L-Arginine Modulates T Cell Metabolism and Enhances Survival and Anti-tumor Activity.

Metabolic activity is intimately linked to T cell fate and function. Using high-resolution mass spectrometry, we generated dynamic metabolome and proteome profiles of human primary naive T cells following activation. We discovered critical changes in the arginine metabolism that led to a drop in intracellular L-arginine concentration. Elevating L-arginine levels induced global metabolic changes including a shift from glycolysis to oxidative phosphorylation in activated T cells and promoted the generation of central memory-like cells endowed with higher survival capacity and, in a mouse model, anti-tumor activity. Proteome-wide probing of structural alterations, validated by the analysis of knockout T cell clones, identified three transcriptional regulators (BAZ1B, PSIP1, and TSN) that sensed L-arginine levels and promoted T cell survival. Thus, intracellular L-arginine concentrations directly impact the metabolic fitness and survival capacity of T cells that are crucial for anti-tumor responses.

Global analysis of aging-related protein structural changes uncovers enzyme-polymerization-based control of longevity.

Aging is associated with progressive phenotypic changes. Virtually all cellular phenotypes are produced by proteins, and their structural alterations can lead to age-related diseases. However, we still lack comprehensive knowledge of proteins undergoing structural-functional changes during cellular aging and their contributions to age-related phenotypes. Here, we conducted proteome-wide analysis of early age-related protein structural changes in budding yeast using limited proteolysis-mass spectrometry (LiP-MS). The results, compiled in online ProtAge catalog, unraveled age-related functional changes in regulators of translation, protein folding, and amino acid metabolism. Mechanistically, we found that folded glutamate synthase Glt1 polymerizes into supramolecular self-assemblies during aging, causing breakdown of cellular amino acid homeostasis. Inhibiting Glt1 polymerization by mutating the polymerization interface restored amino acid levels in aged cells, attenuated mitochondrial dysfunction, and led to lifespan extension. Altogether, this comprehensive map of protein structural changes enables identifying mechanisms of age-related phenotypes and offers opportunities for their reversal.

Size-exclusion chromatography combined with DIA-MS enables deep proteome profiling of extracellular vesicles from melanoma plasma and serum.

Extracellular vesicles (EVs) are important players in melanoma progression, but their use as clinical biomarkers has been limited by the difficulty of profiling blood-derived EV proteins with high depth of coverage, the requirement for large input amounts, and complex protocols. Here, we provide a streamlined and reproducible experimental workflow to identify plasma- and serum- derived EV proteins of healthy donors and melanoma patients using minimal amounts of sample input. SEC-DIA-MS couples size-exclusion chromatography to EV concentration and deep-proteomic profiling using data-independent acquisition. From as little as 200 µL of plasma per patient in a cohort of three healthy donors and six melanoma patients, we identified and quantified 2896 EV-associated proteins, achieving a 3.5-fold increase in depth compared to previously published melanoma studies. To compare the EV-proteome to unenriched blood, we employed an automated workflow to deplete the 14 most abundant proteins from plasma and serum and thereby approximately doubled protein group identifications versus native blood. The EV proteome diverged from corresponding unenriched plasma and serum, and unlike the latter, separated healthy donor and melanoma patient samples. Furthermore, known melanoma markers, such as MCAM, TNC, and TGFBI, were upregulated in melanoma EVs but not in depleted melanoma plasma, highlighting the specific information contained in EVs. Overall, EVs were significantly enriched in intact membrane proteins and proteins related to SNARE protein interactions and T-cell biology. Taken together, we demonstrated the increased sensitivity of an EV-based proteomic workflow that can be easily applied to larger melanoma cohorts and other indications.

Stepwise priming by acidic pH and a high K+ concentration is required for efficient uncoating of influenza A virus cores after penetration.

