Impact of PM10 Pollution on Indoor Bacterial Communities: Correlations Between Bacterial Abundance and Physicochemical Parameters in School Environments

Impact of PM10 Pollution on Indoor Bacterial Communities: Correlations Between Bacterial Abundance and Physicochemical Parameters in School Environments | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of PM 10 Pollution on Indoor Bacterial Communities: Correlations Between Bacterial Abundance and Physicochemical Parameters in School Environments Meher Cheberli, Marwa Jabberi, Jamel Ben Nasr, Habib Chouchane, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7297022/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Indoor air quality (IAQ) is a critical concern in collective childcare establishments, often subjected to regulatory scrutiny worldwide. Objectives: This study aims to assess bacterial diversity and relative abundances of indoor air in early childhood establishments, evaluate the physicochemical quality, and explore correlations within collected data. Materials and Methods: Bacterial species and their abundances were determined via metataxonomic analyses across three early childhood establishments in Korba, Tunisia, during three seasonal periods. In parallel, monitoring of carbon dioxide, indoor (PM 10 ), and outdoor (PM 10ext ) particulate matter, along with comfort parameters, was conducted. Results: Thirty bacterial species were identified (% of classified reads ≥ 1% at the species level), with prevalence of Staphylococcus saprophyticus , Staphylococcus epidermidis , and Pseudomonas stutzeri . Cumulative bacterial abundance and species count correlated significantly with PM 10 and PM 10ext concentrations. Moreover, Staphylococcus haemolyticus relative abundance correlated significantly with temperature. Hygrothermal discomfort and frequent particulate matter exceedances were observed in the establishments. Conclusions: This study underscores the presence of various bacterial species in indoor air environments and reveals correlations with environmental factors like seasonality, particulate matter levels, temperature, and humidity. These insights enhance our understanding of IAQ dynamics in early childhood establishments, guiding interventions for improved air quality and children's well-being. Air pollution Bacteria Child day care centers Environmental monitoring High-throughput nucleotide sequencing Indoor Figures Figure 1 Figure 2 Figure 3 1. Background The atmosphere within buildings comprises a mixture of microbiological, chemical, and physical contaminants sourced from external air, building materials, combustion devices, and human activities. Exposure to these pollutants, particularly chemical and particulate matter, has been linked to heightened risks of allergic and respiratory diseases such as asthma and rhinitis [ 1 ]. Additionally, the presence of pathogens poses significant concerns in indoor environments. Airborne bacteria can exhibit toxicity, allergenicity, and contagiousness. Various bacteria are correlated with a heightened probability of epidemics and may contribute to numerous respiratory and dermatological infections and illnesses [ 2 ]. However, the effects of air pollution depend on several elements: the nature of the pollutants, the dose received, habits, but also the vulnerability of the person. Sensitivity thresholds are not the same for everyone. Children, who are among the most vulnerable populations due to their specific characteristics, notably their immature respiratory system, are particularly exposed and suffer more from the consequences of air pollution. Research has shown that children — inhaling indoor air at a rate of 400 ml/min∙kg per body weight, at rest, have a higher oxygen consumption (more than double (2.76 times)) compared to adults, highlighting their increased susceptibility to problems related to indoor air quality (IAQ) [ 3 , 4 ]. Collective childcare facilities, such as nurseries and daycare centers, warrant special consideration due to the extensive time children spend in these environments compared to other indoor spaces outside the home. Several studies have identified elevated levels of pollutants and pathogens within such childcare centers, establishing a correlation between indoor air pollution and detrimental impacts on children's health [ 5 – 11 ]. Nevertheless, there is a scarcity of studies, particularly those utilizing metataxonomic analyses, that specifically delve into the microbiological aspects of IAQ in childcare environments [ 12 ]. In addition, the control of indoor air microbial communities has emerged as a significant concern during the COVID-19 pandemic. The pathogens (such as Mycobacterium tuberculosis , measles virus, and varicella zoster virus) responsible for several other diseases are known to be transmissible through the airborne route ([ 13 ] and references therein). Assessing IAQ in collective childcare establishments has emerged as a significant global public health concern, leading to the evolution of methodologies, tools, and approaches in this field. However, IAQ remains an aspect often overlooked particularly at the microbiological level using culture-independent methods. This study aims to comprehensively assess the bacterial diversity and relative abundances present in the indoor air of early childhood establishments. Additionally, it seeks to evaluate the physicochemical quality of the indoor environment by monitoring key parameters such as carbon dioxide levels, indoor (PM 10 ), and outdoor (PM 10ext ) particulate matter, along with comfort parameters. Furthermore, the study aims to explore and elucidate correlations between the bacterial communities and the physicochemical data collected, providing insights into the interplay between IAQ and microbial presence in these childcare settings. Through these objectives, the study endeavors to enhance the understanding of IAQ dynamics and inform interventions to improve air quality and promote the well-being of children in early childhood establishments. 2. Materials and methods 2.1. Description of the sites This study was conducted in three childcare facilities — a school daycare (Z1E1) and two kindergartens (Z1E2 and Z1E3), situated in the town of Korba on the northeast coast of Tunisia. A single room was chosen within each of these establishments for the study, which spanned three distinct periods — the summer period (early October 2020), the winter period (end of December 2020), and the spring period (April–May 2021). 2.2. Metataxonomic analyses Air samples intended for microbiological analysis were collected from selected indoor environments using a biocollector (model BK-BAS). The diversity of airborne microorganisms, including potentially pathogenic bacteria, was subsequently characterized using Next-Generation Sequencing (NGS) technology, following previously established protocols [ 14 ]. The raw data underwent analysis using the One Codex data platform due to its various advantages [ 15 – 17 ]. 