Utilizing the biosimulator to analyze the environmental microbiome within the intensive care units of a hospital

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Livornese Jr. This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4757213/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Feb, 2025 Read the published version in BioTechniques → Version 1 posted You are reading this latest preprint version Abstract In our previous study, we demonstrated the ability of an engraved Petri dish, referred to as a "biosimulator," to induce adhesion of non-adherent cells and the microbiome. This paper delves into the utilization of this innovative biosimulator to elucidate the microbiome composition within intensive care units (ICUs) in a hospital setting. The biosimulator, containing a nutrient-rich bacterial growth medium, was strategically placed in various locations within ICUs for a 24-hour period, followed by an incubation period of three days under both aerobic and anaerobic conditions to simulate the diverse environmental niches within the ICUs. By employing 16S rRNA profiling, we meticulously sequenced the microbiome present in the ICU samples. Our findings revealed that the microbiome composition within ICUs closely mirrored that of the patients occupying the facility. Furthermore, the microorganisms thriving within the ICU environment exhibited notably closer interrelationships compared to those observed under control conditions. This study underscores the potential of our biosimulator approach as a valuable tool for comprehensively characterizing and understanding the microbiome dynamics within healthcare environments, particularly in high-risk settings such as ICUs. Biosimulator hospital intensive care unit microbiome environmental microbiome healthcare-associated infections. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Nosocomial infections, commonly referred to as healthcare-associated infections (HAI) or hospital acquired infections, are infections acquired within a healthcare facility that are generally not present or in the incubation stage at the time of admission. Typically, these infections emerge after the patient has been hospitalized and become apparent 48 hours or more post-admission to the hospital (Cruz-López et al. 2023 ). Ongoing research has focused on preventing HAIs due to their linked high costs, elevated mortality and morbidity rates, and the emergence of drug-resistant pathogens as causative agents. The U.S. Centers for Disease Control and Prevention (CDC) approximates that 5% of hospital admissions lead to HAIs, resulting in around 722,000 infections and 75,000 deaths annually. This imposes a financial burden of $ 28–33 billion in costs (source: https://epi.dph.ncdhhs.gov/cd/hai/figures.html ). Ignaz Semmelweis is credited with being the first to recognize that healthcare providers could transmit diseases, particularly by elucidating the mode of transmission of puerperal sepsis (Sydnor and Perl, 2011 ). Since his observations in 1847, clinicians have increasingly recognized the significance of hygiene practices in preventing the spread of infections. Numerous studies indicate that simple infection-control measures, such as using an alcohol-based hand rub for hand hygiene, play a crucial role in preventing HAIs. These measures not only contribute to saving lives but also result in a reduction in morbidity and a decrease in healthcare costs (Haque et al., 2018 ). Around 12–17 microorganisms account for 80–87% of HCAIs. These include S. aureus , Enterococcus species, E. coli , coagulase-negative Staphylococci, Candida species, K. pneumoniae and Klebsiella oxytoca , P. aeruginosa , A. baumannii, Enterobacter species, Proteus species, Clostridioides difficile , Bacteroides species, and other pathogens (Haque et al., 2018 ). Clostridioides difficile (formerly Clostridium difficile ) is the predominant cause of healthcare-associated infectious diarrhea, exhibiting a rising incidence and severity in recent years. The primary factor contributing to hospital-acquired cross infections is often traced back to inadequate hand hygiene practices. C. difficile causes infections in both individuals with normal immune function and those who are immunocompromised. Its significance has grown as it emerges as a notable pathogen in community settings. C. difficile is identified as the principal etiological agent of antibiotic-associated pseudomembranous colitis, a clinically defined syndrome linked to recent antibiotic usage. This condition is characterized by the presence of pseudomembranous nodules or plaques in the distal and sigmoid colon and rectum (Ragusa et al. 2018 , Guh and Kutty, 2018). C. difficile 's pathogenicity is chiefly facilitated by two exotoxins: toxin A (TcdA) and toxin B (TcdB). These toxins predominantly interfere with the cytoskeletal structure and tight junctions of target cells, resulting in cell rounding and eventual cell death (Di Bella et al. 2016 ). The spores of C. difficile are known to frequently contaminate the hospital environment. The mode of transmission of C. difficile within the hospital setting remains unclear. While healthcare professionals such as physicians and nurses contribute to spore transportation, the hospital environment itself also plays a significant role in the dissemination of the pathogen. Dubberke et al. (2007) cultured C. difficile from environmental samples inhabited by C. difficile patients and the microorganism was identified in 27% of the cultured samples. Rooms occupied by patients with C. difficile showed a higher likelihood of being culture positive compared to rooms with non- C. difficile patients. Furthermore, C. difficile was absent in samples collected from areas outside of patient rooms. Presently, ultraviolet lights are utilized for room sanitation once a patient with C. difficile vacates the premises (Nagaraja et al., 2015 ; Ethington et al., 2018). However, there are documented concerns about the effectiveness of UV light in eradicating C. difficile within hospital rooms (Attia et al., 2020 ). The current protocols do not permit the sanitation of rooms while a patient with C. difficile is still present within the intensive care unit (ICU). In our recent study, we established that an engraved surface, referred to as a biosimulator, triggered the adhesion of non-adherent cells. Furthermore, the biosimulator demonstrated the ability to stimulate the proliferation of non-culturable microorganisms (Thomas, 2020 ). Drawing from the data, we formulated a hypothesis suggesting the potential use of the biosimulator for identifying microorganisms in hospital ICUs. This paper provides a comprehensive account of the microorganisms collected from ICUs in a biosimulator, subsequently cultured under aerobic and anaerobic conditions, and sequenced for detailed analysis. MATERIALS AND METHODS The biosimulator was fabricated following Thomas ( 2020 ). Briefly, for the biosimulator, nonpyrogenic, noncytotoxic polystyrene BioLite cell culture dishes from Thermo Scientific (NJ, USA) were employed. To promote microbial cell adhesion, the plastic surface