Multiomic analysis in fibroblasts of patients with inborn errors of cobalamin metabolism reveals concordance with clinical and metabolic variability.

BACKGROUND: The high variability in clinical and metabolic presentations of inborn errors of cobalamin (cbl) metabolism (IECM), such as the cblC/epicblC types with combined deficits in methylmalonyl-coA mutase (MUT) and methionine synthase (MS), are not well understood. They could be explained by the impaired expression/activity of enzymes from other metabolic pathways. METHODS: We performed metabolomic, genomic, proteomic, and post-translational modification (PTM) analyses in fibroblasts from three cblC cases and one epi-cblC case compared with three cblG cases with specific MS deficits and control fibroblasts. FINDINGS: CblC patients had metabolic profilings consistent with altered urea cycle, glycine, and energy mitochondrial metabolism. Metabolomic analysis showed partial disruption and increased glutamate/ketoglutarate anaplerotic pathway of the tricarboxylic acid cycle (TCA), in patient fibroblasts. RNA-seq analysis showed decreased expression of MT-TT (mitochondrial tRNA threonine), MT-TP (mitochondrial tRNA proline), OXCT1 (succinyl CoA:3-oxoacid CoA transferase deficiency), and MT-CO1 (cytochrome C oxidase subunit 1). Proteomic changes were observed for key mitochondrial enzymes, including NADH:ubiquinone oxidoreductase subunit A8 (NDUFA8), carnitine palmitoyltransferase 2 (CPT2), and ubiquinol-cytochrome C reductase, complex III subunit X (UQCR10). Propionaldehyde addition in ornithine aminotransferase was the predominant PTM in cblC cells and could be related with the dramatic cellular increase in propionate and methylglyoxalate. It is consistent with the decreased concentration of ornithine reported in 3 cblC cases. Whether the changes detected after multi-omic analyses underlies clinical features in cblC and cblG types of IECM, such as peripheral and central neuropathy, cardiomyopathy, pulmonary hypertension, development delay, remains to be investigated. INTERPRETATION: The omics-related effects of IECM on other enzymes and metabolic pathways are consistent with the diversity and variability of their age-related metabolic and clinical manifestations. PTMs are expected to produce cumulative effects, which could explain the influence of age on neurological manifestations. FUNDING: French Agence Nationale de la Recherche (Projects PREDICTS and EpiGONE) and Inserm.

Pyrroline-5-carboxylate metabolism protein complex detected in Arabidopsis thaliana leaf mitochondria.

Proline dehydrogenase (ProDH) and pyrroline-5-carboxylate (P5C) dehydrogenase (P5CDH) catalyse the oxidation of proline into glutamate via the intermediates P5C and glutamate-semialdehyde (GSA), which spontaneously interconvert. P5C and GSA are also intermediates in the production of glutamate from ornithine and α-ketoglutarate catalysed by ornithine δ-aminotransferase (OAT). ProDH and P5CDH form a fused bifunctional PutA enzyme in Gram-negative bacteria and are associated in a bifunctional substrate-channelling complex in Thermus thermophilus; however, the physical proximity of ProDH and P5CDH in eukaryotes has not been described. Here, we report evidence of physical proximity and interactions between Arabidopsis ProDH, P5CDH, and OAT in the mitochondria of plants during dark-induced leaf senescence when all three enzymes are expressed. Pairwise interactions and localization of the three enzymes were investigated using bimolecular fluorescence complementation with confocal microscopy in tobacco and sub-mitochondrial fractionation in Arabidopsis. Evidence for a complex composed of ProDH, P5CDH, and OAT was revealed by co-migration of the proteins in native conditions upon gel electrophoresis. Co-immunoprecipitation coupled with mass spectrometry analysis confirmed the presence of the P5C metabolism complex in Arabidopsis. Pull-down assays further demonstrated a direct interaction between ProDH1 and P5CDH. P5C metabolism complexes might channel P5C among the constituent enzymes and directly provide electrons to the respiratory electron chain via ProDH.

Extending the Range of SLIM-Labeling Applications: From Human Cell Lines in Culture to Caenorhabditis elegans Whole-Organism Labeling.

