Surface microbial dynamics and residual diversity in patient rooms with wooden and painted walls

Surface microbial dynamics and residual diversity in patient rooms with wooden and painted walls | 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 Article Surface microbial dynamics and residual diversity in patient rooms with wooden and painted walls Anastasiia Postovoitova, Kateryna Davydenko, Larysa Kucher, Olov Karlsson, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9114856/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Wood is a biobased material that supports long-term carbon storage; however, its suitability for use in healthcare facility interiors remains insufficiently studied. This study assessed surface microbial dynamics and residual diversity in patient rooms with conventional painted wall materials and with designer wooden wall panels. Surface microbial dynamics were evaluated using adenosine triphosphate (ATP) measurements and the swab method with colony-forming unit (CFU) counting. Bacterial and fungal cultures from each patient room were analysed by Sanger sequencing. No significant differences in ATP levels or microbial quantities were observed between rooms. In addition, no correlation was observed between ATP levels and CFU counts within each patient room due to methodological differences. In total, 37 microbial species (24 bacterial and 13 fungal) from 23 genera belonging to risk groups 1 and 2 were identified. Significant differences in microbial biodiversity were observed among the patient rooms studied. Fewer unique taxa were detected in the room with wooden walls. This study confirms that wood, as a decorative indoor material, does not negatively affect surface microbial dynamics or lead to excessive microbial spread or biodiversity. These findings support the feasibility of using wood as a finishing material in hospital facilities. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Microbiology Hospital hygiene Wall material Microbial dynamics ATP measurement Microbial biodiversity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Hospitals are complex public health institutions that must meet numerous standards and requirements to provide high-quality treatment, surgery, and patient care. In addition to high-quality medical services, good interior design of hospital facilities is also one of the factors that positively affect the well-being of patients, their family members, and medical staff. Improving the visual appearance of healthcare settings and rooms through the use of new materials, surface finishes, interior elements, and artwork enhances well-being and mental health outcomes, provides distraction, and evokes positive emotions [ 1 – 3 ]. Together, these factors contribute to more positive hospital experience. Today, a pressing issue is the selection of building and interior materials based on their environmental impact [ 4 ]. The use of biobased materials in the construction industry provides carbon sequestration and long-term storage and makes a significant contribution to the modern global bioeconomy [ 5 ]. Wood, as an organic and renewable material, has significant advantages over plastic, glass, concrete, and steel, which require substantial energy for production. These advantages include wood’s favourable environmental profileand its absence of environmental disturbances, pollution, or hazards to human health [ 6 ]. It has also been found that using wood in buildings reduces embodied energy by 43% and carbon emissions by 68% compared to using concrete [ 4 ]. Despite these benefits and widespread use of wood in furniture and panel manufacturing, its use in healthcare facility interiors remains limited due to concerns related to hygiene, durability, and safety. Hospitals, like any indoor environment, host complex microbiomes influenced by many factors, including construction materials and interior design [ 7 ]. Wood is a hygroscopic, porous material, and its use in high-humidity environments can lead to the accumulation and spread of unwanted microflora. Pathogenic bacteria and fungi present in hospital microbiomes can interact with patients and healthcare staff and may contribute to healthcare-associated infections in susceptible patients [ 8 ]. Although infection transmission often occurs from person to person, contaminated surfaces can also serve as a transmission pathway. Consequently, the hygienic characteristics of the interior materials used in hospitals are critically important and of heightened public interest in light of the recent COVID-19 pandemic. The introduction of new materials or changes to existing materials in a hospital interior can negatively affect the environment and its microbiome, potentially causing adverse consequences for patients [ 9 ]. That is why the potential introduction of wood as a material for hospital facilities prompts reflection on effective surface cleaning and maintenance, durability, and fire safety [ 10 ]. Today, the most widely used methods for assessing the hygienic status of surfaces in public facilities are the swab method and a method based on measuring the amount of adenosine triphosphate (ATP). The swab method, expressed as Colony-Forming Units (CFU), estimates the number of viable microorganisms (bacteria, fungi, etc.) on the surface and provides a measure of microbial quantities or load [ 11 ]. ATP measurement quantifies the total amount of all types of organic contaminants and surface debris, including both microbial and organic contamination sources, such as skin particles, body secretions, and food fragments. ATP level, expressed in Relative Light Units (RLU), provides an instant, relatively inexpensive measure of the surface cleanliness [ 12 , 13 ]. In general, these two methods are often used both independently and in combination and are indispensable for hygienic surface monitoring in hospital facilities [ 11 ]. Considering all of the above, the use of designer wooden wall panels in hospital patient rooms represents an emerging interior design solution with potential environmental and well-being benefits. However, the potential impact of new wood materials on the hygienic status and microbiome of these environments had not been investigated. Therefore, the main aim of this work was to assess surface-year-round microbial dynamics and the resulting residual diversity in two identical patient rooms at Skellefteå Hospital (Sweden) that differed in the presence of wooden wall panels in one room. Materials and Methods Characteristics of patient rooms Two patient rooms in the orthopedic ward at Skellefteå hospital (Skellefteå, Sweden) were selected for this study. The rooms had identical floor area (around 129 m 2 ), orientation (south-facing windows), and number of windows (two per room). The supply and exhaust airflow were 100 l/s and 52 l/s, respectively, in both rooms. The patient rooms were premises with hygiene class 2, specifically designated for activities involving all patient care, treatment, and reception. According to hygiene class 2 requirements all interior surfaces in the room must be washable and wipeable [ 14 ]. Given this, cleaning in both rooms was carried out according to a daily schedule from Monday to Friday, except on Saturday and Sunday, and included wet wiping of surfaces and wet- and dry-mopping of the floor. All the walls of patient rooms were covered with plasterboard with painted fiberglass. The main difference was that designer wood panels were installed on one wall in one room (hereinafter referred to as WoodW ) (Fig. 1 a), while the corresponding wall in the other room remained entirely painted (hereinafter referred to as PaintW ) (Fig. 1 b). The wooden panels were made from three layers of Scots pine ( Pinus sylvestris L.). The panels were 21 mm thick. The specific design pattern shown in Fig. 1 a was produced by sawing out the 7 mm-thick top layers. In total, 0.75 m 3 of Scots pine wood was installed in the WoodW patient room. Before installation, the panels were coated with a transparent, water-based fire-retardant paint NOVATHERM 1FR (Protega AB, Sweden), followed by a clear coat for sealing Top 1FR (Protega AB, Sweden). The manufacturing of the wood panels took about 15 months, with installation completed in September 2021. Sample collection Surface cleanliness and microbial contamination were assessed in two patient rooms (WoodW and PaintW) using ATP measurements and surface sampling by sterile cotton swabs. Since the wood panels were installed in the WoodW room in September 2021, the sample collection began in October 2021 and continued every 2 months until October 2022. Throughout the entire study period, both patient rooms were in regular use for routine patient accommodation and treatment. A total of 7 measurements were carried out at this stage: October 2021, December 2021, February 2022, April 2022, May 2022, August 2022, and October 2022. At this stage, identification of the microorganisms was not carried out. Ten locations were selected for sample collection in each room, namely: left and right dry walls of the left window left and right dry walls of the right window left and right walls of the room, about 1.5 m from the floor left and right sides of the sealing about 1 m from the ventilation channel wall near the ventilation channel doors of the patient lockers ATP measurement Surface cleanliness was assessed by measuring adenosine triphosphate (ATP) levels directly in both patient rooms using a 3M Clean-Trace™ Luminometer (Neogen, USA). The sample was collected from the surface (100 mm × 100 mm) using the one-time Clean-Trace Surface ATP Test Swab (Neogen, USA). The wet cotton swab was applied to the surface with repeated horizontal and vertical strokes, rotating the swab tip for 20 seconds. Following sample collection, the test was activated immediately per the manufacturer’s instructions. The results of ATP measurements were displayed in Relative Light Units (RLU). The higher RLU number indicates a more contaminated sample. The ATP benchmark for hospital surfaces was set at 100 RLU, based on previously published data [ 15 , 16 ]. Microbial quantification measurement Microorganisms were collected from surfaces using the swab method according to the Swedish standard SS-ISO 16000-21:2013 [ 17 ]. A sterile cotton swab was soaked in sterile distilled water and thoroughly wiped the surface (100 mm × 100 mm) for 20 seconds. The swabbing zones for ATP and microbial quantification measurement were located adjacent to each other but did not overlap. After collecting, the swab was then immediately transferred to a sterile tube and transported to the laboratory. Given the proximity of the hospital and the laboratory, sample transport time was approximately 30 minutes, and sample processing began immediately upon arrival. A previously prepared and autoclaved (at 120°C for 15 minutes) dilution buffer was added to each tube containing a swab. The buffer consisted of 0.02 M Potassium dihydrogen phosphate (VWR Chemicals, USA), 0.05 M Disodium hydrogen phosphate dehydrate (Merck KGaA, Germany), 0.074 M Sodium chloride (Sigma Aldrich, USA), 0.01% (v/v) Tween 80 (VWR Chemicals, USA), 1L distilled water. The tubes were shaken for 15 minutes to wash away cells and spores from the swab. Next, 1 ml of the resulting solution from each tube was transferred to Petri dish (Ø90 mm) with sterile malt-extract agar (MEA) (Merck KGaA, Germany) cultivation media, and the solution was evenly distributed over the entire surface of each medium using the same swab. Cultivation was performed in the laboratory chamber (HPP260eco, Memmert, Germany) at 25°C and 90% RH. The number of colonies on the medium surface was counted daily for 7 days. The results of microbial surface quantities were presented as the total number of Colony-Forming Units (CFU) per sample. If the number of colonies was too high to allow reliable counting by visual inspection, the CFU values were capped at 200. Based on public recommendations, a threshold of 2.5 CFU/cm 2 was used to assess the acceptable microbial quantities on hospital surfaces [ 16 , 18 ]. Given the surface area analysed (100 cm 2 ) and the washing and inoculation methods for the samples (described above), the CFU count detected on each Petri dish represented the level of microbial contamination per 10 cm 2 of surface area. For tolerably contaminated hospital surfaces, detected CFU should be no more than 25 CFU per Petri dish (or 2.5 CFU/cm 2 ). Accordingly, if 200 CFU were detected on one Petri dish (20 CFU/cm 2 ), the surface is highly contaminated with microbial agents. To identify residual biodiversity of bacteria and fungi species remaining in both studied patient rooms, additional surface sampling was conducted in March 2024, approximately 2.5 years after the installation of the wooden panels in WoodW room. The protocol for swabbing and washing was identical to that described above. The main difference was that 5 ml of the resulting solution from each tube was inoculated onto five Petri dishes with different cultivation media (1 ml per Petri dish). MEA, potato-dextrose agar (PDA) (Merck KGaA, Germany), nutrient broth agar (NA) (VWR Chemicals, USA), and dicloran 18% glycerol agar (DG 18) (Merck KGaA, Germany) were used as culture media. Subsequently, four Petri dishes containing MEA, PDA, NA, and DG 18 were cultivated in the laboratory chamber (HPP260eco, Memmert, Germany) at 25°C and 90% RH for 7 days. Additionally, a separate laboratory chamber was used to incubate a Petri dish containing MEA at 37℃ and 90% RH to detect the growth of thermophilic microorganisms. Following the CFU enumeration, a fragment of colonies with different morphologies was transferred to separate Petri dishes (Ø 45 mm) with the appropriate medium using a sterile needle, and the cultures were further cultivated in the laboratory chamber at 25℃ or 37℃ and 90% RH for 7 days. A visual inspection for contamination was performed throughout the entire cultivation period, and additional subculturing was carried out when necessary. In this way, both bacterial and fungal pure cultures were isolated and stored at 4℃ in a refrigerator until further use. All culture media were prepared in distilled water according to the manufacturer's recommendations, then autoclaved (120°C, 15 minutes) and poured into sterile plastic Petri dishes (Ø90 mm). All work was carried out in a biosafety cabinet (BSC-700II-I, HMC-Europe, Germany) to ensure aseptic conditions. DNA extraction To identify bacterial and fungal representatives in the WoodW and PaintW patient rooms, total genomic DNA was isolated from pure cultures. DNA extraction was performed using the CTAB protocol [ 19 , 20 ] with minor modifications. A fragment of mycelium or bacterial colony was transferred to a 2 ml Eppendorf tube with a mixture of silica gel 60H - celite 545 (2:1) (Merck KGaA, Germany), one sterile steel ball (Ø 2.4 mm) and 500 µl of CTAB buffer (200 mM Tris-HCl, 200 mM Na-EDTA, 8.2% NaCl w/v, 2% CTAB w/v, pH 7.5 (Merck KGaA, Germany). The sample was homogenised using a homogeniser (Bead Mill MAX, VWR Chemicals, USA) at maximum speed for 1 minute, then incubated at 65°C for 1.5 hours on the block heater (QBD2, Grant, USA). 