Development of a biofilm model that recapitulates the infected wound site

The challenges facing microbiologists working with biofilms in the laboratory are plentiful. This is applicable to any niche in the human body, including the oral cavity, lung, vaginal and skin. Indeed, a plethora of considerations must be made when developing biofilm models, including but not limited to, microbial species inclusion, culture conditions, maturation duration, nutrient constituents, and substrate selection. In the field of wound-related biofilm work this is no different ^1,2. Our ever-improving understanding of the landscape of chronic wounds in vivo is starting to assist development of complex in vitro model systems. However, those models that do exist are far from perfect. At this juncture, our journey to travel the “wound in 80 millimeters” started by optimizing a complex biofilm model that contained a variety of microorganisms. Given the presence of hypoxic or anoxic microenvironments in the infected wound bed ^3-5, we deemed it pertinent to incorporate anaerobic microorganisms alongside fungi, skin commensals and aerophilic bacteria. Their growth was investigated under varying levels of O₂. We believed the resulting mature biofilm complexity matched up well with the polymicrobial and interkingdom nature of infected chronic wounds, including a fungal element, species that are present in vivo yet often overlooked in such models ^6-10.

Mimicking complex host-pathogen interactions in a 24-well plate! 

Once biofilm complexity was assessed through compositional qPCR analysis and visualized with scanning electron microscopy, and after treatment studies and some preliminary co-culture experiments with a THP-1 cell line, the next task was arguably the most complicated of the entire study. This involved combining the mature biofilm with a reconstituted human epidermis (RHE) for assessment of the host response following stimulation. Our research group has published similar co-culture models in recent years pertaining to host-pathogen interactions in the oral cavity and nosocomial infections of the skin ^11,12. Utilising a commercially available RHE from Skinethic, Episkin (https://www.episkin.com/), treated and untreated biofilms were exposed to the tissue for 24 hours prior to transcriptional and proteomic profiling. The latter involved a relatively novel technique called Olink technology, a methodology which, in simple terms, incorporates the principle of ELISAs with qPCR, for identification of a range of biomarkers related to inflammation. To our knowledge this technique had never been seen before using in vitro tissue models, as most Olink studies to date are utilized for clinical samples.

We were able to document an interesting proteomic signature released by the tissue following exposure to different biofilms dependent on the treatment modality, albeit only a third of the panel of 92 proteins were detected. This was likely explained by an oversight in our study design, highlighted by an astute reviewers’ comments that not all proteins might be released by the cells. Indeed, upon further investigation we found that several biomarkers in the “inflammation panel” were, indeed, cell membrane anchored! I suppose this is what happens when microbiologists dabble in the field of immunology! Assessment of the proteomic response of RHE tissue lysates would resolve such an issue, but unfortunately went far beyond the scope of the study. Nevertheless, the spent proteins that were detected provided a unique profile in the RHE, giving rise to an excellent proof-of-concept study for the utilization of the Olink technology in similar, but also results that may influence a clinician’s choice for management of chronic wounds.

Future directions for this and similar co-culture models

Although potentially biased, we believe that the reproducibly of such complex 3D co-culture models are high and provide an excellent platform for investigating a wide range of host-pathogen interactions. Furthermore, given the ever-improving landscape in regard to next-generation platforms for assessing transcriptional, proteomic and metabolic changes, we envisage that these model systems could provide an excellent gateway into preclinical studies for biofilm-driven inflammatory diseases. From running this study, our advice would be to carefully plan your experiments, maximizing the number of outputs for each individual tissue. In our opinion, the scope of research for these organotypic platforms are endless.

 References

1          Kadam, S. et al. Bioengineered Platforms for Chronic Wound Infection Studies: How Can We Make Them More Human-Relevant? Front Bioeng Biotechnol 7, 418, doi:10.3389/fbioe.2019.00418 (2019).

2          Thaarup, I. C. & Bjarnsholt, T. Current In Vitro Biofilm-Infected Chronic Wound Models for Developing New Treatment Possibilities. Adv Wound Care (New Rochelle) 10, 91-102, doi:10.1089/wound.2020.1176 (2021).

3          Ruangsetakit, C., Chinsakchai, K., Mahawongkajit, P., Wongwanit, C. & Mutirangura, P. Transcutaneous oxygen tension: a useful predictor of ulcer healing in critical limb ischaemia. J Wound Care 19, 202-206, doi:10.12968/jowc.2010.19.5.48048 (2010).

4          James, G. A. et al. Microsensor and transcriptomic signatures of oxygen depletion in biofilms associated with chronic wounds. Wound Repair Regen 24, 373-383, doi:10.1111/wrr.12401 (2016).

5          Wu, Y., Klapper, I. & Stewart, P. S. Hypoxia arising from concerted oxygen consumption by neutrophils and microorganisms in biofilms. Pathog Dis 76, doi:10.1093/femspd/fty043 (2018).

6          Chellan, G. et al. Spectrum and prevalence of fungi infecting deep tissues of lower-limb wounds in patients with type 2 diabetes. J Clin Microbiol 48, 2097-2102, doi:10.1128/JCM.02035-09 (2010).

7          Dowd, S. E. et al. Survey of bacterial diversity in chronic wounds using pyrosequencing, DGGE, and full ribosome shotgun sequencing. BMC Microbiol 8, 43, doi:10.1186/1471-2180-8-43 (2008).

8          Kalan, L. et al. Redefining the Chronic-Wound Microbiome: Fungal Communities Are Prevalent, Dynamic, and Associated with Delayed Healing. mBio 7, doi:10.1128/mBio.01058-16 (2016).

9          Kalan, L. & Grice, E. A. Fungi in the Wound Microbiome. Adv Wound Care (New Rochelle) 7, 247-255, doi:10.1089/wound.2017.0756 (2018).

10        Dowd, S. E. et al. Survey of fungi and yeast in polymicrobial infections in chronic wounds. J Wound Care 20, 40-47, doi:10.12968/jowc.2011.20.1.40 (2011).

11        Brown, J. L. et al. Candida auris Phenotypic Heterogeneity Determines Pathogenicity In Vitro. mSphere 5, doi:10.1128/mSphere.00371-20 (2020).

12        Brown, J. L. et al. Biofilm-stimulated epithelium modulates the inflammatory responses in co-cultured immune cells. Scientific reports 9, 15779, doi:10.1038/s41598-019-52115-7 (2019).