In liquid chromatography-mass spectrometry (LC-MS)-based proteomics, many precursors elute from the column simultaneously. In data-dependent analyses, these precursors are fragmented one at a time, whereas the others are discarded entirely. Here we employ trapped ion mobility spectrometry (TIMS) on an orthogonal quadrupole time-of-flight (QTOF) mass spectrometer to remove this limitation. In TIMS, all precursor ions are accumulated in parallel and released sequentially as a function of their ion mobility. Instead of selecting a single precursor mass with the quadrupole mass filter, we here implement synchronized scans in which the quadrupole is mass positioned with sub-millisecond switching times at the m/z values of appropriate precursors, such as those derived from a topN precursor list. We demonstrate serial selection and fragmentation of multiple precursors in single 50 ms TIMS scans. Parallel accumulation-serial fragmentation (PASEF) enables hundreds of MS/MS events per second at full sensitivity. Modeling the effect of such synchronized scans for shotgun proteomics, we estimate that about a 10-fold gain in sequencing speed should be achievable by PASEF without a decrease in sensitivity.

Sustained weight loss is a preferred intervention in a wide range of metabolic conditions, but the effects on an individual's health state remain ill‐defined. Here, we investigate the plasma proteomes of a cohort of 43 obese individuals that had undergone 8 weeks of 12% body weight loss followed by a year of weight maintenance. Using mass spectrometry‐based plasma proteome profiling, we measured 1,294 plasma proteomes. Longitudinal monitoring of the cohort revealed individual‐specific protein levels with wide‐ranging effects of losing weight on the plasma proteome reflected in 93 significantly affected proteins. The adipocyte‐secreted SERPINF1 and apolipoprotein APOF1 were most significantly regulated with fold changes of −16% and +37%, respectively (P < 10−13), and the entire apolipoprotein family showed characteristic differential regulation. Clinical laboratory parameters are reflected in the plasma proteome, and eight plasma proteins correlated better with insulin resistance than the known marker adiponectin. Nearly all study participants benefited from weight loss regarding a ten‐protein inflammation panel defined from the proteomics data. We conclude that plasma proteome profiling broadly evaluates and monitors intervention in metabolic diseases.

BackgroundThe oral cavity is home to one of the most diverse microbial communities of the human body and a major entry portal for pathogens. Its homeostasis is maintained by saliva, which fulfills key functions including lubrication of food, pre-digestion, and bacterial defense. Consequently, disruptions in saliva secretion and changes in the oral microbiome contribute to conditions such as tooth decay and respiratory tract infections. Here we set out to quantitatively map the saliva proteome in great depth with a rapid and in-depth mass spectrometry-based proteomics workflow.MethodsWe used recent improvements in mass spectrometry (MS)-based proteomics to develop a rapid workflow for mapping the saliva proteome quantitatively and at great depth. Standard clinical cotton swabs were used to collect saliva form eight healthy individuals at two different time points, allowing us to study inter-individual differences and interday changes of the saliva proteome. To accurately identify microbial proteins, we developed a method called “split by taxonomy id” that prevents peptides shared by humans and bacteria or between different bacterial phyla to contribute to protein identification.ResultsMicrogram protein amounts retrieved from cotton swabs resulted in more than 3700 quantified human proteins in 100-min gradients or 5500 proteins after simple fractionation. Remarkably, our measurements also quantified more than 2000 microbial proteins from 50 bacterial genera. Co-analysis of the proteomics results with next-generation sequencing data from the Human Microbiome Project as well as a comparison to MALDI-TOF mass spectrometry on microbial cultures revealed strong agreement. The oral microbiome differs between individuals and changes drastically upon eating and tooth brushing.ConclusionRapid shotgun and robust technology can now simultaneously characterize the human and microbiome contributions to the proteome of a body fluid and is therefore a valuable complement to genomic studies. This opens new frontiers for the study of host–pathogen interactions and clinical saliva diagnostics.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-016-0293-0) contains supplementary material, which is available to authorized users.

We assessed the efficacy of simultaneous agonism at the glucagon-like peptide-1 receptor (GLP-1R) and the melanocortin-4 receptor (MC4R) for the treatment of obesity and diabetes in rodents. Diet-induced obese (DIO) mice were chronically treated with either the long-acting GLP-1R agonist liraglutide, the MC4R agonist RM-493 or a combination of RM-493 and liraglutide. Co-treatment of DIO mice with RM-493 and liraglutide improves body weight loss and enhances glycemic control and cholesterol metabolism beyond what can be achieved with either mono-therapy. The superior metabolic efficacy of this combination therapy is attributed to the anorectic and glycemic actions of both drugs, along with the ability of RM-493 to increase energy expenditure. Interestingly, compared to mice treated with liraglutide alone, hypothalamic Glp-1r expression was higher in mice treated with the combination therapy after both acute and chronic treatment. Further, RM-493 enhanced hypothalamic Mc4r expression. Hence, co-dosing with MC4R and GLP-1R agonists increases expression of each receptor, indicative of minimized receptor desensitization. Together, these findings suggest potential opportunities for employing combination treatments that comprise parallel MC4R and GLP-1R agonism for the treatment of obesity and diabetes.