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. 2024 Oct 23;16(5):e70006. doi: 10.1111/1758-2229.70006

Viability discrimination of bacterial microbiomes in home kitchen dish sponges using propidium monoazide treatment

Christina K Carstens 1, Joelle K Salazar 2, Shreela Sharma 3, Wenyaw Chan 3, Charles Darkoh 1,4,✉
PMCID: PMC11497490  PMID: 39440931

Abstract

Dish sponges are known to support the proliferation of human bacterial pathogens, yet they are commonly used by consumers. Exposure to foodborne pathogens via sponge use may lead to illness, a serious concern among susceptible populations. The extent of exposure risks from sponge use has been limited by constraints associated with culture‐independent or dependent methods for bacterial community characterization. Therefore, five used dish sponges were characterized to evaluate the presence of viable bacterial foodborne pathogens using the novel application of propidium monoazide (PMA) treatment and targeted 16S rRNA gene amplicon sequencing. Select pathogen viability was confirmed using targeted selective enrichment. The taxonomic abundance profiles of total and viable sponge microbiomes did not vary significantly. The numbers of unique bacterial species (p = 0.0465) and foodborne pathogens (p = 0.0102) identified were significantly lower in viable sponge microbiomes. Twenty unique bacterial foodborne pathogens were detected across total and viable sponge microbiomes, and three to six viable foodborne pathogens were identified in each sponge. Escherichia coli and Staphylococcus aureus were identified in each viable sponge microbiome, and viable E. coli were recovered from two sponges via targeted selective enrichment. These findings suggest that sponge‐associated bacterial communities are primarily viable and contain multiple viable bacterial foodborne pathogens.

Since dish sponges can serve as reservoirs for foodborne pathogens, this study evaluated the bacterial microbiomes of five kitchen dish sponges from different households. Propidium monoazide treatment was used to differentiate between viable and non‐viable bacteria, including pathogens. The taxonomic abundance profiles of total and viable sponge microbiomes did not vary significantly. However, the numbers of unique bacterial species and foodborne pathogens were markedly lower in viable sponge microbiomes.

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INTRODUCTION

The majority of foodborne illnesses in the United States are home‐associated and sporadic (Medeiros et al., 2001). Although most cases are self‐limiting, severe outcomes are primarily caused by bacteria, including Escherichia coli O157:H7, Salmonella enterica and Listeria monocytogenes (Scallan et al., 2011). Evidence indicates that low‐income and racial‐ethnic minority populations in the United States experience disproportionately higher rates of foodborne illnesses (Quinlan, 2013). Studies also suggest that children from low‐income families are at the greatest risk for numerous foodborne infections compared to those of higher‐income (Bemis et al., 2014; Libby et al., 2020; Whitney et al., 2015), which increases concern for foodborne pathogen presence, survival and growth on home surfaces.

Bacteria are transported into the home via various routes and concentrate at the highest levels within kitchens (Flores et al., 2013). Bacterial contamination within kitchens can lead to cross‐contamination of food, which is a leading cause of foodborne disease outbreaks (Evans et al., 1998). The dominating bacterial presence in domestic kitchens is partially driven by the number of bacteria present on dish sponges, which harbour the highest coliform levels of home kitchen contamination sites (Borrusso & Quinlan, 2017). Dish sponges can support bacterial survival and growth and transfer bacteria to other surfaces (Kusumaningrum et al., 2003), they are considered bacterial reservoir disseminators. Bacterial pathogens, including Salmonella species, are commonly detected in used dish sponges (Borrusso & Quinlan, 2017; Erdoğrul & Erbilir, 2005) and have been observed to survive within them for up to 10 days. Despite this, one European study found that over 70% of consumers do not change their dish sponges until after 3 days of use or more (Møretrø et al., 2021). Further, over 50% of consumers also use their dish sponges to clean the kitchen countertop, which may contribute to cross‐contamination. Among a predominantly low‐income population of parents in Texas, 71% of respondents also reported using a reusable cleaning tool (i.e., dish sponges and cloths) to clean the kitchen counter after food preparation (Carstens et al., 2022a).

Sponge storage and treatment conditions by consumers play a critical role in bacterial survival and growth. Evidence indicates that dry storage of dish sponges may reduce the risk of cross‐contamination as low sponge moisture levels have been linked to decreased bacterial survival over time (Møretrø et al., 2021). Treatment of sponges such as microwaving or dishwashing has been observed to significantly reduce the number of aerobic bacteria present (Sharma et al., 2009), and microwaving has also been observed to reduce bacterial community diversity (Jacksch et al., 2020). However, other research has found that regular sponge sanitization has no significant effect on the number of bacteria present (Cardinale et al., 2017), and sponge cleaning methods have been reported as more effective when conducted in the laboratory than in the home environment (Erdoğrul & Erbilir, 2005). Consumer efforts to sanitize dish sponges may be inhibited by the high levels of organic matter and food residues that build up after frequent and extended use. Sponge sanitization has also been linked to significant differences in microbial community composition (Jacksch et al., 2020) and an increase in the presence of bacteria linked to the production of an unpleasant odour (Cardinale et al., 2017). Sponge treatment with a 4000 ppm hypochlorite solution overnight (16–20 h) has been demonstrated to reduce total bacteria and Salmonella spp. levels and prevent bacterial regrowth (Møretrø et al., 2021). Consumer attempts to sanitize dish sponges may contribute to the proliferation of bacteria that are resistant to sanitization, including those with malodorous or pathogenic properties, depending on the cleaning method used.