500 µl chloroform (VWR Chemicals, USA) was added to each tube and mixed vigorously. The samples were then centrifuged in a micro-centrifuge (Micro Star 17R, VWR Chemicals, USA) at maximum speed for 5 min at room temperature, and the supernatant was transferred to clean tubes. The chloroform extraction step was repeated twice. A double volume of cold isopropanol was added, and the solution was left in the freezer (-20℃) overnight for DNA precipitation. The next day, the mixture was centrifuged at maximum speed for 5 min at 4℃. The supernatant was discarded, and the formed DNA pellet was washed with 70% cold ethanol, then centrifuged at maximum speed for 5 min at 4℃. After removing the supernatant, the pellet was dried in a block heater at 37℃ until the ethanol was completely evaporated. The DNA pellet was resuspended in 50 µl TE buffer (10 mM Tris, 10 mM Na-EDTA, pH 8.0 (Merck KGaA, Germany)). DNA concentration was measured using a fluorometer (Qubit Flex, Thermo Fisher, USA) with a Qubit dsDNA BR Assay Kit (Thermo Fisher, USA) according to the manufacturer's protocol. DNA samples were diluted to 10 ng/µl in TE buffer and stored at 4 ℃ until further analysis. Polymerase chain reaction and Sanger sequencing The polymerase chain reaction (PCR) was performed in a 30 µl reaction mixture using the Thermo Cycler T100 (Bio-Rad, Germany). Each reaction mixture contained 15 µl of DreamTaq PCR Master Mix (2×) (Thermo Fisher, USA), 10 pmole of forward and reverse primers (Merck KGaA, Germany), 10 ng genomic DNA, and nuclease-free water (Thermo Fisher, USA). For bacterial identification, the 16S rRNA gene was used as the primary target for subsequent sequencing. Primers 27F and 1492R were used to amplify the 16S rRNA gene fragment containing the hypervariable regions (V1–V9) [ 21 , 22 ]. The PCR protocol consisted of an initial step for 5 min at 94℃, followed by 35 cycles of a denaturation step for 30 s at 94℃, a primer annealing step for 30 s at 55℃, and an elongation step for 1 min at 72℃. The final elongation was 7 min at 72℃, and reactions were held at 4°C. As an additional gene for bacterial identification, the DNA gyrase subunit B ( gyr B) gene was selected [ 23 , 24 ]. It was used exclusively for identifying bacteria that could not be classified to the species level using the 16S rRNA gene. Primers UP-1 and UP-2r were used for gyr B gene amplification, and primers UP-1S and UP-1Sr were used for Sanger sequencing. The PCR protocol was used as described by Yamamoto and Harayama (1995) [ 23 ]. For fungal identification, PCR amplification of the Internal Transcribed Spacer (ITS) region separated by the 5.8S rRNA gene was amplified using ITS1 and ITS4 primers [ 25 , 26 ]. In total, 43 fungal cultures were identified. The PCR protocol consisted of an initial denaturation step of 2 min at 95°C, followed by 35 cycles of a denaturation step for 45 s at 95°C, a primer annealing step for 30 s at 55°C, and an elongation step for 1 min at 72°C. The final elongation was 4 minutes at 72°C, and reactions were held at 4°C. The size of the target fragments varied between 450 and 600 bp. Due to the inability to identify all fungal representatives using ITS, the β-tubulin gene was chosen as an additional marker for fungal identification [ 27 ]. Primers Bt2a and Bt2b were used. The amplification protocol included an initiation step for 4 min at 95°C, followed by 35 cycles of a denaturation step for 45 s at 94°C, a primer annealing step for 45 s at 58°C, and an elongation step for 1 min at 72°C. The final elongation was 6 minutes at 72°C. The retention was at 4°C. The resulting amplicons were approximately 500 bp in length. The complete list of primers used in the study is shown in Table 1 . Table 1 Primers used for PCR amplification and subsequent Sanger sequencing. Name Primer sense Sequence (5´→3´) Gene Amplification product (bp) Reference 27F Forward AGAGTTTGATYMTGGCTCAG 16S rRNA ∼1.400 [ 21 ] 1492R Reverse GGTTACCTTGTTACGACTT UP-1 Forward GAAGTCATCATGACCGTTCTGCAYGCNGGNGGNAARTTYGA gyrB ∼1.100 [ 23 ] UP-2r Reverse AGCAGGGTACGGATGTGCGAGCCRTCNACRTCNGCRTCNGTCAT UP-1S Forward GAAGTCATCATGACCGTTCTGCA UP-1Sr Reverse AGCAGGGTACGGATGTGCGAGCC ITS 1 Forward TCCGTAGGTGAACCTGCGG ITS1 + 5.8S rDNA +ITS2 450–600 [ 25 ] ITS 4 Reverse TCCTCCGCTTATTGATATGC Bt2a Forward GGTAACCAAATCGGTGCTGCTTTC β-tubulin ~ 500 [ 27 ] Bt2b Reverse ACCCTCAGTGTAGTGACCCTTGGC Amplified PCR products were visualised using a gel electrophoresis system (Bio-Rad, Germany) following the addition of SYBR Safe DNA Gel Stain (Thermo Fisher, USA). Subsequent processing was performed only for samples that contained a single target fragment. The clean-up reaction was performed using 10 u Exonuclease I (Thermo Fisher, USA) and 1 u FastAP Thermosensitive Alkaline Phosphatase (Thermo Fisher, USA) for every 5 µL of unpurified PCR product solution [ 28 ]. The resulting mixture was incubated for 15 minutes at 37°C, then heated for another 15 minutes at 85°C to inactivate enzyme activity in the Thermo Cycler T100 (Bio-Rad, Germany). The concentration of pure amplified fragments was determined using a fluorometer (Qubit Flex, Thermo Fisher, USA) with a Qubit dsDNA BR Assay Kit (Thermo Fisher, USA) according to the manufacturer's protocol. The purified PCR products were stored in a fridge at 4℃. Sanger sequencing of all samples was performed using services from LGC Genomics GmbH (closed at the time of writing the manuscript; Berlin, Germany) and Macrogen Europe ( https://www.macrogen-europe.com/ , Amsterdam, Netherlands). Before shipping, the concentration was adjusted to 10–20 ng/ µl by nuclease-free water (Thermo Fisher, USA) according to the recommendations provided. Bioinformatics and statistical data analysis All ATP and CFU data collected over a 2-year period (Oct-21, Dec-21, Feb-22, Apr-22, May-22, Aug-22, Oct-22), as well as data from the additional sampling in March 2024, were analysed. The Shapiro–Wilk test was used to assess the normality of the distributions of the obtained RLU and CFU data. Calculated W and p-value show how closely the data follow a normal distribution. If W is close to 1, the data are normally distributed. If W is around 0.9, some deviated data are present. W 0.05 indicate that the data are normally distributed; p-values ≤ 0.05 indicate that the data are not normally distributed. The median, first quartile (Q1), third quartile (Q3), interquartile range (IQR), and ranges of RLU values and CFU counts were calculated. Total CFU count was calculated for each time point, and a heat map was generated. To assess surface ATP levels, box plots of RLU values for each time point were created for each room. On boxplots, outliers were defined as values exceeding 1.5 times the IQR above Q3 or below Q1. To assess the strength and direction of association between ATP levels and microbial quantities in WoodW and PaintW rooms separately, non-parametric Spearman’s rank correlation coefficient (ρ) was calculated, and scatter plots were generated. If the ρ coefficient ranges from 0 to 1, it indicates a positive correlation between the two variables. If ρ is 0, there is no correlation, and if ρ varies from − 1 to 0, variables are inversely related [ 29 , 30 ]. All statistical analyses and visualisations were performed in Python 3.14.0 using the matplotlib, seaborn , pandas, scipy and numpy libraries [ 31 – 33 ]. DNA sequences obtained in this study were compared with the GenBank database at the National Center for Biotechnology Information (NCBI) using the Basic Local Alignment Search Tool (BLAST) software on the NCBI website ( http://www.ncbi.nlm.nih.gov/BLAST/ ) to identify their taxonomic affiliation. The mandatory criteria were sequence coverage > 80%, species-level similarity between sequences of 98% − 100%, and genus-level similarity of 94% − 97%. With a similarity < 94%, the organism was defined as an unknown fungus or an unknown bacterium [ 34 ]. The obtained sequences were submitted to GenBank under accession numbers PX917402 - PX917429, PX917474 - PX917488. A four-level Risk Group (RG) classification was used to identify bacteria and fungi as potential etiological agents of human diseases. These levels are based on the intrinsic virulence of microorganisms and routes of infection [ 35 , 20 ]. RG1 - bacteria and fungi with low individual and community risk RG2 - have moderate individual risk and limited community risk, are opportunistic human pathogens. RG3 - have high individual risk and low community risk, and usually cause bacterial diseases or mycoses. RG4 - bacteria with high individual and community risk usually produce serious human diseases. Not used for fungi. The RG of all identified bacteria was determined according to the German technical rule TRBA 466 [ 36 ], and of fungi according to the information provided in the Atlas of Clinical Fungi [ 20 ]. To estimate the relative abundance of detected bacterial and fungal taxa, proportion was calculated based on the number of colonies of each identified bacterial/fungal species per Petri dish. A Venn diagram was constructed to visualise the shared and unique taxonomic units identified in WoodW and PaintW rooms. The presence/absence of each taxonomic unit was taken into account. The diagram was visualized using the matplotlib-venn library in Python 3.14.0 [ 37 ]. In addition, the Jaccard Index was calculated to assess the similarity of microbial community between two locations based on the presence/absence of identified taxonomic units. The index ranges from 0 (completely distinct communities) to 1 (identical communities) [ 38 ]. The calculation was performed in Python 3.14.0 using the pandas library [ 33 ]. Phylogenetic analysis was performed using the Maximum Likelihood method with 1000 bootstrap replicates in MEGA 12 [ 39 ], with preliminary multiple sequence alignment using the ClustalW package [ 40 ]. The iTOL tool provided a visualization of phylogenetic trees [ 41 ]. Results Assessment of surface ATP levels and microbial quantities A total of 308 measurements were conducted in two patient rooms, comprising 154 ATP and 154 CFU measurements. The mean RLU value for the PaintW room was 414.3, with a measurement range of 5 to 6583. For the WoodW room, the mean RLU was 278.4, with a range of 4 to 1622. Since the ATP threshold for hospital surfaces was set at 100 RLU, 48.7% of measurements in the PaintW room and 64.1% in the WoodW room exceeded this threshold. Figure 2 . Estimating the amount of ATP on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW). ( a ) Box plot of RLU values detected during 2021–2022 and in March 2024. (b) Box plot of all RLU values detected between the PaintW and WoodW patient rooms throughout the study period. The red line indicates the 100 RLU threshold permissible for hospital surfaces. Circles indicate outliers; those > 1200 RLU were excluded from the plots. The median RLU values for the PaintW room ranged from 53.0 to 350.5 from October 2021 to March 2024. For the WoodW room, median RLU values ranged from 98.0 to 541.0 during the corresponding study period. Of 154 ATP measurements, 18 were identified as outliers. The highest RLU values were 6583 RLU and 4387 RLU on PaintW surfaces in May 2022. The differences in the distribution of all RLU values measured in both rooms over the entire experimental period are shown in Fig. 2 b. The median values were 150.0 RLU for the PaintW room and 225.5 RLU for the WoodW room. No significant statistical difference in RLU distribution was observed between the two patient rooms (p-value = 0.1606 (> 0.05)). Simultaneously with ATP measurement, CFU counts were determined on the same surfaces in both patient rooms to assess microbial quantities. The difference between the total CFU values during the period 2021–2022 and March 2024 was shown as a barplot and a heatmap in Fig. 3 a and 3 b, respectively. The total CFU count in both patient rooms ranged from 2 to 1203 CFU. The lowest CFU counts were detected at the beginning of the study in October 2021 in both rooms (3 CFU and 2 CFU), as well as in April and May 2022 in WoodW room (2 CFU and 2 CFU respectively), and in March 2024 in PaintW room (5 CFU). The highest CFU counts were detected for August 2022 in both rooms (1013 CFU and 1203 CFU) and in the PaintW room in December 2021 (1030 CFU). The Shapiro–Wilk test indicated that CFU data deviated significantly from normality (W = 0.55, p-value = 9.26 (> 0.05)). Descriptive statistics of CFU counts are shown in Table 2 . In particular, the medium CFU counts vary widely, from 0 to 200. The lowest CFU counts were detected in October 2021, April 2022 and March 2024 in both rooms (median 0, IQR 0 and 0.5), in May 2022 in WoodW (median 0, IQR 0), and in February 2022 in PaintW (median 0, IQR 0.5). The highest CFU counts were recorded in the PaintW room in December 2021 (median 104.5, IQR 199) and in August 22 in both rooms (median 200, IQR 199.5). Using the benchmark threshold of < 2.5 CFU/cm 2 (25 CFU per Petri dish), microbial quantifications on hospital surfaces exceeded acceptable levels on half of the sampling dates, except for October 2021, December 2021, August 2022 in both rooms, February 2022 in WoodW, and May 2022 in PaintW. Table 2 Descriptive statistics of CFU counts detected in PaintW and WoodW patient rooms during 2021–2022 and in March 2024. Non-normal distributed data presented as median (Q1–Q3), Q1, Q3, interquartile range (IQR), and range (minimum–maximum CFU counts) Date Location Median Q1 Q3 IQR Range Oct-21 PaintW 0 0 0 0 0–2 WoodW 0 0 0 0 0–2 Dec-21 PaintW 104,5 1 200 199 0–215 WoodW 15 0 200 200 0–230 Feb-22 PaintW 0 0 0,5 0,5 0–200 WoodW 0 0 200 200 0–200 Apr-22 PaintW 0 0 0 0 0–200 WoodW 0 0 0 0 0–1 May-22 PaintW 0,5 0 200 200 0–200 WoodW 0 0 0 0 0–2 Aug-22 PaintW 200 0,5 200 199,5 0–211 WoodW 200 0,5 200 199,5 0–201 Oct-22 PaintW 22,5 0,5 205,5 205 0–227 WoodW 0 0 91,5 91,5 0–93 Mar-24 PaintW 0 0 0,5 0,5 0–3 WoodW 0 0 0,5 0,5 0–200 Total PaintW 0 0 200 200 0-200 WoodW 0 0 200 200 0-200 After evaluating CFU counts across the two patient rooms over the study period, the median and IQR counts in the PaintW and WoodW rooms were equal, and no significant statistical difference was detected (p = 0.4293 (> 0.05)). Spearman's Rank Correlation was used to assess the relationship between ATP level and microbial quantities in each of the two patient rooms. Figure 4 shows scatterplots with trendlines that visualise the correlation between ATP and CFU measurements across 308 measurements in PaintW (Fig. 4 a) and WoodW (Fig. 4 b) rooms. In the PaintW room, a very weak positive correlation between ATP levels and microbial quantities, essentially zero, was observed (Spearman’s coefficient = 0.092). The Spearman’s coefficient for the WoodW room was − 0.082, indicating a very weak negative correlation, essentially close to zero. In both cases, the distributions of ATP and CFU values within each patient's room were not statistically significant (p > 0.05). Assessment of microbial diversity In March 2024, residual microbial presence was evaluated in both patient rooms. A total of 118 pure cultures were isolated and identified by Sanger sequencing, including 75 bacterial and 43 fungal cultures. Of these, 72 microbial pure cultures (48 bacteria and 24 fungi) were isolated from the PaintW patient room, whereas 46 microbial pure cultures (27 bacteria and 19 fungi) were isolated from the WoodW patient room. By sequencing the full-length 16S rRNA gene, 48 bacterial cultures were identified to species and 27 to genus. In particular, representatives of the genera Methylobacterium, Pantoea , Micrococcus, Microbacterium, Staphylococcus , and Bacillus were additionally identified by the gyrB gene. The gyrB gene was used to identify 8 bacterial cultures from the PaintW patient room and 9 from the WoodW patient room. Overall, the gyrB gene sequencing enabled species-level identification of bacterial genera Pantoea , Micrococcus , and Enterobacter . At the same time, species-level resolution was not achieved for the Methylobacterium, Microbacterium, and Bacillus genera, and amplification of the gyrB gene was unsuccessful for isolates of the Staphylococcus genus. ITS sequencing allowed the identification of 32 pure fungal cultures to species and 11 cultures to genus. For Chaetomium, Aspergillus, Penicillium , and Botrytis genera, species-level identification was insufficient, and additional sequencing using the β-tubulin gene was performed. Thus, 9 fungal cultures from the PaintW room and 10 fungal cultures from the WoodW room were additionally identified by the β-tubulin gene. This marker gene successfully identified representatives of the Chaetomium and Aspergillus genera, but did not provide sufficient resolution for the Penicillium and Botrytis genera. The relative abundance of bacteria and fungi in the PaintW and WoodW patient rooms is shown in Fig. 5 . There were significantly more bacteria than fungi on the surfaces of both patient rooms: 74.6% bacteria and 25.4% fungi in the PaintW room, 68.7% bacteria and 31.3% fungi in the WoodW room. Overall, 37 species from 23 genera were identified, including 24 bacterial and 13 fungal species. Figure 6 demonstrates the relative abundance of the identified bacterial and fungal genera in both patient rooms. The bacterial community comprised representatives of 15 genera belonging to the phyla Bacillota , Actinomycetota , and Pseudomonadota . The most frequently detected bacterial genera were Staphylococcus (20% in PaintW and 18.1% in WoodW) and Bacillus (3% in PaintW and 15.5% in WoodW). Additionally, 26.2% and 14,6% of the bacterial community in the PaintW room belonged to the genera Methylobacterium and Rothia , respectively. The most abundant bacterial genus in the WoodW room was Pantoea , which accounted for approximately 29.7% of the microbial community. All identified fungi belonged to 8 genera of the Ascomycota phylum. In the PaintW room, approximately 1% to 7% of the microbial community was comprised