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. 2014 Sep 26;9(9):e108598.
doi: 10.1371/journal.pone.0108598. eCollection 2014.

Hard surface biocontrol in hospitals using microbial-based cleaning products

Alberta Vandini  1 , Robin Temmerman  2 , Alessia Frabetti  1 , Elisabetta Caselli  3 , Paola Antonioli  4 , Pier Giorgio Balboni  3 , Daniela Platano  5 , Alessio Branchini  6 , Sante Mazzacane  1
Affiliations

Hard surface biocontrol in hospitals using microbial-based cleaning products

Alberta Vandini et al. PLoS One. .

Abstract

Background: Healthcare-Associated Infections (HAIs) are one of the most frequent complications occurring in healthcare facilities. Contaminated environmental surfaces provide an important potential source for transmission of many healthcare-associated pathogens, thus indicating the need for new and sustainable strategies.

Aim: This study aims to evaluate the effect of a novel cleaning procedure based on the mechanism of biocontrol, on the presence and survival of several microorganisms responsible for HAIs (i.e. coliforms, Staphyloccus aureus, Clostridium difficile, and Candida albicans) on hard surfaces in a hospital setting.

Methods: The effect of microbial cleaning, containing spores of food grade Bacillus subtilis, Bacillus pumilus and Bacillus megaterium, in comparison with conventional cleaning protocols, was evaluated for 24 weeks in three independent hospitals (one in Belgium and two in Italy) and approximately 20000 microbial surface samples were collected.

Results: Microbial cleaning, as part of the daily cleaning protocol, resulted in a reduction of HAI-related pathogens by 50 to 89%. This effect was achieved after 3-4 weeks and the reduction in the pathogen load was stable over time. Moreover, by using microbial or conventional cleaning alternatively, we found that this effect was directly related to the new procedure, as indicated by the raise in CFU/m2 when microbial cleaning was replaced by the conventional procedure. Although many questions remain regarding the actual mechanisms involved, this study demonstrates that microbial cleaning is a more effective and sustainable alternative to chemical cleaning and non-specific disinfection in healthcare facilities.

Conclusions: This study indicates microbial cleaning as an effective strategy in continuously lowering the number of HAI-related microorganisms on surfaces. The first indications on the actual level of HAIs in the trial hospitals monitored on a continuous basis are very promising, and may pave the way for a novel and cost-effective strategy to counteract or (bio)control healthcare-associated pathogens.

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Conflict of interest statement

Competing Interests: The authors declare that they received funding from the Copma scrl commercial company, and that Dr. Robin Temmerman is affiliated to a commercial funder of this study (Chrisal, Lommel, Belgium). This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. Effect of microbial cleaning on coliforms surface counts.
Surface counts for coliforms at the San Giorgio (A), Sant'Anna (B) and AZ Lokeren (C) hospital settings. Results are reported as relative percentage of reduction compared to the control, which was cleaned with conventional (disinfecting) cleaning products. The control is represented by the value of microbial surface contamination (CFU count) at the beginning of the trials (week 0), whose CFU count was set as the 100% in order to obtain reliable comparisons among the three structurally different hospital settings. The analysis indicated that results observed were statistically significant (Table S2).
Figure 2
Figure 2. Effect of microbial cleaning on S. aureus surface counts.
Surface counts for S. aureus at the San Giorgio (A), Sant'Anna (B) and AZ Lokeren (C) hospital settings. Results are reported as relative percentage of reduction compared to the control, which was cleaned with conventional (disinfecting) cleaning products. The analysis indicated that results observed were statistically significant (Table S3).
Figure 3
Figure 3. Effect of microbial cleaning on C. difficile surface counts.
Surface counts are reported as relative percentage of reduction compared to the control, which was cleaned with conventional (disinfecting) cleaning products. The statistical analysis is reported in Table S4.
Figure 4
Figure 4. Effect of microbial cleaning on Candida albicans surface counts.
Surface counts are reported as relative percentage of reduction compared to the control, which was cleaned with conventional (disinfecting) cleaning products. The analysis indicated that results observed were statistically significant (Table S5).
Figure 5
Figure 5. Time course of coliforms and S. aureus surface counts.
A time-trial of coliforms (black circles) and S. aureus (white circles) counts was performed at the geriatrics department of the AZ Lokeren hospital. Surface counts, indicated as CFU/m2, were measured after application of conventional (from week −2 to 0) and microbial (from week 0 to 2) cleaning, followed by a subsequent period of conventional cleaning (from week 2 to 10). The application of the probiotic-based products led to a significant decrease in the pathogenic load of coliforms (p<0.0001) and S. aureus (p = 0.003). Black arrow: beginning of the microbial cleaning. Black dotted arrow: conventional cleaning.
Figure 6
Figure 6. Antimicrobial resistance genes profile by qPCR assay.
The DNA of the Bacillus spp. from the cleaning products (Original) and from 20 Bacillus spp. colonies isolated from the treated surfaces up to 12 months after the beginning of the cleaning protocol (Isolates), was analyzed by qPCR Microarray to detect the presence of antibiotic resistance genes (R genes). DNA from E. coli JM101 strain was used as negative control (NTC). Results are reported as folds of gene copy number comparing the detected values with those obtained in the negative control DNA, both normalized for bacterial cell number. Those genes coding for antibiotics that are not included in the figure (i.e. vancomycin, tetracyclins) were negative both in Original and Isolates collections. Results are reported as mean ± standard deviation.
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