2.3. Characterization of the IAQ Concurrently with sampling for metataxonomic analyses, environmental comfort parameters —including temperature (TE), relative humidity (RH), and carbon dioxide (CO 2 ) concentration — were monitored during typical classroom activities using an IAQ analyzer (model Q-TRAK 7575). In parallel, concentrations of particulate matter with diameters less than 10 micrometers (PM 10 ) were assessed both indoors and outdoors using an aerosol monitor (DUSTTRAK II model). All measurements were recorded at one-minute intervals. Evaluation of comfort conditions pertaining to air temperature and relative humidity parameters in the various rooms was undertaken as indicated previously [ 14 , 18 ]. 2.4. Correlation analysis and comparisons Correlations between the bacterial community and physicochemical parameters were established utilizing correlograms generated via the FaDA application [ 19 ]. For the CO 2 data acquired, comparisons were made with the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) standard reference value of 1000 ppm [ 20 ]. Relative humidity (RH) and PM 10 data were evaluated against the World Health Organization (WHO) recommended values of 70% for RH and 50 µg/m 3 for PM 10 , respectively [ 21 ]. 3. Results 3.1. Metataxonomic analyses The accession for the Short Read Archive (SRA) data generated in this study is PRJNA1059615. Bacillus and Staphylococcus , each comprising six species, emerged as the most frequently detected bacterial genera throughout the study (Table 1 ). This study reaffirmed the consistently observed high abundance of Firmicutes, as noted in both previous culture-based and culture-independent investigations ([ 12 ] and references therein). In total, 30 species of airborne bacteria were identified from the collected air samples, with detection frequencies ranging from one to six occurrences (Table 1 ). Sixteen distinct bacterial species were detected only once, while fourteen species were observed at least twice. Staphylococcus saprophyticus (six occurrences), Staphylococcus epidermidis (five occurrences), and Pseudomonas stutzeri (four occurrences) were the most frequently detected species. Regarding abundance, Bacillus sp. exhibited the highest abundance rate (11.62%) within a sample collected from Z1E1 during spring. Additionally, in the same room, S. saprophyticus and S. epidermidis were detected together during winter at an abundance rate exceeding 8% (Table 1 ). Table 1 Relative abundances of bacterial species detected in the indoor air across different rooms (Z1E1, Z1E2, and Z1E3) and seasons (Su: summer, Wi: winter, and Sp: spring) with average values of physicochemical parameters. Room Z1E1Su Z1E1Wi Z1E1Sp Z1E2Sp Z1E3Su Z1E3Wi Physicochemical parameters Temperature (T, °C) 27.3 15.9 18.6 17.5 24.9 15.3 Relative Humidity (HR, %) 79.8 68.7 77.2 61.7 48.7 63.2 Carbone dioxide (CO 2 , ppm) 533.1 746.8 834.3 549.2 687.7 811.7 Indoor concentration of PM 10 (PM 10 , µg/m 3 ) 99.8 124.7 98.3 59.4 81 49.5 Outdoor concentration of PM 10 (PM 10ext , µg/m 3 ) 92.7 161.1 66.3 26.9 98.8 41.5 Bacterial community Bacterial Species Frequency % of classified reads ≥ 1% at the species level Staphylococcus saprophyticus 6 1.84 8.07 4.93 1.97 8.33 1.89 Staphylococcus epidermidis 5 - 8.69 2.47 1.69 1.22 1.98 Pseudomonas stutzeri 4 4.83 1.16 3.1 - 1.24 - Bacillus subtilis 3 - - 1.58 2.26 4.01 - Glutamicibacter ardleyensis 3 - 1.82 5.18 - - 3.35 Planococcus rifietoensis 3 - 2.17 - 1.27 - 1.26 Bacillus licheniformis 2 2.12 1.39 - - - - Bacillus firmus 2 - 1.1 2.75 - - - Bacillus sp. 2 - - 11.61 - - 3.82 Micrococcus luteus 2 2.22 - - - 4.46 - Micrococcus sp. 2 1.75 - - - 2.38 - Planococcus citreus 2 - 3.13 - - - 1.33 Psychrobacter faecalis 2 - 1.55 - - - 1.65 Staphylococcus haemolyticus 2 1.58 - - - 1.58 - Acinetobacter radioresistens 1 - 1.1 - - - - Acinetobacter sp. 1 - 1.14 - - - - Bacillus cereus 1 5.83 - - - - - Bacillus infantis 1 - - - 1.11 - - Exiguobacterium acetylicum 1 2.45 - - - - - Exiguobacterium mexicanum 1 - 1.91 - - - - Leclercia adecarboxylata 1 - - - - 1.22 - Paenarthrobacter aurescens 1 2.28 Psychrobacter celer 1 - - - - - 2.18 Serratia marcescens 1 1.24 - - - - - Staphylococcus aureus 1 2.12 - - - - - Staphylococcus equorum 1 - - - - - 1.43 Staphylococcus hominis 1 - - - - 2.93 - Staphylococcus simulans 1 - - 2.76 - - - Vagococcus fluvialis 1 3.08 - - - - - Virgibacillus proomii 1 - 3.53 - - - - Total number of species detected 30 11 13 8 5 10 9 Cumulative abundance of bacterial species (%) 29.06 36.76 34.38 8.3 29.65 18.89 Cumulative abundance of bacteria of the genus Bacillus (%) 7.95 2.49 15.94 3.37 4.01 3.28 Cumulative abundance of bacteria of the genus Staphylococcus (%) 5.52 16.76 10.16 3.66 14.06 5.3 3.2. Comfort parameters, CO 2 concentrations, and PM 10 fine particles It is noteworthy that all RH measurements (data not shown) taken in Z1E1 during the summer and spring exceeded the limit value recommended by the WHO for this parameter (70%). In addition, hygrothermal comfort conditions within the various classrooms exhibited seasonal variability (Fig. 1 ). During the summer and winter seasons, inadequate hygrothermal conditions were prevalent in most instances. In winter, approximately one-fifth of CO 2 measurements in Z1E3 (median 750 ppm, range 628–1333) exhibited values surpassing the ASHRAE limit of 1000 ppm. The highest CO 2 concentrations were documented during spring in room Z1E1 (median 809 ppm, range 630–1060). Conversely, lower concentrations were observed during summer in rooms Z1E2 (median 493 ppm, range 387–1019 ppm) and Z1E1 (median 497.5 ppm, range 422–877 ppm). Almost all PM 10 measurements taken during summer in the three rooms exceeded the limit value recommended by the WHO (50 µg/m 3 ). In Z1E1, all PM 10 measurements exceeded this value during all three seasons (Fig. 2 ). 3.3. Correlations between the bacterial community and physicochemical parameters The generated correlogram illustrates significant correlations between bacterial taxa and physicochemical parameters, in terms of both number and abundance (Fig. 3 ). Notably, the number of identified species (N.spe) at the sampling sites exhibits a robust positive correlation with outdoor PM 10 concentrations, yielding a correlation coefficient of 0.9 ( p = 0.0142). Furthermore, analyses revealed significant correlations between the cumulative abundance of all bacterial species and indoor PM 10 concentrations (r = 0.85, p = 0.0309), as well as between the cumulative abundance of Staphylococcus species and outdoor PM 10 concentration (r = 0.85, p = 0.0313). Some bacterial species exhibited robust positive correlations between their relative abundance and the temperature parameter — S. haemolyticus (r = 0.96, p = 0.0023), Micrococcus sp. (r = 0.91, p = 0.0102), and Micrococcus luteus (r = 0.83, p = 0.0406) (Fig. 3 ). It is important to note that air samples collected during spring contained the lowest numbers of bacterial species, with five species detected in ZIE1 and eight species in Z1E2. Notably, these rooms were within the hygrothermal comfort zone during this season, suggesting that favorable hygrothermal conditions may contribute to reduced bacterial loads (Table 1 , Fig. 1 , and Fig. 3 ). Regarding the CO 2 parameter, only one significant correlation was observed, which was with Glutamicibacter ardleyensis (r = 0.87 ( p = 0.0236)). 