Metabolite-level regulation of enzyme activity is important for microbes to cope with environmental shifts. Knowledge of such regulations can also guide strain engineering for biotechnology. Here we apply limited proteolysis-small molecule mapping (LiP-SMap) to identify and compare metabolite-protein interactions in the proteomes of two cyanobacteria and two lithoautotrophic bacteria that fix CO2 using the Calvin cycle. Clustering analysis of the hundreds of detected interactions shows that some metabolites interact in a species-specific manner. We estimate that approximately 35% of interacting metabolites affect enzyme activity in vitro, and the effect is often minor. Using LiP-SMap data as a guide, we find that the Calvin cycle intermediate glyceraldehyde-3-phosphate enhances activity of fructose-1,6/sedoheptulose-1,7-bisphosphatase (F/SBPase) from Synechocystis sp. PCC 6803 and Cupriavidus necator in reducing conditions, suggesting a convergent feed-forward activation of the cycle. In oxidizing conditions, glyceraldehyde-3-phosphate inhibits Synechocystis F/SBPase by promoting enzyme aggregation. In contrast, the glycolytic intermediate glucose-6-phosphate activates F/SBPase from Cupriavidus necator but not F/SBPase from Synechocystis. Thus, metabolite-level regulation of the Calvin cycle is more prevalent than previously appreciated.

Metabolite-level regulation of enzyme activity is important for microbes to cope with environmental shifts. Knowledge of such regulations can also guide strain engineering to improve industrial phenotypes. Recently developed chemoproteomics workflows allow for genome-wide detection of metabolite-protein interactions that may regulate pathway activity. We applied limited proteolysis small molecule mapping (LiP-SMap) to identify and compare metabolite-protein interactions in the proteomes of two cyanobacteria and two lithoautotrophic bacteria that fix CO2 using the Calvin cycle. Clustering analysis of the hundreds of detected interactions showed that some metabolites interacted in a species-specific manner, such as interactions of glucose-6-phosphate in Cupriavidus necator and of glyoxylate in Synechocystis sp PCC 6803. These are interpreted in light of the different central carbon conversion pathways present. Metabolites interacting with the Calvin cycle enzymes fructose-1,6/sedoheptulose-1,7-bisphosphatase (F/SBPase) and transketolase were tested for effects on catalytic activity in vitro. The Calvin cycle intermediate glyceraldehyde-3-phosphate activated both Synechocystis and Cupriavidus F/SBPase, which suggests a feed-forward activation of the cycle in both photoautotrophs and chemolithoautotrophs. In contrast to the stimulating effect in reduced conditions, glyceraldehyde-3-phosphate inactivated the Synechocystis F/SBPase in oxidized conditions by accelerating protein aggregation. Thus, metabolite-level regulation of the Calvin cycle is more prevalent than previously appreciated and may act in addition to redox regulation.

Simple Summary Pyruvate kinase muscle type (PKM) is a key enzyme in glycolysis and is a mediator of the Warburg effect in tumors. The association of PKM with survival of cancer patients is controversial. In this study, we investigated the associations of the alternatively spliced transcripts of PKM with cancer patients' survival outcomes and explained the conflicts in previous studies. We discovered three poorly studied alternatively spliced PKM transcripts that exhibited opposite prognostic indications in different human cancers based on integrative systems analysis. We also detected their protein products and explored their potential biological functions based on in-vitro experiments. Our analysis demonstrated that alternatively spliced transcripts of not only PKM but also other genes should be considered in cancer studies, since it may enable the discovery and targeting of the right protein product for development of the efficient treatment strategies. Pyruvate kinase muscle type (PKM) is a key enzyme in glycolysis and plays an important oncological role in cancer. However, the association of PKM expression and the survival outcome of patients with different cancers is controversial. We employed systems biology methods to reveal prognostic value and potential biological functions of PKM transcripts in different human cancers. Protein products of transcripts were shown and detected by western blot and mass spectrometry analysis. We focused on different transcripts of PKM and investigated the associations between their mRNA expression and the clinical survival of the patients in 25 different cancers. We find that the transcripts encoding PKM2 and three previously unstudied transcripts, namely ENST00000389093, ENST00000568883, and ENST00000561609, exhibited opposite prognostic indications in different cancers. Moreover, we validated the prognostic effect of these transcripts in an independent kidney cancer cohort. Finally, we revealed that ENST00000389093 and ENST00000568883 possess pyruvate kinase enzymatic activity and may have functional roles in metabolism, cell invasion, and hypoxia response in cancer cells. Our study provided a potential explanation to the controversial prognostic indication of PKM, and could invoke future studies focusing on revealing the biological and oncological roles of these alternative spliced variants of PKM.

