Bioengineered human gut-on-a-chip for advancing non-clinical pharmaco-toxicology.

INTRODUCTION: There is a growing need for alternative models to advance current non-clinical experimental models because they often fail to accurately predict drug responses in human clinical trials. Human organ-on-a-chip models have emerged as promising approaches for advancing the predictability of drug behaviors and responses. AREAS COVERED: We summarize up-to-date human gut-on-a-chip models designed to demonstrate intricate interactions involving the host, microbiome, and pharmaceutical compounds since these models have been reported a decade ago. This overview covers recent advances in gut-on-a-chip models as a bridge technology between non-clinical and clinical assessments of drug toxicity and metabolism. We highlight the promising potential of gut-on-a-chip platforms, offering a reliable and valid framework for investigating reciprocal crosstalk between the host, gut microbiome, and drug compounds. EXPERT OPINION: Gut-on-a-chip platforms can attract multiple end users as predictive, human-relevant, and non-clinical model. Notably, gut-on-a-chip platforms provide a unique opportunity to recreate a human intestinal microenvironment, including dynamic bowel movement, luminal flow, oxygen gradient, host-microbiome interactions, and disease-specific manipulations restricted in animal and in vitro cell culture models. Additionally, given the profound impact of the gut microbiome on pharmacological bioprocess, it is critical to leverage breakthroughs of gut-on-a-chip technology to address knowledge gaps and drive innovations in predictive drug toxicology and metabolism.

Live probiotic bacteria administered in a pathomimetic Leaky Gut Chip ameliorate impaired epithelial barrier and mucosal inflammation.

Here, we report a pathomimetic Leaky Gut Chip that recapitulates increased epithelial permeability and intestinal inflammation to assess probiotic intervention as live biotherapeutics. We leveraged a mechanodynamic human gut-on-a-chip (Gut Chip) that recreates three-dimensional epithelial layers in a controlled oxygen gradient and biomechanical cues, where the addition of a cocktail of pro-inflammatory cytokines, TNF-α and IL-1ß, reproducibly induced impaired epithelial barrier followed by intestinal inflammation. This inflamed leaky epithelium was not recovered for up to 3 days, although the cytokine treatment ceased. However, when probiotic bacteria, either Lactobacillus rhamnosus GG or a multi-species mixture (VSL#3), were respectively administered on the leaky epithelium, bacterial cells colonized mucosal surface and significantly improved barrier function, enhanced the localization of tight junction proteins such as ZO-1 and occludin, and elevated mucus production. In addition, inflammatory markers, including p65, pSTAT3, and MYD88, that were highly expressed in the germ-free control were significantly reduced when probiotic bacteria were co-cultured in a Leaky Gut Chip. Probiotic treatment also significantly reduced the production of secretory pro-inflammatory cytokines. Hence, our pathomimetic Leaky Gut Chip may offer a translational strategy to dissect the therapeutic mechanism of live biotherapeutic products and validate their clinical potential by incorporating patient-derived organoids.

Quantitation of ethanol in UTI assay for volatile organic compound detection by electronic nose using the validated headspace GC-MS method.

Disease detection through gas analysis has long been the topic of many studies because of its potential as a rapid diagnostic technique. In particular, the pathogens that cause urinary tract infection (UTI) have been shown to generate different profiles of volatile organic compounds, thus enabling the discrimination of causative agents using an electronic nose. While past studies have performed data collection on either agar culture or jellified urine culture, this study measures the headspace volume of liquid urine culture samples. Evaporation of the liquid and the presence of background compounds during electronic nose (e-nose) device operation could introduce variability to the collected data. Therefore, a headspace gas chromatography-mass spectrometry method was developed and validated for quantitating ethanol in the headspace of the urine samples. By leveraging the new method to characterize the sample stability during e-nose measurement, it was revealed that ethanol concentration dropped more than 15% after only three measurement cycles, which equal 30 minutes for this study. It was further shown that by using only data within the first three cycles, better accuracies for between-day classification were achieved, which was 73.7% and 97.0%, compared to using data from within the first nine cycles, which resulted in 65.0% and 81.1% accuracies. Therefore, the newly developed method provides better quality control for data collection, paving ways for the future establishment of a training data library for UTI.