The simple light isotope metabolic-labeling technique relies on the in vivo biosynthesis of amino acids from U-[12C]-labeled molecules provided as the sole carbon source. The incorporation of the resulting U-[12C]-amino acids into proteins presents several key advantages for mass-spectrometry-based proteomics analysis, as it results in more intense monoisotopic ions, with a better signal-to-noise ratio in bottom-up analysis. In our initial studies, we developed the simple light isotope metabolic (SLIM)-labeling strategy using prototrophic eukaryotic microorganisms, the yeasts Candida albicans and Saccharomyces cerevisiae, as well as strains with genetic markers that lead to amino-acid auxotrophy. To extend the range of SLIM-labeling applications, we evaluated (i) the incorporation of U-[12C]-glucose into proteins of human cells grown in a complex RPMI-based medium containing the labeled molecule, considering that human cell lines require a large number of essential amino-acids to support their growth, and (ii) an indirect labeling strategy in which the nematode Caenorhabditis elegans grown on plates was fed U-[12C]-labeled bacteria (Escherichia coli) and the worm proteome analyzed for 12C incorporation into proteins. In both cases, we were able to demonstrate efficient incorporation of 12C into the newly synthesized proteins, opening the way for original approaches in quantitative proteomics.

Capillary liquid chromatography coupled with mass spectrometry for analysis of nanogram protein quantities on a wide-pore superficially porous particle column in top-down proteomics.

In top-down proteomics experiments, intact protein ions are subjected to gas-phase fragmentation for MS analysis without prior digestion. This approach is used to characterize post-translational modifications and clipped forms of proteins, avoids several "inference" problems associated with bottom-up proteomics, and is well suited to the study of proteoforms. In the past decade, top-down proteomics has progressed rapidly, taking advantage of MS instrumentation improvements and the efforts of pioneering groups working to improve sample handling and data processing. The potential of this technology has been established through its successful use in a number of important biological studies. However, many challenges remain to be addressed like improving protein separation capabilities such that it might become possible to expand the dynamic range of whole proteome analysis, address co-elution and convoluted mass spectral data, and aid final data processing from peak identification to quantification. In this study, we investigated the use of a wide-pore silica-based superficially porous media with a high coverage phenyl bonding, commercially packed into customized capillary columns for the purpose of top-down proteomics. Protein samples of increasing complexity were tested, namely subunit digests of a monoclonal antibody, components of purified histones and proteins extracted from eukaryotic ribosomes. High quality mass spectra were obtained from only 100 ng of protein sample while using difluoroacetic acid as an ion pairing agent to improve peak shape and chromatographic resolution. A peak width at half height of about 15 s for a 45 min gradient time was observed on a complex mixture giving an estimated peak capacity close to 100. Most importantly, efficient separations were obtained for highly diverse proteins and there was no need to make method specific adjustments, suggesting this is a highly versatile and easy-to-use setup for top-down proteomics.

The evolutionary conserved proteins CEP90, FOPNL, and OFD1 recruit centriolar distal appendage proteins to initiate their assembly.

In metazoa, cilia assembly is a cellular process that starts with centriole to basal body maturation, migration to the cell surface, and docking to the plasma membrane. Basal body docking involves the interaction of both the distal end of the basal body and the transition fibers/distal appendages, with the plasma membrane. Mutations in numerous genes involved in basal body docking and transition zone assembly are associated with the most severe ciliopathies, highlighting the importance of these events in cilium biogenesis. In this context, the ciliate Paramecium has been widely used as a model system to study basal body and cilia assembly. However, despite the evolutionary conservation of cilia assembly events across phyla, whether the same molecular players are functionally conserved, is not fully known. Here, we demonstrated that CEP90, FOPNL, and OFD1 are evolutionary conserved proteins crucial for ciliogenesis. Using ultrastructure expansion microscopy, we unveiled that these proteins localize at the distal end of both centrioles/basal bodies in Paramecium and mammalian cells. Moreover, we found that these proteins are recruited early during centriole duplication on the external surface of the procentriole. Functional analysis performed both in Paramecium and mammalian cells demonstrate the requirement of these proteins for distal appendage assembly and basal body docking. Finally, we show that mammalian centrioles require another component, Moonraker (MNR), to recruit OFD1, FOPNL, and CEP90, which will then recruit the distal appendage proteins CEP83, CEP89, and CEP164. Altogether, we propose that this OFD1, FOPNL, and CEP90 functional module is required to determine in mammalian cells the future position of distal appendage proteins.