4. Discussion The findings of this study highlight the significant impact of particulate matter concentrations and temperature on the bacterial community composition in early childhood establishments, providing crucial insights for improving IAQ and ensuring the health and well-being of children. It is noteworthy that S. saprophyticus and S. epidermidis , the most dominant and abundant in our study, are classified as risk class 2 pathogens, indicating their potential to cause human diseases [ 22 ]. Additionally, as shown in Table 1 , it is noteworthy that five bacterial species, classified as pathogenic to humans [ 22 ], were identified in the air sample collected from Z1E1 during summer — Vagococcus fluvialis (3.08%), Bacillus licheniformis (2.12%), Staphylococcus aureus (2.12%), Staphylococcus haemolyticus (1.58%), and Serratia marcescens (1.24%). One of few previous studies employed culture-independent high-throughput pyrosequencing to examine bacterial and fungal communities in 50 air samples from daycare centers and elementary schools in Seoul, Korea, revealing previously unidentified taxa and showing different dominant species compared to prior culture-dependent studies [ 12 ]. It was shown that among the bacterial genera detected in the indoor air samples, Micrococcus was the most prevalent at 13.2%, with Paracoccus following at 5.2%, then Staphylococcus at 4.6%, and Enhydrobacter at 4.3% [ 12 ]. Also, previous research demonstrated that in classroom air, the most abundant bacterial genera were Enhydrobacter , Streptococcus , and Micrococcus , whereas in outdoor air, Methylobacterium , Pseudomonas , and Deinococcus predominated, with human occupants serving as the primary source for indoor bacteria such as Enhydrobacter , Micrococcus , Staphylococcus , Streptococcus , Neisseria , and Haemophilus , which commonly inhabit the human skin, mucous membranes, and intestines ([ 23 ] and references therein). Only room Z1E3 was situated within a hygrothermal comfort zone during summer, while only Z1E1 met this criterion during winter. Conversely, Z1E2 was situated outside the hygrothermal comfort zone during both summer and winter. However, the spring season was characterized by favorable hygrothermal atmospheres across all examined rooms (Fig. 1 ). In this context, several studies have highlighted that suboptimal hygrothermal conditions elevate the risk of indoor environment contamination by bacteria, viruses, fungi, and mites, thus constituting significant risk factors for respiratory infections, asthma development, and allergies in both adults and children [ 24 – 26 ]. In concordance with our results indicated in Fig. 2 , recent studies have highlighted a concerning trend of PM 10 pollution in classrooms, with published evidence indicating escalating levels [ 27 – 32 ]. A previous study [ 33 ] concluded that particle concentrations tend to be elevated in schools located near industrial complexes and in close proximity to roads with heavy traffic emissions. Therefore, in addition to the typical sources of PM 10 emissions in various facilities, the heightened levels observed, particularly in summer, could be attributed to particle emissions resulting from road traffic (which is notably significant in the area studied during summer) and increased usage of hydro-alcoholic gels and intensified cleaning practices (due to the onset of the COVID-19 pandemic coinciding with the beginning of the study in summer). As shown in Fig. 3 , our findings align with existing literature, underscoring the role of indoor and outdoor particle pollution in fostering the proliferation of bacterial populations within indoor environments [ 34 , 35 ]. Correlation analysis revealed a significant relationship between indoor and outdoor PM 10 concentrations in Z1E1 and Z1E2, with correlation coefficients of 0.78 and 0.67, respectively. This correlation likely indicates a contribution from outdoor pollution to the elevated PM 10 levels observed within these rooms. These findings align with those reported previously [ 29 ] concluding that the rise in PM 10 concentrations within eight naturally ventilated schools in Serbia (among nine schools studied) is notably influenced by increased PM 10 emissions from external sources, with correlation coefficients ranging from 0.45 to 0.95. Moreover, the significance of indoor PM 10 sources varied depending on the room and season. Specifically, the median indoor-to-outdoor (i/o) ratios of PM 10 were lower than or close to 1 in all three rooms during summer and winter. However, in spring, these ratios notably exceeded 1, with values of 1.55 in Z1E1, 2.75 in Z1E2, and 2.03 in Z1E3, indicating a predominance of interior sources in these rooms. This observation is supported by a study conducted in the Czech Republic, which suggested that the presence of children constitutes a primary indoor PM 10 source [ 36 ]. The movement and vigorous activities of children in classrooms could contribute significantly to the resuspension or delayed deposition of PM 10 within these environments. These findings align with those of a study conducted in three French elementary schools, which underscored the influence of children's occupancy on the indoor-to-outdoor PM 10 concentration ratio [ 37 ]. Previously [ 33 ], the findings of several studies assessing PM 10 levels, in both indoor and outdoor air, across schools worldwide were synthesized. Based on these studies, i/o relationships were established in various school settings. European schools predominantly exhibited indoor PM 10 sources (median (range): 1.5 (0.4–5.6)), whereas outdoor air intrusion was identified as the primary PM 10 source in the United States (0.8 (0.5–0.9)). Asian schools demonstrated median i/o ratio values of 1.0 (0.6–2.3), indicating contributions from both domestic and external sources. The authors attributed the wide range of i/o ratios to factors such as occupancy rates, classroom activities, building characteristics, site specificity, ventilation type (natural versus mechanical, duration, and frequency), as well as seasonal weather variations. 5. Conclusion Metataxonomic analyses of samples collected from investigated childcare facilities suggested potential exposure of children to various bacterial species, including pathogens. Furthermore, it has been demonstrated that elevated particle levels both indoors and outdoors are associated with increased numbers and cumulative abundance of bacterial species within these facilities. The findings of this study revealed that children occupying the examined rooms were subjected to elevated levels of PM 10 and to conditions of hygrothermal discomfort. Consequently, mitigating atmospheric particle emissions and enhancing hygrothermal conditions within classrooms could serve as effective strategies for reducing exposure to certain airborne bacterial species. Declarations Acknowledgement This work was performed under the auspices of the Tunisian National Center for Nuclear Sciences and Technology (CNSTN), the Faculty of Sciences of Tunis (FST) and the Higher Institute of Biotechnology of Sidi Thabet (ISBST). It was supported by the Tunisian Ministry of Higher Education and Scientific Research and the Ministry of Health, without this assistance, this study could not have been undertaken. Competing interests The authors declare that they have no competing interests. References Takizawa H (2011) Impact of air pollution on allergic diseases. 