of fungi from all 8 genera. All fungi found in the WoodW room belonged to the genera Penicillium (30.8%), Chaetomium (0.5%), and Paecilomyces (0.15%). Among the 24 identified bacterial species, both mesophilic aerobic and anaerobic species were found according to information available in databases BacDive and NCBI. Most bacterial representatives were in risk group 1 (RG 1). At the same time, Bacillus cereus, Moraxella osloensis, Pantoea septica , Staphylococcus epidermidis , and Staphylococcus hominis were assigned to RG 2 in PaintW. In the WoodW room, Enterobacter asburiae, P. septica , and S. hominis belonged RG 2. Bacillus sp. and Staphylococcus sp., which were present in the microbial communities of both rooms, were considered to potentially belong RG 1 or RG 2, however species-level assignment was not possible. The vast majority of identified fungi belonged to saprotrophs and moulds, and were classified as RG 1. No representatives of RG 3 and RG 4, which pose a high risk to humans, were identified. Detailed information on all bacterial and fungal species identified in the study is shown in Tables 3 and 4 . Table 3 Bacteria species identified on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW), with their relative abundance, Risk group, and marker genes used for identification. Species Phylum 1 Live style 1 Relative abundance % Risk Group 2 Marker gene PaintW WoodW Bacillus cereus Frankland and Frankland Bacillota anaerobe, mesophilic bacteria, opportunistic human pathogen 0,8 - 2 16S rRNA, gyrB Bacillus sp. Bacillota aerobe or anaerobe, mesophilic bacteria 3,1 14,9 1–2 16S rRNA, gyrB Bacillus subtilis (Ehrenberg) Cohn Bacillota anaerobe, mesophilic bacteria, opportunistic human pathogen - 0,2 1 16S rRNA Bacillus velezensis Ruiz-García Bacillota aerobe, mesophilic bacteria - 0,2 1 16S rRNA Dermacoccus nishinomiyaensis (Oda) Stackebrandt Actinomycetota mesophilic bacteria, opportunistic human pathogen 0,8 - 1 16S rRNA Dietzia cinnamea (Nesterenko and Harrison) Rainey Actinomycetota microaerophile, mesophilic bacteria, opportunistic human pathogen 0,8 - 1 16S rRNA Enterobacter asburiae Brenner Pseudomonadota anaerobe, mesophilic bacteria, opportunistic human pathogen - 0,1 2 16S rRNA, gyrB Kocuria marina Kim Actinomycetota aerobe, mesophilic bacteria, opportunistic human pathogen 1,5 - 1 16S rRNA Methylobacterium adhaesivum Gallego Pseudomonadota aerobic, mesophilic bacteria 2,3 - 1 16S rRNA Methylobacterium sp. Pseudomonadota aerobic, mesophilic bacteria 23,8 - 1 16S rRNA, gyrB Microbacterium sp. Actinomycetota aerobic, heat-resistant bacteria 0,8 - 1 16S rRNA, gyrB Micrococcus luteus (Schroeter) Cohn Actinomycetota aerobe, mesophilic bacteria 1,5 5,3 1 16S rRNA, gyrB Micromonospora aurantiaca Sveshnikova Actinomycetota mesophilic bacteria 0,8 - 1 16S rRNA Moraxella osloensis Bøvre and Henriksen Pseudomonadota aerobe, mesophilic bacteria, symbiont of nematode Phasmarhabditis hermaphrodita Schneider 0,8 - 2 16S rRNA Paenibacillus sp. Bacillota anaerobic, mesophilic bacteria 1,5 - 1 16S rRNA Pantoea septica Brady Pseudomonadota aerobe, mesophilic bacteria, opportunistic human pathogen 0,8 29,7 2 16S rRNA, gyrB Rothia amarae Fan Actinomycetota microaerophile, mesophilic bacteria, opportunistic human pathogen - 0,1 1 16S rRNA Rothia kristinae (Kloos) Nouioui Actinomycetota microaerophile, mesophilic bacteria, opportunistic human pathogen 14,6 0,1 1 16S rRNA Staphylococcus capitis Kloos and Schleifer Bacillota aerobe, mesophilic bacteria, opportunistic human pathogen 5,4 - 1 16S rRNA Staphylococcus epidermidis (Winslow and Winslow) Evans Bacillota anaerobe, mesophilic bacteria, human pathogen 6,9 - 2 16S rRNA Staphylococcus hominis Kloos and Schleifer Bacillota aerobe, mesophilic bacteria, opportunistic human pathogen 3,1 17,8 2 16S rRNA Staphylococcus sp. Bacillota aerobe or anaerobe, mesophilic bacteria, human pathogen 4,6 0,1 1–2 16S rRNA Staphylococcus warner i Kloos and Schleifer Bacillota aerobe, mesophilic bacteria, opportunistic human pathogen - 0,1 2 16S rRNA Streptomyces thermocarboxydus Kim Actinomycetota aerobe, thermophilic bacteria 0,8 - 1 16S rRNA 1 Data taken from databases BacDive ( https://beta.bacdive.dsmz.de/ ), NCBI Taxonomy Browser ( https://www.ncbi.nlm.nih.gov/ ) 2 Risk groups for bacteria are defined according to TRBA 466 technical rule [ 36 ] Table 4 Fungal species identified on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW), with their relative abundance, Risk group, and marker genes used for identification. Species Phylum 1 Live style 1 Relative abundance % Risk Group 2 Marker gene PaintW WoodW Aspergillus niger van Tieghem Ascomycota Saprotroph, mould, opportunistic human pathogen 2,3 - 1 ITS, β-tubulin Aspergillus tubingensis Mosseray Ascomycota Saprotroph, mould, opportunistic human pathogen 2,3 - 1 ITS, β-tubulin Botrytis sp. Ascomycota Saprotroph, mould 2,3 - Unknown ITS, β-tubulin Chaetomium globosum Kunze Ascomycota Saprotroph, mould, opportunistic human pathogen 2,3 0,5 1 ITS, β-tubulin Cladosporium herbarum (Pers.) Link Ascomycota Saprotroph 0,8 - 1 ITS, β-tubulin Cladosporium halotolerans Zalar, de Hoog, Schroers, Crous, Groenewald and Gunde-Cimerman Ascomycota Saprotroph 6,2 - 1 ITS Coniothyrium telephii (Allescher) Verkley and Gruyter Ascomycota Saprotroph, opportunistic human pathogen 0,8 - 1 ITS Paecilomyces variotii Bainier Ascomycota Saprotroph, opportunistic human pathogen 1,5 0,1 1 ITS Penicillium chrysogenum Thom Ascomycota Saprotroph, mould 2,3 - 1 ITS, β-tubulin Penicillium corylophilum Ascomycota Saprotroph, mould 2,3 0,1 1 ITS Penicillium digitatum (Persoon) Saccardo Ascomycota Saprotroph, mould - 0,1 1 ITS Penicillium sp. Ascomycota Saprotroph, mould - 30,4 1 ITS, β-tubulin Pyrenophora triseptata (Drechsler) Rossman and Hyde Ascomycota Plant pathogen 2,3 - 1 ITS 1 NCBI Taxonomy Browser ( https://www.ncbi.nlm.nih.gov/ ), and the Atlas of Clinical Fungi [ 20 ] 2 Risk groups for bacteria are defined according to the Atlas of Clinical Fungi [ 20 ] To assess the similarity of microbial communities between the two rooms, Venn diagrams were constructed to visualise the numbers of unique and shared fungal and bacterial taxa between the PaintW and WoodW patient rooms. Figure 7 a shows that 14 unique genera were identified in PainW room and 1 genus in WoodW room, while eight genera were shared between rooms ( Paecilomyces , Penicillium , Chaetomium, Rothia , Staphylococcus , Pantoea , Micrococcus , and Bacillus) . The corresponding Jaccard Index was 0.35. The diagram in Fig. 7 b shows the presence of 21 unique species in the PaintW room and 7 unique species in the WoodW room. 9 shared species were identified in both patient rooms ( Paecilomyces variotii , Penicillium corylophilum , Chaetomium globosum , Rothia kristinae , S. hominis, Staphylococcus sp ., P. septica , Micrococcus luteus , and Bacillus sp.). The Jaccard Index was 0.24. Overall, the data obtained demonstrates low similarity in microbial species and genus composition between the two patient rooms studied. The phylogenetic relationships among the identified bacterial and fungal species were assessed based on the obtained 16S rRNA and ITS sequences. Figure 8 shows a phylogenetic tree containing the 30 microbial species from the PaintW patient room. A clear clustering of bacterial species was observed, distinct from that of fungal species. Bacteria belonging to the phylum Actinomycetota formed a separate clade, which included Streptomyces thermocarboxydus , Dietzia cinnamea , Micromonospora aurantiaca , Microbacterium sp., Micrococcus luteus , Dermacoccus nishinomiyaensis , Rothia kristinae , and Kocuria marina . Species of the phylum Bacillota ( Paenibacillus , Bacillus , and Staphylococcus sp.) clustered together with a 100% bootstrap rate. The phylogenetic tree, which contains the 15 species isolated from surfaces in the WoodW patient room, is shown in Fig. 9 . Separate clades were formed for bacterial and fungal species. Additionally, a clear separation of bacterial species by phylum affiliation was observed. P. septica and E. asburiae formed a separate clade as representatives of the Pseudomonadota , M. luteus and Rothia species - as Actinomycetota , and Bacillus and Staphylococcus species - as Bacillota . In addition, both phylogenetic trees show clear groupings within the same genus, particularly Staphylococcus , Bacillus , Methylobacterium , Penicillium , Aspergillus , and others. Discussion Improving the hospital environment, particularly through interior changes, positively affects the well-being and comfort of both patients and medical staff [ 3 , 42 ]. However, significant changes in patients' stay conditions, particularly the installation of new materials in patient rooms, such as wood panels, can affect cleanliness, environmental contamination, and the biodiversity of the microbial community within those facilities. The study of such an impact is a crucial step towards the widespread adoption of wooden materials for the decoration and design of hospital premises. This study assessed the microbial dynamics and residual diversity on surfaces in two patient rooms in the same hospital ward. The main difference between the patient rooms was the presence of designer wood panels. Measurements of ATP levels and microbial quantities indicated that surface contamination fluctuated over time in both rooms, reflecting the dynamic nature of hospital environments. Although a substantial proportion of ATP measurements exceeded the benchmark threshold of 100 RLU, no statistically significant differences in ATP levels were observed between the room with painted walls and the room with wooden panels. This suggests that the presence of wooden wall panels did not affect overall surface cleanliness when compared with conventional painted surfaces. During the study period, high microbial levels were observed in both rooms, which frequently exceeded recommended thresholds for hospital surfaces [ 16 , 18 ]. However, no statistically significant differences in CFU levels were detected between the two patient rooms over the study period. These findings indicate that installing wooden wall panels did not lead to increased microbial quantities compared with a standard painted-wall patient room. This is likely due to several factors, such as the characteristics of scheduled cleaning and ventilation, the number of patients, etc. The discussion about the relationship between ATP levels and microbial quantities remains relevant today. Consistent with several previous studies [ 43 – 45 , 12 , 46 ]. no meaningful correlation between ATP levels and microbial quantities on surfaces in both patient rooms. This lack of correlation reflects the fact that ATP bioluminescence detects total organic material on surfaces, including both microbial and non-microbial residues, such as skin flakes, body fluids, and food particles. On the other hand, even if microbial quantities are low, the presence of other biological material on surfaces can serve as a source of nutrients for bacterial and fungal growth, including those pathogenic to [ 12 ]. While ATP monitoring remains a fast tool for assessing overall surface cleanliness, it cannot be used as a direct indicator of microbial load or sterility. Therefore, the removal of organic residues remains important, as such material may serve as a substrate for microbial growth [ 45 ]. This study highlights differences in microbial diversity between patient room surfaces with different wall materials. Molecular identification of the isolates revealed substantially greater diversity of bacterial and fungal species on surfaces in the painted-wall room compared with the room with wooden wall panels. At both the genus and species levels, microbial community similarity between the two rooms was low, suggesting distinct surface-associated microbiomes. Previous studies showed that the formation of the surface microbiome in hospitals is a complex dynamic process influenced by a number of factors, including the effects of surface materials, clinical activities [ 7 ], cleaning and ventilation schedules, and the number of patients who actively release their own microbes into hospital wards, thus changing the environment [ 47 , 48 ]. Because the rooms were located in the same ward and shared similar characteristics, cleaning regimes, ventilation conditions, and patient use, the wall material is a plausible contributing factor to the observed differences. This study showed significantly lower microbial diversity on the surfaces of the room with wood panels. One possible explanation for the lower microbial diversity observed in the room with wooden wall panels relates to the inherent properties of wood. Previous studies have suggested that wood may exhibit antimicrobial effects due to its porous, hygroscopic structure and chemical composition [ 49 , 50 ]. By absorbing moisture from the surface, wood may reduce microbial survival through desiccation [ 9 , 49 , 50 ], while certain wood extractives have been reported to possess antimicrobial activity [ 51 – 53 ]. Although these mechanisms are consistent with the observed patterns, the present study was not designed to directly test antimicrobial activity, and alternative explanations, for instance microclimatic differences at the surface level, cannot be excluded and pattern explanation requires detailed future study. The culture-based approach used in this study allowed detailed identification of viable bacterial and fungal representatives but also imposed limitations on species resolution and community coverage compared with DNA-based approaches. While 16S rRNA gene sequencing and ITS sequencing enabled identification of most isolates, several bacterial and fungal genera required additional markers, and some taxa could not be resolved to the species level. Future studies incorporating complementary molecular approaches, such as high-throughput sequencing, could provide a more comprehensive view of microbial community composition and functional potential. Overall, the results demonstrate that installing wooden wall panels in a hospital patient room did not compromise surface microbial dynamics. At the same time, the presence of wood was associated with a distinct and less diverse surface microbiome compared with a painted-wall room. Our findings support the careful consideration of wood as an interior material in hospitals with appropriate cleaning and maintenance. Further long-term, multi-site studies are needed to better understand the formation of the surface microbiome and to evaluate the broader implications of wood use in healthcare facilities. Conclusion In this study, surface microbial dynamics and residual diversity in two patient rooms with painted and wooden walls were assessed, and the microbial biodiversity in these rooms was investigated. High ATP levels and microbial quantities were detected on the surfaces of both patient rooms at half-time points, indicating abnormal surface contamination and insufficient cleanliness. Importantly, no statistically significant differences in ATP levels or microbial quantities were observed between the two patient rooms throughout the study period. No clear correlation was found between ATP levels and microbial quantities in both patient rooms, because the ATP method measures total organic material on surfaces rather than viable microorganisms alone. This highlights the complementary roles of ATP monitoring and culture-based methods in evaluating hospital surface hygiene. Culture isolation and Sanger sequencing revealed that all bacterial and fungal species belonged exclusively to risk groups 1 and 2, indicating a low risk to human health. Microbial biodiversity differed significantly between the rooms, with a higher number of bacterial and fungal species detected in the painted wall room, whereas the presence of wooden wall panels was associated with lower microbial biodiversity without increased contamination. This pattern may be related to intrinsic properties of wood, such as its physical structure or chemical composition, which confer antimicrobial properties; further targeted studies of these phenomena are required. Overall, the findings indicate that wood, as a decorative indoor material, does not negatively affect surface microbial dynamics or residual diversity in hospital patient rooms. These results support the careful consideration of wood in the design of hospital facilities, together with appropriate cleaning and maintenance practices. Declarations Acknowledgements : The authors express their gratitude to the Kempe Foundation and, personally, to Alice Kempe for providing a postdoctoral fellowship to Anastasia Postovoitova. The authors are also grateful to Bror Sundqvist and Tetiana Krupodorova for their support and assistance in data analysis. Author contributions Conceptualization, O.M., O.K; methodology, O.M.; investigation, A.P., O.M., K.D., L.K.; software, A.P.; writing – original draft, A.P.; writing – review & editing, K.D., O.M., A.P., O.K; project administration and supervision, O.M. All authors have read and agreed with the published version of the manuscript. Funding The financial support provided by Swedish Wood for the project “Träinredning i patientrum” (Wooden interior design in patient rooms, 2019 - 2025), by Swedish Agency for Economic and Regional Growth (Tillväxtverket) as part of the project “Främja ökat byggande av flerfamiljshus i trä” (grant number 20203193). Anastasiia Postovoitova was supported by the Kempe Foundation. Open access funding provided by the Wood Science and Engineering subject atLuleå University of Technology. Data availability The datasets generated and analysed during the current study are available in GenBank database at NCBI, accession numbers PX917402 - PX917429, PX917474 - PX917488. Ethics approval and consent to participate Not applicable Competing interests The authors declare no competing interests. References Mauri, D. et al. Interior design: a new perspective in supportive care of patients with acute onset of debilitating diseases. Palliat. Med. Rep. 2 , 365–368 (2021). Foster, M. W. et al. 