Piero Giansanti

NF-κB-Independent Role of IKKα/IKKβ in Preventing RIPK1 Kinase-Dependent Apoptotic and Necroptotic Cell Death during TNF Signaling

TNF is a master pro-inflammatory cytokine. Activation of TNFR1 by TNF can result in both RIPK1-independent apoptosis and RIPK1 kinase-dependent apoptosis or necroptosis. These cell death outcomes are regulated by two distinct checkpoints during TNFR1 signaling. TNF-mediated NF-κB-dependent induction of pro-survival or anti-apoptotic molecules is a well-known late checkpoint in the pathway, protecting cells from RIPK1-independent death. On the other hand, the molecular mechanism regulating the contribution of RIPK1 to cell death is far less understood. We demonstrate here that the IKK complex phosphorylates RIPK1 at TNFR1 complex I and protects cells from RIPK1 kinase-dependent death, independent of its function in NF-κB activation. We provide in vitro and in vivo evidence that inhibition of IKKα/IKKβ or its upstream activators sensitizes cells to death by inducing RIPK1 kinase-dependent apoptosis or necroptosis. We therefore report on an unexpected, NF-κB-independent role for the IKK complex in protecting cells from RIPK1-dependent death downstream of TNFR1.

Quantitative and Qualitative Proteome Characteristics Extracted from In-Depth Integrated Genomics and Proteomics Analysis

Quantitative and qualitative protein characteristics are regulated at genomic, transcriptomic, and posttranscriptional levels. Here, we integrated in-depth transcriptome and proteome analyses of liver tissues from two rat strains to unravel the interactions within and between these layers. We obtained peptide evidence for 26,463 rat liver proteins. We validated 1,195 gene predictions, 83 splice events, 126 proteins with nonsynonymous variants, and 20 isoforms with nonsynonymous RNA editing. Quantitative RNA sequencing and proteomics data correlate highly between strains but poorly among each other, indicating extensive nongenetic regulation. Our multilevel analysis identified a genomic variant in the promoter of the most differentially expressed gene Cyp17a1, a previously reported top hit in genome-wide association studies for human hypertension, as a potential contributor to the hypertension phenotype in SHR rats. These results demonstrate the power of and need for integrative analysis for understanding genetic control of molecular dynamics and phenotypic diversity in a system-wide manner.

Six alternative proteases for mass spectrometry–based proteomics beyond trypsin

Protein digestion using a dedicated protease represents a key element in a typical mass spectrometry (MS)-based shotgun proteomics experiment. Up to now, digestion has been predominantly performed with trypsin, mainly because of its high specificity, widespread availability and ease of use. Lately, it has become apparent that the sole use of trypsin in bottom-up proteomics may impose certain limits in our ability to grasp the full proteome, missing out particular sites of post-translational modifications, protein segments or even subsets of proteins. To overcome this problem, the proteomics community has begun to explore alternative proteases to complement trypsin. However, protocols, as well as expected results generated from these alternative proteases, have not been systematically documented. Therefore, here we provide an optimized protocol for six alternative proteases that have already shown promise in their applicability in proteomics, namely chymotrypsin, LysC, LysN, AspN, GluC and ArgC. This protocol is formulated to promote ease of use and robustness, which enable parallel digestion with each of the six tested proteases. We present data on protease availability and usage including recommendations for reagent preparation. We additionally describe the appropriate MS data analysis methods and the anticipated results in the case of the analysis of a single protein (BSA) and a more complex cellular lysate (Escherichia coli). The digestion protocol presented here is convenient and robust and can be completed in ∼2 d.

Single-step Enrichment by Ti4+-IMAC and Label-free Quantitation Enables In-depth Monitoring of Phosphorylation Dynamics with High Reproducibility and Temporal Resolution

