Introduction

Given that humans spend most of their lives in indoor environments [1], it is important to understand the microorganisms that can be found in these human-created structures. Previous work based on 16S rRNA gene surveys has described thousands of bacterial taxa from residences (e.g., [2]). Within these residences, periodically wet surfaces– such as shower walls, shower heads, sinks, drains – represent unique (compared to dryer areas within the home - [3–5]) and potentially medically important microbial communities [6]. Humans could readily interface with the microbial communities on these wet surfaces by direct contact or by inhalation from aerosolized particles. Focusing on these airborne microorganisms, Miletto & Lindow [7] collected aerosol particles from residences for genetic analysis and identified over 300 genera which they attributed to various sources including tap water, human occupants, indoor surfaces, and outdoor air.

An important tool in studying microbial communities involves culturing and genome sequencing. In order to expand our work on the microbiology of built environments [8] into a more experimental framework, we cultured bacteria from the air of residential bathrooms and report their genome sequences. Genome sequencing was utilized in order to provide insight into the basic biology of the bacteria collected in indoor environments and to aid with future metagenomic and transcriptomic efforts.

The eight isolates within five genera were isolated during a sampling campaign of residential bathrooms conducted in 2015. While simultaneously filtering aerosols for amplicon-based community composition analysis (which is in preparation and will be published elsewhere), petri dishes were exposed to the air to isolate viable bacteria. After an initial screening of multiple isolates by sequencing the full-length 16S rRNA gene and carrying out preliminary taxonomic classification, eight isolates were selected for further genomic sequencing based on an assessment of their putative importance in the built environment. Specifically, we favored strains that met the following criteria: they are commonly identified in indoor environments, they are likely inputs from a common source for indoor microbes (premise plumbing, outdoor origin [9]), and/or they (or their close relatives) can potentially impact human health. For instance, we include three species (four isolates) of staphylococci. CoNS are typically benign inhabitants of the human skin and mucous membranes, but they are associated with infections and can be pathogenic to humans with compromised immune systems [10]. Mycobacterium iranicum is a newly described species which has been isolated from clinical specimens originating in diverse countries including Iran, Greece, the Netherlands, Sweden and the USA [11], although genomic comparison indicated that this is likely an environmental bacterium [12]. Pseudomonas oryzihabitans (synonym Flavimonas oryzihabitans ) has been isolated from water and damp environments such as rice paddies and sink drains [13]. The only two described species of the genus Plantibacter , P. auratus and P. flavus , have been detected as a tree endophyte [14] and a component from the phyllosphere of grass [15], respectively. Organisms within the genus Microbacterium belong to the class Actinobacteria in which some species are known for the production of a broad spectrum of secondary metabolites. The chemical ecology of microorganisms on indoor surfaces is a component of our ongoing research efforts in the built environment.

Here we report a summary classification and the features of these eight isolates collected as part of the Built Environment Reference Genomes initiative. Strains and their genomes have been deposited according to the following accessions: Staphylococcus capitis strain H36 (DSM-103511; GenBank ID LWCQ00000000), S. capitis strain H65 (DSM-103512; LWCP00000000), S. cohnii strain H62 (DSM-103510; LWAC00000000), S. hominis strain H69 (DSM-103553; LVVO00000000), Microbacterium sp. strain H83 (DSM-103506; LWCU00000000, Pseudomonas oryzihabitans strain H72 (DSM-103505; LWCR00000000), Mycobacterium iranicum strain H39 (DSM-103542; LWCS00000000), and finally Plantibacter sp. strain H53 (DSM-103507; LWCT00000000).

Organism information

Classification and features

Two growth media were used for the initial isolation of bacteria: lysogeny broth agar (LB, Difco Laboratories, Detroit, MI) and R2A agar (Difco Laboratories, Detroit, MI). Petri dishes were exposed to residential bathroom air for 1 h; 30 min during which shower water was running to create shower mist and 30 min after the shower was turned off. Petri dishes were mounted on vertical surfaces (door, wall, cabinets) at a height of approximately 1.50 m. Petri dishes were brought back to the laboratory, where LB plates were incubated at 28 °C for 48 h, and R2A plates were incubated at 28 °C for 5 days and at 35 °C for 3 days. Except for Staphylococcus hominis strain H69, which was isolated on LB agar medium at 35 °C, all other strains were isolated on R2A medium (Additional file 1). Research was approved by the University of California Committee for the Protection of Human Subjects Protocol ID 2015-02-7135, and the sampling was conducted in March, 2015.

