Comprehensive urinary metabolomic characterization of a genetically induced mouse model of prostatic inflammation

Sensing and avoiding sick conspecifics requires Gαi2+ vomeronasal neurons

BACKGROUND

Rodents utilize chemical cues to recognize and avoid other conspecifics infected with pathogens. Infection with pathogens and acute inflammation alter the repertoire and signature of olfactory stimuli emitted by a sick individual. These cues are recognized by healthy conspecifics via the vomeronasal or accessory olfactory system, triggering an innate form of avoidance behavior. However, the molecular identity of the sensory neurons and the higher neural circuits involved in the detection of sick conspecifics remain poorly understood.

RESULTS

We employed mice that are in an acute state of inflammation induced by systemic administration of lipopolysaccharide (LPS). Through conditional knockout of the G-protein Gαi2 and deletion of other key sensory transduction molecules (Trpc2 and a cluster of 16 vomeronasal type 1 receptors), in combination with behavioral testing, subcellular Ca²⁺ imaging, and pS6 and c-Fos neuronal activity mapping in freely behaving mice, we show that the Gαi2⁺ vomeronasal subsystem is required for the detection and avoidance of LPS-treated mice. The active components underlying this avoidance are contained in urine whereas feces extract and two selected bile acids, although detected in a Gαi2-dependent manner, failed to evoke avoidance behavior. Our analyses of dendritic Ca²⁺ responses in vomeronasal sensory neurons provide insight into the discrimination capabilities of these neurons for urine fractions from LPS-treated mice, and how this discrimination depends on Gαi2. We observed Gαi2-dependent stimulation of multiple brain areas including medial amygdala, ventromedial hypothalamus, and periaqueductal grey. We also identified the lateral habenula, a brain region implicated in negative reward prediction in aversive learning, as a previously unknown target involved in these tasks.

CONCLUSIONS

Our physiological and behavioral analyses indicate that the sensing and avoidance of LPS-treated sick conspecifics depend on the Gαi2 vomeronasal subsystem. Our observations point to a central role of brain circuits downstream of the olfactory periphery and in the lateral habenula in the detection and avoidance of sick conspecifics, providing new insights into the neural substrates and circuit logic of the sensing of inflammation in mice.

Male Lower Urinary Tract Dysfunction: An Underrepresented Endpoint in Toxicology Research

Lower urinary tract dysfunction (LUTD) is nearly ubiquitous in men of advancing age and exerts substantial physical, mental, social, and financial costs to society. While a large body of research is focused on the molecular, genetic, and epigenetic underpinnings of the disease, little research has been dedicated to the influence of environmental chemicals on disease initiation, progression, or severity. Despite a few recent studies indicating a potential developmental origin of male LUTD linked to chemical exposures in the womb, it remains a grossly understudied endpoint in toxicology research. Therefore, we direct this review to toxicologists who are considering male LUTD as a new aspect of chemical toxicity studies. We focus on the LUTD disease process in men, as well as in the male mouse as a leading research model. To introduce the disease process, we describe the physiology of the male lower urinary tract and the cellular composition of lower urinary tract tissues. We discuss known and suspected mechanisms of male LUTD and examples of environmental chemicals acting through these mechanisms to contribute to LUTD. We also describe mouse models of LUTD and endpoints to diagnose, characterize, and quantify LUTD in men and mice.

A multi-omic investigation of male lower urinary tract symptoms: Potential role for JC virus