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Cherif","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ameur","middleName":"","lastName":"Cherif","suffix":""},{"id":495806390,"identity":"63197bcc-e553-4ed3-a7e6-3af7771c03a3","order_by":5,"name":"Hadda-Imene Ouzari","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hadda-Imene","middleName":"","lastName":"Ouzari","suffix":""},{"id":495806391,"identity":"88cfa945-d272-449d-9e95-9e53556fd782","order_by":6,"name":"Haitham Sghaier","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-8210-5345","institution":"National Center for Nuclear Sciences and Technology (CNSTN), Sidi Thabet Technopark, Ariana 2020, Tunisia","correspondingAuthor":true,"prefix":"","firstName":"Haitham","middleName":"","lastName":"Sghaier","suffix":""}],"badges":[],"createdAt":"2025-08-05 06:35:17","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7297022/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7297022/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88414192,"identity":"3d051baa-4d80-4efd-82e2-0b4c7c4f615b","added_by":"auto","created_at":"2025-08-06 08:45:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":114379,"visible":true,"origin":"","legend":"\u003cp\u003eHygrothermal comfort data of classrooms (Z1E1, Z1E2, and Z1E3) during the summer (Su), winter (Wi), and spring (Sp) periods, with zone limits (comfortable, still comfortable, and not comfortable) based on a previously established hygrothermal comfort diagram [18].\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7297022/v1/76fa2f88e1d7150991419756.png"},{"id":88414190,"identity":"b2e41db9-0b48-4669-a0b6-b823f056c68b","added_by":"auto","created_at":"2025-08-06 08:45:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":41197,"visible":true,"origin":"","legend":"\u003cp\u003eBox plots illustrating the variation in PM\u003csub\u003e10\u003c/sub\u003e concentrations across different rooms (Z1E1, Z1E2, and Z1E3) and seasons (Su: summer, Wi: winter, and Sp: spring).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7297022/v1/10d81409c0cc1b3a8af23efa.png"},{"id":88414193,"identity":"92e730ff-cdf4-48d7-9754-659de8de54a6","added_by":"auto","created_at":"2025-08-06 08:45:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":76307,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelogram illustrating the relative abundances of bacterial species (detected at least twice) in the air of the studied sites alongside the average values of measured physicochemical parameters. Positive correlations are depicted in shades of red, while negative correlations are represented in shades of blue. Parameter legend: Temperature (T.1), relative humidity (RH.2), carbon dioxide (CO2.3), indoor fine particles with an aerodynamic diameter \u0026lt; 10 µm (PM10.4), outdoor fine particles with an aerodynamic diameter \u0026lt; 10 µm (PM10ext.5), number of species (N.spe.6), cumulative abundance of bacterial species (Cu.Ab.7), cumulative abundance of bacteria of the genus \u003cem\u003eBacillus\u003c/em\u003e (Cu.Ba.8), cumulative abundance of bacteria of the genus \u003cem\u003eStaphylococcus\u003c/em\u003e (Cu.St.9), \u003cem\u003ePseudomonas stutzeri\u003c/em\u003e(Psst.10), \u003cem\u003eMicrococcus luteus\u003c/em\u003e (Milu.11), \u003cem\u003eBacillus licheniformis\u003c/em\u003e(Bali.12), \u003cem\u003eStaphylococcus saprophyticus\u003c/em\u003e (Stsa.13), \u003cem\u003eMicrococcus\u003c/em\u003esp. (Misp.14), \u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e (Stha.15), \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e (Step.16), \u003cem\u003ePlanococcus citreus\u003c/em\u003e (Plci.17), \u003cem\u003ePlanococcus rifietoensis\u003c/em\u003e (Plri.18), \u003cem\u003eGlutamicibacter ardleyensis\u003c/em\u003e (Glar.19), \u003cem\u003eBacillus firmus\u003c/em\u003e (Bafi.20), \u003cem\u003eBacillus subtilis\u003c/em\u003e (Basu.21), \u003cem\u003eBacillus\u003c/em\u003e sp. (Basp.22), and \u003cem\u003ePsychrobacter faecalis\u003c/em\u003e (Psyfa.23).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7297022/v1/7cc58922885a7394c70b4909.png"},{"id":88419108,"identity":"44aa8101-a301-42c1-8150-7ad130be149a","added_by":"auto","created_at":"2025-08-06 09:17:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1042885,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7297022/v1/c0415b30-908e-444a-9bef-5349b26c369c.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eImpact of PM\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e Pollution on Indoor Bacterial Communities: Correlations Between Bacterial Abundance and Physicochemical Parameters in School Environments\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Background","content":"\u003cp\u003eThe atmosphere within buildings comprises a mixture of microbiological, chemical, and physical contaminants sourced from external air, building materials, combustion devices, and human activities. Exposure to these pollutants, particularly chemical and particulate matter, has been linked to heightened risks of allergic and respiratory diseases such as asthma and rhinitis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Additionally, the presence of pathogens poses significant concerns in indoor environments. Airborne bacteria can exhibit toxicity, allergenicity, and contagiousness. Various bacteria are correlated with a heightened probability of epidemics and may contribute to numerous respiratory and dermatological infections and illnesses [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, the effects of air pollution depend on several elements: the nature of the pollutants, the dose received, habits, but also the vulnerability of the person. Sensitivity thresholds are not the same for everyone. Children, who are among the most vulnerable populations due to their specific characteristics, notably their immature respiratory system, are particularly exposed and suffer more from the consequences of air pollution. Research has shown that children \u0026mdash; inhaling indoor air at a rate of 400 ml/min∙kg per body weight, at rest, have a higher oxygen consumption (more than double (2.76 times)) compared to adults, highlighting their increased susceptibility to problems related to indoor air quality (IAQ) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCollective childcare facilities, such as nurseries and daycare centers, warrant special consideration due to the extensive time children spend in these environments compared to other indoor spaces outside the home. Several studies have identified elevated levels of pollutants and pathogens within such childcare centers, establishing a correlation between indoor air pollution and detrimental impacts on children's health [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Nevertheless, there is a scarcity of studies, particularly those utilizing metataxonomic analyses, that specifically delve into the microbiological aspects of IAQ in childcare environments [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition, the control of indoor air microbial communities has emerged as a significant concern during the COVID-19 pandemic. The pathogens (such as \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e, measles virus, and varicella zoster virus) responsible for several other diseases are known to be transmissible through the airborne route ([\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and references therein).