Due to high tolerance to antibiotics and pronounced virulence, bacterial biofilms are considered a key factor and major clinical challenge in persistent wound infections. They are typically composed of multiple species, whose interactions determine the biofilm’s structural development, functional properties and thus the progression of wound infections. However, most attempts to study bacterial biofilms in vitro solely rely on mono-species populations, since cultivating multi-species biofilms, especially for prolonged periods of time, poses significant challenges. To address this, the present study examined the influence of bacterial composition on structural biofilm development, morphology and spatial organization, as well as antibiotic tolerance and virulence on human skin cells in the context of persistent wound infections. By creating a wound-mimetic microenvironment, the successful cultivation of dual-species biofilms of two of the most prevalent wound pathogens, Pseudomonas aeruginosa and Staphylococcus aureus, was realized over a period of 72 h. Combining quantitative analysis with electron microscopy and label-free imaging enabled a comprehensive evaluation of the dynamics of biofilm formation and matrix secretion, revealing a twofold increased maturation of dual-species biofilms. Antibiotic tolerance was comparable for both mono-species cultures, however, dual-species communities showed a 50% increase in tolerance, mediated by a significantly reduced penetration of the applied antibiotic into the biofilm matrix. Further synergistic effects were observed, where dual-species biofilms exacerbated wound healing beyond the effects observed from either Pseudomonas or Staphylococcus. Consequently, predicting biofilm development, antimicrobial tolerance and virulence for multi-species biofilms based solely on the results from mono-species biofilms is unreliable. This study underscores the substantial impact of a multi-species composition on biofilm functional properties and emphasizes the need to tailor future studies reflecting the bacterial composition of the respective in vivo situation, leading to a more comprehensive understanding of microbial communities in the context of basic microbiology and the development of effective treatments.

The increasing incidence of infected skin wounds poses a major challenge in clinical practice, especially when conventional antibiotic therapy fails. In this context, bacteriophages emerged as promising alternatives for the treatment of antibiotic-resistant bacteria. However, clinical implementation remains hampered by the lack of efficient delivery approaches to infected wound tissue. In this study, bacteriophage-loaded electrospun fiber mats were successfully developed as next-generation wound dressings for the treatment of infected wounds. We employed a coaxial electrospinning approach, creating fibers with a protective polymer shell, enveloping bacteriophages in the core while maintaining their antimicrobial activity. The novel fibers exhibited a reproducible fiber diameter range and morphology, while the mechanical fiber properties were ideal for application onto wounds. Further, immediate release kinetics for the phages were confirmed as well as the biocompatibility of the fibers with human skin cells. Antimicrobial activity was demonstrated against Staphylococcus aureus and Pseudomonas aeruginosa and the core/shell formulation maintained the bacteriophage activity for 4 weeks when stored at − 20 °C. Based on these promising characteristics, our approach holds great potential as a platform technology for the encapsulation of bioactive bacteriophages to enable the translation of phage therapy into clinical application.

The human blood–brain barrier (BBB) represents the interface of microvasculature and the central nervous system, regulating the transport of nutrients and protecting the brain from external threats. To gain a deeper understanding of (patho)physiological processes affecting the BBB, sophisticated models mimicking the in vivo situation are required. Currently, most in vitro models are cultivated on stiff, semipermeable, and non-biodegradable Transwell^® membrane inserts, not adequately mimicking the complexity of the extracellular environment of the native human BBB. To overcome these disadvantages, we developed three-dimensional electrospun scaffolds resembling the natural structure of the human extracellular matrix. The polymer fibers of the scaffold imitate collagen fibrils of the human basement membrane, exhibiting excellent wettability and biomechanical properties, thus facilitating cell adhesion, proliferation, and migration. Cultivation of human induced pluripotent stem cells (hiPSCs) on these scaffolds enabled the development of a physiological BBB phenotype monitored via the formation of tight junctions and validated by the paracellular permeability of sodium fluorescein, further accentuating the non-linearity of TEER and barrier permeability. The novel in vitro model of the BBB forms a tight endothelial barrier, offering a platform to study barrier functions in a (patho)physiologically relevant context.

The cultivation of cells forming three-dimensional structures like organoids holds great potential in different fields of life sciences and is gaining increasing interest with regards to clinical applications and personalised medicine. However, conventional hydrogels used as cell cultivation matrices (e.g. Matrigel®) contain animal-derived components in varying quantities, implicating low reproducibility of experiments and limited applicability for clinical use. Based on the strong need for developing novel, well defined, and animal-free hydrogels for 3D cell cultures, this study presents a comprehensive analysis of pancreas organoid cultivation in two synthetic hydrogels. Besides established visualisation techniques to monitor organoid formation and growth, confocal Raman microscopy was used for the first time to evaluate the gel matrices and organoid formation within the gels. The approach revealed so far not accessible information about material-cell interactions and the composition of the organoid lumen in a non-invasive and label-free manner. Confocal Raman microscopy thereby enabled a systematic characterisation of different hydrogels with respect to cell culture compatibility and allowed for the rational selection of a hydrogel formulation to serve as a synthetic and fully defined alternative to animal-derived cultivation matrices.

Recently, confocal Raman microscopy has gained popularity in biomedical research for studying tissues in healthy and diseased state due to its ability to acquire chemically selective data in a noninvasive approach. However, biological samples, such as brain tissue, are inherently difficult to analyze due to the superposition of molecules in the Raman spectra and low variation of spectral features within the sample. The analysis is further impeded by pathological hallmarks, for example beta-amyloid (Aβ) plaques in Alzheimer's disease, which are often solely characterized by subtle shifts in the respective Raman peaks. To unravel the underlying molecular information, convoluted statistical procedures are inevitable. Unfortunately, such statistical methods are often inadequately described, and most natural scientists lack knowledge of their appropriate use, causing unreproducible results and stagnation in the application of hyperspectral Raman imaging. Therefore, we have set out to provide a comprehensive guide to address these challenges with the example of a complex hyperspectral data set of brain tissue samples with Aβ plaques. Our study encompasses established as well as novel statistical methods, including univariate analysis, principal component analysis, cluster analysis, spectral unmixing, and 2D correlation spectroscopy, and critically compares the outcomes of each analysis. Moreover, we transparently demonstrate the effect of preprocessing decisions like denoising and scaling techniques, providing valuable insights into implications of spectral quality for data evaluation. Thereby, this study provides a comprehensive evaluation of analysis approaches for complex hyperspectral Raman data, laying out a blueprint for elucidating meaningful information from biological samples in chemical imaging.