Targeted proteomics is an attractive approach for the analysis of blood proteins. Here, we describe a novel analytical platform based on isotope-labeled recombinant protein standards stored in a chaotropic agent and subsequently dried down to allow storage at ambient temperature. This enables a straightforward protocol suitable for robotic workstations. Plasma samples to be analyzed are simply added to the dried pellet followed by enzymatic treatment and mass spectrometry analysis. Here, we show that this approach can be used to precisely (coefficient of variation <10%) determine the absolute concentrations in human plasma of hundred clinically relevant protein targets, spanning four orders of magnitude, using simultaneous analysis of 292 peptides. The use of this next-generation analytical platform for high-throughput clinical proteome profiling is discussed. 

The proteins secreted by human cells (collectively referred to as the secretome) are important not only for the basic understanding of human biology but also for the identification of potential targets for future diagnostics and therapies. Here, we present a comprehensive analysis of proteins predicted to be secreted in human cells, which provides information about their final localization in the human body, including the proteins actively secreted to peripheral blood. The analysis suggests that a large number of the proteins of the secretome are not secreted out of the cell, but instead are retained intracellularly, whereas another large group of proteins were identified that are predicted to be retained locally at the tissue of expression and not secreted into the blood. Proteins detected in the human blood by mass spectrometry-based proteomics and antibody-based immuno-assays are also presented with estimates of their concentrations in the blood. The results are presented in an updated version 19 of the Human Protein Atlas in which each gene encoding a secretome protein is annotated to provide an open-access knowledge resource of the human secretome, including body-wide expression data, spatial localization data down to the single-cell and subcellular levels, and data about the presence of proteins that are detectable in the blood.

The use of affinity reagents, such as antibodies, for studying specific molecules in complex backgrounds are some of the most powerful tools for researchers in molecular biology. However, all experiments performed using affinity reagents are directly affected by each reagent’s context-dependent ability to bind specifically to a target of interest. A growing issue with non-validated, or poorly validated affinity reagents, has been highlighted by the International Working Group for Antibody Validation (IWGAV). It has been suggested that antibodies should be evaluated in an application-specific manner since they can perform well in one application but fail to deliver reproducible results in another. One of the most commonly used antibody-based applications is the Western blot (WB) technology. When evaluating the result from a WB experiment, the initial measure used for determining whether or not the antibody binds the protein of interest is to determine the molecular weight of the protein detected by the antibody compared to a set of reference proteins. As WB relies on the SDS-PAGE for separating differently sized proteins, the comparison is actually based on protein migration during electrophoresis. It is, however, well known that the migration of a protein can differ significantly from how the reference proteins migrate. Here, we suggest a method for determining the actual migration patterns of proteins instead of relying on the theoretical molecular weight of the protein. Using this approach, called migration capture mass spectrometry (MS), a dataset containing the migration patterns of more than 39,000 protein products from more than 10,500 genes across eleven cell lines and tissues has been created. This migration capture MS approach has been validated using k-fold cross validation against 249 siRNA knockdown WBs showing that the method has a sensitivity of 96.4%, specificity of 87.4% and accuracy of 91.9%, which makes the dataset a useful resource that can facilitate antibody validation strategies in a fit-for-purpose manner. The data set has allowed the automatic evaluation of more than 12,000 antibodies in the Human Protein Atlas using the method.

Metabolite-level regulation of enzyme activity is important for coping with environmental shifts. Recently developed proteomics methodologies allow for mapping of post-translational interactions, including metabolite-protein interactions, that may be relevant for quickly regulating pathway activity. While feedback and feedforward regulation in glycolysis has been investigated, there is relatively little study of metabolite-level regulation in the Calvin cycle, particularly in bacteria. Here, we applied limited proteolysis small molecule mapping (LiP-SMap) to identify metabolite-protein interactions in four Calvin-cycle harboring bacteria, including two cyanobacteria and two chemolithoautotrophs. We identified widespread protein interactions with the metabolites GAP, ATP, and AcCoA in all strains. Some species-specific interactions were also observed, such as sugar phosphates in Cupravidus necator and glyoxylate in Synechocystis sp. PCC 6803. We screened some metabolites with LiP interactions for their effects on kinetics of the enzymes F/SBPase and transketolase, two enzymatic steps of the Calvin cycle. For both Synechocystis and Cupriavidus F/SBPase, GAP showed an activating effect that may be part of feed-forward regulation in the Calvin cycle. While we verified multiple enzyme inhibitors on transketolase, the effect on kinetics was often small. Incorporation of F/SBPase and transketolase regulations into a kinetic metabolic model of Synechocystis central metabolism resulted in a general decreased stability of the network, and altered flux control coefficients of transketolase as well as other reactions. The LiP-SMap methodology is promising for uncovering new modes of metabolic regulation, but will benefit from improved peptide quantification and higher peptide coverage of enzymes, as known interactions are often not detected for low-coverage proteins. . Furthermore, not all LiP interactions appear to be relevant for catalysis, as 4/8 (transketolase) and 5/6 (F/SBPase) of the tested LiP effectors had an effect in in vitroassays.