Mycobacterium tuberculosis-Driven Targeted Recalibration of Macrophage Lipid Homeostasis Promotes the Foamy Phenotype

SummaryUpon infection, Mycobacterium tuberculosis (Mtb) metabolically alters the macrophage to create a niche that is ideally suited to its persistent lifestyle. Infected macrophages acquire a “foamy” phenotype characterized by the accumulation of lipid bodies (LBs), which serve as both a source of nutrients and a secure niche for the bacterium. While the functional significance of the foamy phenotype is appreciated, the biochemical pathways mediating this process are understudied. We found that Mtb induces the foamy phenotype via targeted manipulation of host cellular metabolism to divert the glycolytic pathway toward ketone body synthesis. This dysregulation enabled feedback activation of the anti-lipolytic G protein-coupled receptor GPR109A, leading to perturbations in lipid homeostasis and consequent accumulation of LBs in the macrophage. ESAT-6, a secreted Mtb virulence factor, mediates the enforcement of this feedback loop. Finally, we demonstrate that pharmacological targeting of pathways mediating this host-pathogen metabolic crosstalk provides a potential strategy for developing tuberculosis chemotherapy

The Strength of Receptor Signaling Is Centrally Controlled through a Cooperative Loop between Ca2+ and an Oxidant Signal

SummaryActivation of cell-surface receptors stimulates generation of intracellular signals that, in turn, direct the cellular response. However, mechanisms that ensure combinatorial control of these signaling events are not well understood. We show here that the Ca2+ and reactive oxygen intermediates generated upon BCR activation rapidly engage in a cooperative interaction that acts in a feedback manner to amplify the early signal generated. This cooperativity acts by regulating the concentration of the oxidant produced. The latter exerts its influence through a pulsed inactivation of receptor-coupled phosphatases, where the amplitude of this pulse is determined by oxidant concentration. The extent of phosphatase inhibition, in turn, dictates what proportion of receptor-proximal kinases are activated and, as a result, the net strength of the initial signal. It is the strength of this initial signal that finally determines the eventual duration of BCR signaling and the rate of its transmission through downstream pathways

Genome-wide Analysis of the Host Intracellular Network that Regulates Survival of Mycobacterium tuberculosis

SummaryWe performed a genome-wide siRNA screen to identify host factors that regulated pathogen load in human macrophages infected with a virulent strain of Mycobacterium tuberculosis. Iterative rounds of confirmation, followed by validation, identified 275 such molecules that were all found to functionally associate with each other through a dense network of interactions. This network then yielded to a molecular description of the host cell functional modules that were both engaged and perturbed by the pathogen. Importantly, a subscreen against a panel of field isolates revealed that the molecular composition of the host interface varied with both genotype and the phenotypic properties of the pathogen. An analysis of these differences, however, permitted identification of those host factors that were invariantly involved, regardless of the diversification in adaptive mechanisms employed by the pathogen. Interestingly, these factors were found to predominantly function through the regulation of autophagy

Defining the Akt1 interactome data and delineating alterations in its composition as a function of cell cycle progression

Akt1 is a multi-functional protein implicated in key cellular processes including regulation of proliferation, survival, metabolism and protein synthesis. Its functional diversity results through interactions with other proteins which change with changing context. This study was designed to capture proteins, which interact with Akt1 as the cell cycle progresses from G0 to G1S and then G2 phase. Such an insight might help us understand the role of Akt1 in cell cycle, which as of now is not well explored. Akt1 expressing HEK 293 cells were cultured in light, medium and heavy labeled SILAC media. Normal lysine and arginine were incorporated as light labels; 6 Da (Dalton) heavier isotopes of the same amino acids were used as medium labels; while for heavy labeling the isotopes were 8 and 10 Da heavier. Light labeled cells were arrested in G0 phase while medium and heavy labeled cells were arrested in G2 and G1S phases, respectively. Equal number of cells from each phase was pooled, lysed and subjected to Affinity Purification coupled to Mass Spectroscopy (AP-MS). The obtained Akt1 protein partners were observed to change as the cell cycle progressed from G0 to G1S and then to G2 phase. Additionally, SILAC labeling aided in quantitative estimation of changing association of a number of proteins which were common to two or more phases, with Akt1. Data are available via ProteomeXchange with identifier PXD005557

Rb interactome data and its modulations during cell cycle progression in HEK 293 cells

