Quantitative analysis of the yeast pheromone pathway

Shellhammer, James P.; Pomeroy, Amy E.; Li, Yang; Dujmusic, Lorena; Elston, Timothy C.; Hao, Nan; Dohlman, Henrik G.

doi:10.1002/yea.3395

Cited by 18 publications

(20 citation statements)

References 134 publications

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“…We next applied MISC to determine the underlying signaling motifs from experimental data. We focused on the transcriptional response to environmental stress in budding yeast, which has been studied extensively using time-lapse fluorescence microscopy [ 21 , 28 , 29 ]. To predict the signaling motifs at work in the yeast stress response, we used previously published single-cell data in which two signaling activities were measured in the same cell over time [ 21 ].…”

Section: Resultsmentioning

confidence: 99%

Inferring the structures of signaling motifs from paired dynamic traces of single cells

Haggerty

Purvis

2021

PLoS Comput Biol

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Individual cells show variability in their signaling dynamics that often correlates with phenotypic responses, indicating that cell-to-cell variability is not merely noise but can have functional consequences. Based on this observation, we reasoned that cell-to-cell variability under the same treatment condition could be explained in part by a single signaling motif that maps different upstream signals into a corresponding set of downstream responses. If this assumption holds, then repeated measurements of upstream and downstream signaling dynamics in a population of cells could provide information about the underlying signaling motif for a given pathway, even when no prior knowledge of that motif exists. To test these two hypotheses, we developed a computer algorithm called MISC (Motif Inference from Single Cells) that infers the underlying signaling motif from paired time-series measurements from individual cells. When applied to measurements of transcription factor and reporter gene expression in the yeast stress response, MISC predicted signaling motifs that were consistent with previous mechanistic models of transcription. The ability to detect the underlying mechanism became less certain when a cell’s upstream signal was randomly paired with another cell’s downstream response, demonstrating how averaging time-series measurements across a population obscures information about the underlying signaling mechanism. In some cases, motif predictions improved as more cells were added to the analysis. These results provide evidence that mechanistic information about cellular signaling networks can be systematically extracted from the dynamical patterns of single cells.

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Section: Resultsmentioning

confidence: 99%

Inferring the structures of signaling motifs from paired dynamic traces of single cells

Haggerty

Purvis

2021

PLoS Comput Biol

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“…Rosella plasmid pAS1NB-DsRed.T3-SEP (2µ, amp R , LEU2 + ) was a gift from Mark Prescott and Rodney Devenish (37). The Kss1-9xMyc-tagged strain was generated by homologous recombination of a PCR-amplified 9xMyc cassette harboring a resistance gene to hygromycin B from plasmid pYM20 (pYM-9xMyc-hphNT1) at the C-terminus of the KSS1 open reading frame (ORF) (83,84).…”

Section: Methodsmentioning

confidence: 99%

“…Cell viability was measured using a Celigo S Imaging Cytometer (Nexcelom) as described previously (83). Briefly, 200 µl of cells at OD 600 ~ 0.05 were mixed with 20 µM Propidium Iodide (P3566, Molecular Probes) and plated in half-area, black, clear-bottom 96-well plates (Greiner CELLSTAR) by centrifugation at 500g for 5 min at 4°C.…”

Section: Methodsmentioning

confidence: 99%

“…PhosphoMAPK analysis. MAP kinase activation was measured using quantitative immunoblotting as previously described (83). Briefly, BY4741 Kss1-9xMyc cells were grown to OD 600 ~ 1 in SCD medium and transferred to SCD-nitrogen or SCD-potassium medium (starvation conditions) or treated with 3 µM α factor pheromone (positive control).…”

Section: Gfp-atg8 Immunoblottingmentioning

confidence: 99%

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Potassium starvation induces autophagy in yeast

Rangarajan

Kapoor

et al. 2020

Preprint

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ABSTRACTAutophagy is a conserved process that recycles cellular contents to promote survival. Although nitrogen starvation is the canonical inducer of autophagy, recent studies have revealed several other nutrients important to this process. In this study, we used a quantitative, high-throughput assay to identify potassium starvation as a new and potent inducer of autophagy. We found that potassium-dependent autophagy requires the core pathway kinases Atg1, Atg5, Vps34, as well as other components of Phosphatidylinositol 3-kinase Complex I. Transmission electron microscopy revealed abundant autophagosome formation in response to both stimuli. RNA sequencing indicated distinct transcriptional responses – nitrogen affects transport of ions such as copper while potassium targets the organization of other cellular components. Thus, nitrogen and potassium share the ability to influence metabolic supply and demand but do so in different ways. Both inputs promote catabolism through bulk autophagy, but inhibit cellular anabolism through distinct mechanisms.

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“…We focused on the transcriptional response to environmental stress in budding yeast, which has been studied extensively using time-lapse fluorescence microscopy [21,25,26]. To predict the signaling motifs at work in the yeast stress response, we used previously published single-cell data in which two signaling activities were measured in the same cell over time [21].…”

Section: Different Yeast Stress Response Pathways Show Use Of the Sammentioning

confidence: 99%

Inferring the structures of signaling motifs from paired dynamic traces of single cells

Haggerty¹,

Purvis²

2019

Preprint

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Individual cells show variability in their signaling dynamics that often correlates with phenotypic responses, indicating that cell-to-cell variability is not merely noise but can have functional consequences. Based on this observation, we reasoned that cell-to-cell variability under the same treatment condition could be explained by a single signaling motif that deterministically maps different upstream signals into a corresponding set of downstream responses. If this assumption holds, then repeated measurements of upstream and downstream signaling dynamics in single cells could provide information about the underlying signaling motif for a given pathway, even when no prior knowledge of that motif exists. To test these two hypotheses, we developed a computer algorithm called MISC (Motif Inference from Single Cells) that infers the underlying signaling motif from paired time-series measurements from individual cells. When applied to measurements of transcription factor and reporter gene expression in the yeast stress response, MISC predicted signaling motifs that were consistent with previous mechanistic models of transcription. The ability to detect the underlying mechanism became less certain when a cell's upstream signal was randomly paired with another cell's downstream response, demonstrating how averaging time-series measurements across a population obscures information about the underlying signaling mechanism. In some cases, motif predictions improved as more cells were added to the analysis. These results provide evidence that mechanistic information about cellular signaling networks can be embedded within the dynamical patterns of single cells. Author SummaryCells use molecular signaling networks to translate dynamically changing stimuli into appropriate downstream responses. Specialized network structures, or motifs, allow cells to properly decode a variety of temporal input signals. In this paper, we present an algorithm that infers signaling motifs from multiple examples of an upstream signal paired with its downstream response in the same cell. We compare the predictive power of single-cell versus averaged time-series traces and the incremental benefit of adding more single-cell traces to the algorithm.We use this approach to understand how yeast respond to environmental stresses.

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Quantitative analysis of the yeast pheromone pathway

Cited by 18 publications

References 134 publications

Inferring the structures of signaling motifs from paired dynamic traces of single cells

Inferring the structures of signaling motifs from paired dynamic traces of single cells

Potassium starvation induces autophagy in yeast

Inferring the structures of signaling motifs from paired dynamic traces of single cells

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