Taxonomic classification of these isolates was undertaken after genome sequencing, either using the full-length 16S rRNA gene sequences or a concatenated marker gene approach. For Microbacterium , Mycobacterium , and Plantibacter there were insufficient publicly available genome sequences of close relatives for a concatenated marker approach. In these cases, the full length 16S rRNA gene sequence was uploaded to the Ribosomal Database Project [16] and added to alignments containing representatives of all close relatives (as estimated from BLAST [17]). These alignments were downloaded, cleaned with a custom script [18], and an approximately maximum likelihood tree was inferred using the default setting in FastTree [19]. Outgroups for all trees were type strains of another genus or genera within the same family. The sequence alignments supporting the phylogenetic trees of this article are available in the FigShare repository [20].

All strains were given a specific identifier (e.g., H83) based on our internal culture collection. The 16S rRNA gene trees for both Microbacterium and Plantibacter genera were poorly resolved (e.g., low bootstrap values), and these isolates were placed into polyphyletic clades with respect to the names of taxa in the genera (Additional files 2 and 3). In addition, while Microbacterium sp. H83 falls within a clade that contains mostly M. foliorum , this name also occurs outside the clade. Therefore we have not attempted to assign these isolates to a particular species. On the other hand, the rRNA gene for one isolate is found in a monophyletic clade with other M. iranicum isolates (Additional file 4) and thus we have assigned this the name M. iranicum H39, For the Pseudomonas and Staphylococcus isolates, the 16S rRNA gene trees were inadequate for taxonomic classification at the species level, but the genomes of numerous sequenced representatives of close relatives were available for further analysis. All available genome sequences of close relatives (to a max of 20 randomly selected genomes per species) were downloaded from NCBI. The file names and sequences were reformatted for easier visualization. The assemblies were then screened for 37 core maker genes [21] using PhyloSift [22] in search and align mode using “isolate” and “besthit” flags. PhyloSift concatenates and aligns the hits of interest so the sequences are subsequently extracted from the PhyloSift output files and added to a single file for tree-building. An approximately maximum-likelihood tree was then inferred using FastTree.

The concatenated marker genes for one isolate placed it in a well-supported clade of P. oryzihabitans isolates (Additional file 5) and thus we have named this P. oryzihabitans H72. Based on this tree, we believe that one of the (unpublished) strains of P. psychrotolerans has been misclassified and should also be considered P. oryzihabitans . Four of the isolates were Staphylococcus species, for which we created a single concatenated marker tree containing the relevant close relatives of the isolates (Fig. 1). Two of our Staphylococcus isolates placed within a well-supported (i.e., high bootstrap support) monophyletic clade of S. capitis strains and thus we have named these S. capitis H36 and S. capitis H65. One Staphylococcus isolate placed within a well-supported clade of S. cohnii strains and thus we have named it S. cohnii H62. Our fourth Staphylococcus isolate was placed within a well-supported clade containing mostly S. hominis isolates but which also contains a few S. haemolyticus isolates. Because this tree shows a distinct clade containing many S. haemolyticus isolates, we have named this isolate S. hominis H69. It is unclear from this tree alone whether these few S. haemolyticus isolates are misnamed or whether further taxonomic revision of this group is needed.

Fig. 1
figure 1

Maximum Likelihood tree based on concatenated markers from Staphylococcus spp. genomes. The tree was inferred using FastTree from an Hmmalign alignment in Phylosift of 37 highly conserved marker genes. Numbers at the nodes represent local support values. The tree was rooted to Macrococcus caseolyticus as an outgroup (not shown) since this species is a close relative to Staphylococcus

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General description of the isolates are summarized in Table 1, and micrographs appear in Fig. 2.

