Utilizing Nonequilibrium Isotope Enrichments to Dramatically Increase Turnover Measurement Ranges in Single Biopsy Samples from Humans.

The synthesis of new proteins and the degradation of old proteins in vivo can be quantified in serial samples using metabolic isotope labeling to measure turnover. Because serial biopsies in humans are impractical, we set out to develop a method to calculate the turnover rates of proteins from single human biopsies. This method involved a new metabolic labeling approach and adjustments to the calculations used in previous work to calculate protein turnover. We demonstrate that using a nonequilibrium isotope enrichment strategy avoids the time dependent bias caused by variable lag in label delivery to different tissues observed in traditional metabolic labeling methods. Turnover rates are consistent for the same subject in biopsies from different labeling periods, and turnover rates calculated in this study are consistent with previously reported values. We also demonstrate that by measuring protein turnover we can determine where proteins are synthesized. In human subjects a significant difference in turnover rates differentiated proteins synthesized in the salivary glands versus those imported from the serum. We also provide a data analysis tool, DeuteRater-H, to calculate protein turnover using this nonequilibrium metabolic 2H2O method.

Improved Sensitivity for Protein Turnover Quantification by Monitoring Immonium Ion Isotopologue Abundance.

We describe an analytical strategy allowing for the direct quantification of stable isotope label incorporation in newly synthesized proteins following administration of the stable isotope tracer deuterium oxide. We present a demonstration of coupling high-resolution mass spectrometry, metabolic stable isotope labeling, and MS/MS-based isotopologue quantification for the measurement of protein turnover. Stable isotope labeling with deuterium oxide, followed by immonium ion isotopologue quantification, is a more sensitive strategy for determining protein fractional synthesis rates compared to peptide centric mass isotopomer distribution analysis approaches when labeling time and/or stable isotope tracer exposure is limited and, as such, offers a great advantage for human studies.

Mechanisms of In Vivo Ribosome Maintenance Change in Response to Nutrient Signals.

Control of protein homeostasis is fundamental to the health and longevity of all organisms. Because the rate of protein synthesis by ribosomes is a central control point in this process, regulation, and maintenance of ribosome function could have amplified importance in the overall regulatory circuit. Indeed, ribosomal defects are commonly associated with loss of protein homeostasis, aging, and disease (1-4), whereas improved protein homeostasis, implying optimal ribosomal function, is associated with disease resistance and increased lifespan (5-7). To maintain a high-quality ribosome population within the cell, dysfunctional ribosomes are targeted for autophagic degradation. It is not known if complete degradation is the only mechanism for eukaryotic ribosome maintenance or if they might also be repaired by replacement of defective components. We used stable-isotope feeding and protein mass spectrometry to measure the kinetics of turnover of ribosomal RNA (rRNA) and 71 ribosomal proteins (r-proteins) in mice. The results indicate that exchange of individual proteins and whole ribosome degradation both contribute to ribosome maintenance in vivo In general, peripheral r-proteins and those with more direct roles in peptide-bond formation are replaced multiple times during the lifespan of the assembled structure, presumably by exchange with a free cytoplasmic pool, whereas the majority of r-proteins are stably incorporated for the lifetime of the ribosome. Dietary signals impact the rates of both new ribosome assembly and component exchange. Signal-specific modulation of ribosomal repair and degradation could provide a mechanistic link in the frequently observed associations among diminished rates of protein synthesis, increased autophagy, and greater longevity (5, 6, 8, 9).

DeuteRater: a tool for quantifying peptide isotope precision and kinetic proteomics.

MOTIVATION: Using mass spectrometry to measure the concentration and turnover of the individual proteins in a proteome, enables the calculation of individual synthesis and degradation rates for each protein. Software to analyze concentration is readily available, but software to analyze turnover is lacking. Data analysis workflows typically don't access the full breadth of information about instrument precision and accuracy that is present in each peptide isotopic envelope measurement. This method utilizes both isotope distribution and changes in neutromer spacing, which benefits the analysis of both concentration and turnover. RESULTS: We have developed a data analysis tool, DeuteRater, to measure protein turnover from metabolic D 2 O labeling. DeuteRater uses theoretical predictions for label-dependent change in isotope abundance and inter-peak (neutromer) spacing within the isotope envelope to calculate protein turnover rate. We have also used these metrics to evaluate the accuracy and precision of peptide measurements and thereby determined the optimal data acquisition parameters of different instruments, as well as the effect of data processing steps. We show that these combined measurements can be used to remove noise and increase confidence in the protein turnover measurement for each protein. AVAILABILITY AND IMPLEMENTATION: Source code and ReadMe for Python 2 and 3 versions of DeuteRater are available at https://github.com/JC-Price/DeuteRater . Data is at https://chorusproject.org/pages/index.html project number 1147. Critical Intermediate calculation files provided as Tables S3 and S4. Software has only been tested on Windows machines. CONTACT: jcprice@chem.byu.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Imaging regiospecific lipid turnover in mouse brain with desorption electrospray ionization mass spectrometry.

Compartmentalization of metabolism into specific regions of the cell, tissue, and organ is critical to life for all organisms. Mass spectrometric imaging techniques have been valuable in identifying and quantifying concentrations of metabolites in specific locations of cells and tissues, but a true understanding of metabolism requires measurement of metabolite flux on a spatially resolved basis. Here, we utilize desorption ESI-MS (DESI-MS) to measure lipid turnover in the brains of mice. We show that anatomically distinct regions of the brain have distinct lipid turnover rates. These turnover measurements, in conjunction with relative concentration, will enable calculation of regiospecific synthesis rates for individual lipid species in vivo. Monitoring spatially dependent changes in metabolism has the potential to significantly facilitate research in many areas, such as brain development, cancer, and neurodegeneration.