Although consumer use of dish sponges can lead to bacterial reservoir generation and cross‐contamination, the full scope of foodborne pathogen exposure risk from sponges is not understood. For example, studies that have relied on culture‐based methods to detect pathogens within sponges have been limited by the choice of specific pathogen targets and their culturability. Further, studies that evaluated sponge microbial communities via culture‐independent methods (i.e., genetic sequencing) (Cardinale et al., 2017; Flores et al., 2013; Jacksch et al., 2020) have been unable to determine the risk of pathogen exposure as species level identifications were not obtained and microbial community viability was not assessed, despite the availability of chemical‐based viability discrimination methods.

As metataxonomic sequencing is unable to indicate if sequenced DNA originated from live or dead bacteria, viability discrimination is a process by which DNA from solely intact, viable bacterial cells is isolated prior to downstream genetic sequencing. Several studies of the microbial communities present within the indoor built environment, such as cleanrooms and public transit systems (Wang et al., 2021; Weinmaier et al., 2015), have utilized propidium monoazide (PMA) to differentiate between DNA from viable and non‐viable cells (relic DNA). PMA is a DNA‐binding dye that can penetrate compromised cell membranes but is excluded from viable Gram‐positive and Gram‐negative cells (Nocker et al., 2007). During the ideal reaction mechanism, PMA covalently binds to available relic DNA upon photoactivation, renders it insoluble and allows for selective downstream gene amplification and targeted 16S rRNA gene sequencing of DNA from exclusively viable cells. Although the use of PMA for viability discrimination has limitations, including insufficient PMA inactivation of relic DNA (Zeng et al., 2016), the method is well documented in the literature (Agusti et al., 2010; Josefsen et al., 2010; Li et al., 2015; Li & Chen, 2013; Nocker et al., 2007; Weinmaier et al., 2015).

Viability discrimination via PMA treatment paired with subsequent targeted 16S rRNA gene sequencing is a novel approach to evaluate dish sponge bacterial communities and detect viable bacterial foodborne pathogens. This study aimed to examine the total and viable bacterial microbiomes of dish sponges to assess viable foodborne pathogen presence. The goals of this research were to (1) estimate the taxonomic diversity and distribution of the total and viable dish sponge bacterial communities and (2) differentiate viable and non‐viable foodborne pathogens present on the dish sponges via culture‐independent and culture‐dependent methods.

EXPERIMENTAL PROCEDURES

Sponge acquisition, processing and biomass quantification

Sponge sample collection and processing were conducted as described previously (Carstens et al., 2022b) from the homes of predominantly low‐income families with at least one child enrolled in a Houston Independent School District (Houston, TX, USA) elementary school. In brief, parents were recruited via the distribution of flyers in partnership with the nonprofit nutrition intervention Brighter Bites, which operates in schools where at least 75% of the students are receiving free or reduced‐price lunch (Sharma et al., 2016). Sponge samples were placed into sterile bags containing 50 mL 1× phosphate‐buffered saline (PBS) and massaged by hand for 1 min. Sponge sample aliquots of 1 mL were supplemented with glycerol at 20% and stored at −20°C until further processing. Of the 10 original sponge samples collected, a random sub‐sample of five sponges representing five households was examined in this study. Sample collection was approved by the University of Texas Health Science Center Committee for the Protection of Human Subjects (reference number: HSC‐SPH‐20‐1155; approval date: 18 November 2020), and written consent was obtained from each parent from which a sponge was collected.

For biomass quantification, bacterial genomic DNA was extracted from each of the five sponges using the DNeasy Blood & Tissue Kit (Qiagen Inc., Germantown, MA). Extracted DNA was quantified using the Qubit dsDNA HS Assay Kit (Invitrogen, Carlsbad, CA). DNA extraction and quantification were performed according to the manufacturer's instructions with a 100‐μL starting volume. A negative control consisting of 1× PBS was subjected to all DNA extraction steps to ensure microbial cross‐contamination due to the DNA extraction kit components or buffers did not occur. All genomic DNA was stored at −20°C until further analysis. The estimation of the total number of 16S rRNA gene copies present in each sample was conducted via qPCR targeting the 16S rRNA gene and performed on a 7500 Fast Real‐Time PCR system (Applied Biosystems, Foster City, CA). Reactions were conducted in triplicate using PowerUp SYBR Green Master Mix (Thermo Fisher Scientific, Inc, Waltham, MA) with 0.5 μL of 10 μM forward primer 26F2a, 0.5 μL of 10 μM reverse primer 534R2 (Salazar et al., 2018) and 4 μL DNA template in a total volume of 10 μL. Cycling conditions were 50°C for 2 min, 95°C for 2 min, 40 cycles of 95°C for 15 s, 56°C for 30 s and then 72°C for 2 min. A negative control that consisted of all reagents aside from the DNA template was included in each run.