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Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 09 May, 2026 Reviewers agreed at journal 14 Apr, 2026 Reviewers agreed at journal 29 Mar, 2026 Reviewers invited by journal 24 Mar, 2026 Editor assigned by journal 24 Mar, 2026 Editor invited by journal 24 Mar, 2026 Submission checks completed at journal 18 Mar, 2026 First submitted to journal 18 Mar, 2026 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9114856","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":612097351,"identity":"1f1a8ae4-c8d4-4598-885e-09cd4c439c55","order_by":0,"name":"Anastasiia Postovoitova","email":"","orcid":"","institution":"Luleå University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Anastasiia","middleName":"","lastName":"Postovoitova","suffix":""},{"id":612097352,"identity":"f2ffbf9d-1072-4b83-abb5-8a8b9d0b258e","order_by":1,"name":"Kateryna Davydenko","email":"","orcid":"","institution":"Swedish University of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kateryna","middleName":"","lastName":"Davydenko","suffix":""},{"id":612097354,"identity":"c2fcb819-78aa-4840-a1b9-4a9deab52c0d","order_by":2,"name":"Larysa Kucher","email":"","orcid":"","institution":"National University of Life and Environmental Sciences of Ukraine","correspondingAuthor":false,"prefix":"","firstName":"Larysa","middleName":"","lastName":"Kucher","suffix":""},{"id":612097356,"identity":"0f509039-8944-43bf-9132-8ee4404080aa","order_by":3,"name":"Olov Karlsson","email":"","orcid":"","institution":"Luleå University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Olov","middleName":"","lastName":"Karlsson","suffix":""},{"id":612097359,"identity":"f48f80f0-68ec-4112-b7e4-a9d4a3536872","order_by":4,"name":"Olena Myronycheva","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYDACdmQOYwNIpLkBvxZmDC08Bxvx68HUIpGIXws/M/OxBz8YtiVub+89JvFzh01i/8yH7Y95GOrkcGmRbGZLN+xhuJ0458y5NMneM2mJM24nNjbzMBw2xqXF4DCPmQQPUMsMiRwzacY2oEqIlgOJuFxncJj/m+QfhJb/xvI3D4K01NXj1sLDJo1kywE5gxuMIC3MCXj8YiYtY3DbeAbPGWPL3rZkOcMziY0z5xgcNsRlCz978zPJNxW3ZWew9xje+NlmxyN3/PCBD28q6uRx2QJ1HoMj0EwWCWQRgsAeiJk/EFY3CkbBKBgFIxEAALO/VXWcljiiAAAAAElFTkSuQmCC","orcid":"","institution":"Luleå University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Olena","middleName":"","lastName":"Myronycheva","suffix":""}],"badges":[],"createdAt":"2026-03-13 12:39:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9114856/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9114856/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105566498,"identity":"20491df0-7860-4ac1-8eff-24d2ddcde2d7","added_by":"auto","created_at":"2026-03-27 12:56:33","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":4991755,"visible":true,"origin":"","legend":"\u003cp\u003eView of the patient rooms in which the study was conducted. \u003cstrong\u003e(a)\u003c/strong\u003eRoom with a wood-paneled wall with a specific design pattern (WoodW). \u003cstrong\u003e(b)\u003c/strong\u003e Room with only painted walls (PaintW).\u003c/p\u003e","description":"","filename":"Fig1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/f157f25dcccfb409506f48f5.jpeg"},{"id":105497654,"identity":"3ac1eb5b-c113-4687-9c99-d84337724360","added_by":"auto","created_at":"2026-03-26 16:46:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":136910,"visible":true,"origin":"","legend":"\u003cp\u003eEstimating the amount of ATP on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW). (\u003cstrong\u003ea\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eBox plot of RLU values detected during 2021-2022 and in March 2024. \u003cstrong\u003e(b)\u003c/strong\u003e Box plot of all RLU values detected between the PaintW and WoodW patient rooms throughout the study period. The red line indicates the 100 RLU threshold permissible for hospital surfaces. Circles indicate outliers; those \u0026gt;1200 RLU were excluded from the plots.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/35a52fa620429f6d8a1d7560.jpg"},{"id":105567062,"identity":"d3116481-2447-4246-be46-915c418546ae","added_by":"auto","created_at":"2026-03-27 12:58:12","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":634670,"visible":true,"origin":"","legend":"\u003cp\u003eAssessment of microbial dynamics on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW). Bar plot (\u003cstrong\u003ea\u003c/strong\u003e) and heatmap (\u003cstrong\u003eb\u003c/strong\u003e) with total CFU counts detected during 2021-2022 and in March 2024 are shown.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/7b1b03626141b24dc5e5bc09.jpg"},{"id":105567084,"identity":"e9f4dfe3-4f5b-42ad-9b01-236a6c807233","added_by":"auto","created_at":"2026-03-27 12:58:15","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":671317,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between the ATP levels and microbial quantities in patient rooms with painted (PaintW) (\u003cstrong\u003ea\u003c/strong\u003e) and wood walls (WoodW) (\u003cstrong\u003eb\u003c/strong\u003e) using Spearman's Rank Correlation. Each RLU value and CFU count was given a rank as the position of a value when all values were ordered from smallest to largest. The obtained RLU and CFU ranks are displayed on the y- and x-axes in scatter plots, respectively. The trendlines (green) show the general direction of correlation between these two variables. In addition, Spearman’s rank correlation coefficient (Spearman's ρ) and the corresponding p-value are shown for data from both rooms.\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/679df6f8c1fc77d8d3993042.jpg"},{"id":105566649,"identity":"19d14560-52ed-439b-81cc-ee729436d439","added_by":"auto","created_at":"2026-03-27 12:56:53","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":49457,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of bacterial and fungal representatives at the domain level on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW).\u003c/p\u003e","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/4273c1bef3f2898371ea338e.jpg"},{"id":105566266,"identity":"9e73d773-749b-40dd-a182-aad1fd25516c","added_by":"auto","created_at":"2026-03-27 12:55:56","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":677535,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of bacterial and fungal representatives detected on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW) at the genus level.\u003c/p\u003e","description":"","filename":"Fig6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/777e6e25d8797f30238fdad1.jpeg"},{"id":105567359,"identity":"af4d8f37-d70a-47a7-9dbd-8386a7bd2c6e","added_by":"auto","created_at":"2026-03-27 12:59:05","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":908867,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagrams illustrate the unique and shared genera (\u003cstrong\u003ea\u003c/strong\u003e) and species (\u003cstrong\u003eb\u003c/strong\u003e) of fungi and bacteria identified in patient rooms with painted (PaintW) and wood walls (WoodW). The yellow circle represents unique taxa from the PaintW room, the blue circle represents unique taxa from the WoodW room. The green overlap area shows the number of shared taxa. The Jaccard Index (below the diagrams) illustrates the level of similarity between the microbial communities in the two rooms at the genus(\u003cstrong\u003ea\u003c/strong\u003e) and species (\u003cstrong\u003eb\u003c/strong\u003e)levels.\u003c/p\u003e","description":"","filename":"Fig7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/f3f7884dbab32e4f6ceba54f.jpeg"},{"id":105565926,"identity":"103a9be5-05e8-4a90-9da8-9e16684348c0","added_by":"auto","created_at":"2026-03-27 12:54:46","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":204167,"visible":true,"origin":"","legend":"\u003cp\u003eMaximum Likelihood phylogenetic tree showing the taxonomic position of all identified bacterial and fungal species isolated from the surfaces in patient rooms with painted (PaintW) based on multiple alignments of \u003cem\u003e16S rRNA\u003c/em\u003e and ITS sequences. Bootstrap values (\u0026gt; 50 %) are indicated on branches as blue circles. Species detected in the WoodW patient room are marked with a yellow star as well. The green or yellow rectangles (on the right side) indicate risk groups (RG) of each species.\u003c/p\u003e","description":"","filename":"Fig8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/7607a5ac858d71b02f9e1095.jpg"},{"id":105567442,"identity":"a531488e-ee9c-43b8-bbc0-75aab3336da1","added_by":"auto","created_at":"2026-03-27 12:59:33","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":101823,"visible":true,"origin":"","legend":"\u003cp\u003eMaximum Likelihood phylogenetic tree showing the taxonomic position of all identified bacterial and fungal species isolated from the surfaces in patient rooms with wood wall (WoodW) based on multiple alignments of \u003cem\u003e16S rRNA\u003c/em\u003e and ITS sequences. Bootstrap values (\u0026gt; 50 %) are indicated on branches as blue circles. Species detected in the PaintW patient room are marked with a yellow star as well. The green or yellow rectangles (on the right side) indicate risk groups (RG) of each species.\u003c/p\u003e","description":"","filename":"Fig9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/03136334d807717b32104c14.jpg"},{"id":105571417,"identity":"10ec5170-5b01-4051-b737-df0dc56b8559","added_by":"auto","created_at":"2026-03-27 13:23:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9672042,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9114856/v1/2c9e63a8-855c-47ae-80a3-6c22b2eb5338.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Surface microbial dynamics and residual diversity in patient rooms with wooden and painted walls","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHospitals are complex public health institutions that must meet numerous standards and requirements to provide high-quality treatment, surgery, and patient care. In addition to high-quality medical services, good interior design of hospital facilities is also one of the factors that positively affect the well-being of patients, their family members, and medical staff. Improving the visual appearance of healthcare settings and rooms through the use of new materials, surface finishes, interior elements, and artwork enhances well-being and mental health outcomes, provides distraction, and evokes positive emotions [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Together, these factors contribute to more positive hospital experience.\u003c/p\u003e \u003cp\u003eToday, a pressing issue is the selection of building and interior materials based on their environmental impact [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The use of biobased materials in the construction industry provides carbon sequestration and long-term storage and makes a significant contribution to the modern global bioeconomy [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Wood, as an organic and renewable material, has significant advantages over plastic, glass, concrete, and steel, which require substantial energy for production. These advantages include wood\u0026rsquo;s favourable environmental profileand its absence of environmental disturbances, pollution, or hazards to human health [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. It has also been found that using wood in buildings reduces embodied energy by 43% and carbon emissions by 68% compared to using concrete [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Despite these benefits and widespread use of wood in furniture and panel manufacturing, its use in healthcare facility interiors remains limited due to concerns related to hygiene, durability, and safety.\u003c/p\u003e \u003cp\u003eHospitals, like any indoor environment, host complex microbiomes influenced by many factors, including construction materials and interior design [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Wood is a hygroscopic, porous material, and its use in high-humidity environments can lead to the accumulation and spread of unwanted microflora. Pathogenic bacteria and fungi present in hospital microbiomes can interact with patients and healthcare staff and may contribute to healthcare-associated infections in susceptible patients [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Although infection transmission often occurs from person to person, contaminated surfaces can also serve as a transmission pathway. Consequently, the hygienic characteristics of the interior materials used in hospitals are critically important and of heightened public interest in light of the recent COVID-19 pandemic. The introduction of new materials or changes to existing materials in a hospital interior can negatively affect the environment and its microbiome, potentially causing adverse consequences for patients [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. That is why the potential introduction of wood as a material for hospital facilities prompts reflection on effective surface cleaning and maintenance, durability, and fire safety [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eToday, the most widely used methods for assessing the hygienic status of surfaces in public facilities are the swab method and a method based on measuring the amount of adenosine triphosphate (ATP). The swab method, expressed as Colony-Forming Units (CFU), estimates the number of viable microorganisms (bacteria, fungi, etc.) on the surface and provides a measure of microbial quantities or load [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. ATP measurement quantifies the total amount of all types of organic contaminants and surface debris, including both microbial and organic contamination sources, such as skin particles, body secretions, and food fragments. ATP level, expressed in Relative Light Units (RLU), provides an instant, relatively inexpensive measure of the surface cleanliness [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In general, these two methods are often used both independently and in combination and are indispensable for hygienic surface monitoring in hospital facilities [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsidering all of the above, the use of designer wooden wall panels in hospital patient rooms represents an emerging interior design solution with potential environmental and well-being benefits. However, the potential impact of new wood materials on the hygienic status and microbiome of these environments had not been investigated. Therefore, the main aim of this work was to assess surface-year-round microbial dynamics and the resulting residual diversity in two identical patient rooms at Skellefte\u0026aring; Hospital (Sweden) that differed in the presence of wooden wall panels in one room.