was intricately engraved with parallel lines using a sterile sharp blade under aseptic conditions. The engravings had a width ranging from 30 to 50 µm and a depth of 5 µm. The biosimulator was loaded with 15 ml of Luria-Bertani medium (LB medium) and positioned in the corners of ICU rooms in the Lankenau Medical Center or office rooms of Lankenau Institute for Medical Research for a duration of 24 hours. Notably, a portion of the patients housed within the ICUs presented with C. difficile infection. After 24 hours, the samples were transferred to a new biosimulator. Fifty percent of the samples underwent culture in aerobic conditions to assess the presence of aerobic microorganisms, while the remaining half were cultured under anaerobic conditions to evaluate the anaerobic microbial community. The samples were incubated for three days. After three days of culture, the media were pelleted in a centrifuge at 5000×g and the samples subjected to 16S rRNA marker gene sequencing at the Children's Hospital of Philadelphia (CHOP) Microbiome Center for taxonomic identification. Microbial DNA was extracted from samples using the DNeasy PowerSoil Pro Kit (Qiagen, Germany) following the manufacturer’s directions (Thomas et al. 2022, 2023). Following amplification of the V1-V2 region of the 16S rRNA marker gene, amplicon libraries were sequenced on an Illumina MiSeq instrument. Paired-end sequence reads were processed using the QIIME 2 pipeline [PMID 31341288]. Reads were joined and denoised to form Amplicon Sequence Variants (ASVs) using DADA2 [PMID 27214047]. Taxonomic assignments were generated using the q2-feature-classifier plugin [PMID 29773078] with the SILVA reference database [PMID 23193283]. RESULTS Our data demonstrated that the hospital microbiome was less diverse than the microbiome of the office environment (Fig. 1 , 2 ). All hospital samples (12 of 12) exhibited a high relative abundance of Firmicutes under anaerobic conditions (Fig. 1 ). Under aerobic conditions, 9 of 12 hospital samples were dominated by Firmicutes , and the remaining three were dominated by other phyla, namely Bacteroidota , Actinobacteriota , and Proteobacteria . In the office environment, three of five samples showed > 10% relative abundance of Proteobacteria under both aerobic and anaerobic conditions, with Firmicutes accounting for the vast majority of remaining taxa. In the initial analysis, we identified the bacterial families in each sample. The office environment displayed greater bacterial diversity compared to the hospital ICU. Specifically, the office samples exhibited high relative abundance of Comamonadaceae, Staphylococcaceae, Lachnospiraceae, Burkholdariaceae , and Ruminococcaceae . Conversely, the hospital ICU samples had elevated levels of Bacillaceae, Enterococcaceae , and Staphylococcaceae . Predominant aerobic bacterial families in the hospital ICU included Micrococcaceae, Moraxellaceae , and Wecksellaceae . Additionally, Clostridiaceae was a predominant anaerobic bacterial family, particularly associated with patients in those rooms experiencing C. difficile infection (Fig. 2 ). Figure 3 summarizes the relative abundance of bacteria from each environment and treatment at the genus level. In the office environment, Staphylococcus was the predominant bacterial genus in samples cultured under both aerobic and anaerobic conditions. Within the hospital ICU, major aerobic microorganisms included Ralstonia, Staphylococcus, Enterococcus, Bacillus, Chryseobacterium , and Micrococcus . Under anaerobic conditions, we observed Staphylococcus, Enterococcus, Bacillus, Clostridium , and Actinomyces in samples from the ICU. Alpha diversity reflects the diversity of microorganisms within a particular environment, such as bacteria in a specific ecological niche. In this context, it quantifies the number or effective number of bacterial species and provides a measure of the bacterial community’s ability to serve as a reservoir for organisms. A comparison of richness, or the number of unique species in a sample, revealed that microbial samples from the hospital ICU were less diverse than those from the office environment (Fig. 4 A). Shannon diversity, which accounts for species evenness, provides an abundance-weighted diversity measure. In this study, microorganisms from the hospital ICU exhibited a lower Shannon diversity index compared to samples from the office environment (Fig. 4 B). Finally, we applied Faith's Phylogenetic Diversity (Faith’s PD) to measure the extent of evolutionary history within a community. In this investigation, microorganisms from the hospital ICU demonstrated a diminished Faith’s PD in comparison to samples from the office environment (Fig. 4 C). Beta diversity quantifies the dissimilarity between two or more microbial communities and provides a way to assess the differences in microbial composition or diversity across different environments, samples, or conditions. UniFrac represents a β-diversity measure utilizing phylogenetic information for the comparison of environmental samples. When combined with conventional multivariate statistical techniques such as principal coordinates analysis (PCoA), UniFrac helps identify factors that account for variations among microbial communities (Lozupone et al. 2011 ). The PCoA plot showed that microbial samples from the hospital ICU exhibited high dissimilarity to bacterial samples of office environment (Fig. 5 ). Differential abundance analysis (DAA) is pivotal in microbiome research, revealing key microbial entities with precision and robustness. It lays the groundwork for biological validation (Yang and Chen, 2022 ), and goes beyond mere data analysis, enabling deeper insights into disease mechanisms. By pinpointing microbial features correlated with specific variables, DAA advances our understanding of microbial profiles and associated diseases (Yang and Chen, 2023 ). In this study, the most sizable difference in DAA occurred between the microbiota of the office versus hospital ICUs (Fig. 6 ). The data showed increase in abundance of Blautia , Ralstonia , and Faecalibacterium in the office environmental samples. Bacillus , Paenibacillus , Enterococcus , Clostridium , and Micrococcus were increased in ICU samples. DISCUSSION Healthcare-associated infections (HAIs) pose significant concerns for patients, hospital administrators, and policymakers (Upadhyay and Smith, 2023 ). In the United States, around 2 million patients experience HAIs annually, with an estimated 90,000 of them succumbing to these infections. The direct financial impact on hospitals due to HAIs is estimated to range from US $ 28 billion to 45 billion (Stone, 2009 ). Clostridium difficile , a Gram-positive bacterium, is a major contributor to HAIs. Its ability to form resilient spores allows it to survive for extended periods in the environment, posing challenges for infection control. C. difficile thrives in healthcare settings, particularly hospitals and long-term care facilities, where disruptions in gut microorganism balance, often caused by antibiotics, create favorable conditions for its proliferation. This