To generate the standard curve, DNA was extracted from E. coli K12 (ATCC 25253), quantified, serially diluted 1:10 and enumerated via plate count assay. Escherichia coli strain K12 was obtained from the US Food and Drug Administration (FDA) strain stock inventory (Bedford Park, IL) and working stocks were maintained on tryptic soy agar (TSA; BD Difco, Franklin Lakes, NJ). Cultures were grown in tryptic soy broth (TSB; BD Difco) incubated at 37°C for 16–18 h. Results were expressed as log CFU/sponge.

Sponge treatment

Viability discrimination was conducted on each of the five sponge samples via PMA (Biotium, Inc., Fremont, CA) treatment as previously described (Nocker et al., 2007; Wang et al., 2021), with modifications. Briefly, PMA reactions were performed for each sponge in the replicate and consisted of 50 μM PMA with a light exposure time of 3 min (n = 10). Reaction tubes were covered with aluminium foil and incubated at ambient temperature for 5 min with inversion at 1 min increments. Samples were then transferred to the reaction surface, which consisted of aluminium foil placed over ice. Light exposure treatment was conducted using a 600 W halogen lamp located at least 20 cm away from the reaction tubes. The reaction surface was shaken at 30 s increments during light exposure to ensure reaction homogeneity. After treatment, samples were placed on ice for 5 min. The temperature of the reaction surface was tracked using a digital temperature probe (Fisherbrand, Waltham, MA). PMA addition and reactions were conducted in a dark room. Replicate PMA‐free samples for each sponge also underwent PMA reaction conditions (n = 10). Once the reaction was complete, DNA from each of the PMA‐free and PMA‐treated sponge samples (n = 20) was extracted and quantified.

Amplification of 16S rRNA genes, library construction and sequencing

DNA extracted from each sponge sample (n = 20) was used as template DNA for amplification of bacterial 16S rRNA genes. Primer pairs to target the V1–V3 region were randomly distributed equally among the DNA samples as described in Salazar et al. (2018). A negative control that consisted of all reagents aside from the DNA template was included in each run. PCR products were visualized via agarose gel electrophoresis, quantified and purified using AMPure XP beads (Beckman‐Coulter, Indianapolis, IN) according to the manufacturer's instructions. The Nextera XT Kit (Illumina, San Diego, CA) was used to index the 16S rRNA gene PCR products as previously described (Salazar et al., 2018). Indexed PCR products were normalized to 2 nM, pooled, and diluted to 12 pM. The library was spiked with 10% of 12.5 pM PhiX and sequenced using 150 cycles of MiSeq version 3 chemistry (Illumina).

Targeted enrichment and colony identification

Any samples for which E. coli or Salmonella spp. were identified via 16S rRNA gene sequencing were enriched according to the US FDA Bacteriological Analytical Manual (FDA, 2017) modified with a sample volume of 100 μL in each primary enrichment. Presumptive colonies of E. coli or Salmonella were streaked onto TSA and verified via 16S rRNA gene sequencing as previously described using colony PCR to amplify the 16S rRNA gene fragment.

Data analysis

To compute the biomass of PMA‐free bacterial communities for each sponge, the linear regression line equation obtained from the comparison of C t values to log colony‐forming units (CFU) associated with the E. coli culture was used. Biomass values were reported as log CFU/sponge. Analysis of the 16S rRNA gene sequencing of sponge samples was conducted as previously described (Salazar et al., 2018). Briefly, raw, paired‐end reads were merged, and then filtered based on quality (Q30, 99.9% accuracy) and length (minimum 300 base pairs). Sequences were aligned to the Ribosomal Database Project (RDP) (Cole et al., 2014) and the National Center for Biotechnology Information (NCBI) 16S databases (O'Leary et al., 2016) and taxonomically classified at the species level using Kraken2 (Wood et al., 2019). Bracken (Lu et al., 2017) was used to estimate the relative abundance of each bacterial taxa. A filter of 0.05% relative abundance was used to exclude sequencing artefacts and singletons. Any bacterium known to cause foodborne illness (FDA, 2012) was considered a potential bacterial foodborne pathogen. As identified E. coli species were of unknown serotype, E. coli species were included as possible foodborne pathogens when identified. Relative abundance values were averaged across replicate samples to summarize the number of unique bacterial species and bacterial foodborne pathogens identified among sponge microbiomes according to PMA treatment. The median numbers of unique bacterial species and bacterial foodborne pathogens identified within PMA‐free and PMA‐treated sponge samples were statistically compared via the Mann–Whitney U test. Averaged relative abundance values for each taxon were also used to compute changes in relative abundance between PMA‐free and PMA‐treated bacterial communities for each sponge.

