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Sivakumar, P.

Publications and source records attributed to Sivakumar, P..

4 recordsLinked to original sources

Sporophyte Directed Gametogenesis via the Ubiquitin Proteasome System

Plants alternate between diploid sporophyte and haploid gametophyte generations. In mosses which retain features of ancestral land plants, the gametophyte is dominant and has an independent existence. However, in flowering plants the gametophyte has undergone evolutionary reduction to just a few cells enclosed within the sporophyte. The gametophyte is thought to retain genetic control of its development even after reduction. Here we demonstrate that male gametophyte development in Arabidopsis, long considered to be autonomous, is also under genetic control of the sporophyte via a repressive mechanism involving large-scale regulation of protein turnover. We identify an Arabidopsis gene SHUKR as an inhibitor of male gametogenesis. SHUKR is unrelated to proteins of known function and acts sporophytically in meiosis to control gametophyte development by negatively regulating expression of a large set of ubiquitination genes specific to post-meiotic gametogenesis. This control is late-emerging as SHUKR homologs are found only in eudicots. We show that SHUKR is rapidly evolving under positive selection suggesting that variation in control of protein turnover during male gametogenesis has played an important role in evolution within eudicots.

plant biology↗

Improved Validation of Protein Interactions usingBicistronic BiFC (Bi2FC)

Refolding based Bimolecular Fluorescence Complementation (BiFC) has emerged as an important in vivo technique to identify protein interactions. Significant improvements have been made to enhance the detection capacities of BiFC, however less attention has been paid to the detection of expression levels of proteins. Here we demonstrate development and validation of an improved method to identify protein interactions that incorporates an expression control based on bicistronic expression of the protein of interest and a fluorescent protein separated by a self-cleaving peptide. This method gives robust identification of positive interactions and more reliably identifies absence of interactions. We also show an earlier identified non-interacting pair in yeast two-hybrid (Y2H) to be interacting in vivo. BackgroundBimolecular Fluorescence Complementation (BiFC) is a well-utilized method to detect protein interactions in vivo (Kodama and Hu 2012). It is dependent on the refolding of a fluorescent protein split into two parts. The proximity between the two parts leads to functional refolding of the protein and a corresponding increase in the fluorescence intensity. Proteins of interest can be tagged to either part of the split fluorescent protein and be expressed together in a single cell. The physical proximity provided due to interactions between the proteins brings the two parts of the split fluorescent protein closer leading to the formation of a functional fluorescent complex. BiFC has at times been used as the sole technique to identify protein interactions in vivo or else as a step following identification of candidate positives by yeast two-hybrid (Y2H). In order to identify the interactions reliably it is also important to validate the gene expression status of BiFC elements (Kudla and Bock 2016). However, systems to visualize the interactions and expression status together are not available for plants. ResultsWe generated and validated a vector system, called Bi2FC (Bicistronic BiFC) vector system for verifying protein interactions in plants. Bicistronic expression of proteins of interest fused with the two different BiFC components and a fluorescent protein, separated by a self-cleaving peptide identified the expression status of the fusion, while simultaneously identifying positive and negative interactions. As a test, we identified interaction between MPK8 and GRF4 using our system, which were previously identified to not show interaction via Y2H. ConclusionWe described an improved BiFC method to current BiFC to identify the expression of individual proteins tagged with split fluorescent protein as well as to monitor their interaction in a plant cell. This method incorporates additional controls that express only the split fragments together with a vector control, while also providing a set of validated positive and negative controls. Using our method, we also show a previously identified non-interacting pair in yeast two-hybrid (Y2H) to be interacting, emphasizing the need for improved detection and validations.

molecular biology↗

The long non-coding RNA NEAT1 regulates the transcriptional landscape of cardiomyocytes

Long non-coding RNAs (lncRNAs) play a crucial role in fine-tuning the gene expression. In the present study, we identified that the lncRNA NEAT1 is upregulated in failing murine hearts and in human hypertrophic cardiomyopathies. Further investigations demonstrated that NEAT1 expression is regulated by calcium dependent NFAT (nuclear factor of activated T cells). Overexpression of NEAT1 led to increased cardiomyocyte size and elevated expression of cardiac stress markers while its depletion had the opposite effect. Through transcriptomic analysis in NEAT1-KO cells, we demonstrated the cis-regulatory role of NEAT1, wherein it maintains the transcription of neighboring genes by interacting with the coactivator p300. Additionally, NEAT1 depletion resulted in decreased expression of GRK2 (G protein-coupled receptor kinase 2), a key player in the development of cardiac hypertrophy, suggesting that NEAT1 contributes to the development of cardiac hypertrophy by regulating GRK2 expression. Consistent with this, Neat1-/- mice are resistant to {beta}-adrenergic stimulation. Overall, our study provides enough evidence that NEAT1 is a calcium-regulated, pro-hypertrophic lncRNA that exerts significant control over the transcriptional landscape of cardiomyocytes during heart failure.

cell biology↗

Integrative network modeling reveals mechanisms underlying T cell exhaustion

Failure to clear antigens causes CD8+ T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpin exhaustion. Topological analysis and simulation modeling of the network suggests CD8+ T cells undergo 2 major transitions in state following stimulation. The time cells spend in the earlier proliferative/pro-memory (PP) state is a fixed and inherent property of the network structure. Transition to the second state is necessary for exhaustion. Combining insights from network topology analysis and simulation modeling, we predict the extent to which each node in our network drives cells towards an exhausted state. We demonstrate the utility of our approach by experimentally testing the prediction that druginduced interference with EZH2 function increases the proportion of proliferative/pro-memory cells in the early days post-activation.

systems biology↗