bacterium produces toxins that can lead to infections ranging from mild diarrhea to severe colitis, significantly endangering vulnerable populations such as the elderly and immunocompromised individuals. Preventing and managing C. difficile infections requires a comprehensive approach, including prudent antibiotic use, meticulous infection control practices, and maintaining a hygienic healthcare environment. Hospitals and healthcare facilities employ strategies including hand hygiene protocols, environmental cleaning, and surveillance to reduce C. difficile transmission. Ongoing research is essential for advancing prevention and treatment strategies due to the significant impact of C. difficile on patient health and healthcare systems (Murphy et al. 2020 ). In our investigation, we identified C. difficile within the biosimulator situated in the ICUs of patients afflicted with C. difficile infection. These rooms exhibited a notable presence of C. difficile in comparison to other microorganisms. The study confirmed the abundance of C. difficile in the ICU environments. The transfer of spores to patients via medical personnel is one of the most frequent paths of C. difficile transmission (Lemiech-Mirowska et al. 2023 ). A device that could clean the air of ICU rooms continuously would benefit the patients, and caregivers in ICUs. Our study indicates that ICUs harbor a collection of pathological microflorae, characterized by lower diversity when contrasted with the environmental microbiome found in office settings. Actinomyces was isolated from several ICU rooms; these pathogens most commonly infect areas around the mouth and face. The head and face are the only non-covered area of ICU patients. This study underscores the unique microbial composition within ICUs and highlights the prevalence of Actinomyces in these settings, emphasizing the potential implications for patient health. The confirmation of specific pathogens in ICUs sheds light on the importance of targeted measures to mitigate the risk of infections, particularly in vulnerable areas such as the head and face, which are crucial for patient care but also more susceptible to microbial colonization. Further exploration of the patient microbiome in ICUs is essential for advancing our understanding of HAIs and refining strategies for infection prevention and control. Within hospital ICUs, the presence of bacteria from the Microbacteriaceae family was observed. This family predominantly consists of aerobic Gram-positive bacteria characterized by a high G + C content. Currently, the specific diseases caused by microbes of the Microbacteriaceae family remain unknown, although they are commonly found in the ear and oral cavity, as documented by Frank et al. ( 2021 ). In clinical settings, bacteria belonging to the Micrococcaceae family are frequently encountered. Micrococcal infections tend to manifest in individuals with medical devices, coupled with an underlying health condition. Examples of such infections include Central Line-Associated Bloodstream Infections (CLABSI) in leukemia patients, peritonitis in those undergoing Continuous Ambulatory Peritoneal Dialysis (CAPD), cerebrospinal fluid (CSF) shunt infections, and endocarditis in individuals with prosthetic valves, as highlighted by Toltzis (2018). Our investigations revealed elevated levels of bacteria from the Bacillaceae family within ICUs. Members of Bacillaceae exhibit both aerobic and anaerobic characteristics. Additionally, Enterococcaceae and Staphylococcaceae , known pathogens in individuals with underlying health conditions, were found to be abundant in the ICUs during our studies. This emphasizes the importance of understanding and addressing the microbial composition within ICUs to implement targeted measures for infection prevention and enhance the overall quality of patient care. Contamination of DNA is a pervasive issue across commonly used DNA extraction kits and laboratory reagents, where the types and levels of contaminants can vary significantly not only between different kits but also among batches of the same kit. This variability poses a substantial challenge, particularly in studies involving samples with low microbial biomass, as it can distort research outcomes significantly. This contamination has profound implications for both PCR-based 16S rRNA gene surveys and shotgun metagenomics analyses, as even trace amounts of contaminant DNA can influence results and lead to misleading conclusions. Salter et al. ( 2014 ) extensively documented numerous genera known to potentially contaminate samples, emphasizing the critical need for robust contamination control strategies to ensure the reliability and accuracy of microbiome research findings. Ralstonia from the phylum Proteobacteria and Micrococcus from the phylum Actinobacteria are recognized contaminants in human microbiome studies. However, our own research indicates that these bacteria are not uniformly present across all experimental conditions; instead, their presence seems restricted to specific environments. This suggests that they are autochthonous to those particular locations, rather than introduced contaminants from laboratory procedures. These observations highlight the complexity of microbial ecology and the importance of careful interpretation when assessing microbial community data. Implementing stringent contamination control measures, as advocated by Salter et al. ( 2014 ) remains crucial for maintaining the integrity and validity of microbiome research outcomes. Overall, the biosimulator holds potential as a versatile tool capable of both cultivating and assessing the microbiome within hospital ICUs. By harnessing its capabilities, healthcare professionals could effectively study and manage the microbial communities present in these critical environments. This technology not only allows for the controlled growth of diverse microbial populations but also enables comprehensive analysis to better understand the dynamics and implications of microbiome composition in ICUs. Thus, integrating the biosimulator into ICU settings could significantly enhance our ability to monitor and optimize microbial environments for improved patient care, safety and infection control strategies. Declarations ACKNOWLEDGEMENTS We express our gratitude to the Sharpe Strumia Research Foundation, Wawa Foundation, and Abraham Thomas Foundation for providing support to the project. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. CONFLICT OF INTEREST The authors declare no conflict of interest. AUTHOR CONTRIBUTIONS S.T., K.B., L.L.L. performed the experiments. S.T., K.B., L.L.L. reviewed data and wrote the manuscript. All authors reviewed the manuscript. References Attia F, Whitener C, Mincemoyer S, Houck J, Julian K (2020) The effect of pulsed xenon ultraviolet light disinfection on healthcare-associated Clostridioides difficile rates in a tertiary care hospital. Am J Infect Control 48(9):1116–1118 Cruz-López F, Martínez-Meléndez A, Garza-González E (2023) How Does Hospital Microbiota Contribute to Healthcare-Associated Infections? Microorganisms 11(1):192 Di Bella S, Ascenzi P, Siarakas S, Petrosillo N, di Masi A (2016) Clostridium difficile Toxins A and B: Insights into Pathogenic Properties and Extraintestinal Effects. Toxins (Basel) 8(5):134 Frank DN, Giese APJ, Hafren L, Bootpetch TC, Yarza TKL, Steritz MJ et al (2021) Otitis media susceptibility and shifts in the head and neck microbiome due to SPINK5 variants. J Med Genet 58(7):442–452 Haque M, Sartelli M, McKimm J, Abu Bakar M (2018) Health care-associated infections - an overview. Infect Drug Resist 11:2321–2333 Lemiech-Mirowska E, Michałkiewicz M, Sierocka A, Gaszyńska E, Marczak M (2023) The Hospital Environment as a Potential Source for Clostridioides difficile Transmission Based on Spore Detection Surveys Conducted at Paediatric Oncology and Gastroenterology Units. Int J Environ Res Public Health 20(2):1590 Lozupone C, Lladser ME, Knights D, Stombaugh J, Knight R (2011) UniFrac: an effective distance metric for microbial community comparison. ISME J 5(2):169–172 Murphy P, Kang L, Fleming M, Atkinson C, Pryor R, Cooper K, Godbout E, Stevens MP, Doll M, Bearman G (2020) Effect of ultraviolet-C light disinfection at terminal patient discharge on hospital-acquired infections in bone marrow transplant and oncology units. Am J Infect Control 48(6):705–707 Nagaraja A, Visintainer P, Haas JP, Menz J, Wormser GP, Montecalvo MA (2015) Clostridium difficile infections before and during use of ultraviolet disinfection. Am J Infect Control 43(9):940–945 Ragusa R, Giorgianni G, Lupo L, Sciacca A, Rametta S, La Verde M, Mulè S, Marranzano M (2018) Healthcare-associated Clostridium difficile infection: role of correct hand hygiene in cross-infection control. J Prev Med Hyg 59(2):E145–E152 Salter SJ, Cox MJ, Turek EM et al (2014) Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol 12:87 Stone PW (2009) Economic burden of healthcare-associated infections: an American perspective. Expert Rev Pharmacoecon Outcomes Res 9(5):417–422 Sydnor ER, Perl TM (2011) Hospital epidemiology and infection control in acute-care settings. Clin Microbiol Rev 24(1):141–173 Thomas S (2020) An engraved surface induces weak adherence and high proliferation of nonadherent cells and microorganisms during culture. Biotechniques 69(2):113–125 Toltzis P Coagulase-Negative Staphylococci and Micrococcaceae. In: Principles and Practice of Pediatric Infectious Diseases (Sixth Edition) (: Long SS, Prober CG, Fischer M (2023) and Kimberlin D) Upadhyay S, Smith DG (2023) Healthcare Associated Infections, Nurse Staffing, and Financial Performance. Inquiry. Jan-Dec;60:469580231159315 Yang L, Chen J (2022) A comprehensive evaluation of microbial differential abundance analysis methods: current status and potential solutions. Microbiome 10:130 Yang L, Chen J (2023) Benchmarking differential abundance analysis methods for correlated microbiome sequencing data. Brief Bioinform 24:bbac607 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Published Journal Publication published 25 Feb, 2025 Read the published version in BioTechniques → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4757213","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":328308202,"identity":"d75e7ba4-7f5c-41cf-97bd-86f0aaf50f10","order_by":0,"name":"Sunil Thomas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYDACCSjNxt58gOFhAxE6eGBa+HmOJTAkkqRFckaOAXFa7KWbj2748aeOweBAztcNiTvqGPilj1/Ab4vMsbSbvW2HgVrObruReOYwg2RfTgEBh+WY3eBtOFC/4WAvUEvbAQaDMzwJBLXc/ANy2GGeZ0AtdcRpuc3Dxswg2cbDBtTCDNTCfgC/lhtpabdlgX7h52EzA2o5zCPZw4NXBwP7jORjN98AHcYm//jZjY9tdXL8POwP8OvBsBaIDEjTArKZRFtGwSgYBaNguAMAgRtKaB+WRp8AAAAASUVORK5CYII=","orcid":"","institution":"Lankenau Institute for Medical Research","correspondingAuthor":true,"prefix":"","firstName":"Sunil","middleName":"","lastName":"Thomas","suffix":""},{"id":328308203,"identity":"6995b2be-27a6-486e-8306-782c739e4b2e","order_by":1,"name":"Kyle Bittinger","email":"","orcid":"","institution":"Division of Gastroenterology, Hepatology, and Nutrition, Children's Hospital of Philadelphia","correspondingAuthor":false,"prefix":"","firstName":"Kyle","middleName":"","lastName":"Bittinger","suffix":""},{"id":328308204,"identity":"e365c816-d992-43da-9f2b-a9a272072e1f","order_by":2,"name":"Lawrence L. Livornese Jr.","email":"","orcid":"","institution":"Lankenau Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Lawrence","middleName":"L.","lastName":"Livornese","suffix":"Jr."}],"badges":[],"createdAt":"2024-07-17 15:17:57","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-4757213/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4757213/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1080/07366205.2025.2467550","type":"published","date":"2025-02-26T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60808931,"identity":"6ea3243e-aa71-4a4b-b339-c731474d7567","added_by":"auto","created_at":"2024-07-22 10:38:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53422,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe microbiome of hospital ICU is less diverse than the control office environment.\u003c/strong\u003e Bacteria of phylum Firmicutes is abundant in the aerobic and anaerobic culture of ICU microbiome. The microbiome of ICU collected in a Biosimulator for 24 hours were cultured in aerobic and anaerobic conditions for 3 days before 16S rRNA analysis.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4757213/v1/72713e5ac71b21a28d4d4161.png"},{"id":60808933,"identity":"ea3e2c71-c091-4d3e-8b67-569b18077b7a","added_by":"auto","created_at":"2024-07-22 10:38:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":61304,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe office environment displayed greater bacterial diversity compared to the hospital ICU.\u003c/strong\u003e The microbiome of ICU collected in a Biosimulator for 24 hours were cultured in aerobic and anaerobic conditions for 3 days before 16S rRNA analysis.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4757213/v1/31746f83f2f2e1f2e0b4ad68.png"},{"id":60808936,"identity":"766692e0-595b-4147-8686-060fd3962ada","added_by":"auto","created_at":"2024-07-22 10:38:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56400,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelative abundance of all bacterial species cultured by aerobic and anaerobic methods from samples from ICU and office environments.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4757213/v1/4c994d8935558a6f58aaf068.png"},{"id":60808934,"identity":"cb8e3e3d-c2b8-4343-98f7-3671d6b369a2","added_by":"auto","created_at":"2024-07-22 10:38:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":53346,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlpha diversity of aerobic and anaerobic microorganisms of hospital ICU.\u003c/strong\u003e The microbial alpha diversity of ICU environment is less diverse compared to samples from office environments.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4757213/v1/8686690b5d3e653e645160cb.png"},{"id":60810144,"identity":"5c8dfe15-9155-451a-8cb1-54b984fa2071","added_by":"auto","created_at":"2024-07-22 10:46:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":45891,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBeta diversity of aerobic and anaerobic microorganisms of hospital ICU.