Table 1 Classification and general features of the eight isolates in accordance with the MIGS recommendations [60]
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Fig. 2
figure 2

Transmitted light microscope images of the eight isolates. Bar is 5 μm. a Rod-shaped cells of Microbacterium sp. H83 b Mycobacterium iranicum H39; note, this organism was sparse in the images and tended to be highly clumped, so two snapshots were used for the sake of visualization c pleomorphic, rod-shaped cells of Plantibacter sp. H53 d Pseudomonas oryzihabitans H72, rods with rounded ends typically occurring as solitary cells but rarely also in pairs, e Staphylococcus capitis H36, occurring in pairs or strings of cells f Staphylococcus capitis H65, as single cells and pairs g Staphylococcus cohnii H62, as single cells, pairs, and occasionally threes or tetrads, h Staphylococcus hominis H69, as single cells and pairs. Images were collected using a Zeiss M1 AxioImager equipped with DIC and a Hamamatsu Orca 03 camera run by BioVision’s iVision software. Images were cropped and organized into a plate using Adobe Photoshop CS6

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Staphylococcus are non-spore-forming, non-motile round-shaped cells (Fig. 2 e-h). They demonstrate habitat preference in the human body with S. capitis mainly being found on the adult head and S. cohnii on the feet [10]. S. hominis is the main colonizer of head, axillae, arms, and legs, and is frequently encountered in nosocomial infections.

Organisms within the genus Microbacterium spp. are yellow-pigmented, aerobic, rod-shaped, Gram-positive bacteria [23] (Fig. 2a). They have been isolated from numerous and variable environments, including soil and water [24], the phyllosphere [25], human patients [26], and a residential toilet [27], and they have been associated with endophthalmitis [28] and catheter infections [29].

Pseudomonas oryzihabitans (Fig. 2d) is a Gram-negative, non-fermenting, yellow-pigmented bacterium [30]. Despite its environmental origin, P. oryzihabitans has been recognized as a potential pathogen in recent years, especially in immunocompromised hosts, both in nosocomial or community-level settings. It can form biofilms in aquifers in association with suspended particulate matter, which can be subsequently entrained into the drinking water distribution systems, posing a potential risk for human health given their resistance to chlorine compared to their planktonic counterparts [13]. This species has been associated with catheter [31] and bloodstream infections, endophthalmitis [32], necrotic enteritis [33], and peritonitis ([34] and references therein). There are two instances in which the source of human infection has been well documented, and the source has been found to be a synthetic sponge, one used by an immunocompromised individual [31] and another in the milk kitchen of a neonatal intensive care unit [33].

Mycobacterium iranicum (Fig. 2b) is a newly described, rapidly growing, orange-pigmented scotochromogenic, non-tuberculous mycobacterial species. Its clinical significance is still under study but it has been associated with patients with pulmonary infections, such as pneumonia, chronic obstructive airway disease, and bronchiectasis [11, 35].

Lastly, Plantibacter (Fig. 2c) are pleomorphic, rod-shaped, yellow-pigmented, aerobic, Gram-positive bacteria that belong to the class of Actinobacteria .

Genome sequencing information

Genome project history

These genomes were generated as part of a project to sequence reference genomes from the built Environment, funded by the Alfred P. Sloan Foundation through their “Microbiology of the Built Environment” Program. Sequencing and assembly of all isolates were performed at the University of California, Davis. The genome sequences were deposited in GenBank and given a Genome On-Line Database identifier [36]. Project information and association with MIGS version 2.0 are presented in Table 2.

Table 2 Project information
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Growth conditions and genomic DNA preparation

Strains were initially collected through environmental sampling (see Classification and features section) and were subsequently deposited into the DMSZ. Glycerol stocks of all isolates were initially grown at 28 °C on LB plates. A single colony was then inoculated in LB and incubated at 28 °C for 18 h (except for M. iranicum strain H39, grown at 37 °C for 5 days). DNA was subsequently extracted from the cultures using the DNeasy Blood and Tissue kit (Qiagen), and the quality was assessed using a NanoDropTM spectrophotometer.