The Rb protein is a tumor suppressor protein that regulates the key G1S checkpoint consequently blocking the progression of cell cycle into S-phase. Despite its pertinent role in cell cycle regulation, comprehensive information on its interacting partners across cell cycle progression is lacking. Here, we aim to submit a comprehensive set of Rb interactors as the cell progresses from G0 through G1 and S into G2 phase in HEK 293 cell line. Affinity purification of HA-tagged Rb protein along with its interactors was analyzed by mass spectrometry (AP-MS). SILAC labeling enabled differentiation of Rb interactors in different cell cycle stages as well as their quantification - G0 cells were labeled with light labels of lysine and arginine (K0R0), cells in G1S transition were labeled with heavy labels (K8R10) while the G2 cells were labeled with medium labels (K6R6). LC-MS/MS analysis resulted in 6 wiff files which were submitted to protein pilot software for peptide identification and quantification. Here we submit the dataset which clearly captures the changing interacting partners of the Rb protein as the cell cycle progressed from G0 through G1S checkpoint into G2 phase. Data is publicly available via ProteomeXchange with identifier PXD007708. Keywords: Rb, Cell cycle, Interactome, SILAC, AP-MS, HEK 293 cell

Dataset to delineate changes in association between Akt1 and its interacting partners as a function of active state of Akt1 protein

Akt1 is a multi-functional protein, implicated in multiple human solid tumors. Pertaining to its key role in cell survival, Akt1 is under focus for development of targeted therapies. Functional diversity of Akt1 is a result of its interactions with other proteins; which changes with changing context. This investigation was designed to capture the dynamics of Akt1 Interactome as a function of its active state. Delineating dynamic changes in association of Akt1 with its interactors could help us comprehend how it changes as a function of inhibition of its active form. Similar information on changes in Akt1 interactome as of now is not well explored. Akt1 expressing HEK293 cells were cultured in light and heavy labeled SILAC media. Normal lysine and arginine were incorporated as light labels while for heavy labeling the isotopes were 8 and 10 Da heavier. Light labeled cells represented the indigenous state of Akt1 interactome while heavy labeled cells represented Akt1 interactome in presence of its allosteric inhibitor, MK-2206. Equal number of cells from both conditions were pooled, lysed and subjected to Affinity Purification coupled to Mass Spectroscopy (AP-MS). Additionally, SILAC labeling aided in quantitative estimation of changing association of a number of proteins which were common to the two experimental conditions, with Akt1. Data are available via ProteomeXchange with identifier PXD005976. Keywords: Akt1, SILAC, Interactome, Affinity purification, Mass spectrometr

Delineation of key regulatory elements identifies points of vulnerability in the mitogen-activated signaling network

Drug development efforts against cancer are often hampered by the complex properties of signaling networks. Here we combined the results of an RNAi screen targeting the cellular signaling machinery, with graph theoretical analysis to extract the core modules that process both mitogenic and oncogenic signals to drive cell cycle progression. These modules encapsulated mechanisms for coordinating seamless transition of cells through the individual cell cycle stages and, importantly, were functionally conserved across different cancer cell types. Further analysis also enabled extraction of the core signaling axes that progressively guide commitment of cells to the division cycle. Importantly, pharmacological targeting of the least redundant nodes in these axes yielded a synergistic disruption of the cell cycle in a tissue-type-independent manner. Thus, the core elements that regulate temporally distinct stages of the cell cycle provide attractive targets for the development of multi-module-based chemotherapeutic strategies

Dataset generated using hyperplexing and click chemistry to monitor temporal dynamics of newly synthesized macrophage secretome post infection by mycobacterial strains

Here we provide data for SILAC and iTRAQ based hyperplexing combined with BONCAT based click chemistry for selective enrichment of newly synthesized proteins secreted by THP1 macrophages at various time points after infection with four different strains of Mycobacterium tuberculosis. The macrophages were infected with H37Ra, H37Rv, BND433 and JAL2287 strains of M. tuberculosis. Newly-synthesized secreted host proteins were observed, starting from six hours post-infection till 26 h, at 4 h intervals. We have combined BONCAT with hyperplexing (18-plex), which blends SILAC and iTRAQ, for the first time. Two sets of triplex SILAC were used to encode the strains of M. tuberculosis - H37Ra & H37Rv in one and BND433 & JAL2287 in another with a control in each. BONCAT was used to enrich the secretome for newly synthesized proteins while 6-plex iTRAQ labeling was employed to quantify the temporal changes in the captured proteome. Each set of 18-plex was run in 4 MS replicates with two linear and two non-linear separation modes. This new variant of hyperplexing method, combining triplex SILAC with 6-plex iTRAQ, achieves 18-plex quantitation in a single MS run. Hyperplexing enables large scale spatio-temporal systems biology studies where large number of samples can be processed simultaneously and in quantitative manner. Data are available via ProteomeXchange with identifier ProteomeXchange: PXD004281