Mohan Malleshaiah
Université de Montréal
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Publication
Featured researches published by Mohan Malleshaiah.
Nature | 2010
Mohan Malleshaiah; Vahid Shahrezaei; Peter S. Swain; Stephen W. Michnick
Evolution has resulted in numerous innovations that allow organisms to increase their fitness by choosing particular mating partners, including secondary sexual characteristics, behavioural patterns, chemical attractants and corresponding sensory mechanisms. The haploid yeast Saccharomyces cerevisiae selects mating partners by interpreting the concentration gradient of pheromone secreted by potential mates through a network of mitogen-activated protein kinase (MAPK) signalling proteins. The mating decision in yeast is an all-or-none, or switch-like, response that allows cells to filter weak pheromone signals, thus avoiding inappropriate commitment to mating by responding only at or above critical concentrations when a mate is sufficiently close. The molecular mechanisms that govern the switch-like mating decision are poorly understood. Here we show that the switching mechanism arises from competition between the MAPK Fus3 and a phosphatase Ptc1 for control of the phosphorylation state of four sites on the scaffold protein Ste5. This competition results in a switch-like dissociation of Fus3 from Ste5 that is necessary to generate the switch-like mating response. Thus, the decision to mate is made at an early stage in the pheromone pathway and occurs rapidly, perhaps to prevent the loss of the potential mate to competitors. We argue that the architecture of the Fus3–Ste5–Ptc1 circuit generates a novel ultrasensitivity mechanism, which is robust to variations in the concentrations of these proteins. This robustness helps assure that mating can occur despite stochastic or genetic variation between individuals. The role of Ste5 as a direct modulator of a cell-fate decision expands the functional repertoire of scaffold proteins beyond providing specificity and efficiency of information processing. Similar mechanisms may govern cellular decisions in higher organisms and be disrupted in cancer.
Nature | 2017
Ryohichi Sugimura; Deepak Kumar Jha; Areum Han; Clara Soria-Valles; Edroaldo Lummertz da Rocha; Yi-Fen Lu; Jeremy A. Goettel; Erik Serrao; R. Grant Rowe; Mohan Malleshaiah; Irene Wong; Patricia Sousa; Ted N. Zhu; Andrea Ditadi; Gordon Keller; Alan Engelman; Scott B. Snapper; Sergei Doulatov; George Q. Daley
A variety of tissue lineages can be differentiated from pluripotent stem cells by mimicking embryonic development through stepwise exposure to morphogens, or by conversion of one differentiated cell type into another by enforced expression of master transcription factors. Here, to yield functional human haematopoietic stem cells, we perform morphogen-directed differentiation of human pluripotent stem cells into haemogenic endothelium followed by screening of 26 candidate haematopoietic stem-cell-specifying transcription factors for their capacity to promote multi-lineage haematopoietic engraftment in mouse hosts. We recover seven transcription factors (ERG, HOXA5, HOXA9, HOXA10, LCOR, RUNX1 and SPI1) that are sufficient to convert haemogenic endothelium into haematopoietic stem and progenitor cells that engraft myeloid, B and T cells in primary and secondary mouse recipients. Our combined approach of morphogen-driven differentiation and transcription-factor-mediated cell fate conversion produces haematopoietic stem and progenitor cells from pluripotent stem cells and holds promise for modelling haematopoietic disease in humanized mice and for therapeutic strategies in genetic blood disorders.
Methods in Enzymology | 2010
Stephen W. Michnick; Po Hien Ear; Christian R. Landry; Mohan Malleshaiah; Vincent Messier
Protein-fragment complementation assays (PCAs) are a family of assays for detecting protein-protein interactions (PPIs) that have been developed to provide simple and direct ways to study PPIs in any living cell, multicellular organism or in vitro. PCAs can be used to detect PPI between proteins of any molecular weight and expressed at their endogenous levels. Proteins are expressed in their appropriate cellular compartments and can undergo any posttranslational modification or degradation that, barring effects of the PCA fragment fusion, they would normally undergo. Applications of PCAs in yeast have been limited until recently, simply because appropriate expression plasmids or cassettes had not been developed. However, we have now developed and reported on several PCAs in Saccharomyces cerevisiae that cover the gamut of applications one could envision for studying any aspect of PPIs. Here, we present detailed protocols for large-scale analysis of PPIs with the survival-selection dihydrofolate reductase (DHFR) reporter PCA and a new PCA based on a yeast cytosine deaminase reporter that allows for both survival and death selection. This PCA should prove a powerful way to dissect PPIs. We then present a method to study spatial localization and dynamics of PPIs based on fluorescent protein reporter PCAs and finally, two luciferase reporter PCAs that have proved useful for studies of dynamics of PPIs.