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of patient rooms\u003c/h2\u003e \u003cp\u003eTwo patient rooms in the orthopedic ward at Skellefte\u0026aring; hospital (Skellefte\u0026aring;, Sweden) were selected for this study. The rooms had identical floor area (around 129 m\u003csup\u003e2\u003c/sup\u003e), orientation (south-facing windows), and number of windows (two per room). The supply and exhaust airflow were 100 l/s and 52 l/s, respectively, in both rooms. The patient rooms were premises with hygiene class 2, specifically designated for activities involving all patient care, treatment, and reception. According to hygiene class 2 requirements all interior surfaces in the room must be washable and wipeable [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Given this, cleaning in both rooms was carried out according to a daily schedule from Monday to Friday, except on Saturday and Sunday, and included wet wiping of surfaces and wet- and dry-mopping of the floor.\u003c/p\u003e \u003cp\u003eAll the walls of patient rooms were covered with plasterboard with painted fiberglass. The main difference was that designer wood panels were installed on one wall in one room (hereinafter referred to as \u003cb\u003eWoodW\u003c/b\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), while the corresponding wall in the other room remained entirely painted (hereinafter referred to as \u003cb\u003ePaintW\u003c/b\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe wooden panels were made from three layers of Scots pine (\u003cem\u003ePinus sylvestris\u003c/em\u003e L.). The panels were 21 mm thick. The specific design pattern shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ea was produced by sawing out the 7 mm-thick top layers. In total, 0.75 m\u003csup\u003e3\u003c/sup\u003e of Scots pine wood was installed in the WoodW patient room. Before installation, the panels were coated with a transparent, water-based fire-retardant paint NOVATHERM 1FR (Protega AB, Sweden), followed by a clear coat for sealing Top 1FR (Protega AB, Sweden). The manufacturing of the wood panels took about 15 months, with installation completed in September 2021.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample collection\u003c/h3\u003e\n\u003cp\u003eSurface cleanliness and microbial contamination were assessed in two patient rooms (WoodW and PaintW) using ATP measurements and surface sampling by sterile cotton swabs. Since the wood panels were installed in the WoodW room in September 2021, the sample collection began in October 2021 and continued every 2 months until October 2022. Throughout the entire study period, both patient rooms were in regular use for routine patient accommodation and treatment. A total of 7 measurements were carried out at this stage: October 2021, December 2021, February 2022, April 2022, May 2022, August 2022, and October 2022. At this stage, identification of the microorganisms was not carried out. Ten locations were selected for sample collection in each room, namely:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eleft and right dry walls of the left window\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eleft and right dry walls of the right window\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eleft and right walls of the room, about 1.5 m from the floor\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eleft and right sides of the sealing about 1 m from the ventilation channel\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ewall near the ventilation channel\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003edoors of the patient lockers\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003eATP measurement\u003c/h3\u003e\n\u003cp\u003eSurface cleanliness was assessed by measuring adenosine triphosphate (ATP) levels directly in both patient rooms using a 3M Clean-Trace\u0026trade; Luminometer (Neogen, USA). The sample was collected from the surface (100 mm \u0026times; 100 mm) using the one-time Clean-Trace Surface ATP Test Swab (Neogen, USA). The wet cotton swab was applied to the surface with repeated horizontal and vertical strokes, rotating the swab tip for 20 seconds. Following sample collection, the test was activated immediately per the manufacturer\u0026rsquo;s instructions. The results of ATP measurements were displayed in Relative Light Units (RLU). The higher RLU number indicates a more contaminated sample. The ATP benchmark for hospital surfaces was set at 100 RLU, based on previously published data [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eMicrobial quantification measurement\u003c/h3\u003e\n\u003cp\u003eMicroorganisms were collected from surfaces using the swab method according to the Swedish standard SS-ISO 16000-21:2013 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. A sterile cotton swab was soaked in sterile distilled water and thoroughly wiped the surface (100 mm \u0026times; 100 mm) for 20 seconds. The swabbing zones for ATP and microbial quantification measurement were located adjacent to each other but did not overlap. After collecting, the swab was then immediately transferred to a sterile tube and transported to the laboratory. Given the proximity of the hospital and the laboratory, sample transport time was approximately 30 minutes, and sample processing began immediately upon arrival.\u003c/p\u003e \u003cp\u003eA previously prepared and autoclaved (at 120\u0026deg;C for 15 minutes) dilution buffer was added to each tube containing a swab. The buffer consisted of 0.02 M Potassium dihydrogen phosphate (VWR Chemicals, USA), 0.05 M Disodium hydrogen phosphate dehydrate (Merck KGaA, Germany), 0.074 M Sodium chloride (Sigma Aldrich, USA), 0.01% (v/v) Tween 80 (VWR Chemicals, USA), 1L distilled water. The tubes were shaken for 15 minutes to wash away cells and spores from the swab. Next, 1 ml of the resulting solution from each tube was transferred to Petri dish (\u0026Oslash;90 mm) with sterile malt-extract agar (MEA) (Merck KGaA, Germany) cultivation media, and the solution was evenly distributed over the entire surface of each medium using the same swab. Cultivation was performed in the laboratory chamber (HPP260eco, Memmert, Germany) at 25\u0026deg;C and 90% RH. The number of colonies on the medium surface was counted daily for 7 days. The results of microbial surface quantities were presented as the total number of Colony-Forming Units (CFU) per sample. If the number of colonies was too high to allow reliable counting by visual inspection, the CFU values were capped at 200.\u003c/p\u003e \u003cp\u003eBased on public recommendations, a threshold of 2.5 CFU/cm\u003csup\u003e2\u003c/sup\u003e was used to assess the acceptable microbial quantities on hospital surfaces [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Given the surface area analysed (100 cm\u003csup\u003e2\u003c/sup\u003e) and the washing and inoculation methods for the samples (described above), the CFU count detected on each Petri dish represented the level of microbial contamination per 10 cm\u003csup\u003e2\u003c/sup\u003e of surface area. For tolerably contaminated hospital surfaces, detected CFU should be no more than 25 CFU per Petri dish (or 2.5 CFU/cm\u003csup\u003e2\u003c/sup\u003e). Accordingly, if 200 CFU were detected on one Petri dish (20 CFU/cm\u003csup\u003e2\u003c/sup\u003e), the surface is highly contaminated with microbial agents.\u003c/p\u003e \u003cp\u003eTo identify residual biodiversity of bacteria and fungi species remaining in both studied patient rooms, additional surface sampling was conducted in March 2024, approximately 2.5 years after the installation of the wooden panels in WoodW room. The protocol for swabbing and washing was identical to that described above. The main difference was that 5 ml of the resulting solution from each tube was inoculated onto five Petri dishes with different cultivation media (1 ml per Petri dish). MEA, potato-dextrose agar (PDA) (Merck KGaA, Germany), nutrient broth agar (NA) (VWR Chemicals, USA), and dicloran 18% glycerol agar (DG 18) (Merck KGaA, Germany) were used as culture media. Subsequently, four Petri dishes containing MEA, PDA, NA, and DG 18 were cultivated in the laboratory chamber (HPP260eco, Memmert, Germany) at 25\u0026deg;C and 90% RH for 7 days. Additionally, a separate laboratory chamber was used to incubate a Petri dish containing MEA at 37℃ and 90% RH to detect the growth of thermophilic microorganisms.\u003c/p\u003e \u003cp\u003eFollowing the CFU enumeration, a fragment of colonies with different morphologies was transferred to separate Petri dishes (\u0026Oslash; 45 mm) with the appropriate medium using a sterile needle, and the cultures were further cultivated in the laboratory chamber at 25℃ or 37℃ and 90% RH for 7 days. A visual inspection for contamination was performed throughout the entire cultivation period, and additional subculturing was carried out when necessary. In this way, both bacterial and fungal pure cultures were isolated and stored at 4℃ in a refrigerator until further use.\u003c/p\u003e \u003cp\u003e All culture media were prepared in distilled water according to the manufacturer's recommendations, then autoclaved (120\u0026deg;C, 15 minutes) and poured into sterile plastic Petri dishes (\u0026Oslash;90 mm). All work was carried out in a biosafety cabinet (BSC-700II-I, HMC-Europe, Germany) to ensure aseptic conditions.\u003c/p\u003e\n\u003ch3\u003eDNA extraction\u003c/h3\u003e\n\u003cp\u003eTo identify bacterial and fungal representatives in the WoodW and PaintW patient rooms, total genomic DNA was isolated from pure cultures. DNA extraction was performed using the CTAB protocol [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] with minor modifications. A fragment of mycelium or bacterial colony was transferred to a 2 ml Eppendorf tube with a mixture of silica gel 60H - celite 545 (2:1) (Merck KGaA, Germany), one sterile steel ball (\u0026Oslash; 2.4 mm) and 500 \u0026micro;l of CTAB buffer (200 mM Tris-HCl, 200 mM Na-EDTA, 8.2% NaCl w/v, 2% CTAB w/v, pH 7.5 (Merck KGaA, Germany). The sample was homogenised using a homogeniser (Bead Mill MAX, VWR Chemicals, USA) at maximum speed for 1 minute, then incubated at 65\u0026deg;C for 1.5 hours on the block heater (QBD2, Grant, USA). 500 \u0026micro;l chloroform (VWR Chemicals, USA) was added to each tube and mixed vigorously. The samples were then centrifuged in a micro-centrifuge (Micro Star 17R, VWR Chemicals, USA) at maximum speed for 5 min at room temperature, and the supernatant was transferred to clean tubes. The chloroform extraction step was repeated twice. A double volume of cold isopropanol was added, and the solution was left in the freezer (-20℃) overnight for DNA precipitation. The next day, the mixture was centrifuged at maximum speed for 5 min at 4℃. The supernatant was discarded, and the formed DNA pellet was washed with 70% cold ethanol, then centrifuged at maximum speed for 5 min at 4℃. After removing the supernatant, the pellet was dried in a block heater at 37℃ until the ethanol was completely evaporated. The DNA pellet was resuspended in 50 \u0026micro;l TE buffer (10 mM Tris, 10 mM Na-EDTA, pH 8.0 (Merck KGaA, Germany)). DNA concentration was measured using a fluorometer (Qubit Flex, Thermo Fisher, USA) with a Qubit dsDNA BR Assay Kit (Thermo Fisher, USA) according to the manufacturer's protocol. DNA samples were diluted to 10 ng/\u0026micro;l in TE buffer and stored at 4 ℃ until further analysis.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePolymerase chain reaction and Sanger sequencing\u003c/h2\u003e \u003cp\u003eThe polymerase chain reaction (PCR) was performed in a 30 \u0026micro;l reaction mixture using the Thermo Cycler T100 (Bio-Rad, Germany). Each reaction mixture contained 15 \u0026micro;l of DreamTaq PCR Master Mix (2\u0026times;) (Thermo Fisher, USA), 10 pmole of forward and reverse primers (Merck KGaA, Germany), 10 ng genomic DNA, and nuclease-free water (Thermo Fisher, USA).\u003c/p\u003e \u003cp\u003eFor bacterial identification, the \u003cem\u003e16S rRNA\u003c/em\u003e gene was used as the primary target for subsequent sequencing. Primers 27F and 1492R were used to amplify the \u003cem\u003e16S rRNA\u003c/em\u003e gene fragment containing the hypervariable regions (V1\u0026ndash;V9) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The PCR protocol consisted of an initial step for 5 min at 94℃, followed by 35 cycles of a denaturation step for 30 s at 94℃, a primer annealing step for 30 s at 55℃, and an elongation step for 1 min at 72℃. The final elongation was 7 min at 72℃, and reactions were held at 4\u0026deg;C.\u003c/p\u003e \u003cp\u003eAs an additional gene for bacterial identification, the DNA gyrase subunit B (\u003cem\u003egyr B)\u003c/em\u003e gene was selected [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. It was used exclusively for identifying bacteria that could not be classified to the species level using the \u003cem\u003e16S rRNA\u003c/em\u003e gene. Primers UP-1 and UP-2r were used for \u003cem\u003egyr B\u003c/em\u003e gene amplification, and primers UP-1S and UP-1Sr were used for Sanger sequencing. The PCR protocol was used as described by Yamamoto and Harayama (1995) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor fungal identification, PCR amplification of the Internal Transcribed Spacer (ITS) region separated by the 5.8S rRNA gene was amplified using ITS1 and ITS4 primers [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In total, 43 fungal cultures were identified. The PCR protocol consisted of an initial denaturation step of 2 min at 95\u0026deg;C, followed by 35 cycles of a denaturation step for 45 s at 95\u0026deg;C, a primer annealing step for 30 s at 55\u0026deg;C, and an elongation step for 1 min at 72\u0026deg;C. The final elongation was 4 minutes at 72\u0026deg;C, and reactions were held at 4\u0026deg;C. The size of the target fragments varied between 450 and 600 bp.\u003c/p\u003e \u003cp\u003eDue to the inability to identify all fungal representatives using ITS, the \u003cem\u003eβ-tubulin\u003c/em\u003e gene was chosen as an additional marker for fungal identification [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Primers Bt2a and Bt2b were used. The amplification protocol included an initiation step for 4 min at 95\u0026deg;C, followed by 35 cycles of a denaturation step for 45 s at 94\u0026deg;C, a primer annealing step for 45 s at 58\u0026deg;C, and an elongation step for 1 min at 72\u0026deg;C. The final elongation was 6 minutes at 72\u0026deg;C. The retention was at 4\u0026deg;C. The resulting amplicons were approximately 500 bp in length. The complete list of primers used in the study is shown in 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\u003ePrimers used for PCR amplification and subsequent Sanger sequencing.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimer sense\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence (5\u0026acute;\u0026rarr;3\u0026acute;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAmplification\u003c/p\u003e \u003cp\u003eproduct (bp)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGAGTTTGATYMTGGCTCAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003e16S rRNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026sim;1.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1492R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGTTACCTTGTTACGACTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUP-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGAAGTCATCATGACCGTTCTGCAYGCNGGNGGNAARTTYGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003egyrB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026sim;1.