\u003c/strong\u003e The PCoA plot showed that microbial samples from the hospital ICU are unrelated to bacterial samples of office environment.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4757213/v1/01e4f616aec5e17cac4d4320.png"},{"id":60808932,"identity":"dcb197c2-1be4-41b4-9711-330ad621780a","added_by":"auto","created_at":"2024-07-22 10:38:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":125065,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential abundance analysis (DAA) of the microorganisms of hospital ICU and office environments.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4757213/v1/cc401c477b16cc30a4ecf432.png"},{"id":81414661,"identity":"84248630-3885-4817-baff-621dd2fcee86","added_by":"auto","created_at":"2025-04-25 22:53:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":980351,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4757213/v1/28350b61-9634-4e7a-8219-75804f49f1d8.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eUtilizing the biosimulator to analyze the environmental microbiome within the intensive care units of a hospital\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eNosocomial infections, commonly referred to as healthcare-associated infections (HAI) or hospital acquired infections, are infections acquired within a healthcare facility that are generally not present or in the incubation stage at the time of admission. Typically, these infections emerge after the patient has been hospitalized and become apparent 48 hours or more post-admission to the hospital (Cruz-L\u0026oacute;pez et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Ongoing research has focused on preventing HAIs due to their linked high costs, elevated mortality and morbidity rates, and the emergence of drug-resistant pathogens as causative agents. The U.S. Centers for Disease Control and Prevention (CDC) approximates that 5% of hospital admissions lead to HAIs, resulting in around 722,000 infections and 75,000 deaths annually. This imposes a financial burden of \u003cspan\u003e$\u003c/span\u003e28\u0026ndash;33\u0026nbsp;billion in costs (source: \u003cspan class=\"ExternalRef\"\u003e \u003cspan class=\"RefSource\"\u003ehttps://epi.dph.ncdhhs.gov/cd/hai/figures.html\u003c/span\u003e \u003cspan address=\"https://epi.dph.ncdhhs.gov/cd/hai/figures.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e \u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIgnaz Semmelweis is credited with being the first to recognize that healthcare providers could transmit diseases, particularly by elucidating the mode of transmission of puerperal sepsis (Sydnor and Perl, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Since his observations in 1847, clinicians have increasingly recognized the significance of hygiene practices in preventing the spread of infections. Numerous studies indicate that simple infection-control measures, such as using an alcohol-based hand rub for hand hygiene, play a crucial role in preventing HAIs. These measures not only contribute to saving lives but also result in a reduction in morbidity and a decrease in healthcare costs (Haque et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAround 12\u0026ndash;17 microorganisms account for 80\u0026ndash;87% of HCAIs. These include \u003cem\u003eS. aureus\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e species, \u003cem\u003eE. coli\u003c/em\u003e, coagulase-negative \u003cem\u003eStaphylococci, Candida\u003c/em\u003e species, \u003cem\u003eK. pneumoniae\u003c/em\u003e and \u003cem\u003eKlebsiella oxytoca\u003c/em\u003e, \u003cem\u003eP. aeruginosa\u003c/em\u003e, \u003cem\u003eA. baumannii, Enterobacter\u003c/em\u003e species, \u003cem\u003eProteus\u003c/em\u003e species, \u003cem\u003eClostridioides difficile\u003c/em\u003e, \u003cem\u003eBacteroides\u003c/em\u003e species, and other pathogens (Haque et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eClostridioides difficile\u003c/em\u003e (formerly \u003cem\u003eClostridium difficile\u003c/em\u003e) is the predominant cause of healthcare-associated infectious diarrhea, exhibiting a rising incidence and severity in recent years. The primary factor contributing to hospital-acquired cross infections is often traced back to inadequate hand hygiene practices. \u003cem\u003eC. difficile\u003c/em\u003e causes infections in both individuals with normal immune function and those who are immunocompromised. Its significance has grown as it emerges as a notable pathogen in community settings. \u003cem\u003eC. difficile\u003c/em\u003e is identified as the principal etiological agent of antibiotic-associated pseudomembranous colitis, a clinically defined syndrome linked to recent antibiotic usage. This condition is characterized by the presence of pseudomembranous nodules or plaques in the distal and sigmoid colon and rectum (Ragusa et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Guh and Kutty, 2018). \u003cem\u003eC. difficile\u003c/em\u003e's pathogenicity is chiefly facilitated by two exotoxins: toxin A (TcdA) and toxin B (TcdB). These toxins predominantly interfere with the cytoskeletal structure and tight junctions of target cells, resulting in cell rounding and eventual cell death (Di Bella et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe spores of \u003cem\u003eC. difficile\u003c/em\u003e are known to frequently contaminate the hospital environment. The mode of transmission of \u003cem\u003eC. difficile\u003c/em\u003e within the hospital setting remains unclear. While healthcare professionals such as physicians and nurses contribute to spore transportation, the hospital environment itself also plays a significant role in the dissemination of the pathogen. Dubberke et al. (2007) cultured \u003cem\u003eC. difficile\u003c/em\u003e from environmental samples inhabited by \u003cem\u003eC. difficile\u003c/em\u003e patients and the microorganism was identified in 27% of the cultured samples. Rooms occupied by patients with \u003cem\u003eC. difficile\u003c/em\u003e showed a higher likelihood of being culture positive compared to rooms with non-\u003cem\u003eC. difficile\u003c/em\u003e patients. Furthermore, \u003cem\u003eC. difficile\u003c/em\u003e was absent in samples collected from areas outside of patient rooms. Presently, ultraviolet lights are utilized for room sanitation once a patient with \u003cem\u003eC. difficile\u003c/em\u003e vacates the premises (Nagaraja et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ethington et al., 2018). However, there are documented concerns about the effectiveness of UV light in eradicating \u003cem\u003eC. difficile\u003c/em\u003e within hospital rooms (Attia et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The current protocols do not permit the sanitation of rooms while a patient with \u003cem\u003eC. difficile\u003c/em\u003e is still present within the intensive care unit (ICU).