Quantitative Proteomics in Yeast : From bSLIM and Proteome Discoverer Outputs to Graphical Assessment of the Significance of Protein Quantification Scores.

Simple light isotope metabolic labeling (bSLIM) is an innovative method to accurately quantify differences in protein abundance at the proteome level in standard bottom-up experiments. The quantification process requires computation of the ratio of intensity of several isotopologs in the isotopic cluster of every identified peptide. Thus, appropriate bioinformatic workflows are required to extract the signals from the instrument files and calculate the required ratio to infer peptide/protein abundance. In a previous study (Sénécaut et al., J Proteome Res 20:1476-1487, 2021), we developed original open-source workflows based on OpenMS nodes implemented in a KNIME working environment. Here, we extend the use of the bSLIM labeling strategy in quantitative proteomics by presenting an alternative procedure to extract isotopolog intensities and process them by taking advantage of new functionalities integrated into the Minora node of Proteome Discoverer 2.4 software. We also present a graphical strategy to evaluate the statistical robustness of protein quantification scores and calculate the associated false discovery rates (FDR). We validated these approaches in a case study in which we compared the differences between the proteomes of two closely related yeast strains.

Fetal Programming by Methyl Donor Deficiency Produces Pathological Remodeling of the Ascending Aorta.

[Figure: see text].

The M-phase regulatory phosphatase PP2A-B55δ opposes protein kinase A on Arpp19 to initiate meiotic division.

Oocytes are held in meiotic prophase for prolonged periods until hormonal signals trigger meiotic divisions. Key players of M-phase entry are the opposing Cdk1 kinase and PP2A-B55δ phosphatase. In Xenopus, the protein Arpp19, phosphorylated at serine 67 by Greatwall, plays an essential role in inhibiting PP2A-B55δ, promoting Cdk1 activation. Furthermore, Arpp19 has an earlier role in maintaining the prophase arrest through a second serine (S109) phosphorylated by PKA. Prophase release, induced by progesterone, relies on Arpp19 dephosphorylation at S109, owing to an unknown phosphatase. Here, we identified this phosphatase as PP2A-B55δ. In prophase, PKA and PP2A-B55δ are simultaneously active, suggesting the presence of other important targets for both enzymes. The drop in PKA activity induced by progesterone enables PP2A-B55δ to dephosphorylate S109, unlocking the prophase block. Hence, PP2A-B55δ acts critically on Arpp19 on two distinct sites, opposing PKA and Greatwall to orchestrate the prophase release and M-phase entry.

Novel Insights into Quantitative Proteomics from an Innovative Bottom-Up Simple Light Isotope Metabolic (bSLIM) Labeling Data Processing Strategy.

Simple light isotope metabolic labeling (SLIM labeling) is an innovative method to quantify variations in the proteome based on an original in vivo labeling strategy. Heterotrophic cells grown in U-[12C] as the sole source of carbon synthesize U-[12C]-amino acids, which are incorporated into proteins, giving rise to U-[12C]-proteins. This results in a large increase in the intensity of the monoisotope ion of peptides and proteins, thus allowing higher identification scores and protein sequence coverage in mass spectrometry experiments. This method, initially developed for signal processing and quantification of the incorporation rate of 12C into peptides, was based on a multistep process that was difficult to implement for many laboratories. To overcome these limitations, we developed a new theoretical background to analyze bottom-up proteomics data using SLIM-labeling (bSLIM) and established simple procedures based on open-source software, using dedicated OpenMS modules, and embedded R scripts to process the bSLIM experimental data. These new tools allow computation of both the 12C abundance in peptides to follow the kinetics of protein labeling and the molar fraction of unlabeled and 12C-labeled peptides in multiplexing experiments to determine the relative abundance of proteins extracted under different biological conditions. They also make it possible to consider incomplete 12C labeling, such as that observed in cells with nutritional requirements for nonlabeled amino acids. These tools were validated on an experimental dataset produced using various yeast strains of Saccharomyces cerevisiae and growth conditions. The workflows are built on the implementation of appropriate calculation modules in a KNIME working environment. These new integrated tools provide a convenient framework for the wider use of the SLIM-labeling strategy.