UNLABELLED: Influenza A virus (IAV) uses the low pH in late endocytic vacuoles as a cue for penetration by membrane fusion. Here, we analyzed the prefusion reactions that prepare the core for uncoating after it has been delivered to the cytosol. We found that this priming process occurs in two steps that are mediated by the envelope-embedded M2 ion channel. The first weakens the interactions between the matrix protein, M1, and the viral ribonucleoprotein bundle. It involves a conformational change in a linker sequence and the C-terminal domain of M1 after exposure to a pH below 6.5. The second step is triggered by a pH of <6.0 and by the influx of K(+) ions. It causes additional changes in M1 as well as a loss of stability in the viral ribonucleoprotein bundle. Our results indicate that both the switch from Na(+) to K(+) in maturing endosomes and the decreasing pH are needed to prime IAV cores for efficient uncoating and infection of the host cell. IMPORTANCE: The entry of IAV involves several steps, including endocytosis and fusion at late endosomes. Entry also includes disassembly of the viral core, which is composed of the viral ribonucleoproteins and the RNA genome. We have found that the uncoating process of IAV is initiated long before the core is delivered into the cytosol. M2, an ion channel in the viral membrane, is activated when the virus passes through early endosomes. Here, we show that protons entering the virus through M2 cause a conformational change in the matrix protein, M1. This weakens interactions between M1 and the viral ribonucleoproteins. A second change was found to occur when the virus enters late endosomes. The preacidified core is then exposed to a high concentration of K(+), which affects the interactions between the ribonucleoproteins. Thus, when cores are finally delivered to the cytosol, they are already partially destabilized and, therefore, uncoating competent and infectious.

Elovanoid-N34 modulates TXNRD1 key in protection against oxidative stress-related diseases.

The thioredoxin (TXN) system is an NADPH + H+/FAD redox-triggered effector that sustains homeostasis, bioenergetics, detoxifying drug networks, and cell survival in oxidative stress-related diseases. Elovanoid (ELV)-N34 is an endogenously formed lipid mediator in neural cells from omega-3 fatty acid precursors that modulate neuroinflammation and senescence gene programming when reduction-oxidation (redox) homeostasis is disrupted, enhancing cell survival. Limited proteolysis (LiP) screening of human retinal pigment epithelial (RPE) cells identified TXNRD1 isoforms 2, 3, or 5, the reductase of the TXN system, as an intracellular target of ELV-N34. TXNRD1 silencing confirmed that the ELV-N34 target was isoform 2 or 3. This lipid mediator induces TXNRD1 structure changes that modify the FAD interface domain, leading to its activity modulation. The addition of ELV-N34 decreased membrane and cytosolic TXNRD1 activity, suggesting localizations for the targeted reductase. These results show for the first time that the lipid mediator ELV-N34 directly modulates TXNRD1 activity, underling its protection in several pathologies when uncompensated oxidative stress (UOS) evolves.

Compounds activating VCP D1 ATPase enhance both autophagic and proteasomal neurotoxic protein clearance.

Enhancing the removal of aggregate-prone toxic proteins is a rational therapeutic strategy for a number of neurodegenerative diseases, especially Huntington's disease and various spinocerebellar ataxias. Ideally, such approaches should preferentially clear the mutant/misfolded species, while having minimal impact on the stability of wild-type/normally-folded proteins. Furthermore, activation of both ubiquitin-proteasome and autophagy-lysosome routes may be advantageous, as this would allow effective clearance of both monomeric and oligomeric species, the latter which are inaccessible to the proteasome. Here we find that compounds that activate the D1 ATPase activity of VCP/p97 fulfill these requirements. Such effects are seen with small molecule VCP activators like SMER28, which activate autophagosome biogenesis by enhancing interactions of PI3K complex components to increase PI(3)P production, and also accelerate VCP-dependent proteasomal clearance of such substrates. Thus, this mode of VCP activation may be a very attractive target for many neurodegenerative diseases.

Mechanistic Insights into a CDK9 Inhibitor Via Orthogonal Proteomics Methods.