\u003c/p\u003e \u003cp\u003eIn our recent study, we established that an engraved surface, referred to as a biosimulator, triggered the adhesion of non-adherent cells. Furthermore, the biosimulator demonstrated the ability to stimulate the proliferation of non-culturable microorganisms (Thomas, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Drawing from the data, we formulated a hypothesis suggesting the potential use of the biosimulator for identifying microorganisms in hospital ICUs. This paper provides a comprehensive account of the microorganisms collected from ICUs in a biosimulator, subsequently cultured under aerobic and anaerobic conditions, and sequenced for detailed analysis.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003eThe biosimulator was fabricated following Thomas (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Briefly, for the biosimulator, nonpyrogenic, noncytotoxic polystyrene BioLite cell culture dishes from Thermo Scientific (NJ, USA) were employed. To promote microbial cell adhesion, the plastic surface was intricately engraved with parallel lines using a sterile sharp blade under aseptic conditions. The engravings had a width ranging from 30 to 50 \u0026micro;m and a depth of 5 \u0026micro;m.\u003c/p\u003e \u003cp\u003eThe biosimulator was loaded with 15 ml of Luria-Bertani medium (LB medium) and positioned in the corners of ICU rooms in the Lankenau Medical Center or office rooms of Lankenau Institute for Medical Research for a duration of 24 hours. Notably, a portion of the patients housed within the ICUs presented with \u003cem\u003eC. difficile\u003c/em\u003e infection. After 24 hours, the samples were transferred to a new biosimulator. Fifty percent of the samples underwent culture in aerobic conditions to assess the presence of aerobic microorganisms, while the remaining half were cultured under anaerobic conditions to evaluate the anaerobic microbial community. The samples were incubated for three days.\u003c/p\u003e \u003cp\u003eAfter three days of culture, the media were pelleted in a centrifuge at 5000\u0026times;g and the samples subjected to 16S rRNA marker gene sequencing at the Children's Hospital of Philadelphia (CHOP) Microbiome Center for taxonomic identification. Microbial DNA was extracted from samples using the DNeasy PowerSoil Pro Kit (Qiagen, Germany) following the manufacturer\u0026rsquo;s directions (Thomas et al. 2022, 2023). Following amplification of the V1-V2 region of the 16S rRNA marker gene, amplicon libraries were sequenced on an Illumina MiSeq instrument.\u003c/p\u003e \u003cp\u003ePaired-end sequence reads were processed using the QIIME 2 pipeline [PMID 31341288]. Reads were joined and denoised to form Amplicon Sequence Variants (ASVs) using DADA2 [PMID 27214047]. Taxonomic assignments were generated using the q2-feature-classifier plugin [PMID 29773078] with the SILVA reference database [PMID 23193283].\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOur data demonstrated that the hospital microbiome was less diverse than the microbiome of the office environment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). All hospital samples (12 of 12) exhibited a high relative abundance of \u003cem\u003eFirmicutes\u003c/em\u003e under anaerobic conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Under aerobic conditions, 9 of 12 hospital samples were dominated by \u003cem\u003eFirmicutes\u003c/em\u003e, and the remaining three were dominated by other phyla, namely \u003cem\u003eBacteroidota\u003c/em\u003e, \u003cem\u003eActinobacteriota\u003c/em\u003e, and \u003cem\u003eProteobacteria\u003c/em\u003e. In the office environment, three of five samples showed\u0026thinsp;\u0026gt;\u0026thinsp;10% relative abundance of \u003cem\u003eProteobacteria\u003c/em\u003e under both aerobic and anaerobic conditions, with \u003cem\u003eFirmicutes\u003c/em\u003e accounting for the vast majority of remaining taxa.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the initial analysis, we identified the bacterial families in each sample. The office environment displayed greater bacterial diversity compared to the hospital ICU. Specifically, the office samples exhibited high relative abundance of \u003cem\u003eComamonadaceae, Staphylococcaceae, Lachnospiraceae, Burkholdariaceae\u003c/em\u003e, and \u003cem\u003eRuminococcaceae\u003c/em\u003e. Conversely, the hospital ICU samples had elevated levels of \u003cem\u003eBacillaceae, Enterococcaceae\u003c/em\u003e, and \u003cem\u003eStaphylococcaceae\u003c/em\u003e. Predominant aerobic bacterial families in the hospital ICU included \u003cem\u003eMicrococcaceae, Moraxellaceae\u003c/em\u003e, and \u003cem\u003eWecksellaceae\u003c/em\u003e. Additionally, \u003cem\u003eClostridiaceae\u003c/em\u003e was a predominant anaerobic bacterial family, particularly associated with patients in those rooms experiencing \u003cem\u003eC. difficile\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the relative abundance of bacteria from each environment and treatment at the genus level. In the office environment, \u003cem\u003eStaphylococcus\u003c/em\u003e was the predominant bacterial genus in samples cultured under both aerobic and anaerobic conditions. Within the hospital ICU, major aerobic microorganisms included \u003cem\u003eRalstonia, Staphylococcus, Enterococcus, Bacillus, Chryseobacterium\u003c/em\u003e, and \u003cem\u003eMicrococcus\u003c/em\u003e. Under anaerobic conditions, we observed \u003cem\u003eStaphylococcus, Enterococcus, Bacillus, Clostridium\u003c/em\u003e, and \u003cem\u003eActinomyces\u003c/em\u003e in samples from the ICU.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlpha diversity reflects the diversity of microorganisms within a particular environment, such as bacteria in a specific ecological niche. In this context, it quantifies the number or effective number of bacterial species and provides a measure of the bacterial community\u0026rsquo;s ability to serve as a reservoir for organisms. A comparison of richness, or the number of unique species in a sample, revealed that microbial samples from the hospital ICU were less diverse than those from the office environment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Shannon diversity, which accounts for species evenness, provides an abundance-weighted diversity measure. In this study, microorganisms from the hospital ICU exhibited a lower Shannon diversity index compared to samples from the office environment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Finally, we applied Faith's Phylogenetic Diversity (Faith\u0026rsquo;s PD) to measure the extent of evolutionary history within a community. In this investigation, microorganisms from the hospital ICU demonstrated a diminished Faith\u0026rsquo;s PD in comparison to samples from the office environment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBeta diversity quantifies the dissimilarity between two or more microbial communities and provides a way to assess the differences in microbial composition or diversity across different environments, samples, or conditions. UniFrac represents a β-diversity measure utilizing phylogenetic information for the comparison of environmental samples. When