\u003c/p\u003e\u003cp\u003eAssessing IAQ in collective childcare establishments has emerged as a significant global public health concern, leading to the evolution of methodologies, tools, and approaches in this field. However, IAQ remains an aspect often overlooked particularly at the microbiological level using culture-independent methods.\u003c/p\u003e\u003cp\u003eThis study aims to comprehensively assess the bacterial diversity and relative abundances present in the indoor air of early childhood establishments. Additionally, it seeks to evaluate the physicochemical quality of the indoor environment by monitoring key parameters such as carbon dioxide levels, indoor (PM\u003csub\u003e10\u003c/sub\u003e), and outdoor (PM\u003csub\u003e10ext\u003c/sub\u003e) particulate matter, along with comfort parameters. Furthermore, the study aims to explore and elucidate correlations between the bacterial communities and the physicochemical data collected, providing insights into the interplay between IAQ and microbial presence in these childcare settings. Through these objectives, the study endeavors to enhance the understanding of IAQ dynamics and inform interventions to improve air quality and promote the well-being of children in early childhood establishments.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Description of the sites\u003c/h2\u003e\u003cp\u003eThis study was conducted in three childcare facilities \u0026mdash; a school daycare (Z1E1) and two kindergartens (Z1E2 and Z1E3), situated in the town of Korba on the northeast coast of Tunisia. A single room was chosen within each of these establishments for the study, which spanned three distinct periods \u0026mdash; the summer period (early October 2020), the winter period (end of December 2020), and the spring period (April\u0026ndash;May 2021).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Metataxonomic analyses\u003c/h2\u003e\u003cp\u003eAir samples intended for microbiological analysis were collected from selected indoor environments using a biocollector (model BK-BAS). The diversity of airborne microorganisms, including potentially pathogenic bacteria, was subsequently characterized using Next-Generation Sequencing (NGS) technology, following previously established protocols [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The raw data underwent analysis using the One Codex data platform due to its various advantages [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Characterization of the IAQ\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eConcurrently with sampling for metataxonomic analyses, environmental comfort parameters \u0026mdash;including temperature (TE), relative humidity (RH), and carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) concentration \u0026mdash; were monitored during typical classroom activities using an IAQ analyzer (model Q-TRAK 7575). In parallel, concentrations of particulate matter with diameters less than 10 micrometers (PM\u003csub\u003e10\u003c/sub\u003e) were assessed both indoors and outdoors using an aerosol monitor (DUSTTRAK II model). All measurements were recorded at one-minute intervals. Evaluation of comfort conditions pertaining to air temperature and relative humidity parameters in the various rooms was undertaken as indicated previously [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Correlation analysis and comparisons\u003c/h2\u003e\u003cp\u003eCorrelations between the bacterial community and physicochemical parameters were established utilizing correlograms generated \u003cem\u003evia\u003c/em\u003e the FaDA application [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. For the CO\u003csub\u003e2\u003c/sub\u003e data acquired, comparisons were made with the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) standard reference value of 1000 ppm [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Relative humidity (RH) and PM\u003csub\u003e10\u003c/sub\u003e data were evaluated against the World Health Organization (WHO) recommended values of 70% for RH and 50 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e for PM\u003csub\u003e10\u003c/sub\u003e, respectively [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Metataxonomic analyses\u003c/h2\u003e\u003cp\u003eThe accession for the Short Read Archive (SRA) data generated in this study is PRJNA1059615. \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003eStaphylococcus\u003c/em\u003e, each comprising six species, emerged as the most frequently detected bacterial genera throughout the study (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This study reaffirmed the consistently observed high abundance of Firmicutes, as noted in both previous culture-based and culture-independent investigations ([\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and references therein). In total, 30 species of airborne bacteria were identified from the collected air samples, with detection frequencies ranging from one to six occurrences (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Sixteen distinct bacterial species were detected only once, while fourteen species were observed at least twice. \u003cem\u003eStaphylococcus saprophyticus\u003c/em\u003e (six occurrences), \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e (five occurrences), and \u003cem\u003ePseudomonas stutzeri\u003c/em\u003e (four occurrences) were the most frequently detected species. Regarding abundance, \u003cem\u003eBacillus\u003c/em\u003e sp. exhibited the highest abundance rate (11.62%) within a sample collected from Z1E1 during spring. Additionally, in the same room, \u003cem\u003eS. saprophyticus\u003c/em\u003e and \u003cem\u003eS. epidermidis\u003c/em\u003e were detected together during winter at an abundance rate exceeding 8% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRelative abundances of bacterial species detected in the indoor air across different rooms (Z1E1, Z1E2, and Z1E3) and seasons (Su: summer, Wi: winter, and Sp: spring) with average values of physicochemical parameters.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eRoom\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eZ1E1Su\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eZ1E1Wi\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZ1E1Sp\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eZ1E2Sp\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eZ1E3Su\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eZ1E3Wi\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003ePhysicochemical parameters\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTemperature (T, \u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e15.