The ‘vegan’ package for R (Oksanen et al., 2013) was used to calculate alpha and beta diversity parameters for each replicate sponge sample. Observed OTU counts, the Chao 1 index, Shannon's diversity index, Simpson's index and Simpson's reciprocal index were computed to examine sample alpha diversity and summarized across replicates with averages and standard deviations. The beta diversity of sponge microbiomes was visually compared with non‐metric multidimensional scaling (NMDS) using Bray–Curtis dissimilarity. A permutational multivariate analysis of variance (PERMANOVA) test was used to evaluate beta diversity across PMA‐free and PMA‐treated sponge samples using the ‘vegan’ package. A p‐value of <0.05 was considered statistically significant for all statistical tests. Data analysis was conducted using the R language (RCoreTeam, 2017) (version 3.6.3, R Foundation for Statistical Computing, Vienna, Austria) and RStudio software (RStudioTeam, 2020) (version 4.1.2; RStudio, Inc., Boston, MA). Data were also visualized using Tableau software (version 2020.2.4, Tableau Software, Inc., Seattle, WA).

RESULTS

The biomass of the total bacterial community within each sponge was estimated using qPCR targeting the 16S rRNA gene and comparison with a standard curve (Figure S1). Sponge biomass levels ranged from 0.25 to 5.18 log CFU/sponge. The biomass level for one sponge was low (0.25 log CFU/sponge), while the biomass for the remaining four sponges was at least 1.73 log CFU/sponge higher (1.98–5.18 log CFU/sponge). When dish sponges were collected from each household, observations were made regarding the state of each sponge. Notably, high‐biomass sponges were visibly wet when collected, whereas the low‐biomass sponge was dry.

Sponge microbial diversity

A total of five dish sponge bacterial communities were subjected to viability discrimination via PMA treatment. Alpha diversity parameters were computed for total (PMA‐free) and viable (PMA‐treated) sponge bacterial communities (Table S1). The alpha diversity of sponge microbiomes, as measured by the average Shannon's diversity index across replicates, ranged from 1.29 to 2.36 for total sponge microbiomes and 1.24 to 2.99 for viable sponge microbiomes. The average number of operational taxonomic units (OTU) observed ranged from 16.0 to 29.0 for total sponge microbiomes and 8.0 to 37.0 for viable sponge microbiomes. Differences between total and viable bacterial communities were evaluated via NMDS using Bray–Curtis dissimilarity (Figure 1). However, the taxonomic composition of sponge microbiomes was not observed to vary significantly according to PMA treatment.

FIGURE 1.

FIGURE 1

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The taxonomic abundance profiles of sponge bacterial communities did not vary significantly according to treatment. Non‐metric multidimensional scaling (NMDS) of Bray–Curtis dissimilarity for sponge bacterial communities according to propidium monoazide (PMA) treatment. Beta diversity computations were conducted for replicate sponge samples using the relative abundances for each taxon.

Sponge microbiome response to PMA treatment

The relative abundances of bacterial species identified in total and viable sponge microbiomes were averaged across replicate samples and compared according to PMA treatment. A total of 142 unique bacterial species were identified among total sponge microbiomes, and the number of species per total sponge bacterial community ranged from 34 to 49 (median: 44.0). Of the 142 unique species identified, 103 only appeared in one out of the five total sponge microbiomes evaluated. The most common species identified were E. coli and Klebsiella pneumoniae (five out of five sponges each). Among viable sponge microbiomes, a total of 97 bacterial species were identified and the number of species ranged from 11 to 40 (median: 28.0). Escherichia coli and Staphylococcus aureus were the most common species identified among viable sponge bacterial communities (five out of five sponges each). Most species identified among viable sponge microbiomes also only appeared once across the five communities evaluated (74 species). A significantly higher number of unique bacterial species was identified among total sponge microbiomes (median: 44.0 species) compared to viable sponge microbiomes (median: 28.0 species; p = 0.0465).

Dominant species in each sponge microbiome were evaluated according to their mean relative abundance across replicate samples and PMA treatment status. Among total sponge bacterial communities, K. pneumoniae was the dominant species in two out of the five sponges evaluated, with mean relative abundances of 29.6% (sponge 4) and 39.7% (sponge 5). Each of the five total sponge microbiomes contained K. pneumoniae with a mean relative abundance ≥13%. The dominant species in the remaining three total sponge bacterial communities, according to the highest mean relative abundance, were Brucella suis (sponge 1; 17.2%), Acinetobacter baumannii (sponge 2; 61.3%) and Methylobacterium sp. 17Sr1‐28 (sponge 3; 50.1%). In viable sponge microbiomes, K. pneumoniae was also the dominant species in two instances, with mean relative abundances of 29.1% (sponge 3) and 46.5% (sponge 4); however, it was only present in three of the five communities after PMA treatment. Streptomyces sp. ICC4 (sponge 1; 15.8%), Acinetobacter baumannii (sponge 2; 53.6%) and Ralstonia pickettii (sponge 5; 32.3%) were the dominant species in the remaining three viable sponge microbiomes according to mean relative abundance levels.