Genome sequencing and assembly

Barcoded Illumina paired-end libraries were generated from all samples using the Nextera XT kit (Illumina). After pooling, the libraries were size-selected for a range of 600–900 bp on a Pippin Prep (Sage Science) and then sequenced on an Illumina MiSeq (Paired End 300 bp). After demultiplexing with a custom script, the reads from each sample were assembled using the A5-miseq pipeline, which automates the process of adapter removal, quality trimming, error-correction, and contig generation [37, 38]. The completeness and contamination of the assemblies was estimated using PhyloSift [22] and CheckM [39]. Across all strains, genome completeness was determined to be a minimum of 98.9%, and the maximum contamination was 0.99% (Additional file 1).

Genome annotation

Isolates were predominantly annotated using the IMG system [40] with no additional manual curation. Table 3 summarizes genome statistics and Table 4 the COG functional categories for the eight isolates according to IMG. Additional annotations were performed with PGAP [41] and RAST [42]. The full-length 16S rRNA gene sequences for each isolate, used for tree building (see above), were extracted from RAST.

Table 3 Genome statistics
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Table 4 Numbers of genes associated with general COG functional categories
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Genome properties

Genome sizes were smallest for the Staphylococcus isolates at approximately 2.5 Mbps and largest for M. iranicum H39 at nearly 6.5 Mbps (Table 3). Similarly, the DNA G + C content was lowest for the Staphylococcus isolates (approximately 31%) and much higher for the other four isolates (at least 65% content). Predicted coding regions accounted for 83–93% of the genomes for all eight isolates, and the total number of predicted genes ranged from 2450 in S. hominis H69 to 6227 in M. iranicum H39. The percentage of genes with a functional prediction was fairly consistent across the genomes, ranging from 75 to 80%. The percentage of RNA genes for the Staphylococcus isolates ranged from 3 to 4% and were higher than the others isolates (1–2%). Conversely, the percentage of genes in internal clusters (an indicator of non-redundant sequences) ranged from 18 to 21% in the Staphylococcus isolates but ranged from 25 to 35% in the other isolates. The genome of P. oryzihabitans H72 encoded a much higher percentage of signal peptides than the other genomes (Tables 3 and 4). Neither pseudogenes nor CRISPR repeats were identified in any of the genomes.

For all strains, 27–37% of the proteins were not predicted to be part of a COG category (Table 4). P. oryzihabitans was the only recognized motile organism (Table 1), and P. oryzihabitans H72 showed a much greater percentage of genes related to motility (Table 4). M. iranicum H39 harbored a much higher percentage of genes for the COG categories of lipid transport/metabolism and secondary metabolites biosynthesis/transport/catabolism than the other isolates. There was no observed relationship between genome coverage (Table 2) and the percentage of unassigned proteins (Table 4).

Insights from the genome sequences

Phylogenetic comparisons

The genomes of the sequenced isolates were compared to publicly available closely related genomes to determine the ANI values [43]. For those six isolates in which a species epithet was given based on gene trees, ANI values were greater than 90% (Additional file 6), and were greater than 96% for the Staphylococcus isolates. The genomes of those isolates that were assigned to genera based on gene trees were compared to closely related publicly available genomes. For Microbacterium sp. H83, the ANI value with M. hydrocarbonoxydans was 84.1% and for Plantibacter sp. H53 was 87.8% with another Plantibacter sp. (Additional file 6).

Virulence and biofilm production

CoNS are opportunistic pathogens and they do not encode for virulence factors (e.g., exotoxins) commonly found in pathogenic species such as S. aureus . However, they do encode genes related to biofilm formation, persistence and immune invasion [44]. The attachment to a surface is the first step to successful colonization and a precursor for the establishment of infection. In the IMG annotation, we found genes with predicted functions to be associated with cell wall-associated FBP, such as fbe, and several other surface-associated proteins such as a bifunctional autolysin and putative adhesins. However, the gene fbe was not found in S. capitis H36, and another gene known to be important for surface adhesion in Staphylococcus, ebh [44], was not observed in any isolate. Both Ebh and FBP act as adhesins but FBP also acts as an invasin, facilitating binding and internalization in host cells [45]. Additionally, we found genes with predicted functions to be associated with Microbial Surface Components Recognizing Adhesive Matrix Molecules, such as the sdrG gene. Further biofilm accumulation is mediated by exopolysaccharides such as PNAG and PGA. Genes related only to PGA (cap operon), which have been shown to provide resistance to phagocytosis and to a host’s antimicrobial peptides in S. epidermidis [46], were identified. Genes encoding predicted pro-inflammatory molecules with cytolytic and antimicrobial properties such as β-type phenol soluble modulins (PSM) [44] were found in all four staphylococci strains, along with genes encoding their accessory regulator B (Agr) [47]. Other systems important for the regulation of virulence in staphylococci that were found in our strains included the staphylococcal accessory regulator Sar, one of the two components of each of the regulatory systems, SaeRS and ArlRS, and an infection-related protease, ClpC [44].