combined with conventional multivariate statistical techniques such as principal coordinates analysis (PCoA), UniFrac helps identify factors that account for variations among microbial communities (Lozupone et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The PCoA plot showed that microbial samples from the hospital ICU exhibited high dissimilarity to bacterial samples of office environment (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDifferential abundance analysis (DAA) is pivotal in microbiome research, revealing key microbial entities with precision and robustness. It lays the groundwork for biological validation (Yang and Chen, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and goes beyond mere data analysis, enabling deeper insights into disease mechanisms. By pinpointing microbial features correlated with specific variables, DAA advances our understanding of microbial profiles and associated diseases (Yang and Chen, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this study, the most sizable difference in DAA occurred between the microbiota of the office versus hospital ICUs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The data showed increase in abundance of \u003cem\u003eBlautia\u003c/em\u003e, \u003cem\u003eRalstonia\u003c/em\u003e, and \u003cem\u003eFaecalibacterium\u003c/em\u003e in the office environmental samples. \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003ePaenibacillus\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eClostridium\u003c/em\u003e, and \u003cem\u003eMicrococcus\u003c/em\u003e were increased in ICU samples.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eHealthcare-associated infections (HAIs) pose significant concerns for patients, hospital administrators, and policymakers (Upadhyay and Smith, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In the United States, around 2\u0026nbsp;million patients experience HAIs annually, with an estimated 90,000 of them succumbing to these infections. The direct financial impact on hospitals due to HAIs is estimated to range from US\u003cspan\u003e$\u003c/span\u003e28\u0026nbsp;billion to 45\u0026nbsp;billion (Stone, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eClostridium difficile\u003c/em\u003e, a Gram-positive bacterium, is a major contributor to HAIs. Its ability to form resilient spores allows it to survive for extended periods in the environment, posing challenges for infection control. \u003cem\u003eC. difficile\u003c/em\u003e thrives in healthcare settings, particularly hospitals and long-term care facilities, where disruptions in gut microorganism balance, often caused by antibiotics, create favorable conditions for its proliferation. This bacterium produces toxins that can lead to infections ranging from mild diarrhea to severe colitis, significantly endangering vulnerable populations such as the elderly and immunocompromised individuals.\u003c/p\u003e \u003cp\u003ePreventing and managing \u003cem\u003eC. difficile\u003c/em\u003e infections requires a comprehensive approach, including prudent antibiotic use, meticulous infection control practices, and maintaining a hygienic healthcare environment. Hospitals and healthcare facilities employ strategies including hand hygiene protocols, environmental cleaning, and surveillance to reduce \u003cem\u003eC. difficile\u003c/em\u003e transmission. Ongoing research is essential for advancing prevention and treatment strategies due to the significant impact of \u003cem\u003eC. difficile\u003c/em\u003e on patient health and healthcare systems (Murphy et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our investigation, we identified \u003cem\u003eC. difficile\u003c/em\u003e within the biosimulator situated in the ICUs of patients afflicted with \u003cem\u003eC. difficile\u003c/em\u003e infection. These rooms exhibited a notable presence of \u003cem\u003eC. difficile\u003c/em\u003e in comparison to other microorganisms. The study confirmed the abundance of \u003cem\u003eC. difficile\u003c/em\u003e in the ICU environments. The transfer of spores to patients via medical personnel is one of the most frequent paths of \u003cem\u003eC. difficile\u003c/em\u003e transmission (Lemiech-Mirowska et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A device that could clean the air of ICU rooms continuously would benefit the patients, and caregivers in ICUs.\u003c/p\u003e \u003cp\u003eOur study indicates that ICUs harbor a collection of pathological microflorae, characterized by lower diversity when contrasted with the environmental microbiome found in office settings. \u003cem\u003eActinomyces\u003c/em\u003e was isolated from several ICU rooms; these pathogens most commonly infect areas around the mouth and face. The head and face are the only non-covered area of ICU patients. This study underscores the unique microbial composition within ICUs and highlights the prevalence of \u003cem\u003eActinomyces\u003c/em\u003e in these settings, emphasizing the potential implications for patient health. The confirmation of specific pathogens in ICUs sheds light on the importance of targeted measures to mitigate the risk of infections, particularly in vulnerable areas such as the head and face, which are crucial for patient care but also more susceptible to microbial colonization. Further exploration of the patient microbiome in ICUs is essential for advancing our understanding of HAIs and refining strategies for infection prevention and control.\u003c/p\u003e \u003cp\u003eWithin hospital ICUs, the presence of bacteria from the \u003cem\u003eMicrobacteriaceae\u003c/em\u003e family was observed. This family predominantly consists of aerobic Gram-positive bacteria characterized by a high G\u0026thinsp;+\u0026thinsp;C content. Currently, the specific diseases caused by microbes of the \u003cem\u003eMicrobacteriaceae\u003c/em\u003e family remain unknown, although they are commonly found in the ear and oral cavity, as documented by Frank et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn clinical settings, bacteria belonging to the \u003cem\u003eMicrococcaceae\u003c/em\u003e family are frequently encountered. Micrococcal infections tend to manifest in individuals with medical devices, coupled with an underlying health condition. Examples of such infections include Central Line-Associated Bloodstream Infections (CLABSI) in leukemia patients, peritonitis in those undergoing Continuous Ambulatory Peritoneal Dialysis (CAPD), cerebrospinal fluid (CSF) shunt infections, and endocarditis in individuals with prosthetic valves, as highlighted by Toltzis (2018).\u003c/p\u003e \u003cp\u003eOur investigations revealed elevated levels of bacteria from the \u003cem\u003eBacillaceae\u003c/em\u003e family within ICUs. Members of \u003cem\u003eBacillaceae\u003c/em\u003e exhibit both aerobic and anaerobic characteristics.\u003c/p\u003e \u003cp\u003eAdditionally, \u003cem\u003eEnterococcaceae\u003c/em\u003e and \u003cem\u003eStaphylococcaceae\u003c/em\u003e, known pathogens in individuals with underlying health conditions, were found to be abundant in the ICUs during our studies. This emphasizes the importance of understanding and addressing the microbial composition within ICUs to implement targeted measures for infection prevention and enhance the overall quality of patient care.