Nature Communications | 2011
Eduard Stefan; Mohan Malleshaiah; Billy Breton; Po Hien Ear; Verena Bachmann; Michael Beyermann; Michel Bouvier; Stephen W. Michnick
G-protein-coupled receptors sense extracellular chemical or physical stimuli and transmit these signals to distinct trimeric G-proteins. Activated Gα-proteins route signals to interconnected effector cascades, thus regulating thresholds, amplitudes and durations of signalling. Gαs- or Gαi-coupled receptor cascades are mechanistically conserved and mediate many sensory processes, including synaptic transmission, cell proliferation and chemotaxis. Here we show that a central, conserved component of Gαs-coupled receptor cascades, the regulatory subunit type-II (RII) of protein kinase A undergoes adenosine 3′-5′-cyclic monophosphate (cAMP)-dependent binding to Gαi. Stimulation of a mammalian Gαi-coupled receptor and concomitant cAMP-RII binding to Gαi, augments the sensitivity, amplitude and duration of Gαi:βγ activity and downstream mitogen-activated protein kinase signalling, independent of protein kinase A kinase activity. The mechanism is conserved in budding yeast, causing nutrient-dependent modulation of a pheromone response. These findings suggest a direct mechanism by which coincident activation of Gαs-coupled receptors controls the precision of adaptive responses of activated Gαi-coupled receptor cascades.
Methods of Molecular Biology | 2011
Stephen W. Michnick; Po Hien Ear; Christian R. Landry; Mohan Malleshaiah
Protein-fragment Complementation Assays (PCAs) are a family of assays for detecting protein-protein interactions (PPIs) that have been developed to provide simple and direct ways to study PPIs in any living cell, multicellular organism, or in vitro. PCAs can be used to detect PPI between proteins of any molecular weight and expressed at their endogenous levels. Proteins are expressed in their appropriate cellular compartments and can undergo any posttranslational modification or degradation that, barring effects of the PCA fragment fusion, they would normally undergo. Assays can be performed in any cell type or model organism that can be transformed or transfected with gene expression DNA constructs. Here we focus on recent applications of PCA in the budding yeast, Saccharomyces cerevisiae, that cover the gamut of applications one could envision for studying any aspect of PPIs. We present detailed protocols for large-scale analysis of PPIs with the survival-selection dihydrofolate reductase (DHFR), reporter PCA, and a new PCA based on a yeast cytosine deaminase reporter that allows for both survival and death selection. This PCA should prove a powerful way to dissect PPIs. We then present methods to study spatial localization and dynamics of PPIs based on fluorescent protein reporter PCAs.
PLOS ONE | 2008
Emily N. Manderson; Mohan Malleshaiah; Stephen W. Michnick
Background Despite extensive large scale analyses of expression and protein-protein interactions (PPI) in the model organism Saccharomyces cerevisiae, over a thousand yeast genes remain uncharacterized. We have developed a novel strategy in yeast that directly combines genetics with proteomics in the same screen to assign function to proteins based on the observation of genetic perturbations of sentinel protein interactions (GePPI). As proof of principle of the GePPI screen, we applied it to identify proteins involved in the regulation of an important yeast cell cycle transcription factor, SBF that activates gene expression during G1 and S phase. Methodology/Principle Findings The principle of GePPI is that if a protein is involved in a pathway of interest, deletion of the corresponding gene will result in perturbation of sentinel PPIs that report on the activity of the pathway. We created a fluorescent protein-fragment complementation assay (PCA) to detect the interaction between Cdc28 and Swi4, which leads to the inactivation of SBF. The PCA signal was quantified by microscopy and image analysis in deletion strains corresponding to 25 candidate genes that are periodically expressed during the cell cycle and are substrates of Cdc28. We showed that the serine-threonine kinase Elm1 plays a role in the inactivation of SBF and that phosphorylation of Elm1 by Cdc28 may be a mechanism to inactivate Elm1 upon completion of mitosis. Conclusions/Significance Our findings demonstrate that GePPI is an effective strategy to directly link proteins of known or unknown function to a specific biological pathway of interest. The ease in generating PCA assays for any protein interaction and the availability of the yeast deletion strain collection allows GePPI to be applied to any cellular network. In addition, the high degree of conservation between yeast and mammalian proteins and pathways suggest GePPI could be used to generate insight into human disease.