Cyclin-dependent-kinases (CDKs) are members of the serine/threonine kinase family and are highly regulated by cyclins, a family of regulatory subunits that bind to CDKs. CDK9 represents one of the most studied examples of these transcriptional CDKs. CDK9 forms a heterodimeric complex with its regulatory subunit cyclins T1, T2 and K to form the positive transcription elongation factor b (P-TEFb). This complex regulates transcription via the phosphorylation of RNA polymerase II (RNAPolII) on Ser-2, facilitating promoter clearance and transcription elongation and thus remains an attractive therapeutic target. Herein, we have utilized classical affinity purification chemical proteomics, kinobeads assay, compressed CEllular Thermal Shift Assay (CETSA)-MS and Limited Proteolysis (LiP) to study the selectivity, target engagement and downstream mechanistic insights of a CDK9 tool compound. The above experiments highlight the value of quantitative mass spectrometry approaches to drug discovery, specifically proteome wide target identification and selectivity profiling. The approaches utilized in this study unanimously indicated that the CDK family of kinases are the main target of the compound of interest, with CDK9, showing the highest target affinity with remarkable consistency across approaches. We aim to provide guidance to the scientific community on the available chemical biology/proteomic tools to study advanced lead molecules and to highlight pros and cons of each technology while describing our findings in the context of the CDKs biology.

Reversible protein aggregation is a protective mechanism to ensure cell cycle restart after stress.

Protein aggregation is mostly viewed as deleterious and irreversible causing several pathologies. However, reversible protein aggregation has recently emerged as a novel concept for cellular regulation. Here, we characterize stress-induced, reversible aggregation of yeast pyruvate kinase, Cdc19. Aggregation of Cdc19 is regulated by oligomerization and binding to allosteric regulators. We identify a region of low compositional complexity (LCR) within Cdc19 as necessary and sufficient for reversible aggregation. During exponential growth, shielding the LCR within tetrameric Cdc19 or phosphorylation of the LCR prevents unscheduled aggregation, while its dephosphorylation is necessary for reversible aggregation during stress. Cdc19 aggregation triggers its localization to stress granules and modulates their formation and dissolution. Reversible aggregation protects Cdc19 from stress-induced degradation, thereby allowing cell cycle restart after stress. Several other enzymes necessary for G1 progression also contain LCRs and aggregate reversibly during stress, implying that reversible aggregation represents a conserved mechanism regulating cell growth and survival.

Measuring protein structural changes on a proteome-wide scale using limited proteolysis-coupled mass spectrometry.

Protein structural changes induced by external perturbations or internal cues can profoundly influence protein activity and thus modulate cellular physiology. A number of biophysical approaches are available to probe protein structural changes, but these are not applicable to a whole proteome in a biological extract. Limited proteolysis-coupled mass spectrometry (LiP-MS) is a recently developed proteomics approach that enables the identification of protein structural changes directly in their complex biological context on a proteome-wide scale. After perturbations of interest, proteome extracts are subjected to a double-protease digestion step with a nonspecific protease applied under native conditions, followed by complete digestion with the sequence-specific protease trypsin under denaturing conditions. This sequential treatment generates structure-specific peptides amenable to bottom-up MS analysis. Next, a proteomics workflow involving shotgun or targeted MS and label-free quantification is applied to measure structure-dependent proteolytic patterns directly in the proteome extract. Possible applications of LiP-MS include discovery of perturbation-induced protein structural alterations, identification of drug targets, detection of disease-associated protein structural states, and analysis of protein aggregates directly in biological samples. The approach also enables identification of the specific protein regions involved in the structural transition or affected by the binding event. Sample preparation takes approximately 2 d, followed by one to several days of MS and data analysis time, depending on the number of samples analyzed. Scientists with basic biochemistry training can implement the sample preparation steps. MS measurement and data analysis require a background in proteomics.

Selected Reaction Monitoring to Measure Proteins of Interest in Complex Samples: A Practical Guide.