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eRelative Humidity (HR, %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e77.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e61.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e48.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e63.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCarbone dioxide (CO\u003csub\u003e2\u003c/sub\u003e, ppm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e533.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e746.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e834.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e549.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e687.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e811.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eIndoor concentration of PM\u003csub\u003e10\u003c/sub\u003e (PM\u003csub\u003e10\u003c/sub\u003e, \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e124.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e98.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e59.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e49.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eOutdoor concentration of PM\u003csub\u003e10\u003c/sub\u003e (PM\u003csub\u003e10ext\u003c/sub\u003e, \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e161.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e98.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e41.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eBacterial community\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBacterial Species\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e\u003cp\u003e% of classified reads\u0026thinsp;\u0026ge;\u0026thinsp;1% at the species level\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaphylococcus saprophyticus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePseudomonas stutzeri\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBacillus subtilis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGlutamicibacter ardleyensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePlanococcus rifietoensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBacillus licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBacillus firmus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBacillus\u003c/em\u003e sp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMicrococcus luteus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMicrococcus\u003c/em\u003e sp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePlanococcus citreus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePsychrobacter faecalis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAcinetobacter radioresistens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAcinetobacter\u003c/em\u003e sp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBacillus infantis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eExiguobacterium acetylicum\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eExiguobacterium mexicanum\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLeclercia adecarboxylata\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePaenarthrobacter aurescens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePsychrobacter celer\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSerratia marcescens\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaphylococcus equorum\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaphylococcus hominis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaphylococcus simulans\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eVagococcus fluvialis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eVirgibacillus proomii\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal number of species detected\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCumulative abundance of bacterial species (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e18.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCumulative abundance of bacteria of the genus \u003cem\u003eBacillus\u003c/em\u003e (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCumulative abundance of bacteria of the genus \u003cem\u003eStaphylococcus\u003c/em\u003e (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e14.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Comfort parameters, CO\u003csub\u003e2\u003c/sub\u003e concentrations, and PM\u003csub\u003e10\u003c/sub\u003e fine particles\u003c/h2\u003e\u003cp\u003eIt is noteworthy that all RH measurements (data not shown) taken in Z1E1 during the summer and spring exceeded the limit value recommended by the WHO for this parameter (70%). In addition, hygrothermal comfort conditions within the various classrooms exhibited seasonal variability (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During the summer and winter seasons, inadequate hygrothermal conditions were prevalent in most instances.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn winter, approximately one-fifth of CO\u003csub\u003e2\u003c/sub\u003e measurements in Z1E3 (median 750 ppm, range 628\u0026ndash;1333) exhibited values surpassing the ASHRAE limit of 1000 ppm. The highest CO\u003csub\u003e2\u003c/sub\u003e concentrations were documented during spring in room Z1E1 (median 809 ppm, range 630\u0026ndash;1060). Conversely, lower concentrations were observed during summer in rooms Z1E2 (median 493 ppm, range 387\u0026ndash;1019 ppm) and Z1E1 (median 497.5 ppm, range 422\u0026ndash;877 ppm).\u003c/p\u003e\u003cp\u003eAlmost all PM\u003csub\u003e10\u003c/sub\u003e measurements taken during summer in the three rooms exceeded the limit value recommended by the WHO (50 \u0026micro;g/m\u003csup\u003e3\u003c/sup\u003e). In Z1E1, all PM\u003csub\u003e10\u003c/sub\u003e measurements exceeded this value during all three seasons (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e\u003cem\u003e3.3. Correlations between the bacterial community and physicochemical parameters\u003c/em\u003e\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe generated correlogram illustrates significant correlations between bacterial taxa and physicochemical parameters, in terms of both number and abundance (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Notably, the number of identified species (N.spe) at the sampling sites exhibits a robust positive correlation with outdoor PM\u003csub\u003e10\u003c/sub\u003e concentrations, yielding a correlation coefficient of 0.9 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0142). Furthermore, analyses revealed significant correlations between the cumulative abundance of all bacterial species and indoor PM\u003csub\u003e10\u003c/sub\u003e concentrations (r\u0026thinsp;=\u0026thinsp;0.85, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0309), as well as between the cumulative abundance of \u003cem\u003eStaphylococcus\u003c/em\u003e species and outdoor PM\u003csub\u003e10\u003c/sub\u003e concentration (r\u0026thinsp;=\u0026thinsp;0.85, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0313).