Urinary Metabolomic and Proteomic Analyses in a Mouse Model of Prostatic Inflammation

Establishment of new transurethral catheterization methods for male mice

Transurethral catheterization in mice is multifaceted, serving essential functions such as perfusion and drug delivery, and is critical in the development of various urological animal disease models. The complex anatomy of the male mouse urethra presents significant challenges in transurethral catheterization, leading to a predominance of research focused on female specimens. This bias limits the utilization of male mice in lower urinary tract disease studies. Our research aims to develop new reliable methods for transurethral catheterization in adult male mice, thereby expanding their use in relevant disease research. Experiments were conducted on adult male C57BL/6J mice. Utilizing a PE10 catheter measuring 4.5-5 cm in length, the catheter was inserted into the bladder via the mouse's urethra under anesthesia. The intubation technique entailed regulating the insertion force, ensuring the catheter's lubrication, using a trocar catheter, modifying the catheter's trajectory, and accommodating the curvature of the bladder neck. Post-catheter insertion, ultrasound imaging was employed to confirm the catheter's accurate positioning within the bladder. Subsequent to catheterization, the bladder was perfused using trypan blue. This method was further validated through its successful application in establishing an acute urinary retention (AUR) model, where the mouse bladder was infused with saline to a pressure of 50 or 80 cm H2O, maintained steadily for 30 min. A thorough morphological assessment of the mouse bladder was conducted after the infusion. Our study successfully pioneered methods for transurethral catheterization in male mice. This technique not only facilitates precise transurethral catheterization but also proves applicable to male mouse models for lower urinary tract diseases, such as AUR.

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

Metabolomics meets systems immunology

Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.

Urinary Amine Metabolomics Characterization with Custom 12-Plex Isobaric DiLeu Labeling

Lower urinary tract symptoms (LUTS) is common in aging males. Disease etiology is largely unknown but likely includes inflammation and age-related changes in steroid hormones. Diagnosis is currently based on subjective symptom scores, and mainstay treatments can be ineffective and bothersome. Biomarker discovery efforts could facilitate objective diagnostic criteria for personalized medicine and new potential druggable pathways. To identify urine metabolite markers specific to hormone-induced bladder outlet obstruction, we applied our custom synthesized multiplex isobaric tags to monitor the development of bladder outlet obstruction across time in an experimental mouse model of LUTS. Mouse urine samples were collected before treatment and after 2, 4, and 8 weeks of steroid hormone treatment and subsequently analyzed by nanoflow ultrahigh-performance liquid chromatography coupled to tandem mass spectrometry. Accurate and high-throughput quantification of amine-containing metabolites was achieved by 12-plex DiLeu isobaric labeling. Metandem, a novel online software tool for large-scale isobaric labeling-based metabolomics, was used for identification and relative quantification of labeled metabolites. A total of 59 amine-containing metabolites were identified and quantified, 9 of which were changed significantly by the hormone treatment. Metabolic pathway analyses showed that three metabolic pathways were potentially disrupted. Among them, the arginine and proline metabolism pathway was significantly dysregulated both in this model and in a prior analysis of LUTS patient samples. Proline and citrulline were significantly changed in both samples and serve as attractive candidate biomarkers. The 12-plex DiLeu isobaric labeling with Metandem data processing presents an accessible and efficient workflow for an amine-containing metabolome study in biological specimens.