The species with the top 10 largest absolute changes in relative abundance between total and viable sponge microbiomes were examined to assess the species that were most affected by PMA treatment (Figure 2). Among species with the top 10 largest absolute changes across sponges, a total of 20 unique species decreased in relative abundance after PMA treatment, while 17 increased in relative abundance. K. pneumoniae (three sponges) was the most common species to decrease in relative abundance after PMA treatment, while S. aureus (five sponges) and Streptomyces sp. ICC4 (three sponges) most frequently increased in relative abundance. The relative abundance of E. coli increased in three sponge bacterial communities after PMA treatment and decreased in two communities.

FIGURE 2.

FIGURE 2

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Species with the largest absolute changes in relative abundance across sponge samples after PMA treatment. Taxa with the top ten largest changes in relative abundance between propidium monoazide (PMA) free and PMA‐treated sponge samples for sponge 1 (A), sponge 2 (B), sponge 3 (C), sponge 4 (D), and sponge 5 (E). Changes in relative abundance between PMA‐free and PMA‐treated samples were computed using the averaged relative abundances of each taxon across replicate samples.

Species with <1.0% changes in relative abundance after PMA treatment were identified. The majority of these species were present in small initial relative quantities within the total sponge bacterial communities. A total of 124 unique species were identified with at least one instance of a < 1.0% change in relative abundance across the five sponge microbiomes evaluated. The number of unique species per sponge with small changes in relative abundance after PMA treatment ranged from 26 to 36 (median: 35.0). Species that frequently experienced these small changes in relative abundance included Alkalitalea saponilacus, Betaproteobacteria bacterium GR16‐43, Draconibacterium orientale, Pasteurella multocida, Raoultella ornithinolytica and Thermoanaerobacterium thermosaccharolyticum (three sponges each, respectively). The most common bacterial foodborne pathogens with small changes in relative abundance included Bacillus thuringiensis (three sponges), Enterobacter cloacae (three sponges), Bacillus sp. FJAT‐45348 (two sponges), Providencia alcalifaciens (two sponges) and Streptococcus pneumoniae (two sponges).

Species identified in the PMA‐free sponge bacterial communities but not in the respective PMA‐treated bacterial communities were examined to ascertain species that were not likely viable in the total sponge microbiome. Across the five sponges evaluated, a total of 136 unique species were identified in a total sponge microbiome and not in the respective viable sponge microbiome in at least one instance. The number of species identified in the total community that were not identified in the respective viable community per sponge ranged from 19 to 40 (median: 38.0). The most common species that were identified as likely non‐viable in sponge microbiomes via PMA treatment included R. ornithinolytica (four sponges), Betaproteobacteria bacterium GR16‐43 (three sponges) and Nitrospirillum amazonense (three sponges). Bacillus thuringiensis (three sponges) was the most frequently identified bacterial foodborne pathogen in total sponge microbiomes, which was subsequently not identified in viable sponge microbiomes.

Potential foodborne pathogen presence and response to PMA treatment

A total of 20 unique bacterial foodborne pathogens were identified across the five sponge bacterial communities, regardless of PMA treatment. Among total sponge microbiomes, 19 unique foodborne pathogens were identified and ranged from 7 to 13 per sponge (median: 8.0). Klebsiella pneumoniae was the dominant foodborne pathogen in four total sponge bacterial communities (sponges 2–5) with relative abundance >16%, while B. suis was the dominant foodborne pathogen in the total microbiome of sponge 1. A total of eight unique bacterial foodborne pathogens were identified among viable sponge microbiomes; at least three were identified within each dish sponge evaluated, with a maximum of six (median: 5.0). The dominant foodborne pathogens identified among viable sponge microbiomes according to mean relative abundance included S. aureus in sponges 1 and 2 (11.7% and 13.9%, respectively), K. pneumoniae in sponges 3 and 4 (29.1% and 46.5%, respectively) and E. coli in sponge 5 (28.7%). The number of unique foodborne pathogens identified per sponge was significantly higher among total sponge microbiomes (median: 8.0 species) than viable sponge microbiomes (median: 5.0 species; p = 0.0102).

The most common foodborne pathogens identified among total sponge bacterial communities included E. coli (five sponges), K. pneumoniae (five sponges), E. cloacae (four sponges), P. alcalifaciens (four sponges) and S. aureus (four sponges). Nine unique foodborne pathogens were only identified in one out of the five total sponge microbiomes evaluated. E. coli (five sponges), S. aureus (five sponges), E. cloacae (three sponges), K. pneumoniae (three sponges) and P. alcalifaciens (three sponges) were the most common foodborne pathogens identified among viable sponge bacterial communities. Streptococcus pyogenes was only identified in one of the five viable sponge microbiomes evaluated (sponge 4). Viable E. coli was identified in all five sponge bacterial communities and was recovered via targeted selective enrichment from sponges 1 and 5. Salmonella enterica was identified in the viable bacterial communities for sponges 1 and 2 via PMA‐based viability discrimination with relative abundance <3.0% but was not recovered via targeted selective enrichment.