Antibiotic resistance

We used the Resistance Gene Identifier of CARD [48] to explore possible genes related to antimicrobial resistance. Microbial genome sequencing has the potential to be used as a prediction tool of antibiotic resistance in clinical settings [49, 50], and in fact has been shown to be a promising approach in S. aureus [51, 52] as well as other bacteria [53]. However, at the moment, clinical testing of antibiotic resistance is restricted to PCR-based targeting of specific genes [54, 55], and many of the genes in antibiotic databases have not been verified in clinical settings and are subject to errors in annotation (e.g., [56]). Nevertheless, we surveyed genes predicted to confer antibiotic resistance in order to explore commonalities across the different isolates. Additional file 7 details the Gene ID and other information stemming from the IMG annotation of putative antibiotic resistance genes identified in CARD. Limiting the results to “perfect” and “strict” hits, many of these genes included efflux pumps predicted to confer resistance to more than one class of antimicrobials (e.g., fluoroquinolones, tetracyclines, polymyxins) as well as genes predicted to be associated with resistance to specific antimicrobials (e.g., beta-lactams, aminocoumarins, chloramphenicol, aminoglycosides, and fosfomycin). Some antimicrobial genes were common to many strains; others were limited to specific taxonomic groups. For example, all eight strains were found to contain genes predicted to confer resistance to mupirocin and fosfomycin, while genes for fusidic acid resistance were only observed in S. capitis H65 (Additional file 7).

In addition to general targeting of antibiotic resistance genes, we also looked specifically for genes related to triclosan resistance. TCS is a synthetic antimicrobial agent that is commonly used in home and personal care products such as hand soaps, toothpastes, deodorants, body washes, hand creams, body lotions, and cosmetics. It has been directly associated with the development of multidrug antibiotic resistance in a variety of primarily pathogenic bacteria via in vitro assays [57]. TCS induces resistance through mutations in the gene (fabI) that encodes TCS’s target enzyme (enoyl-acyl carrier protein reductase FabI) through overexpression, or through efflux pumps, with the latter only to be associated with multi-antibiotic resistance [57]. The fabI gene was identified only in one out of four staphylococci isolates, S. capitis H65, as well as in the M. iranicum H39 and P. oryzihabitans H72 genomes. We found several genes related to non-specific multidrug efflux pumps, such as mex genes (mexJKL) in their genomes. The MexJK efflux pump can efflux triclosan, but also requires the outer membrane protein channel composed of the OprM in order to efflux other antibiotics in Pseudomonas aeruginosa [58]. MexJK-OprM was found through CARD in all our genomes, except for Plantibacter sp. H53 that did not carry OprM. The triclosan efflux transporter TriABC–OpmH [59] was only partially present in P. oryzihabitans H72 (TriB was absent). Additionally, P. oryzihabitans H72 was the only isolate to contain an efflux pump predicted to offer triclosan resistance (Additional file 7). Susceptibility to TCS or other antibiotics has not been experimentally tested for the strains described here.

Conclusions

The genomes of these eight isolates of bacteria collected from a residential environment will be valuable tools for exploring the basic microbiology of indoor microbes (e.g., overexpression of genes targeted by drugs/antimicrobial agents, such as triclosan, can provide insight into the mode of action of antibiotics and the associated development of resistance) as well as interpreting future metagenomic and transcriptomic datasets. These isolates represent seven species across five genera and likely originate from the dominant sources of indoor bacteria: the outdoor environment, human commensals, and premise plumbing.