\u003c/p\u003e \u003cp\u003eContamination of DNA is a pervasive issue across commonly used DNA extraction kits and laboratory reagents, where the types and levels of contaminants can vary significantly not only between different kits but also among batches of the same kit. This variability poses a substantial challenge, particularly in studies involving samples with low microbial biomass, as it can distort research outcomes significantly. This contamination has profound implications for both PCR-based 16S rRNA gene surveys and shotgun metagenomics analyses, as even trace amounts of contaminant DNA can influence results and lead to misleading conclusions. Salter et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) extensively documented numerous genera known to potentially contaminate samples, emphasizing the critical need for robust contamination control strategies to ensure the reliability and accuracy of microbiome research findings.\u003c/p\u003e \u003cp\u003eRalstonia from the phylum Proteobacteria and Micrococcus from the phylum Actinobacteria are recognized contaminants in human microbiome studies. However, our own research indicates that these bacteria are not uniformly present across all experimental conditions; instead, their presence seems restricted to specific environments. This suggests that they are autochthonous to those particular locations, rather than introduced contaminants from laboratory procedures. These observations highlight the complexity of microbial ecology and the importance of careful interpretation when assessing microbial community data. Implementing stringent contamination control measures, as advocated by Salter et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) remains crucial for maintaining the integrity and validity of microbiome research outcomes.\u003c/p\u003e \u003cp\u003eOverall, the biosimulator holds potential as a versatile tool capable of both cultivating and assessing the microbiome within hospital ICUs. By harnessing its capabilities, healthcare professionals could effectively study and manage the microbial communities present in these critical environments. This technology not only allows for the controlled growth of diverse microbial populations but also enables comprehensive analysis to better understand the dynamics and implications of microbiome composition in ICUs. Thus, integrating the biosimulator into ICU settings could significantly enhance our ability to monitor and optimize microbial environments for improved patient care, safety and infection control strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express our gratitude to the Sharpe Strumia Research Foundation, Wawa Foundation, and Abraham Thomas Foundation for providing support to the project. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\u003cp\u003e \u003ch2\u003eCONFLICT OF INTEREST\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAUTHOR CONTRIBUTIONS\u003c/h2\u003e \u003cp\u003eS.T., K.B., L.L.L. performed the experiments. S.T., K.B., L.L.L. reviewed data and wrote the manuscript. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAttia F, Whitener C, Mincemoyer S, Houck J, Julian K (2020) The effect of pulsed xenon ultraviolet light disinfection on healthcare-associated Clostridioides difficile rates in a tertiary care hospital. Am J Infect Control 48(9):1116\u0026ndash;1118\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCruz-L\u0026oacute;pez F, Mart\u0026iacute;nez-Mel\u0026eacute;ndez A, Garza-Gonz\u0026aacute;lez E (2023) How Does Hospital Microbiota Contribute to Healthcare-Associated Infections? Microorganisms 11(1):192\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDi Bella S, Ascenzi P, Siarakas S, Petrosillo N, di Masi A (2016) Clostridium difficile Toxins A and B: Insights into Pathogenic Properties and Extraintestinal Effects. 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Microbiome 10:130\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang L, Chen J (2023) Benchmarking differential abundance analysis methods for correlated microbiome sequencing data. Brief Bioinform 24:bbac607\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"Lankenau Institute for Medical Research","isAcceptedByJournal":true,"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":"Biosimulator, hospital, intensive care unit, microbiome, environmental microbiome, healthcare-associated infections.","lastPublishedDoi":"10.21203/rs.3.rs-4757213/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4757213/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn our previous study, we demonstrated the ability of an engraved Petri dish, referred to as a \"biosimulator,\" to induce adhesion of non-adherent cells and the microbiome. This paper delves into the utilization of this innovative biosimulator to elucidate the microbiome composition within intensive care units (ICUs) in a hospital setting. The biosimulator, containing a nutrient-rich bacterial growth medium, was strategically placed in various locations within ICUs for a 24-hour period, followed by an incubation period of three days under both aerobic and anaerobic conditions to simulate the diverse environmental niches within the ICUs. By employing 16S rRNA profiling, we meticulously sequenced the microbiome present in the ICU samples. Our findings revealed that the microbiome composition within ICUs closely mirrored that of the patients occupying the facility. Furthermore, the microorganisms thriving within the ICU environment exhibited notably closer interrelationships compared to those observed under control conditions. This study underscores the potential of our biosimulator approach as a valuable tool for comprehensively characterizing and understanding the microbiome dynamics within healthcare environments, particularly in high-risk settings such as ICUs.\u003c/p\u003e","manuscriptTitle":"Utilizing the biosimulator to analyze the environmental microbiome within the intensive care units of a hospital","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-22 10:38:43","doi":"10.21203/rs.3.rs-4757213/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":"953b616b-97af-40d3-a438-77d44f078757","owner":[],"postedDate":"July 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-25T22:53:25+00:00","versionOfRecord":{"articleIdentity":"rs-4757213","link":"https://doi.org/10.1080/07366205.2025.2467550","journal":{"identity":"biotechniques","isVorOnly":true,"title":"BioTechniques"},"publishedOn":"2025-02-26 00:00:00","publishedOnDateReadable":"February 26th, 2025"},"versionCreatedAt":"2024-07-22 10:38:43","video":"","vorDoi":"10.1080/07366205.2025.2467550","vorDoiUrl":"https://doi.org/10.1080/07366205.2025.2467550","workflowStages":[]},"version":"v1","identity":"rs-4757213","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4757213","identity":"rs-4757213","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}