Quantitative phosphoproteomics workflows traditionally involve additional sample labeling and fractionation steps for accurate and in-depth analysis. Here we report a high-throughput, straightforward, and comprehensive label-free phosphoproteomics approach using the highly selective, reproducible, and sensitive Ti4+-IMAC phosphopeptide enrichment method. We demonstrate the applicability of this approach by monitoring the phosphoproteome dynamics of Jurkat T cells stimulated by prostaglandin E2 (PGE2) over six different time points, measuring in total 108 snapshots of the phosphoproteome. In total, we quantitatively monitored 12,799 unique phosphosites over all time points with very high quantitative reproducibility (average r > 0.9 over 100 measurements and a median cv < 0.2). PGE2 is known to increase cellular cAMP levels, thereby activating PKA. The in-depth analysis revealed temporal regulation of a wide variety of phosphosites associated not only with PKA, but also with a variety of other classes of kinases. Following PGE2 stimulation, several pathways became only transiently activated, revealing that in-depth dynamic profiling requires techniques with high temporal resolution. Moreover, the large publicly available dataset provides a valuable resource for downstream PGE2 signaling dynamics in T cells, and cAMP-mediated signaling in particular. More generally, our method enables in-depth, quantitative, high-throughput phosphoproteome screening on any system, requiring very little sample, sample preparation, and analysis time.

An Augmented Multiple-Protease-Based Human Phosphopeptide Atlas

Although mass-spectrometry-based screens enable thousands of protein phosphorylation sites to be monitored simultaneously, they often do not cover important regulatory sites. Here, we hypothesized that this is due to the fact that nearly all large-scale phosphoproteome studies are initiated by trypsin digestion. We tested this hypothesis using multiple proteases for protein digestion prior to Ti(4+)-IMAC-based enrichment. This approach increases the size of the detectable phosphoproteome substantially and confirms the considerable tryptic bias in public repositories. We define and make available a less biased human phosphopeptide atlas of 37,771 unique phosphopeptides, correlating to 18,430 unique phosphosites, of which fewer than 1/3 were identified in more than one protease data set. We demonstrate that each protein phosphorylation site can be linked to a preferred protease, enhancing its detection by mass spectrometry (MS). For specific sites, this approach increases their detectability by more than 1,000-fold.

Daily Rhythms in the Cyanobacterium Synechococcus elongatus Probed by High-resolution Mass Spectrometry–based Proteomics Reveals a Small Defined Set of Cyclic Proteins

Circadian rhythms are self-sustained and adjustable cycles, typically entrained with light/dark and/or temperature cycles. These rhythms are present in animals, plants, fungi, and several bacteria. The central mechanism behind these “pacemakers” and the connection to the circadian regulated pathways are still poorly understood. The circadian rhythm of the cyanobacterium Synechococcus elongatus PCC 7942 (S. elongatus) is highly robust and controlled by only three proteins, KaiA, KaiB, and KaiC. This central clock system has been extensively studied functionally and structurally and can be reconstituted in vitro. These characteristics, together with a relatively small genome (2.7 Mbp), make S. elongatus an ideal model system for the study of circadian rhythms. Different approaches have been used to reveal the influence of the central S. elongatus clock on rhythmic gene expression, rhythmic mRNA abundance, rhythmic DNA topology changes, and cell division. However, a global analysis of its proteome dynamics has not been reported yet. To uncover the variation in protein abundances during 48 h under light and dark cycles (12:12 h), we used quantitative proteomics, with TMT 6-plex isobaric labeling. We queried the S. elongatus proteome at 10 different time points spanning a single 24-h period, leading to 20 time points over the full 48-h period. Employing multidimensional separation and high-resolution mass spectrometry, we were able to find evidence for a total of 82% of the S. elongatus proteome. Of the 1537 proteins quantified over the time course of the experiment, only 77 underwent significant cyclic variations. Interestingly, our data provide evidence for in- and out-of-phase correlation between mRNA and protein levels for a set of specific genes and proteins. As a range of cyclic proteins are functionally not well annotated, this work provides a resource for further studies to explore the role of these proteins in the cyanobacterial circadian rhythm.

Interrogating cAMP-dependent Kinase Signaling in Jurkat T Cells via a Protein Kinase A Targeted Immune-precipitation Phosphoproteomics Approach

