e Multidrug-resistant bacterial pathogens are an increasing threat to public health, and lytic bacteriophages have reemerged as a potential therapeutic option. In this work, we isolated and assembled a five-member cocktail of wild phages against Acinetobacter baumannii and demonstrated therapeutic efficacy in a mouse full-thickness dorsal infected wound model. The cocktail lowers the bioburden in the wound, prevents the spread of infection and necrosis to surrounding tissue, and decreases infection-associated morbidity. Interestingly, this effective cocktail is composed of four phages that do not kill the parent strain of the infection and one phage that simply delays bacterial growth in vitro via a strong but incomplete selection event. The cocktail here appears to function in a combinatorial manner, as one constituent phage targets capsulated A. baumannii bacteria and selects for loss of receptor, shifting the population to an uncapsulated state that is then sensitized to the remaining four phages in the cocktail. Additionally, capsule is a known virulence factor for A. baumannii, and we demonstrated that the emergent uncapsulated bacteria are avirulent in a Galleria mellonella model. These results highlight the importance of anticipating population changes during phage therapy and designing intelligent cocktails to control emergent strains, as well as the benefits of using phages that target virulence factors. Because of the efficacy of this cocktail isolated from a limited environmental pool, we have established a pipeline for developing new phage therapeutics against additional clinically relevant multidrug-resistant pathogens by using environmental phages sourced from around the globe.

In recent years, matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has become the standard for routine bacterial species identification due to its rapidity and low costs for consumables compared to those of traditional DNA-based methods. However, it has been observed that strains of some bacterial species, such as Acinetobacter baumannii strains, cannot be reliably identified using mass spectrometry (MS). Raman spectroscopy is a rapid technique, as fast as MALDI-TOF, and has been shown to accurately identify bacterial strains and species. In this study, we compared hierarchical clustering results for MS, genomic, and antimicrobial susceptibility test data to hierarchical clustering results from Raman spectroscopic data for 31 A. baumannii clinical isolates labeled according to their pulsed-field gel electrophoresis data for strain differentiation. In addition to performing hierarchical cluster analysis (HCA), multiple chemometric methods of analysis, including principal-component analysis (PCA) and partial least-squares discriminant analysis (PLSDA), were performed on the MS and Raman spectral data, along with a variety of spectral preprocessing techniques for best discriminative results. Finally, simple HCA algorithms were performed on all of the data sets to explore the relationships between, and natural groupings of, the strains and to compare results for the four data sets. To obtain numerical comparison values of the clustering results, the external cluster evaluation criteria of the Rand index of the HCA dendrograms were calculated. With a Rand index value of 0.88, Raman spectroscopy outperformed the other techniques, including MS (with a Rand index value of 0.58).

Current clinical methodology for identification of bacterial infections relies predominantly on culturing microbes from patient material and performing biochemical tests. This can often be an inefficient and lengthy process, which has a significant detrimental effect upon patient care. Techniques used in other aspects of molecular research have the potential to revolutionize the way in which diagnostic tests are used and delivered in the clinical setting. The need for rapid, accurate, and cost-effective molecular techniques in the diagnostic laboratory is imperative to improving patient care, preventing the spread of drug resistance and decreasing the overall burden associated with nosocomial infections. Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) are powerful vibrational spectroscopy techniques that are being developed for highly sensitive pathogen identification in complex clinical samples. Raman spectroscopy is a molecular technique that is capable of probing samples noninvasively and nondestructively. It has been used with high specificity to assess tissue and bacterial samples at the molecular level with diverse clinical and diagnostic applications. SERS has recently developed out of the advances in the Raman spectroscopy arena. This technique is designed to amplify Raman scattering and allows for better differentiation of bacterial isolates. Although the current parameters for the use of SERS require a pure culture and are relatively monoparametric, current breakthroughs and testing are pushing the technology to new levels and thus changing the face of modern bacterial diagnostics.

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