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSome bacterial species exhibited robust positive correlations between their relative abundance and the temperature parameter \u0026mdash; \u003cem\u003eS. haemolyticus\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.96, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0023), \u003cem\u003eMicrococcus\u003c/em\u003e sp. (r\u0026thinsp;=\u0026thinsp;0.91, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0102), and \u003cem\u003eMicrococcus luteus\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.83, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0406) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). It is important to note that air samples collected during spring contained the lowest numbers of bacterial species, with five species detected in ZIE1 and eight species in Z1E2. Notably, these rooms were within the hygrothermal comfort zone during this season, suggesting that favorable hygrothermal conditions may contribute to reduced bacterial loads (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Regarding the CO\u003csub\u003e2\u003c/sub\u003e parameter, only one significant correlation was observed, which was with \u003cem\u003eGlutamicibacter ardleyensis\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.87 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0236)).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe findings of this study highlight the significant impact of particulate matter concentrations and temperature on the bacterial community composition in early childhood establishments, providing crucial insights for improving IAQ and ensuring the health and well-being of children. It is noteworthy that \u003cem\u003eS. saprophyticus\u003c/em\u003e and \u003cem\u003eS. epidermidis\u003c/em\u003e, the most dominant and abundant in our study, are classified as risk class 2 pathogens, indicating their potential to cause human diseases [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Additionally, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, it is noteworthy that five bacterial species, classified as pathogenic to humans [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], were identified in the air sample collected from Z1E1 during summer \u0026mdash; \u003cem\u003eVagococcus fluvialis\u003c/em\u003e (3.08%), \u003cem\u003eBacillus licheniformis\u003c/em\u003e (2.12%), \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (2.12%), \u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e (1.58%), and \u003cem\u003eSerratia marcescens\u003c/em\u003e (1.24%). One of few previous studies employed culture-independent high-throughput pyrosequencing to examine bacterial and fungal communities in 50 air samples from daycare centers and elementary schools in Seoul, Korea, revealing previously unidentified taxa and showing different dominant species compared to prior culture-dependent studies [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It was shown that among the bacterial genera detected in the indoor air samples, \u003cem\u003eMicrococcus\u003c/em\u003e was the most prevalent at 13.2%, with \u003cem\u003eParacoccus\u003c/em\u003e following at 5.2%, then \u003cem\u003eStaphylococcus\u003c/em\u003e at 4.6%, and \u003cem\u003eEnhydrobacter\u003c/em\u003e at 4.3% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Also, previous research demonstrated that in classroom air, the most abundant bacterial genera were \u003cem\u003eEnhydrobacter\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, and \u003cem\u003eMicrococcus\u003c/em\u003e, whereas in outdoor air, \u003cem\u003eMethylobacterium\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e, and \u003cem\u003eDeinococcus\u003c/em\u003e predominated, with human occupants serving as the primary source for indoor bacteria such as \u003cem\u003eEnhydrobacter\u003c/em\u003e, \u003cem\u003eMicrococcus\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eNeisseria\u003c/em\u003e, and \u003cem\u003eHaemophilus\u003c/em\u003e, which commonly inhabit the human skin, mucous membranes, and intestines ([\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and references therein).\u003c/p\u003e\u003cp\u003eOnly room Z1E3 was situated within a hygrothermal comfort zone during summer, while only Z1E1 met this criterion during winter. Conversely, Z1E2 was situated outside the hygrothermal comfort zone during both summer and winter. However, the spring season was characterized by favorable hygrothermal atmospheres across all examined rooms (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In this context, several studies have highlighted that suboptimal hygrothermal conditions elevate the risk of indoor environment contamination by bacteria, viruses, fungi, and mites, thus constituting significant risk factors for respiratory infections, asthma development, and allergies in both adults and children [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In concordance with our results indicated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, recent studies have highlighted a concerning trend of PM\u003csub\u003e10\u003c/sub\u003e pollution in classrooms, with published evidence indicating escalating levels [\u003cspan additionalcitationids=\"CR28 CR29 CR30 CR31\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. A previous study [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] concluded that particle concentrations tend to be elevated in schools located near industrial complexes and in close proximity to roads with heavy traffic emissions. Therefore, in addition to the typical sources of PM\u003csub\u003e10\u003c/sub\u003e emissions in various facilities, the heightened levels observed, particularly in summer, could be attributed to particle emissions resulting from road traffic (which is notably significant in the area studied during summer) and increased usage of hydro-alcoholic gels and intensified cleaning practices (due to the onset of the COVID-19 pandemic coinciding with the beginning of the study in summer).\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, our findings align with existing literature, underscoring the role of indoor and outdoor particle pollution in fostering the proliferation of bacterial populations within indoor environments [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Correlation analysis revealed a significant relationship between indoor and outdoor PM\u003csub\u003e10\u003c/sub\u003e concentrations in Z1E1 and Z1E2, with correlation coefficients of 0.78 and 0.67, respectively. This correlation likely indicates a contribution from outdoor pollution to the elevated PM\u003csub\u003e10\u003c/sub\u003e levels observed within these rooms. These findings align with those reported previously [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] concluding that the rise in PM\u003csub\u003e10\u003c/sub\u003e concentrations within eight naturally ventilated schools in Serbia (among nine schools studied) is notably influenced by increased PM\u003csub\u003e10\u003c/sub\u003e emissions from external sources, with correlation coefficients ranging from 0.45 to 0.95.