In the past decade, mass-spectrometry-based methods have emerged for the quantitative profiling of dynamic changes in protein phosphorylation, allowing the behavior of thousands of phosphorylation sites to be monitored in a single experiment. However, when one is interested in specific signaling pathways, such shotgun methodologies are not ideal because they lack selectivity and are not cost and time efficient with respect to instrument and data analysis time. Here we evaluate and explore a peptide-centric antibody generated to selectively enrich peptides containing the cAMP-dependent protein kinase (PKA) consensus motif. This targeted phosphoproteomic strategy is used to profile temporal quantitative changes of potential PKA substrates in Jurkat T lymphocytes upon prostaglandin E2 (PGE2) stimulation, which increases intracellular cAMP, activating PKA. Our method combines ultra-high-specificity motif-based immunoaffinity purification with cost-efficient stable isotope dimethyl labeling. We identified 655 phosphopeptides, of which 642 (i.e. 98%) contained the consensus motif [R/K][R/K/X]X[pS/pT]. When our data were compared with a large-scale Jurkat T-lymphocyte phosphoproteomics dataset containing more than 10,500 phosphosites, a minimal overlap of 0.2% was observed. This stresses the need for such targeted analyses when the interest is in a particular kinase. Our data provide a resource of likely substrates of PKA, and potentially some substrates of closely related kinases. Network analysis revealed that about half of the observed substrates have been implicated in cAMP-induced signaling. Still, the other half of the here-identified substrates have been less well characterized, representing a valuable resource for future research.

PZR coordinates Shp2 Noonan and LEOPARD syndrome signaling in zebrafish and mice

ABSTRACT Noonan syndrome (NS) is an autosomal dominant disorder caused by activating mutations in the PTPN11 gene encoding Shp2, which manifests in congenital heart disease, short stature, and facial dysmorphia. The complexity of Shp2 signaling is exemplified by the observation that LEOPARD syndrome (LS) patients possess inactivating PTPN11 mutations yet exhibit similar symptoms to NS. Here, we identify “protein zero-related” (PZR), a transmembrane glycoprotein that interfaces with the extracellular matrix to promote cell migration, as a major hyper-tyrosyl-phosphorylated protein in mouse and zebrafish models of NS and LS. PZR hyper-tyrosyl phosphorylation is facilitated in a phosphatase-independent manner by enhanced Src recruitment to NS and LS Shp2. In zebrafish, PZR overexpression recapitulated NS and LS phenotypes. PZR was required for zebrafish gastrulation in a manner dependent upon PZR tyrosyl phosphorylation. Hence, we identify PZR as an NS and LS target. Enhanced PZR-mediated membrane recruitment of Shp2 serves as a common mechanism to direct overlapping pathophysiological characteristics of these PTPN11 mutations.

PhosphoPath : Visualization of Phosphosite-centric Dynamics in Temporal Molecular Networks

Protein phosphorylation is an essential post-translational modification (PTM) regulating many biological processes at the cellular and multicellular level. Continuous improvements in phosphoproteomics technology allow the analysis of this PTM in an expanding biological content, yet up until now proteome data visualization tools are still very gene centric, hampering the ability to comprehensively map and study PTM dynamics. Here we present PhosphoPath, a Cytoscape app designed for the visualization and analysis of quantitative proteome and phosphoproteome data sets. PhosphoPath brings knowledge into the biological network by importing publically available data and enables PTM site-specific visualization of information from quantitative time series. To showcase PhosphoPath performance we use a quantitative proteomics data set comparing patient-derived melanoma cell lines grown in either conventional cell culture or xenografts.

Evaluating the promiscuous nature of tyrosine kinase inhibitors assessed in A431 epidermoid carcinoma cells by both chemical- and phosphoproteomics

Deregulation of protein tyrosine kinase signaling has been linked to many diseases, most notably cancer. As a consequence, small molecule inhibitors of protein tyrosine kinases may provide powerful strategies for treatment. Following the successful introduction of imatinib in the treatment of chronic myelogenous leukemia, such drugs are also now evaluated for other types of cancer. However, many developed kinase inhibitors are not very target-specific and therefore may induce side effects. The importance of such side effects is certainly cell-proteome dependent. Understanding the all-inclusive action of a tyrosine kinase inhibitor on each individual cell-type entails the identification of potential targets, combined with monitoring the downstream effects revealing the signaling networks involved. Here, we explored a multilevel quantitative mass spectrometry-based proteomic strategy to identify the direct targets and downstream signaling effect of four tyrosine kinase inhibitors (imatinib, dasatinib, bosutinib, and nilotinib) in epidermoid carcinoma cells, as a model system for skin-cancer. More than 25 tyrosine kinases showed affinity to the drugs, with imatinib and nilotinib displaying a high specificity, especially when compared to dasatinib and bosutinib. Consequently, the latter two drugs showed a larger effect on downstream phosphotyrosine signaling. Many of the proteins affected are key regulators in cell adhesion and invasion. Our data represents a multiplexed view on the promiscuous action of certain tyrosine kinase inhibitors that needs to be taking into consideration prior to the application of these drugs in the treatment of different forms of cancer.