Combining offline high performance liquid chromatography fractionation of peptides and intact proteins to enhance proteome coverage in bottom-up proteomics.

Offline peptide separation (PS) using high-performance liquid chromatography (HPLC) is currently used to enhance liquid chromatography-tandem mass spectrometry (LC-MS/MS) detection of proteins. In search of more effective methods for enhancing MS proteome coverage, we developed a robust method for intact protein separation (IPS), an alternative first-dimension separation technique, and explored additional benefits that it offers. Comparing IPS to the traditional PS method, we found that both enhance detection of unique protein IDs to a similar magnitude, though in diverse ways. IPS was especially effective in serum, which has a small number of extremely high abundance proteins. PS was more effective in tissues with fewer dominating high-abundance proteins and was more effective in enhancing detection of post-translational modifications (PTMs). Combining the IPS and PS methods together (IPS+PS) was especially beneficial, enhancing proteome detection more than either method could independently. The comparison of IPS+PS versus six PS fractionation pools increased total number of proteins IDs by nearly double, while also significantly increasing number of unique peptides detected per protein, percent peptide sequence coverage of each protein, and detection of PTMs. This IPS+PS combined method requires fewer LC-MS/MS runs than current PS methods would need to obtain similar improvements in proteome detection, and it is robust, time- and cost-effective, and generally applicable to various tissue and sample types.

Regioselective base-free intermolecular aminohydroxylations of hindered and functionalized alkenes.

Regioselective base-free intermolecular aminohydroxylations of functionalized trisubstituted and 1,1-disubstituted alkenes employing benzoyloxycarbamate 3a and catalytic OsO(4) are described. In all cases, the more substituted alcohol isomer is favored. Sluggish reactions could be promoted by gentle heating, the use of amine ligands, or increased catalyst loadings. A competitive rearrangement was observed with a secondary allylic alcohol substrate. The adducts serve as useful precursors to dehydroamino acids.

QSRR Automator: A Tool for Automating Retention Time Prediction in Lipidomics and Metabolomics.

The use of retention time is often critical for the identification of compounds in metabolomic and lipidomic studies. Standards are frequently unavailable for the retention time measurement of many metabolites, thus the ability to predict retention time for these compounds is highly valuable. A number of studies have applied machine learning to predict retention times, but applying a published machine learning model to different lab conditions is difficult. This is due to variation between chromatographic equipment, methods, and columns used for analysis. Recreating a machine learning model is likewise difficult without a dedicated bioinformatician. Herein we present QSRR Automator, a software package to automate retention time prediction model creation and demonstrate its utility by testing data from multiple chromatography columns from previous publications and in-house work. Analysis of these data sets shows similar accuracy to published models, demonstrating the software's utility in metabolomic and lipidomic studies.

Mitochondrial fatty acid synthesis coordinates oxidative metabolism in mammalian mitochondria.

Cells harbor two systems for fatty acid synthesis, one in the cytoplasm (catalyzed by fatty acid synthase, FASN) and one in the mitochondria (mtFAS). In contrast to FASN, mtFAS is poorly characterized, especially in higher eukaryotes, with the major product(s), metabolic roles, and cellular function(s) being essentially unknown. Here we show that hypomorphic mtFAS mutant mouse skeletal myoblast cell lines display a severe loss of electron transport chain (ETC) complexes and exhibit compensatory metabolic activities including reductive carboxylation. This effect on ETC complexes appears to be independent of protein lipoylation, the best characterized function of mtFAS, as mutants lacking lipoylation have an intact ETC. Finally, mtFAS impairment blocks the differentiation of skeletal myoblasts in vitro. Together, these data suggest that ETC activity in mammals is profoundly controlled by mtFAS function, thereby connecting anabolic fatty acid synthesis with the oxidation of carbon fuels.

In human, plant and other eukaryotic cells, fats are an important source of energy and also play many other roles including waterproofing, thermal insulation and energy storage. Eukaryotic cells have two systems that make the building blocks of fats (known as fatty acids) and one of these systems, called the mtFAS pathway, operates in small compartments known as mitochondria. This pathway only has one known product, a small fat molecule called lipoic acid, which mitochondria attach to several enzymes to allow them to work properly. The main role of mitochondria is to break down fats and other molecules to release chemical energy that powers many processes in cells. They achieve this using large groups of proteins known as ETC complexes. To build these complexes, families of proteins known as ETC assembly factors carefully coordinate the assembly of many proteins and small molecules into specific structures. However, it remains unclear precisely how this process works. Here, Nowinski et al. used a gene editing technique to mutate the genes encoding three enzymes in the mtFAS pathway in mammalian cells. The experiments found that the mutant cells had fewer ETC complexes and seemed to be less able to break down fats and other molecules than 'normal' cells. Furthermore, a family of ETC assembly factors were less stable in the mutant cells. These findings suggest that the mtFAS pathway controls how mitochondria assemble ETC complexes. Further experiments indicated that lipoic acid is not involved in the assembly of ETC complexes and that the mtFAS pathway produces another, as yet unidentified, product that regulates this process, instead. MEPAN syndrome is a rare neurological disorder that leads to progressive loss of control of movement, slurred speech and impaired vision in children. Patients with this syndrome have genetic mutations affecting components of the mtFAS pathway, therefore, a better understanding of how the pathway works may help researchers develop new treatments in the future. More broadly, these findings will have important ramifications for many other situations in which the activity of ETC complexes in mitochondria is modified.