Discovery of Candidate Stool Biomarker Proteins for Biliary Atresia Using Proteome Analysis by Data-Independent Acquisition Mass Spectrometry

Fecal and Urinary Adipokines as Disease Biomarkers

The use of biomarkers is of great clinical value for the diagnosis and prognosis of disease and the assessment of treatment efficacy. In this context, adipokines secreted from adipose tissue are of interest, as their elevated circulating levels are associated with a range of metabolic dysfunctions, inflammation, renal and hepatic diseases and cancers. In addition to serum, adipokines can also be detected in the urine and feces, and current experimental evidence on the analysis of fecal and urinary adipokine levels points to their potential as disease biomarkers. This includes increased urinary adiponectin, lipocalin-2, leptin and interleukin-6 (IL-6) levels in renal diseases and an association of elevated urinary chemerin as well as urinary and fecal lipocalin-2 levels with active inflammatory bowel diseases. Urinary IL-6 levels are also upregulated in rheumatoid arthritis and may become an early marker for kidney transplant rejection, while fecal IL-6 levels are increased in decompensated liver cirrhosis and acute gastroenteritis. In addition, galectin-3 levels in urine and stool may emerge as a biomarker for several cancers. With the analysis of urine and feces from patients being cost-efficient and non-invasive, the identification and utilization of adipokine levels as urinary and fecal biomarkers could become a great advantage for disease diagnosis and predicting treatment outcomes. This review article highlights data on the abundance of selected adipokines in urine and feces, underscoring their potential to serve as diagnostic and prognostic biomarkers.

Single-Shot 10K Proteome Approach: Over 10,000 Protein Identifications by Data-Independent Acquisition-Based Single-Shot Proteomics with Ion Mobility Spectrometry

The evolution of mass spectrometry (MS) and analytical techniques has led to the demand for proteome analysis with high proteome coverage in single-shot measurements. Focus has been placed on data-independent acquisition (DIA)-MS and ion mobility spectrometry as techniques for deep proteome analysis. We aimed to expand the proteome coverage by single-shot measurements using optimizing high-field asymmetric waveform ion mobility spectrometry parameters in DIA-MS. With our established proteome analysis system, more than 10,000 protein groups were identified from HEK293 cell digests within 120 min of MS measurement time. Additionally, we applied our approach to the analysis of host proteins in mouse feces and detected as many as 892 host protein groups (771 upregulated/121 downregulated proteins) in a mouse model of repeated social defeat stress (R-SDS) used in studying depression. Interestingly, 285 proteins elevated by R-SDS were related to mental disorders. The fecal host protein profiling by deep proteome analysis may help us understand mental illness pathologies noninvasively. Thus, our approach will be helpful for an in-depth comparison of protein expression levels for biological and medical research because it enables the analysis of highly proteome coverage in a single-shot measurement.