Disorders of autophagy, a key regulator of cellular homeostasis, cause a number of human diseases. Due to the role of autophagy in metabolic dysregulation, there is a need to identify autophagy regulators as therapeutic targets. To address this need, we conducted an autophagy phenotype-based screen and identified the natural compound kaempferide (Kaem) as an autophagy enhancer. Kaem promoted autophagy through translocation of transcription factor EB (TFEB) without MTOR perturbation, suggesting it is safe for administration. Moreover, Kaem accelerated lipid droplet degradation in a lysosomal activity-dependent manner in vitro and ameliorated metabolic dysregulation in a diet-induced obesity mouse model. To elucidate the mechanism underlying Kaem’s biological activity, the target protein was identified via combined drug affinity responsive target stability and LC–MS/MS analyses. Kaem directly interacted with the mitochondrial elongation factor TUFM, and TUFM absence reversed Kaem-induced autophagy and lipid degradation. Kaem also induced mitochondrial reactive oxygen species (mtROS) to sequentially promote lysosomal Ca2+ efflux, TFEB translocation and autophagy induction, suggesting a role of TUFM in mtROS regulation. Collectively, these results demonstrate that Kaem is a potential therapeutic candidate/chemical tool for treating metabolic dysregulation and reveal a role for TUFM in autophagy for metabolic regulation with lipid overload.

Human glycoproteins exhibit enormous heterogeneity at each N-glycosite, but few studies have attempted to globally characterize the site-specific structural features. We have developed Integrated GlycoProteome Analyzer (I-GPA) including mapping system for complex N-glycoproteomes, which combines methods for tandem mass spectrometry with a database search and algorithmic suite. Using an N-glycopeptide database that we constructed, we created novel scoring algorithms with decoy glycopeptides, where 95 N-glycopeptides from standard α1-acid glycoprotein were identified with 0% false positives, giving the same results as manual validation. Additionally automated label-free quantitation method was first developed that utilizes the combined intensity of top three isotope peaks at three highest MS spectral points. The efficiency of I-GPA was demonstrated by automatically identifying 619 site-specific N-glycopeptides with FDR ≤ 1%, and simultaneously quantifying 598 N-glycopeptides, from human plasma samples that are known to contain highly glycosylated proteins. Thus, I-GPA platform could make a major breakthrough in high-throughput mapping of complex N-glycoproteomes, which can be applied to biomarker discovery and ongoing global human proteome project.

Glycoprotein conformations are complex and heterogeneous. Currently, site-specific characterization of glycopeptides is a challenge. We sought to establish an efficient method of N-glycoprotein characterization using mass spectrometry (MS). Using alpha-1-acid glycoprotein (AGP) as a model N-glycoprotein, we identified its tryptic N-glycopeptides and examined the data reproducibility in seven laboratories running different LC-MS/MS platforms. We used three test samples and one blind sample to evaluate instrument performance with entire sample preparation workflow. 165 site-specific N-glycopeptides representative of all N-glycosylation sites were identified from AGP 1 and AGP 2 isoforms. The glycopeptide fragmentations by collision-induced dissociation or higher-energy collisional dissociation (HCD) varied based on the MS analyzer. Orbitrap Elite identified the greatest number of AGP N-glycopeptides, followed by Triple TOF and Q-Exactive Plus. Reproducible generation of oxonium ions, glycan-cleaved glycopeptide fragment ions, and peptide backbone fragment ions was essential for successful identification. Laboratory proficiency affected the number of identified N-glycopeptides. The relative quantities of the 10 major N-glycopeptide isoforms of AGP detected in four laboratories were compared to assess reproducibility. Quantitative analysis showed that the coefficient of variation was <25% for all test samples. Our analytical protocol yielded identification and quantification of site-specific N-glycopeptide isoforms of AGP from control and disease plasma sample.

These findings suggest that glycopeptide-based LC-MS/MS is a promising method and that AFP-fuc% is a clinically useful parameter for differentiating between early HCC and liver cirrhosis.