Male lower urinary tract symptoms (LUTS) comprise a common syndrome of aging that negatively impacts quality of life. The etiology of LUTS is multifactorial, involving benign prostatic hyperplasia, smooth muscle and neurologic dysfunction, inflammation, sexually transmitted infections, fibrosis, and potentially dysbiosis, but this aspect remains poorly explored. We investigated whether the presence of infectious agents in urine might be associated with LUTS by combining next-generation DNA sequencing for virus discovery, microbiome analysis for characterization of bacterial communities, and mass spectrometry-based metabolomics. In urine from 29 LUTS cases and 9 controls from Wisconsin, we found a statistically significant association between a diagnosis of LUTS and the presence of JC virus (JCV), a common neurotropic human polyomavirus (Polyomaviridae, Betapolyomavirus) linked to severe neurologic disease in rare cases. This association (based on metagenomics) was not borne out when specific polymerase chain reaction (PCR) testing was applied to this set of samples, likely due to the greater sensitivity of PCR. Interestingly, urine metabolomics analysis identified dysregulation of metabolites associated with key LUTS processes. Microbiome analysis found no evidence of microbial community dysbiosis in LUTS cases, but JCV-positive samples contained more Anaerococcus species, which are involved in polymicrobial infections of the urinary tract. Neither age nor body mass index were significantly associated with the presence of urinary JCV-in the initial group or in an additional, regionally distinct group. These data provide preliminary support the hypothesis that viruses such as JCV may play a role in the development or progression of LUTS, together with other infectious agents and host metabolic responses.

Systems analysis of benign bladder disorders: insights from omics analysis

The signaling pathways and effectors that drive the response of the bladder to nonmalignant insults or injury are incompletely defined. Interrogation of biological systems has been revolutionized by the ability to generate high-content data sets that capture information on a variety of biomolecules in cells and tissues, from DNA to RNA to proteins. In oncology, such an approach has led to the identification of cancer subtypes, improved prognostic capability, and has provided a basis for precision treatment of patients. In contrast, systematic molecular characterization of benign bladder disorders has lagged behind, such that our ability to uncover novel therapeutic interventions or increase our mechanistic understanding of such conditions is limited. Here, we discuss existing literature on the application of omics approaches, including transcriptomics and proteomics, to urinary tract conditions characterized by pathological tissue remodeling. We discuss molecular pathways implicated in remodeling, challenges in the field, and aspirations for omics-based research in the future.

Metandem: An online software tool for mass spectrometry-based isobaric labeling metabolomics

Mass spectrometry-based stable isotope labeling provides the advantages of multiplexing capability and accurate quantification but requires tailored bioinformatics tools for data analysis. Despite the rapid advancements in analytical methodology, it is often challenging to analyze stable isotope labeling-based metabolomics data, particularly for isobaric labeling using MS/MS reporter ions for quantification. We report Metandem, a novel online software tool for isobaric labeling-based metabolomics, freely available at http://metandem.com/web/. Metandem provides a comprehensive data analysis pipeline integrating feature extraction, metabolite quantification, metabolite identification, batch processing of multiple data files, online parameter optimization for custom datasets, data normalization, and statistical analysis. Systematic evaluation of the Metandem tool was demonstrated on UPLC-MS/MS, nanoLC-MS/MS, CE-MS/MS and MALDI-MS platforms, via duplex, 4-plex, 10-plex, and 12-plex isobaric labeling experiments and the application to various biological samples.

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

Lower urinary tract symptoms (LUTS) are common among aging men. Since prostatic inflammation is one of its etiologies, it is plausible that urinary metabolite and protein biomarkers could be identified and used to diagnose inflammation-induced LUTS. We characterized the urine metabolome and proteome in a mouse model of bacterial-induced prostatic inflammation. Mass Spectrometry (MS)-based multi-omics analysis was employed to discover urinary protein and metabolite-based biomarkers. The investigation of isobaric dimethylated leucine (DiLeu) labeling on metabolites allowed metabolomics and proteomics analysis on the same liquid chromatography (LC)-MS platform. In total, 143 amine-containing metabolites and 1058 urinary proteins were identified and quantified (data are available via ProteomeXchange with identifier PXD018023); among them, 14 metabolites and 168 proteins were significantly changed by prostatic inflammation. Five metabolic pathways and four inflammation-related biological processes were potentially disrupted. By comparing our findings with urinary biomarkers identified in a mouse model of genetic-induced prostate inflammation and with those previously found to be associated with LUTS in older men, we identified creatine, haptoglobin, immunoglobulin kappa constant and polymeric Ig receptor as conserved biomarkers for prostatic inflammation associated with LUTS. These data suggest that these putative biomarkers could be used to identify men in which prostate inflammation is present and contributing to LUTS.