CARD (Jia et al., 2017), each circle indicating the relative abundance of one single ARG in a single sample belonging to a specific antibiotic class. The colors indicate the different antibiotic classes.
<b>ARG class relative abundances in drinking water and livestock stool metagenomes.</b&g... more <b>ARG class relative abundances in drinking water and livestock stool metagenomes.</b>ARGs were quantified as for dust in <b>Fig. 1</b>(average per gene across samples) from 25 drinking water and 13 animal stool metagenomes (Ma et al., 2017; Hu et al., 2017). ARG levels per class in <b>A)</b>drinking water were similar to those in dust, as were overall ARG levels (<b>Fig. 4</b>), while <b>B) </b>in livestock most classes and particularly tetracycline, streptothricin, macrolide, and lincosamide resistance were much more abundant.
Fig S4 Genome of the <i>S. equorum</i>dust isolate reconstructed from whole genome se... more Fig S4 Genome of the <i>S. equorum</i>dust isolate reconstructed from whole genome sequencing (Illumina technology). The genome was reconstructed using SPades and represented using DNAPlotter (Carver et al., 2009). Red dashes on the second circle indicate annotated antibiotic resistance genes on the forward DNA strand while the third circle shows the ones detected on the reverse strand; orange dashes on the first circle: other annotated genes, light grey: repeat regions, long turquoise dashes: mobile genetic element genes, dark green and dark purple: GC plot, light green and purple: GC skew.
Background While indoor microbiomes impact our health and well-being, much remains unknown about ... more Background While indoor microbiomes impact our health and well-being, much remains unknown about taxonomic and functional transitions that occur in human-derived microbial communities once they are transferred away from human hosts. Toothbrushes are a model to investigate the potential response of oral-derived microbiota to conditions of the built environment. Here, we characterize metagenomes of toothbrushes from 34 subjects to define the toothbrush microbiome and resistome and possible influential factors. Results Toothbrush microbiomes often comprised a dominant subset of human oral taxa and less abundant or site-specific environmental strains. Although toothbrushes contained lower taxonomic diversity than oral-associated counterparts (determined by comparison with the Human Microbiome Project), they had relatively broader antimicrobial resistance gene (ARG) profiles. Toothbrush resistomes were enriched with a variety of ARGs, notably those conferring multidrug efflux and putativ...
The decades-long global trend of urbanization has led to a population that spends increasing amou... more The decades-long global trend of urbanization has led to a population that spends increasing amounts of time indoors. Exposure to microbes in buildings, and specifically in dust, is thus also increasing, and has been linked to various health outcomes and to antibiotic resistance genes (ARGs). These are most efficiently screened using DNA sequencing, but this method does not determine which microbes are viable, nor does it reveal whether their ARGs can actually disseminate to other microbes. We have thus performed the first study to: 1) examine the potential for ARG dissemination in indoor dust microbial communities, and 2) validate the presence of detected mobile ARGs in viable dust bacteria. Specifically, we integrated 166 dust metagenomes from 43 different buildings. Sequences were assembled, annotated, and screened for potential integrons, transposons, plasmids, and associated ARGs. The same dust samples were further investigated using cultivation and isolate genome and plasmid sequencing. Potential ARGs were detected in dust isolate genomes, and we confirmed their placement on mobile genetic elements using long-read sequencing. We found 183 ARGs, of which 52 were potentially mobile (associated with a putative plasmid, transposon or integron). One dust isolate related to Staphylococcus equorum proved to contain a plasmid carrying an ARG that was detected metagenomically and confirmed through whole genome and plasmid sequencing. This study thus highlights the power of combining cultivation with metagenomics to assess the risk of potentially mobile ARGs for public health.
Journal of Exposure Science & Environmental Epidemiology, 2019
The indoor environment is an important source of microbial exposures for its human occupants. Whi... more The indoor environment is an important source of microbial exposures for its human occupants. While we naturally want to favor positive health outcomes, built environment design and operation may counter-intuitively favor negative health outcomes, particularly with regard to antibiotic resistance. Indoor environments contain microbes from both human and non-human origins, providing a unique venue for microbial interactions, including horizontal gene transfer. Furthermore, stressors present in the built environment could favor the exchange of genetic material in general and the retention of antibiotic resistance genes in particular. Intrinsic and acquired antibiotic resistance both pose a potential threat to human health; these phenomena need to be considered and controlled separately. The presence of both environmental and human-associated microbes, along with their associated antibiotic resistance genes, in the face of stressors, including antimicrobial chemicals, creates a unique ...
Wastewater treatment plants (WWTPs) contain high density and diversity of viruses which can signi... more Wastewater treatment plants (WWTPs) contain high density and diversity of viruses which can significantly impact microbial communities in aquatic systems. While previous studies have investigated viruses in WWTP samples that have been specifically concentrated for viruses and filtered to exclude bacteria, little is known about viral communities associated with bacterial communities throughout wastewater treatment systems. Additionally, differences in viral composition between attached and suspended growth wastewater treatment bioprocesses are not well characterized. Here, shotgun metagenomics was used to analyse wastewater and biomass from transects through two full-scale WWTPs for viral composition and associations with bacterial hosts. One WWTP used a suspended growth activated sludge bioreactor and the other used a biofilm reactor (trickling filter). Myoviridae, Podoviridae and Siphoviridae were the dominant viral families throughout both WWTPs, which are all from the order Caudovirales. Beta diversity analysis of viral sequences showed that samples clustered significantly both by plant and by specific sampling location. For each WWTP, the overall bacterial community structure was significantly different than community structure of bacterial taxa associated with viral sequences. These findings highlight viral community composition in transects through different WWTPs and provide context for dsDNA viral sequences in bacterial communities from these systems.
This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmer... more This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
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