Madden, V. J. | bioRxiv Science

bioRxiv2020

Potassium starvation induces autophagy in yeast

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.Competing Interest StatementThe authors have declared no competing interest.ABBREVIATIONSPIPhosphatidylinositolATGAutophagy-related geneSCDSynthetic Complete medium with DextroseYNBYeast Nitrogen BaseTEMTransmission Electron MicroscopyMAPKMitogen-Activated Protein KinaseDEGDifferentially Expressed Gene.View Full Text

biochemistry↗

bioRxiv2019

Rethinking pain threshold as a zone of uncertainty

BackgroundThe pain threshold is traditionally conceptualised as a boundary that lies between painful and non-painful events, suggesting a reasonably stable relationship between stimulus and response. In two previous experiments, participants received laser stimuli of various intensities and rated each stimulus on the Sensation and Pain Rating Scale (SPARS), which includes ranges for rating painful and non-painful events and clearly defines the presumed boundary between them. In the second experiment, participants also provided ratings on the conventional 0-100 Numerical Rating Scale for pain (NRS) and a new rating scale for non-painful events. Those data showed the SPARS to have a curvilinear stimulus-response relationship, reflecting that several different intensities may be rated as painful and non-painful in different trials. This suggests that participants were uncertain about painfulness over a range of intensities and calls into question the idea of a boundary between non-painful and painful events. The current study aimed to determine the number of different stimulus intensities across which each participant provided painful and non-painful reports in different trials.\n\nMethodsWe undertook novel exploratory analyses on data from the aforementioned two experiments (n = 19, 11 female, 18-31 years old; n = 7, 5 female, 21-30 years old). We used the binomial test to formally determine the width of this zone of uncertainty about painfulness, using ratings on the SPARS and the comparator scales, and data visualisation to assess whether trial-to-trial change in stimulus intensity influences ratings.\n\nResultsWe found that the width of the zone of uncertainty varied notably between individuals and that the zone was non-continuous for most participants. Plots of group-level data concealed the inter-individual variability apparent in the individual plots, but still showed a wide zone of uncertainty on both the SPARS and the NRS, but a narrow zone on the scale for non-painful events. There was no evidence that trial-to-trial change in stimulus intensity influenced ratings.\n\nConclusionsThe variability revealed by this study has important design implications for experiments that include initial calibration of repeatedly delivered stimuli. The variability also stands to inflate the size of sample that is required for adequate statistical powering of experiments, and provides rationale for the use of statistical approaches that account for individual variability in studies of pain. Finally, the high variability implies that, if experimental stimuli are to be used in clinical phenotyping, many trials may be required to obtain results that represent a single patients actual response profile.

neuroscience↗