\u003c/p\u003e\u003cp\u003eMoreover, the significance of indoor PM\u003csub\u003e10\u003c/sub\u003e sources varied depending on the room and season. Specifically, the median indoor-to-outdoor (i/o) ratios of PM\u003csub\u003e10\u003c/sub\u003e were lower than or close to 1 in all three rooms during summer and winter. However, in spring, these ratios notably exceeded 1, with values of 1.55 in Z1E1, 2.75 in Z1E2, and 2.03 in Z1E3, indicating a predominance of interior sources in these rooms. This observation is supported by a study conducted in the Czech Republic, which suggested that the presence of children constitutes a primary indoor PM\u003csub\u003e10\u003c/sub\u003e source [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The movement and vigorous activities of children in classrooms could contribute significantly to the resuspension or delayed deposition of PM\u003csub\u003e10\u003c/sub\u003e within these environments. These findings align with those of a study conducted in three French elementary schools, which underscored the influence of children's occupancy on the indoor-to-outdoor PM\u003csub\u003e10\u003c/sub\u003e concentration ratio [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Previously [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], the findings of several studies assessing PM\u003csub\u003e10\u003c/sub\u003e levels, in both indoor and outdoor air, across schools worldwide were synthesized. Based on these studies, i/o relationships were established in various school settings. European schools predominantly exhibited indoor PM\u003csub\u003e10\u003c/sub\u003e sources (median (range): 1.5 (0.4\u0026ndash;5.6)), whereas outdoor air intrusion was identified as the primary PM\u003csub\u003e10\u003c/sub\u003e source in the United States (0.8 (0.5\u0026ndash;0.9)). Asian schools demonstrated median i/o ratio values of 1.0 (0.6\u0026ndash;2.3), indicating contributions from both domestic and external sources. The authors attributed the wide range of i/o ratios to factors such as occupancy rates, classroom activities, building characteristics, site specificity, ventilation type (natural versus mechanical, duration, and frequency), as well as seasonal weather variations.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eMetataxonomic analyses of samples collected from investigated childcare facilities suggested potential exposure of children to various bacterial species, including pathogens. Furthermore, it has been demonstrated that elevated particle levels both indoors and outdoors are associated with increased numbers and cumulative abundance of bacterial species within these facilities. The findings of this study revealed that children occupying the examined rooms were subjected to elevated levels of PM\u003csub\u003e10\u003c/sub\u003e and to conditions of hygrothermal discomfort. Consequently, mitigating atmospheric particle emissions and enhancing hygrothermal conditions within classrooms could serve as effective strategies for reducing exposure to certain airborne bacterial species.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was performed under the auspices of the Tunisian National Center for Nuclear Sciences and Technology (CNSTN), the Faculty of Sciences of Tunis (FST) and the Higher Institute of Biotechnology of Sidi Thabet (ISBST). It was supported by the Tunisian Ministry of Higher Education and Scientific Research and the Ministry of Health, without this assistance, this study could not have been undertaken.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTakizawa H (2011) Impact of air pollution on allergic diseases. Korean J Intern Med 26(3):262\u0026ndash;273\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYoo K, Lee TK, Choi EJ, Yang J, Shukla SK, Hwang SI, Park J (2017) Molecular approaches for the detection and monitoring of microbial communities in bioaerosols: A review. 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Atmos Environ 54:250\u0026ndash;259\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"National Center for Nuclear Sciences and Technology (CNSTN), Sidi Thabet Technopark, Ariana 2020, Tunisia","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Air pollution, Bacteria, Child day care centers, Environmental monitoring, High-throughput nucleotide sequencing, Indoor","lastPublishedDoi":"10.21203/rs.3.rs-7297022/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7297022/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Indoor air quality (IAQ) is a critical concern in collective childcare establishments, often subjected to regulatory scrutiny worldwide.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives:\u003c/strong\u003e This study aims to assess bacterial diversity and relative abundances of indoor air in early childhood establishments, evaluate the physicochemical quality, and explore correlations within collected data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Methods:\u003c/strong\u003e Bacterial species and their abundances were determined \u003cem\u003evia\u003c/em\u003e metataxonomic analyses across three early childhood establishments in Korba, Tunisia, during three seasonal periods. In parallel, monitoring of carbon dioxide, indoor (PM\u003csub\u003e10\u003c/sub\u003e), and outdoor (PM\u003csub\u003e10ext\u003c/sub\u003e) particulate matter, along with comfort parameters, was conducted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Thirty bacterial species were identified (% of classified reads ≥ 1% at the species level), with prevalence of \u003cem\u003eStaphylococcus saprophyticus\u003c/em\u003e, \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e, and \u003cem\u003ePseudomonas stutzeri\u003c/em\u003e. Cumulative bacterial abundance and species count correlated significantly with PM\u003csub\u003e10\u003c/sub\u003e and PM\u003csub\u003e10ext\u003c/sub\u003e concentrations. Moreover, \u003cem\u003eStaphylococcus haemolyticus\u003c/em\u003e relative abundance correlated significantly with temperature. Hygrothermal discomfort and frequent particulate matter exceedances were observed in the establishments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e This study underscores the presence of various bacterial species in indoor air environments and reveals correlations with environmental factors like seasonality, particulate matter levels, temperature, and humidity. These insights enhance our understanding of IAQ dynamics in early childhood establishments, guiding interventions for improved air quality and children's well-being.\u003c/p\u003e","manuscriptTitle":"Impact of PM10 Pollution on Indoor Bacterial Communities: Correlations Between Bacterial Abundance and Physicochemical Parameters in School Environments","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-06 08:45:03","doi":"10.21203/rs.3.rs-7297022/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ab7527ea-f727-4fe4-b878-45598001f62f","owner":[],"postedDate":"August 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-06T08:45:03+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-06 08:45:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7297022","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7297022","identity":"rs-7297022","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}