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUP-2r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGCAGGGTACGGATGTGCGAGCCRTCNACRTCNGCRTCNGTCAT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUP-1S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGAAGTCATCATGACCGTTCTGCA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUP-1Sr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGCAGGGTACGGATGTGCGAGCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eITS 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCCGTAGGTGAACCTGCGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eITS1\u0026thinsp;+\u0026thinsp;5.8S rDNA\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e+ITS2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e450\u0026ndash;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eITS 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCCTCCGCTTATTGATATGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBt2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGTAACCAAATCGGTGCTGCTTTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eβ-tubulin\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e~\u0026thinsp;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBt2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACCCTCAGTGTAGTGACCCTTGGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmplified PCR products were visualised using a gel electrophoresis system (Bio-Rad, Germany) following the addition of SYBR Safe DNA Gel Stain (Thermo Fisher, USA). Subsequent processing was performed only for samples that contained a single target fragment. The clean-up reaction was performed using 10 u Exonuclease I (Thermo Fisher, USA) and 1 u FastAP Thermosensitive Alkaline Phosphatase (Thermo Fisher, USA) for every 5 \u0026micro;L of unpurified PCR product solution [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The resulting mixture was incubated for 15 minutes at 37\u0026deg;C, then heated for another 15 minutes at 85\u0026deg;C to inactivate enzyme activity in the Thermo Cycler T100 (Bio-Rad, Germany). The concentration of pure amplified fragments was determined using a fluorometer (Qubit Flex, Thermo Fisher, USA) with a Qubit dsDNA BR Assay Kit (Thermo Fisher, USA) according to the manufacturer's protocol. The purified PCR products were stored in a fridge at 4℃.\u003c/p\u003e \u003cp\u003eSanger sequencing of all samples was performed using services from LGC Genomics GmbH (closed at the time of writing the manuscript; Berlin, Germany) and Macrogen Europe (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.macrogen-europe.com/\u003c/span\u003e\u003cspan address=\"https://www.macrogen-europe.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, Amsterdam, Netherlands). Before shipping, the concentration was adjusted to 10\u0026ndash;20 ng/ \u0026micro;l by nuclease-free water (Thermo Fisher, USA) according to the recommendations provided.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBioinformatics and statistical data analysis\u003c/h3\u003e\n\u003cp\u003eAll ATP and CFU data collected over a 2-year period (Oct-21, Dec-21, Feb-22, Apr-22, May-22, Aug-22, Oct-22), as well as data from the additional sampling in March 2024, were analysed. The Shapiro\u0026ndash;Wilk test was used to assess the normality of the distributions of the obtained RLU and CFU data. Calculated W and p-value show how closely the data follow a normal distribution. If W is close to 1, the data are normally distributed. If W is around 0.9, some deviated data are present. W\u0026thinsp;\u0026lt;\u0026thinsp;0.85 indicates strong deviation from normality. p-values\u0026thinsp;\u0026gt;\u0026thinsp;0.05 indicate that the data are normally distributed; p-values\u0026thinsp;\u0026le;\u0026thinsp;0.05 indicate that the data are not normally distributed.\u003c/p\u003e \u003cp\u003eThe median, first quartile (Q1), third quartile (Q3), interquartile range (IQR), and ranges of RLU values and CFU counts were calculated. Total CFU count was calculated for each time point, and a heat map was generated. To assess surface ATP levels, box plots of RLU values for each time point were created for each room. On boxplots, outliers were defined as values exceeding 1.5 times the IQR above Q3 or below Q1.\u003c/p\u003e \u003cp\u003eTo assess the strength and direction of association between ATP levels and microbial quantities in WoodW and PaintW rooms separately, non-parametric Spearman\u0026rsquo;s rank correlation coefficient (ρ) was calculated, and scatter plots were generated. If the ρ coefficient ranges from 0 to 1, it indicates a positive correlation between the two variables. If ρ is 0, there is no correlation, and if ρ varies from \u0026minus;\u0026thinsp;1 to 0, variables are inversely related [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. All statistical analyses and visualisations were performed in Python 3.14.0 using the \u003cem\u003ematplotlib, seaborn\u003c/em\u003e, \u003cem\u003epandas, scipy\u003c/em\u003e and \u003cem\u003enumpy\u003c/em\u003e libraries [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDNA sequences obtained in this study were compared with the GenBank database at the National Center for Biotechnology Information (NCBI) using the Basic Local Alignment Search Tool (BLAST) software on the NCBI website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov/BLAST/\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov/BLAST/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to identify their taxonomic affiliation. The mandatory criteria were sequence coverage\u0026thinsp;\u0026gt;\u0026thinsp;80%, species-level similarity between sequences of 98% \u0026minus;\u0026thinsp;100%, and genus-level similarity of 94% \u0026minus;\u0026thinsp;97%. With a similarity\u0026thinsp;\u0026lt;\u0026thinsp;94%, the organism was defined as an unknown fungus or an unknown bacterium [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The obtained sequences were submitted to GenBank under accession numbers PX917402 - PX917429, PX917474 - PX917488.\u003c/p\u003e \u003cp\u003eA four-level \u003cem\u003eRisk Group\u003c/em\u003e (RG) classification was used to identify bacteria and fungi as potential etiological agents of human diseases. These levels are based on the intrinsic virulence of microorganisms and routes of infection [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eRG1 - bacteria and fungi with low individual and community risk\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eRG2 - have moderate individual risk and limited community risk, are opportunistic human pathogens.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eRG3 - have high individual risk and low community risk, and usually cause bacterial diseases or mycoses.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eRG4 - bacteria with high individual and community risk usually produce serious human diseases. Not used for fungi.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe RG of all identified bacteria was determined according to the German technical rule TRBA 466 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and of fungi according to the information provided in the Atlas of Clinical Fungi [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo estimate the relative abundance of detected bacterial and fungal taxa, proportion was calculated based on the number of colonies of each identified bacterial/fungal species per Petri dish.\u003c/p\u003e \u003cp\u003eA Venn diagram was constructed to visualise the shared and unique taxonomic units identified in WoodW and PaintW rooms. The presence/absence of each taxonomic unit was taken into account. The diagram was visualized using the \u003cem\u003ematplotlib-venn\u003c/em\u003e library in Python 3.14.0 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In addition, the Jaccard Index was calculated to assess the similarity of microbial community between two locations based on the presence/absence of identified taxonomic units. The index ranges from 0 (completely distinct communities) to 1 (identical communities) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The calculation was performed in Python 3.14.0 using the \u003cem\u003epandas\u003c/em\u003e library [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePhylogenetic analysis was performed using the Maximum Likelihood method with 1000 bootstrap replicates in MEGA 12 [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], with preliminary multiple sequence alignment using the ClustalW package [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The iTOL tool provided a visualization of phylogenetic trees [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of surface ATP levels and microbial quantities\u003c/h2\u003e \u003cp\u003eA total of 308 measurements were conducted in two patient rooms, comprising 154 ATP and 154 CFU measurements. The mean RLU value for the PaintW room was 414.3, with a measurement range of 5 to 6583. For the WoodW room, the mean RLU was 278.4, with a range of 4 to 1622. Since the ATP threshold for hospital surfaces was set at 100 RLU, 48.7% of measurements in the PaintW room and 64.1% in the WoodW room exceeded this threshold.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Estimating the amount of ATP on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW). (\u003cb\u003ea\u003c/b\u003e) Box plot of RLU values detected during 2021\u0026ndash;2022 and in March 2024. \u003cb\u003e(b)\u003c/b\u003e Box plot of all RLU values detected between the PaintW and WoodW patient rooms throughout the study period. The red line indicates the 100 RLU threshold permissible for hospital surfaces. Circles indicate outliers; those\u0026thinsp;\u0026gt;\u0026thinsp;1200 RLU were excluded from the plots.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe median RLU values for the PaintW room ranged from 53.0 to 350.5 from October 2021 to March 2024. For the WoodW room, median RLU values ranged from 98.0 to 541.0 during the corresponding study period. Of 154 ATP measurements, 18 were identified as outliers. The highest RLU values were 6583 RLU and 4387 RLU on PaintW surfaces in May 2022.\u003c/p\u003e \u003cp\u003eThe differences in the distribution of all RLU values measured in both rooms over the entire experimental period are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eb. The median values were 150.0 RLU for the PaintW room and 225.5 RLU for the WoodW room. No significant statistical difference in RLU distribution was observed between the two patient rooms (p-value\u0026thinsp;=\u0026thinsp;0.1606 (\u0026gt;\u0026thinsp;0.05)).\u003c/p\u003e \u003cp\u003eSimultaneously with ATP measurement, CFU counts were determined on the same surfaces in both patient rooms to assess microbial quantities. The difference between the total CFU values during the period 2021\u0026ndash;2022 and March 2024 was shown as a barplot and a heatmap in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe total CFU count in both patient rooms ranged from 2 to 1203 CFU. The lowest CFU counts were detected at the beginning of the study in October 2021 in both rooms (3 CFU and 2 CFU), as well as in April and May 2022 in WoodW room (2 CFU and 2 CFU respectively), and in March 2024 in PaintW room (5 CFU). The highest CFU counts were detected for August 2022 in both rooms (1013 CFU and 1203 CFU) and in the PaintW room in December 2021 (1030 CFU).\u003c/p\u003e \u003cp\u003eThe Shapiro\u0026ndash;Wilk test indicated that CFU data deviated significantly from normality (W\u0026thinsp;=\u0026thinsp;0.55, p-value\u0026thinsp;=\u0026thinsp;9.26 (\u0026gt;\u0026thinsp;0.05)). Descriptive statistics of CFU counts are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In particular, the medium CFU counts vary widely, from 0 to 200. The lowest CFU counts were detected in October 2021, April 2022 and March 2024 in both rooms (median 0, IQR 0 and 0.5), in May 2022 in WoodW (median 0, IQR 0), and in February 2022 in PaintW (median 0, IQR 0.5).\u003c/p\u003e \u003cp\u003eThe highest CFU counts were recorded in the PaintW room in December 2021 (median 104.5, IQR 199) and in August 22 in both rooms (median 200, IQR 199.5). Using the benchmark threshold of \u0026lt;\u0026thinsp;2.5 CFU/cm\u003csup\u003e2\u003c/sup\u003e (25 CFU per Petri dish), microbial quantifications on hospital surfaces exceeded acceptable levels on half of the sampling dates, except for October 2021, December 2021, August 2022 in both rooms, February 2022 in WoodW, and May 2022 in PaintW.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of CFU counts detected in PaintW and WoodW patient rooms during 2021\u0026ndash;2022 and in March 2024. Non-normal distributed data presented as median (Q1\u0026ndash;Q3), Q1, Q3, interquartile range (IQR), and range (minimum\u0026ndash;maximum CFU counts)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIQR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eOct-21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eDec-21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;230\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFeb-22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eApr-22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMay-22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAug-22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e199,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;211\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e199,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eOct-22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e205,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e91,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMar-24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026ndash;200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePaintW\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0-200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eWoodW\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0-200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAfter evaluating CFU counts across the two patient rooms over the study period, the median and IQR counts in the PaintW and WoodW rooms were equal, and no significant statistical difference was detected (p\u0026thinsp;=\u0026thinsp;0.4293 (\u0026gt;\u0026thinsp;0.05)).\u003c/p\u003e \u003cp\u003eSpearman's Rank Correlation was used to assess the relationship between ATP level and microbial quantities in each of the two patient rooms. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows scatterplots with trendlines that visualise the correlation between ATP and CFU measurements across 308 measurements in PaintW (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) and WoodW (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eb) rooms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the PaintW room, a very weak positive correlation between ATP levels and microbial quantities, essentially zero, was observed (Spearman\u0026rsquo;s coefficient\u0026thinsp;=\u0026thinsp;0.092). The Spearman\u0026rsquo;s coefficient for the WoodW room was \u0026minus;\u0026thinsp;0.082, indicating a very weak negative correlation, essentially close to zero. In both cases, the distributions of ATP and CFU values within each patient's room were not statistically significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of microbial diversity\u003c/h2\u003e \u003cp\u003eIn March 2024, residual microbial presence was evaluated in both patient rooms. A total of 118 pure cultures were isolated and identified by Sanger sequencing, including 75 bacterial and 43 fungal cultures. Of these, 72 microbial pure cultures (48 bacteria and 24 fungi) were isolated from the PaintW patient room, whereas 46 microbial pure cultures (27 bacteria and 19 fungi) were isolated from the WoodW patient room.\u003c/p\u003e \u003cp\u003eBy sequencing the full-length \u003cem\u003e16S rRNA\u003c/em\u003e gene, 48 bacterial cultures were identified to species and 27 to genus. In particular, representatives of the genera \u003cem\u003eMethylobacterium, Pantoea\u003c/em\u003e, \u003cem\u003eMicrococcus, Microbacterium, Staphylococcus\u003c/em\u003e, and \u003cem\u003eBacillus\u003c/em\u003e were additionally identified by the \u003cem\u003egyrB\u003c/em\u003e gene. The \u003cem\u003egyrB\u003c/em\u003e gene was used to identify 8 bacterial cultures from the PaintW patient room and 9 from the WoodW patient room. Overall, the \u003cem\u003egyrB\u003c/em\u003e gene sequencing enabled species-level identification of bacterial genera \u003cem\u003ePantoea\u003c/em\u003e, \u003cem\u003eMicrococcus\u003c/em\u003e, and \u003cem\u003eEnterobacter\u003c/em\u003e. At the same time, species-level resolution was not achieved for the \u003cem\u003eMethylobacterium, Microbacterium, and Bacillus\u003c/em\u003e genera, and amplification of the \u003cem\u003egyrB\u003c/em\u003e gene was unsuccessful for isolates of the \u003cem\u003eStaphylococcus\u003c/em\u003e genus.\u003c/p\u003e \u003cp\u003eITS sequencing allowed the identification of 32 pure fungal cultures to species and 11 cultures to genus. For \u003cem\u003eChaetomium, Aspergillus, Penicillium\u003c/em\u003e, and \u003cem\u003eBotrytis\u003c/em\u003e genera, species-level identification was insufficient, and additional sequencing using the \u003cem\u003eβ-tubulin\u003c/em\u003e gene was performed. Thus, 9 fungal cultures from the PaintW room and 10 fungal cultures from the WoodW room were additionally identified by the \u003cem\u003eβ-tubulin\u003c/em\u003e gene. This marker gene successfully identified representatives of the \u003cem\u003eChaetomium\u003c/em\u003e and \u003cem\u003eAspergillus\u003c/em\u003e genera, but did not provide sufficient resolution for the \u003cem\u003ePenicillium\u003c/em\u003e and \u003cem\u003eBotrytis\u003c/em\u003e genera.