Changes in relative abundance for the 20 identified foodborne pathogens within sponge bacterial communities after PMA treatment are displayed in Figure 3. Across the five sponge microbiomes, a total of 18 unique foodborne pathogens decreased in relative abundance after PMA treatment in at least one instance, while eight unique foodborne pathogens increased in relative abundance in at least one instance. The foodborne pathogens that most frequently decreased in relative abundance were B. thuringiensis and K. pneumoniae (three sponges, respectively). Conversely, S. aureus (five sponges), E. cloacae (three sponges), E. coli (three sponges) and P. alcalifaciens (three sponges) most frequently increased in relative abundance after PMA treatment.

FIGURE 3.

FIGURE 3

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Dish sponges contained multiple viable bacterial foodborne pathogens. Changes in relative abundance for identified bacterial foodborne pathogen species between propidium monoazide (PMA) free and PMA‐treated sponge samples. Numerical labels on the x‐axis correspond to sponge identifiers (1–5) and PMA treatment status (PMA‐free or PMA‐treated). Grey tiles indicate the respective pathogen was not identified in either the PMA‐free or PMA‐treated sample for the corresponding sponge. Changes in relative abundance between PMA‐free and PMA‐treated samples were computed using the averaged relative abundances of each taxon across replicate samples.

DISCUSSION

The total and viable bacterial communities of five dish sponges were evaluated using 16S rRNA gene sequencing paired with viability discrimination via PMA treatment and targeted selective enrichment. The dish sponges evaluated in this study were a subset of environmental samples collected from the households of 10 predominantly low‐income families as reported elsewhere (Carstens et al., 2022b). Although past studies have used culture‐dependent or independent methods to examine the bacteria present in dish sponges, this is the first study to evaluate dish sponge microbiomes using PMA‐based viability discrimination and targeted selective enrichment. The approach used in this study for viability discrimination via PMA treatment avoided traditional limitations associated with culture‐based methods, including bacterial target selection and culturability. In addition, advancements in 16S rRNA gene databases enabled the identification of dish sponge microbiomes to the species level.

A wide range of biomass levels were observed across the five sponges evaluated in this study. The estimated number of bacterial cells per sponge ranged from 0.25 to 5.18 log CFU/sponge, although four of the five sponges had ≥1.98 log CFU/sponge. As research has determined the influence of material type (e.g., rayon, cellular foam) on the uptake and release of bacteria (Warnke et al., 2014), it should be noted that the biomass results obtained in this study were dependent on the buffer and homogenization method used and were likely to vary according to sponge material type. Studies that have used culture‐based methods to enumerate bacteria in dish sponges obtained from domestic environments have found average quantities of ~6–7 log CFU/sponge (Josephson et al., 1997; Marshall et al., 2012). Heterotrophic bacteria counts from kitchen sponges have been also observed to range from ~2 to 8 log CFU/sponge (Josephson et al., 1997), similar to the range observed in the present study. The variation in sponge biomass levels observed in the present study may be due to various factors, such as the frequency and duration of sponge use, sponge cleaning treatments or the sponge material and resulting uptake/release of bacteria during homogenization, as previously mentioned. Consumers have reported microwave heating and rinsing with hot water and soap to clean sponges (Cardinale et al., 2017); however, this study did not capture information on cleaning procedures or sponge use history. Variations in sponge size or material may also have affected sponge biomass levels detected, as sponge characteristics were not standard across households. As sponges were collected after consumer use, original details that may have been obtained from packaging, such as original dimensions and sponge material, were not available. Although specific characteristics, treatments and usage details for sponges were not obtained, observations of sponge moisture levels were made during sponge collection. Notably, the one sponge that appeared dry when collected contained the lowest biomass level identified, but moisture levels were not measured directly. Previous research on artificially contaminated dish sponges with various water absorption properties indicated that the survival of Salmonella spp. over time was greater in sponges with slower drying times (Møretrø et al., 2021). Dry storage of dish sponges may reduce bacterial loads; however, the addition of water and potential nutrients at the point of reuse may lead to rapid sponge recolonization by surviving bacteria.

