Bioimage analysis of Shigella infection reveals targeting of colonic crypts

Few studies within the pathogenic field have used advanced imaging and analytical tools to quantitatively measure pathogenicity in vivo. In this work, we present a novel approach for the investigation of host–pathogen processes based on medium-throughput 3D fluorescence imaging. The guinea pig model for Shigella flexneri invasion of the colonic mucosa was used to monitor the infectious process over time with GFP-expressing S. flexneri. A precise quantitative imaging protocol was devised to follow individual S. flexneri in a large tissue volume. An extensive dataset of confocal images was obtained and processed to extract specific quantitative information regarding the progression of S. flexneri infection in an unbiased and exhaustive manner. Specific parameters included the analysis of S. flexneri positions relative to the epithelial surface, S. flexneri density within the tissue, and volume of tissue destruction. In particular, at early time points, there was a clear association of S. flexneri with crypts, key morphological features of the colonic mucosa. Numerical simulations based on random bacterial entry confirmed the bias of experimentally measured S. flexneri for early crypt targeting. The application of a correlative light and electron microscopy technique adapted for thick tissue samples further confirmed the location of S. flexneri within colonocytes at the mouth of crypts. This quantitative imaging approach is a novel means to examine host–pathogen systems in a tailored and robust manner, inclusive of the infectious agent.The light microscope is an important tool in resolving the interactions between microbes and their hosts. With the advancement of both optical and computational techniques, quantification of biological events is not only possible, but essential in deciphering the complex interplays between host and pathogen. Acquired images are multidimensional datasets that capture complex biological phenomena, and a major task is to computationally extract statistically relevant data from those images. Such techniques have been readily applied in Cellular Microbiology, a discipline at the interface between cellular biology and microbiology (1). This field is dominated by studies focusing on microbe–host interactions at the in vitro, cellular scale, and a multitude of bioimage analysis tools have been developed and used to decipher pathogenic strategies at the cellular, as well as the molecular, level in high resolution in both space and time (2).The next imaging challenge exists on a much larger scale in the growing field of Tissue Microbiology, which places the pathogen in its native in vivo environment, the host (3). Biologically speaking, this environment is essential for the full understanding of a given pathogen’s invasive strategies and the complex host response; however, this also places additional complexity and limitations in regards to imaging, particularly in maintaining cellular and molecular resolution. Novel tools and studies addressing bacterial infection in vivo are frequently reported in the literature (4, 5). However, emphasis has been traditionally placed on qualitative observations at the expense of extensive quantitative efforts. The importance of bioimage analyses to automatically extract data from medium- to large-scale image sampling of infected tissue is often underappreciated as a method to expand our understanding of pathogens’ strategies and disease progression. In this work, we aim to bring quantitative image analysis into the realm of host–pathogen interactions, specifically examining the progression of tissue invasion by a model enteropathogenic bacterium, Shigella flexneri.S. flexneri is the causative agent of bacillary dysentery, an infectious rectocolitis, which remains a major pediatric public health concern in developing countries. This human-specific pathogen is transmitted via the fecal–oral route, and namely targets the large intestine, resulting in acute inflammation, tissue edema, and erosion of the colonic epithelium (6). The infection strategy of S. flexneri relies on (i) the transfer of bacterial proteins, termed “effectors,” into targeted host cells through the type III secretion apparatus (T3SA), which induces the uptake of the bacteria and perturbs host cellular processes, and (ii) the capacity of the intracellular bacteria to spread from cell to cell using actin microfilament-mediated cytoplasmic movement and reactivation of the T3SA (7–10).Herein, we present a straightforward approach that relies on the combination of light microscopy and computer analyses to study the mucosal invasion of a newly developed in vivo model for shigellosis, S. flexneri intrarectal inoculation of the guinea pig colon (11). Through the application of simple, open-source image analysis tools, we built up a medium-throughput analysis that allows observing and robustly measuring host–pathogen interactions. Most importantly, this approach can be adapted to other host–pathogen systems, thereby providing generic tools that bridge Cellular and Tissue Microbiology.