\u003c/p\u003e \u003cp\u003eThe relative abundance of bacteria and fungi in the PaintW and WoodW patient rooms is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003e. There were significantly more bacteria than fungi on the surfaces of both patient rooms: 74.6% bacteria and 25.4% fungi in the PaintW room, 68.7% bacteria and 31.3% fungi in the WoodW room.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOverall, 37 species from 23 genera were identified, including 24 bacterial and 13 fungal species. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003e demonstrates the relative abundance of the identified bacterial and fungal genera in both patient rooms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe bacterial community comprised representatives of 15 genera belonging to the phyla \u003cem\u003eBacillota\u003c/em\u003e, \u003cem\u003eActinomycetota\u003c/em\u003e, and \u003cem\u003ePseudomonadota\u003c/em\u003e. The most frequently detected bacterial genera were \u003cem\u003eStaphylococcus\u003c/em\u003e (20% in PaintW and 18.1% in WoodW) and \u003cem\u003eBacillus\u003c/em\u003e (3% in PaintW and 15.5% in WoodW). Additionally, 26.2% and 14,6% of the bacterial community in the PaintW room belonged to the genera \u003cem\u003eMethylobacterium\u003c/em\u003e and \u003cem\u003eRothia\u003c/em\u003e, respectively. The most abundant bacterial genus in the WoodW room was \u003cem\u003ePantoea\u003c/em\u003e, which accounted for approximately 29.7% of the microbial community.\u003c/p\u003e \u003cp\u003eAll identified fungi belonged to 8 genera of the \u003cem\u003eAscomycota\u003c/em\u003e phylum. In the PaintW room, approximately 1% to 7% of the microbial community was comprised of fungi from all 8 genera. All fungi found in the WoodW room belonged to the genera \u003cem\u003ePenicillium\u003c/em\u003e (30.8%), \u003cem\u003eChaetomium\u003c/em\u003e (0.5%), and \u003cem\u003ePaecilomyces\u003c/em\u003e (0.15%).\u003c/p\u003e \u003cp\u003e Among the 24 identified bacterial species, both mesophilic aerobic and anaerobic species were found according to information available in databases BacDive and NCBI. Most bacterial representatives were in risk group 1 (RG 1). At the same time, \u003cem\u003eBacillus cereus, Moraxella osloensis, Pantoea septica\u003c/em\u003e, \u003cem\u003eStaphylococcus epidermidis\u003c/em\u003e, and \u003cem\u003eStaphylococcus hominis\u003c/em\u003e were assigned to RG 2 in PaintW. In the WoodW room, \u003cem\u003eEnterobacter asburiae, P. septica\u003c/em\u003e, and \u003cem\u003eS. hominis\u003c/em\u003e belonged RG 2. \u003cem\u003eBacillus\u003c/em\u003e sp. and \u003cem\u003eStaphylococcus\u003c/em\u003e sp., which were present in the microbial communities of both rooms, were considered to potentially belong RG 1 or RG 2, however species-level assignment was not possible. The vast majority of identified fungi belonged to saprotrophs and moulds, and were classified as RG 1. No representatives of RG 3 and RG 4, which pose a high risk to humans, were identified. Detailed information on all bacterial and fungal species identified in the study is shown in Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBacteria species identified on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW), with their relative abundance, Risk group, and marker genes used for identification.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhylum\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLive style\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRelative abundance %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRisk Group\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMarker gene\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e Frankland and Frankland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eanaerobe, mesophilic bacteria, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\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\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA, \u003cem\u003egyrB\u003c/em\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\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe or anaerobe, mesophilic bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA, \u003cem\u003egyrB\u003c/em\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 (Ehrenberg) Cohn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eanaerobe, mesophilic bacteria, opportunistic human pathogen\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\u003e0,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBacillus velezensis\u003c/em\u003e Ruiz-Garc\u0026iacute;a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe, mesophilic bacteria\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\u003e0,2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDermacoccus nishinomiyaensis (Oda) Stackebrandt\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActinomycetota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emesophilic bacteria, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDietzia cinnamea\u003c/em\u003e (Nesterenko and Harrison) Rainey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActinomycetota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emicroaerophile, mesophilic bacteria, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter asburiae\u003c/em\u003e Brenner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePseudomonadota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eanaerobe, mesophilic bacteria, opportunistic human pathogen\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\u003e0,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA, \u003cem\u003egyrB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKocuria marina\u003c/em\u003e Kim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActinomycetota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe, mesophilic bacteria, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,5\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMethylobacterium adhaesivum\u003c/em\u003e Gallego\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePseudomonadota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobic, mesophilic bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,3\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMethylobacterium\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePseudomonadota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobic, mesophilic bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23,8\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA, gyrB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMicrobacterium\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActinomycetota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobic, heat-resistant bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA, gyrB\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 (Schroeter) Cohn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActinomycetota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe, mesophilic bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA, gyrB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMicromonospora aurantiaca\u003c/em\u003e Sveshnikova\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActinomycetota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emesophilic\u0026nbsp;bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMoraxella osloensis\u003c/em\u003e B\u0026oslash;vre and Henriksen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePseudomonadota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe, mesophilic bacteria, symbiont of nematode \u003cem\u003ePhasmarhabditis hermaphrodita\u003c/em\u003e Schneider\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\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\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePaenibacillus\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eanaerobic, mesophilic bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,5\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePantoea septica\u003c/em\u003e Brady\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePseudomonadota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe, mesophilic bacteria, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA, gyrB\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRothia amarae\u0026nbsp;Fan\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActinomycetota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emicroaerophile, mesophilic bacteria, opportunistic human pathogen\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\u003e0,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRothia kristinae\u003c/em\u003e (Kloos) Nouioui\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActinomycetota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emicroaerophile, mesophilic bacteria, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus capitis\u003c/em\u003e Kloos and Schleifer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe, mesophilic bacteria, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,4\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStaphylococcus epidermidis (Winslow and Winslow) Evans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eanaerobe, mesophilic bacteria, human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,9\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\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\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 Kloos and Schleifer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe, mesophilic bacteria, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17,8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe or anaerobe, mesophilic bacteria, human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus warner\u003c/em\u003ei Kloos and Schleifer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBacillota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe, mesophilic bacteria, opportunistic human pathogen\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\u003e0,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStreptomyces thermocarboxydus\u003c/em\u003e Kim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActinomycetota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaerobe, thermophilic bacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16S rRNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Data taken from databases BacDive (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://beta.bacdive.dsmz.de/\u003c/span\u003e\u003cspan address=\"https://beta.bacdive.dsmz.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), NCBI Taxonomy Browser (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e2\u003c/sup\u003e Risk groups for bacteria are defined according to TRBA 466 technical rule [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFungal species identified on surfaces in patient rooms with painted (PaintW) and wood walls (WoodW), with their relative abundance, Risk group, and marker genes used for identification.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhylum\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLive style\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRelative abundance %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRisk Group\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMarker gene\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePaintW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWoodW\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAspergillus niger\u003c/em\u003e van Tieghem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, mould, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,3\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS, β-tubulin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAspergillus tubingensis\u003c/em\u003e\u0026nbsp;Mosseray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, mould, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,3\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS, β-tubulin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBotrytis\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, mould\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,3\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\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS, β-tubulin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChaetomium globosum\u003c/em\u003e Kunze\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, mould, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS, β-tubulin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCladosporium herbarum\u003c/em\u003e (Pers.) Link\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS, β-tubulin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCladosporium\u0026nbsp;halotolerans\u003c/em\u003e Zalar, de Hoog, Schroers, Crous, Groenewald and Gunde-Cimerman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,2\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eConiothyrium telephii\u003c/em\u003e (Allescher) Verkley and Gruyter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,8\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePaecilomyces variotii\u003c/em\u003e Bainier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, opportunistic human pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePenicillium chrysogenum\u003c/em\u003e Thom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, mould\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,3\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS, β-tubulin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePenicillium corylophilum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, mould\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePenicillium digitatum\u003c/em\u003e (Persoon) Saccardo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, mould\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\u003e0,1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePenicillium\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSaprotroph, mould\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\u003e30,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS, β-tubulin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePyrenophora triseptata\u003c/em\u003e (Drechsler) Rossman and Hyde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAscomycota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlant pathogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,3\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eITS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e NCBI Taxonomy Browser (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and the Atlas of Clinical Fungi [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e2\u003c/sup\u003e Risk groups for bacteria are defined according to the Atlas of Clinical Fungi [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo assess the similarity of microbial communities between the two rooms, Venn diagrams were constructed to visualise the numbers of unique and shared fungal and bacterial taxa between the PaintW and WoodW patient rooms. Figure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003ea shows that 14 unique genera were identified in PainW room and 1 genus in WoodW room, while eight genera were shared between rooms (\u003cem\u003ePaecilomyces\u003c/em\u003e, \u003cem\u003ePenicillium\u003c/em\u003e, \u003cem\u003eChaetomium, Rothia\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e, \u003cem\u003ePantoea\u003c/em\u003e, \u003cem\u003eMicrococcus\u003c/em\u003e, and \u003cem\u003eBacillus)\u003c/em\u003e. The corresponding Jaccard Index was 0.35.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe diagram in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eb shows the presence of 21 unique species in the PaintW room and 7 unique species in the WoodW room. 9 shared species were identified in both patient rooms (\u003cem\u003ePaecilomyces variotii\u003c/em\u003e, \u003cem\u003ePenicillium corylophilum\u003c/em\u003e, \u003cem\u003eChaetomium globosum\u003c/em\u003e, \u003cem\u003eRothia kristinae\u003c/em\u003e, \u003cem\u003eS. hominis, Staphylococcus sp\u003c/em\u003e., \u003cem\u003eP. septica\u003c/em\u003e, \u003cem\u003eMicrococcus luteus\u003c/em\u003e, and \u003cem\u003eBacillus\u003c/em\u003e sp.). The Jaccard Index was 0.24. Overall, the data obtained demonstrates low similarity in microbial species and genus composition between the two patient rooms studied.