Biology and especially systems biology projects increasingly require the capability to detect and quantify specific sets of proteins across multiple samples, for example the components of a biological pathway through a set of perturbation-response experiments. Targeted proteomics based on selected reaction monitoring (SRM) has emerged as an ideal tool to this purpose, and complements the discovery capabilities of shotgun proteomics methods. SRM experiments rely on the development of specific, quantitative mass spectrometric assays for each protein of interest and their application to the quantification of the protein set in various biological samples. SRM measurements are multiplexed, namely, multiple proteins can be quantified simultaneously, and are characterized by a high reproducibility and a broad dynamic range. We provide here a practical guide to the development of SRM assays targeting a set of proteins of interest and to their application to complex biological samples.

Global analysis of protein structural changes in complex proteomes.

Changes in protein conformation can affect protein function, but methods to probe these structural changes on a global scale in cells have been lacking. To enable large-scale analyses of protein conformational changes directly in their biological matrices, we present a method that couples limited proteolysis with a targeted proteomics workflow. Using our method, we assessed the structural features of more than 1,000 yeast proteins simultaneously and detected altered conformations for ~300 proteins upon a change of nutrients. We find that some branches of carbon metabolism are transcriptionally regulated whereas others are regulated by enzyme conformational changes. We detect structural changes in aggregation-prone proteins and show the functional relevance of one of these proteins to the metabolic switch. This approach enables probing of both subtle and pronounced structural changes of proteins on a large scale.

Reproducibility of combinatorial peptide ligand libraries for proteome capture evaluated by selected reaction monitoring.

UNLABELLED: Systems biology studies require the capability to quantify with high precision proteins spanning a broad range of abundances across multiple samples. However, the broad range of protein expression in cells often precludes the detection of low-abundance proteins. Different sample processing techniques can be applied to increase proteome coverage. Among these, combinatorial (hexa)peptide ligand libraries (CPLLs) bound to solid matrices have been used to specifically capture and detect low-abundance proteins in complex samples. To assess whether CPLL capture can be applied in systems biology studies involving the precise quantitation of proteins across a multitude of samples, we evaluated its performance across the whole range of protein abundances in Saccharomyces cerevisiae. We used selected reaction monitoring assays for a set of target proteins covering a broad abundance range to quantitatively evaluate the precision of the approach and its capability to detect low-abundance proteins. Replicated CPLL-isolates showed an average variability of ~10% in the amount of the isolated proteins. The high reproducibility of the technique was not dependent on the abundance of the protein or the amount of beads used for the capture. However, the protein-to-bead ratio affected the enrichment of specific proteins. We did not observe a normalization effect of CPLL beads on protein abundances. However, CPLLs enriched for and depleted specific sets of proteins and thus changed the abundances of proteins from a whole proteome extract. This allowed the identification of ~400 proteins otherwise undetected in an untreated sample, under the experimental conditions used. CPLL capture is thus a useful tool to increase protein identifications in proteomic experiments, but it should be coupled to the analysis of untreated samples, to maximize proteome coverage. Our data also confirms that CPLL capture is reproducible and can be confidently used in quantitative proteomic experiments. SIGNIFICANCE: Combinatorial hexapeptide ligand libraries (CPLLs) bound to solid matrices have been proposed to specifically capture and detect low-abundance proteins in complex samples. To assess whether the CPLL capture can be confidently applied in systems biology studies involving the precise quantitation of proteins across a broad range of abundances and a multitude of samples, we evaluated its reproducibility and performance features. Using selected reaction monitoring assays for proteins covering the whole range of abundances we show that the technique is reproducible and compatible with quantitative proteomic studies. However, the protein-to-bead ratio affects the enrichment of specific proteins and CPLLs depleted specific sets of proteins from a whole proteome extract. Our results suggest that CPLL-based analyses should be coupled to the analysis of untreated samples, to maximize proteome coverage. Overall, our data confirms the applicability of CPLLs in systems biology research and guides the correct use of this technique.