In vitro modeling of polyclonal infection dynamics within the human airways by Haemophilus influenzae differential fluorescent labeling

ABSTRACT Standardized clinical procedures for antibiotic administration rely on pathogen identification and antibiotic susceptibility testing, often performed on single-colony bacterial isolates. For respiratory pathogens, this could be questionable, as chronic patients may be persistently colonized by multiple clones or lineages from the same bacterial pathogen species. Indeed, multiple strains of nontypeable Haemophilus influenzae, with different antibiotic susceptibility profiles, can be co-isolated from cystic fibrosis and chronic obstructive pulmonary disease sputum specimens. Despite this clinical evidence, we lack information about the dynamics of H. influenzae polyclonal infections, which limits the optimization of therapeutics. Here, we present the engineering and validation of a plasmid toolkit (pTBH, toolbox for Haemophilus), with standardized modules consisting of six reporter genes for fluorescent or bioluminescent labeling of H. influenzae. This plasmid set was independently introduced in a panel of genomically and phenotypically different H. influenzae strains, and two of them were used as a proof of principle to analyze mixed biofilm growth architecture and antibiotic efficacy, and to visualize the dynamics of alveolar epithelial co-infection. The mixed biofilms showed a bilayer architecture, and antibiotic efficacy correlated with the antibiotic susceptibility of the respective single-species strains. Furthermore, differential kinetics of bacterial intracellular location within subcellular acidic compartments were quantified upon co-infection of cultured airway epithelial cells. Overall, we present a panel of novel plasmid tools and quantitative image analysis methods with the potential to be used in a whole range of bacterial host species, assay types, and/or conditions and generate meaningful information for clinically relevant settings. IMPORTANCE Genomic diversity of nontypeable H. influenzae strains confers phenotypic heterogeneity. Multiple strains of H. influenzae can be simultaneously isolated from clinical specimens, but we lack detailed information about polyclonal infection dynamics by this pathogen. A long-term barrier to our understanding of this host-pathogen interplay is the lack of genetic tools for strain engineering and differential labeling. Here, we present a novel plasmid toolkit named pTBH (toolbox for Haemophilus), with standardized modules for fluorescent or bioluminescent labeling, adapted to H. influenzae requirements but designed to be versatile so it can be utilized in other bacterial species. We present detailed experimental and quantitative image analysis methods, together with proof-of-principle examples, and show the ample possibilities of 3D microscopy, combined with quantitative image analysis, to model H. influenzae polyclonal infection lifestyles and unravel the co-habitation and co-infection dynamics of this respiratory pathogen. Genomic diversity of nontypeable H. influenzae strains confers phenotypic heterogeneity. Multiple strains of H. influenzae can be simultaneously isolated from clinical specimens, but we lack detailed information about polyclonal infection dynamics by this pathogen. A long-term barrier to our understanding of this host-pathogen interplay is the lack of genetic tools for strain engineering and differential labeling. Here, we present a novel plasmid toolkit named pTBH (toolbox for Haemophilus), with standardized modules for fluorescent or bioluminescent labeling, adapted to H. influenzae requirements but designed to be versatile so it can be utilized in other bacterial species. We present detailed experimental and quantitative image analysis methods, together with proof-of-principle examples, and show the ample possibilities of 3D microscopy, combined with quantitative image analysis, to model H. influenzae polyclonal infection lifestyles and unravel the co-habitation and co-infection dynamics of this respiratory pathogen.