\u003c/p\u003e \u003cp\u003eThe phylogenetic relationships among the identified bacterial and fungal species were assessed based on the obtained 16S rRNA and ITS sequences. Figure\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows a phylogenetic tree containing the 30 microbial species from the PaintW patient room. A clear clustering of bacterial species was observed, distinct from that of fungal species. Bacteria belonging to the phylum \u003cem\u003eActinomycetota\u003c/em\u003e formed a separate clade, which included \u003cem\u003eStreptomyces thermocarboxydus\u003c/em\u003e, \u003cem\u003eDietzia cinnamea\u003c/em\u003e, \u003cem\u003eMicromonospora aurantiaca\u003c/em\u003e, \u003cem\u003eMicrobacterium\u003c/em\u003e sp., \u003cem\u003eMicrococcus luteus\u003c/em\u003e, \u003cem\u003eDermacoccus nishinomiyaensis\u003c/em\u003e, \u003cem\u003eRothia kristinae\u003c/em\u003e, and \u003cem\u003eKocuria marina\u003c/em\u003e. Species of the phylum \u003cem\u003eBacillota\u003c/em\u003e (\u003cem\u003ePaenibacillus\u003c/em\u003e, \u003cem\u003eBacillus\u003c/em\u003e, and \u003cem\u003eStaphylococcus\u003c/em\u003e sp.) clustered together with a 100% bootstrap rate.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe phylogenetic tree, which contains the 15 species isolated from surfaces in the WoodW patient room, is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e9\u003c/span\u003e. Separate clades were formed for bacterial and fungal species. Additionally, a clear separation of bacterial species by phylum affiliation was observed. \u003cem\u003eP. septica\u003c/em\u003e and \u003cem\u003eE. asburiae\u003c/em\u003e formed a separate clade as representatives of the \u003cem\u003ePseudomonadota\u003c/em\u003e, \u003cem\u003eM. luteus\u003c/em\u003e and \u003cem\u003eRothia\u003c/em\u003e species - as \u003cem\u003eActinomycetota\u003c/em\u003e, and \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003eStaphylococcus\u003c/em\u003e species - as \u003cem\u003eBacillota\u003c/em\u003e. In addition, both phylogenetic trees show clear groupings within the same genus, particularly \u003cem\u003eStaphylococcus\u003c/em\u003e, \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003eMethylobacterium\u003c/em\u003e, \u003cem\u003ePenicillium\u003c/em\u003e, \u003cem\u003eAspergillus\u003c/em\u003e, and others.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eImproving the hospital environment, particularly through interior changes, positively affects the well-being and comfort of both patients and medical staff [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. However, significant changes in patients' stay conditions, particularly the installation of new materials in patient rooms, such as wood panels, can affect cleanliness, environmental contamination, and the biodiversity of the microbial community within those facilities. The study of such an impact is a crucial step towards the widespread adoption of wooden materials for the decoration and design of hospital premises.\u003c/p\u003e \u003cp\u003eThis study assessed the microbial dynamics and residual diversity on surfaces in two patient rooms in the same hospital ward. The main difference between the patient rooms was the presence of designer wood panels. Measurements of ATP levels and microbial quantities indicated that surface contamination fluctuated over time in both rooms, reflecting the dynamic nature of hospital environments. Although a substantial proportion of ATP measurements exceeded the benchmark threshold of 100 RLU, no statistically significant differences in ATP levels were observed between the room with painted walls and the room with wooden panels. This suggests that the presence of wooden wall panels did not affect overall surface cleanliness when compared with conventional painted surfaces.\u003c/p\u003e \u003cp\u003eDuring the study period, high microbial levels were observed in both rooms, which frequently exceeded recommended thresholds for hospital surfaces [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, no statistically significant differences in CFU levels were detected between the two patient rooms over the study period. These findings indicate that installing wooden wall panels did not lead to increased microbial quantities compared with a standard painted-wall patient room. This is likely due to several factors, such as the characteristics of scheduled cleaning and ventilation, the number of patients, etc.\u003c/p\u003e \u003cp\u003eThe discussion about the relationship between ATP levels and microbial quantities remains relevant today. Consistent with several previous studies [\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. no meaningful correlation between ATP levels and microbial quantities on surfaces in both patient rooms. This lack of correlation reflects the fact that ATP bioluminescence detects total organic material on surfaces, including both microbial and non-microbial residues, such as skin flakes, body fluids, and food particles. On the other hand, even if microbial quantities are low, the presence of other biological material on surfaces can serve as a source of nutrients for bacterial and fungal growth, including those pathogenic to\u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While ATP monitoring remains a fast tool for assessing overall surface cleanliness, it cannot be used as a direct indicator of microbial load or sterility. Therefore, the removal of organic residues remains important, as such material may serve as a substrate for microbial growth [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study highlights differences in microbial diversity between patient room surfaces with different wall materials. Molecular identification of the isolates revealed substantially greater diversity of bacterial and fungal species on surfaces in the painted-wall room compared with the room with wooden wall panels. At both the genus and species levels, microbial community similarity between the two rooms was low, suggesting distinct surface-associated microbiomes. Previous studies showed that the formation of the surface microbiome in hospitals is a complex dynamic process influenced by a number of factors, including the effects of surface materials, clinical activities [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], cleaning and ventilation schedules, and the number of patients who actively release their own microbes into hospital wards, thus changing the environment [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Because the rooms were located in the same ward and shared similar characteristics, cleaning regimes, ventilation conditions, and patient use, the wall material is a plausible contributing factor to the observed differences.\u003c/p\u003e \u003cp\u003eThis study showed significantly lower microbial diversity on the surfaces of the room with wood panels. One possible explanation for the lower microbial diversity observed in the room with wooden wall panels relates to the inherent properties of wood. Previous studies have suggested that wood may exhibit antimicrobial effects due to its porous, hygroscopic structure and chemical composition [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. By absorbing moisture from the surface, wood may reduce microbial survival through desiccation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], while certain wood extractives have been reported to possess antimicrobial activity [\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Although these mechanisms are consistent with the observed patterns, the present study was not designed to directly test antimicrobial activity, and alternative explanations, for instance microclimatic differences at the surface level, cannot be excluded and pattern explanation requires detailed future study.\u003c/p\u003e \u003cp\u003eThe culture-based approach used in this study allowed detailed identification of viable bacterial and fungal representatives but also imposed limitations on species resolution and community coverage compared with DNA-based approaches. While 16S rRNA gene sequencing and ITS sequencing enabled identification of most isolates, several bacterial and fungal genera required additional markers, and some taxa could not be resolved to the species level. Future studies incorporating complementary molecular approaches, such as high-throughput sequencing, could provide a more comprehensive view of microbial community composition and functional potential.\u003c/p\u003e \u003cp\u003eOverall, the results demonstrate that installing wooden wall panels in a hospital patient room did not compromise surface microbial dynamics. At the same time, the presence of wood was associated with a distinct and less diverse surface microbiome compared with a painted-wall room. Our findings support the careful consideration of wood as an interior material in hospitals with appropriate cleaning and maintenance. Further long-term, multi-site studies are needed to better understand the formation of the surface microbiome and to evaluate the broader implications of wood use in healthcare facilities.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, surface microbial dynamics and residual diversity in two patient rooms with painted and wooden walls were assessed, and the microbial biodiversity in these rooms was investigated. High ATP levels and microbial quantities were detected on the surfaces of both patient rooms at half-time points, indicating abnormal surface contamination and insufficient cleanliness. Importantly, no statistically significant differences in ATP levels or microbial quantities were observed between the two patient rooms throughout the study period. No clear correlation was found between ATP levels and microbial quantities in both patient rooms, because the ATP method measures total organic material on surfaces rather than viable microorganisms alone. This highlights the complementary roles of ATP monitoring and culture-based methods in evaluating hospital surface hygiene.\u003c/p\u003e \u003cp\u003eCulture isolation and Sanger sequencing revealed that all bacterial and fungal species belonged exclusively to risk groups 1 and 2, indicating a low risk to human health. Microbial biodiversity differed significantly between the rooms, with a higher number of bacterial and fungal species detected in the painted wall room, whereas the presence of wooden wall panels was associated with lower microbial biodiversity without increased contamination. This pattern may be related to intrinsic properties of wood, such as its physical structure or chemical composition, which confer antimicrobial properties; further targeted studies of these phenomena are required.\u003c/p\u003e \u003cp\u003eOverall, the findings indicate that wood, as a decorative indoor material, does not negatively affect surface microbial dynamics or residual diversity in hospital patient rooms. These results support the careful consideration of wood in the design of hospital facilities, together with appropriate cleaning and maintenance practices.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: The authors express their gratitude to the Kempe Foundation and, personally, to Alice Kempe for providing a postdoctoral fellowship to Anastasia Postovoitova. The authors are also grateful to Bror Sundqvist and Tetiana Krupodorova for their support and assistance in data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003eConceptualization, O.M., O.K; methodology, O.M.; investigation, A.P., O.M., K.D., L.K.; software, A.P.; writing \u0026ndash; original draft, A.P.; writing \u0026ndash; review \u0026amp; editing, K.D., O.M., A.P., O.K; project administration and supervision, O.M. All authors have read and agreed with the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003eThe financial support provided by Swedish Wood for the project \u0026ldquo;Tr\u0026auml;inredning i patientrum\u0026rdquo; (Wooden interior design in patient rooms, 2019 - 2025), by Swedish Agency for Economic and Regional Growth (Tillv\u0026auml;xtverket) as part of the project \u0026ldquo;Fr\u0026auml;mja \u0026ouml;kat byggande av flerfamiljshus i tr\u0026auml;\u0026rdquo; (grant number 20203193). Anastasiia Postovoitova was supported by the Kempe Foundation. Open access funding provided by the Wood Science and Engineering subject atLule\u0026aring; University of Technology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e The datasets generated and analysed during the current study are available in GenBank database at NCBI, accession numbers PX917402 - PX917429, PX917474 - PX917488.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMauri, D. et al. Interior design: a new perspective in supportive care of patients with acute onset of debilitating diseases. \u003cem\u003ePalliat. Med. 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Wood Wood Prod.\u003c/em\u003e \u003cb\u003e83\u003c/b\u003e, 165. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00107-025-02315-y\u003c/span\u003e\u003cspan address=\"10.1007/s00107-025-02315-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hospital hygiene, Wall material, Microbial dynamics, ATP measurement, Microbial biodiversity","lastPublishedDoi":"10.21203/rs.3.rs-9114856/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9114856/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWood is a biobased material that supports long-term carbon storage; however, its suitability for use in healthcare facility interiors remains insufficiently studied. This study assessed surface microbial dynamics and residual diversity in patient rooms with conventional painted wall materials and with designer wooden wall panels. Surface microbial dynamics were evaluated using adenosine triphosphate (ATP) measurements and the swab method with colony-forming unit (CFU) counting. Bacterial and fungal cultures from each patient room were analysed by Sanger sequencing. No significant differences in ATP levels or microbial quantities were observed between rooms. In addition, no correlation was observed between ATP levels and CFU counts within each patient room due to methodological differences. In total, 37 microbial species (24 bacterial and 13 fungal) from 23 genera belonging to risk groups 1 and 2 were identified. Significant differences in microbial biodiversity were observed among the patient rooms studied. Fewer unique taxa were detected in the room with wooden walls. This study confirms that wood, as a decorative indoor material, does not negatively affect surface microbial dynamics or lead to excessive microbial spread or biodiversity. These findings support the feasibility of using wood as a finishing material in hospital facilities.\u003c/p\u003e","manuscriptTitle":"Surface microbial dynamics and residual diversity in patient rooms with wooden and painted walls","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 16:46:46","doi":"10.21203/rs.3.rs-9114856/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"74184713838106042657322531109872398739","date":"2026-05-09T17:59:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9079659055110687537445665839789352732","date":"2026-04-14T19:01:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293709752777061506240617918396838708508","date":"2026-03-29T19:02:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-24T17:31:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-24T16:36:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-24T13:05:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-18T09:31:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-18T07:48:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"460d5cd6-7470-4284-87f5-77f9c8700d9b","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"74184713838106042657322531109872398739","date":"2026-05-09T17:59:34+00:00","index":72,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":65129044,"name":"Biological sciences/Ecology"},{"id":65129045,"name":"Earth and environmental sciences/Ecology"},{"id":65129046,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2026-03-26T16:46:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 16:46:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9114856","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9114856","identity":"rs-9114856","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}