Cell Reports | 2016
Mohan Malleshaiah; Megha Padi; Pau Rué; John Quackenbush; Alfonso Martinez-Arias; Jeremy Gunawardena
Pluripotent cells give rise to distinct cell types during development and are regulated by often self-reinforcing molecular networks. How such networks allow cells to differentiate is less well understood. Here, we use integrative methods to show that external signals induce reorganization of the mouse embryonic stem cell pluripotency network and that a sub-network of four factors, Nac1, Oct4, Tcf3, and Sox2, regulates their differentiation into the alternative mesendodermal and neuroectodermal fates. In the mesendodermal fate, Nac1 and Oct4 were constrained within quantitative windows, whereas Sox2 and Tcf3 were repressed. In contrast, in the neuroectodermal fate, Sox2 and Tcf3 were constrained while Nac1 and Oct4 were repressed. In addition, we show that Nac1 coordinates differentiation by activating Oct4 and inhibiting both Sox2 and Tcf3. Reorganization of progenitor cell networks around shared factors might be a common differentiation strategy and our integrative approach provides a general methodology for delineating such networks.
Scientific Reports | 2015
Ruth Röck; Verena Bachmann; Hyo Eun C Bhang; Mohan Malleshaiah; Philipp Raffeiner; Johanna E. Mayrhofer; Philipp Tschaikner; Klaus Bister; Pia Aanstad; Martin G. Pomper; Stephen W. Michnick; Eduard Stefan
Membrane receptor-sensed input signals affect and modulate intracellular protein-protein interactions (PPIs). Consequent changes occur to the compositions of protein complexes, protein localization and intermolecular binding affinities. Alterations of compartmentalized PPIs emanating from certain deregulated kinases are implicated in the manifestation of diseases such as cancer. Here we describe the application of a genetically encoded Protein-fragment Complementation Assay (PCA) based on the Renilla Luciferase (Rluc) enzyme to compare binary PPIs of the spatially and temporally controlled protein kinase A (PKA) network in diverse eukaryotic model systems. The simplicity and sensitivity of this cell-based reporter allows for real-time recordings of mutually exclusive PPIs of PKA upon activation of selected endogenous G protein-coupled receptors (GPCRs) in cancer cells, xenografts of mice, budding yeast, and zebrafish embryos. This extends the application spectrum of Rluc PCA for the quantification of PPI-based receptor-effector relationships in physiological and pathological model systems.
Nature Communications | 2018
Edroaldo Lummertz da Rocha; R. Grant Rowe; Vanessa Lundin; Mohan Malleshaiah; Deepak Kumar Jha; Carlos R. Rambo; Hu Li; Trista E. North; James J. Collins; George Q. Daley
A better understanding of the cell-fate transitions that occur in complex cellular ecosystems in normal development and disease could inform cell engineering efforts and lead to improved therapies. However, a major challenge is to simultaneously identify new cell states, and their transitions, to elucidate the gene expression dynamics governing cell-type diversification. Here, we present CellRouter, a multifaceted single-cell analysis platform that identifies complex cell-state transition trajectories by using flow networks to explore the subpopulation structure of multi-dimensional, single-cell omics data. We demonstrate its versatility by applying CellRouter to single-cell RNA sequencing data sets to reconstruct cell-state transition trajectories during hematopoietic stem and progenitor cell (HSPC) differentiation to the erythroid, myeloid and lymphoid lineages, as well as during re-specification of cell identity by cellular reprogramming of monocytes and B-cells to HSPCs. CellRouter opens previously undescribed paths for in-depth characterization of complex cellular ecosystems and establishment of enhanced cell engineering approaches.Single cell analysis provides insight into cell states and transitions, but to interpret the data, improved algorithms are needed. Here, the authors present CellRouter as a method to analyse single-cell trajectories from RNA-sequencing data, and provide insight into erythroid, myeloid and lymphoid differentiation.
Developmental Cell | 2016
Mohan Malleshaiah; Jeremy Gunawardena
A new paper in Science reveals how repetitive stimulation can identify and help to repair fragilities within a signaling network, while using linear mathematical models inspired by engineering, thereby suggesting how cybernetic methods can be integrated into systems and synthetic biology.