The alpha diversity for total sponge microbiomes according to the mean Shannon's diversity index ranged from 1.29 to 2.36 and mean observed OTU counts ranged from 16.0 to 29.0 per sponge. Other studies that used culture‐independent methods to examine used dish sponges acquired from residential homes found a higher range of observed OTUs (Jacksch et al., 2020) and a wider range of Shannon diversity index values (0.93–5.07) (Cardinale et al., 2017) than those observed in the present study. Aside from differences in methodology (shotgun sequencing and 454‐pyrosequencing of 16S rRNA gene, respectively) and the level of taxonomic classification obtained (genus level), this variation may be attributable to the lower number of sponges evaluated in this study, which may have limited the range of sponge microbiome diversity observed. Regarding sponge beta diversity, the taxonomic abundance profiles of total and viable sponge microbiomes examined in this study were not observed to vary significantly. However, the median numbers of unique bacterial species and bacterial foodborne pathogens identified within viable sponge microbiomes were significantly lower than those observed in total sponge microbiomes. Although the numbers of species varied, only 10 species across all five sponges examined experienced at least one change in relative abundance ≥15% after PMA treatment. This lack of variation in bacterial community composition may indicate that total and viable sponge microbiomes have similar taxonomic abundance profiles. Cellular features observed via fluorescence in situ hybridization analysis have demonstrated that most bacterial cells present in used dish sponges are in an active state of growth (Cardinale et al., 2017). As dish sponges can provide conditions necessary for bacterial survival and proliferation, including moisture and nutrients, a high degree of bacterial viability within dish sponges is likely.

Common species identified across all total sponge microbiomes included E. coli and K. pneumoniae. Two previous studies of the microbiomes of domestically used dish sponges conducted in Germany did not find that members of the Enterobacteriaceae family were dominant in dish sponge bacterial communities. Specifically, the most frequently identified genera in one study were Acinetobacter, Enhydrobacter, Agrobacterium, Pseudomonas and Chryseobacterium, while in the other, Acinetobacter, Moraxella and Chryseobacterium were most frequently observed (Cardinale et al., 2017). A study of kitchen surface microbiomes in the United States (Boulder, Colorado) similarly found that members of the family Moraxellaceae (40.4%) were dominant in the one sponge evaluated (Flores et al., 2013). However, the US study also found that the bacterial family with the second‐highest relative abundance in the sponge microbiome was Enterobacteriaceae (16.8%). Several factors may contribute to the differences in the composition of dish sponge bacterial communities observed in this study. Food and water are two major sources of bacteria in kitchen microbiomes (Flores et al., 2013). Therefore, variations in food preferences and water supplies across geographic locations could contribute to the observed differences in taxonomic abundance. Other external factors such as human residents or hygiene behaviours, and internal factors such as sponge size and material, may also contribute to these differences.

Bacterial genera that include foodborne pathogens identified among total sponge microbiomes in the present study have also been observed in other studies with low relative abundance (≤2%), including Brucella, Citrobacter, Enterobacter, Escherichia, Klebsiella, Salmonella, Staphylococcus and Streptococcus (Cardinale et al., 2017; Jacksch et al., 2020). In the present study, Brucella suis, E. coli, Klebsiella aerogenes, K. pneumoniae, S. enterica and S. aureus were identified among total sponge microbiomes with at least one instance of a relative abundance >2%. Among viable sponge microbiomes, E. cloacae, E. coli, K. pneumoniae, Providencia alcalifaciens, S. enterica and S. aureus were identified with at least one instance of a relative abundance >2%. Metataxonomic sequencing of dish sponges artificially inoculated with a food soil suspension (i.e., 0.1% poultry soil, 0.1% egg‐based soil, 1% lettuce soil) and kitchen‐isolated bacteria (including Staphylococcus, Salmonella and Campylobacter species) demonstrated that pathogens remained minority contributors to sponge bacterial communities over 7 days of storage at room temperature (Møretrø et al., 2021). Although foodborne pathogens have been observed as minor components of both naturally occurring and artificially inoculated dish sponge communities, the same pattern was not observed in this study. The food safety habits of dish sponge users may play a role in sponge contamination levels as a lack of serious concern for food contamination with germs among consumers has been linked to an increased variety of foodborne pathogens within home kitchens (Carstens et al., 2022b). Competition dynamics of bacterial communities, as well as varying bacterial sources, initial loads, nutrient availability and storage conditions, may also have led to the more dominant contributions of foodborne pathogens in the total and viable microbiomes observed in this study.

Viability discrimination using PMA treatment revealed that each dish sponge evaluated contained at least three unique bacterial foodborne pathogens. Viable foodborne pathogens identified in this study, including E. cloacae (ALwakeel, 2007), E. coli (Adiga et al., 2012; Borrusso & Quinlan, 2017; Erdoğrul & Erbilir, 2005; Josephson et al., 1997), Klebsiella spp. (Adiga et al., 2012; ALwakeel, 2007), Salmonella spp. (Erdoğrul & Erbilir, 2005) and Staphylococcus spp. (ALwakeel, 2007; Borrusso & Quinlan, 2017; Josephson et al., 1997) have also been recovered from used dish sponges via culture‐based methods. Salmonella spp. have even been observed to proliferate during the first day after artificial inoculation onto dish sponges stored at room temperature (Møretrø et al., 2021). Although viable E. coli (five sponges) and S. enterica (two sponges) were identified using PMA‐based viability discrimination, only E. coli was recovered from two sponges via targeted selective enrichment. The traditional limitations of culture‐based methods, such as the inability to detect microorganisms that are viable but not culturable, under environmental stress or out‐competed in the bacterial community, may have inhibited the recovery of these bacterial targets.

In this study, dish sponges were observed to harbour viable bacterial foodborne pathogens and therefore the use of sponges may present a direct exposure risk to these pathogens. Dish sponges are commonly used for cleaning purposes aside from washing dishes (Møretrø et al., 2021). Contamination of dish sponges and cloths with S. aureus is also significantly associated with the same type of contamination on kitchen counters, sinks, refrigerator shelves and refrigerator handles within the same kitchen (Borrusso & Quinlan, 2017). Consequently, contaminated dish sponges may also serve as vehicles for cross‐contamination of food and other kitchen surfaces. Consumers should be educated on the risks of bacterial foodborne pathogen exposure and the potential for cross‐contamination linked to dish sponge use. Elimination of sponges used for dishwashing and cleaning would prevent the associated risks of direct pathogen exposure and cross‐contamination; however, this prevention measure may not be economically feasible for low‐income communities. Handwashing before and after handling sponges may reduce the risks of direct pathogen exposure. Frequent dish sponge replacement may also mitigate these risks. A limitation of this study is the small number of sponges that were evaluated, which may have constrained the levels of sponge microbiome diversity and the number of bacterial foodborne pathogen species observed. Future research could evaluate the effects of sponge treatments, such as microwaving and bleach application, to inform recommendations for consumers on safe sponge handling practices. Future research could also further examine the total and viable microbiomes of kitchen surfaces from a diverse range of households to improve the understanding of indoor surface microbiomes, in addition to the risks of viable pathogen exposure and cross‐contamination.

AUTHOR CONTRIBUTIONS

Christina K. Carstens: Conceptualization; investigation; writing – original draft; methodology; visualization; formal analysis; data curation; project administration. Joelle K. Salazar: Conceptualization; investigation; funding acquisition; methodology; formal analysis; supervision; writing – review and editing. Shreela Sharma: Conceptualization; supervision; writing – review and editing. Wenyaw Chan: Conceptualization; writing – review and editing; formal analysis; supervision. Charles Darkoh: Supervision; writing – review and editing; formal analysis; conceptualization.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

ETHICS STATEMENT

Sample collection was approved by the University of Texas Health Science Center Committee For the Protection of Human Subjects (reference number: HSC‐SPH‐20‐1155).

Supporting information

Figure S1. The biomass of bacterial communities within each sponge ranged from 0.25 to 5.18 log CFU/sponge. Sponge bacterial community biomass was assessed via qPCR targeting the 16S rRNA gene to estimate the total number of 16S rRNA gene copies present for each sponge. The standard curve was generated from a 1:10 serially diluted Escherichia coli K12 culture. Open, black circles represent the enumerated E. coli culture, and the dashed line represents the standard curve. Points of various shapes and colours represent each sponge's estimated biomass level in log colony‐forming units (CFU) per sponge.

Table S1. Unique taxa identified and alpha diversity parameters of sponge bacterial communities according to propidium monoazide (PMA) treatment.

EMI4-16-e70006-s001.docx (93.6KB, docx)

ACKNOWLEDGEMENTS

The authors would like to thank Brighter Bites staff members and volunteers for their generous assistance. The authors are also grateful to Behzad Imanian and Deena Awad (Institute for Food Safety and Health, Bedford Park, IL), as well as Diana Stewart (U.S. FDA) for their gracious support during this study. The authors acknowledge funding from NIH/NIAID grants R01AI116914 and R01AI150685.

Carstens, C.K. , Salazar, J.K. , Sharma, S. , Chan, W. & Darkoh, C. (2024) Viability discrimination of bacterial microbiomes in home kitchen dish sponges using propidium monoazide treatment. Environmental Microbiology Reports, 16(5), e70006. Available from: 10.1111/1758-2229.70006

DATA AVAILABILITY STATEMENT

The sequence files and metadata generated in this study have been deposited to NCBI under BioProject PRJNA83087, BioSamples SAMN28037372‐SAMN28037381.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1. The biomass of bacterial communities within each sponge ranged from 0.25 to 5.18 log CFU/sponge. Sponge bacterial community biomass was assessed via qPCR targeting the 16S rRNA gene to estimate the total number of 16S rRNA gene copies present for each sponge. The standard curve was generated from a 1:10 serially diluted Escherichia coli K12 culture. Open, black circles represent the enumerated E. coli culture, and the dashed line represents the standard curve. Points of various shapes and colours represent each sponge's estimated biomass level in log colony‐forming units (CFU) per sponge.

Table S1. Unique taxa identified and alpha diversity parameters of sponge bacterial communities according to propidium monoazide (PMA) treatment.

EMI4-16-e70006-s001.docx (93.6KB, docx)

Data Availability Statement

The sequence files and metadata generated in this study have been deposited to NCBI under BioProject PRJNA83087, BioSamples SAMN28037372‐SAMN28037381.

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