Growth media carbon source Acetate Galactose Glucose Coordinated mechanisms in the nucleus and cytoplasm mediate global tuning of gene expression as a function of growth rate Rodoniki Athanasiadou1, Benjy Neymotin1, Daniel Tranchina1,2, Naomi Ziv1, Nathan Brandt1, David Gresham1 1Center for Genomics and Systems Biology, New York University; 2Courant Institute of Mathematical Sciences, New York University, New York, USA A. Motivation Saccharomyces cerevisiae Growth rate, GR (hour-1) Growth media carbon source 0.2% 0.2% 0.2% Acetate Galactose Glucose 0.4 0.3 0.2 0.1 1. The environment exerts a strong effect on a cell’s growth rate (GR). 2. Growth rate (GR) is positively correlated with RNA density in the cell’s cytoplasm. In the literature The intensity of the response depends on the limiting nutrient Nutrient concentration Nutrient molecular form Growth rate manipulation of unicellular organisms Eschericia coli, Streptomyces coelicolor, Selenomonad ruminantium, Mycobacterium bovis, Saccharomyces cerevisiae, Neurospora crassa, Prototheca zopfii (Karpinets et al. 2006) Within population natural growth rate variability and RNA measurements Cricetulus ariseus (CHO line) (Darzynkiewicz et al. 1979) Overexpression of the c-Myc oncogene and total RNA content in mammalian cell cultures (Lovén et al. 20012) Microcolony assay Calculations based on quantitative RNA extractions Cell diameters measured with a Coulter counter The micro-colony assay uses real-time microscopy, to capture the change in yeast colony size, derived from a single cell, as a function of time. Method N2-controlled C-controlled 0.12 0.2 0.3 Growth rate (hour-1) 15 10 5 RNA density (fg/fl) N2-controlled chemostats B. Relative abundance of each RNA class per GR RNA content (pg/cell) ES cells HEK293 cells (kidney) Neurons Cellular differentiation in multicellular organisms has a profound effect on growth rate GR≈0.04 divisions/h GR≈0.02 divisions/h GR=0 divisions/h Chemostats allow the precise control of growth rate by controlling the concentration of a single specific nutrient in the growth media. Method Input media Output media & cells Ks,1 Ks,3 Ks,2 Population size Time rRNA Calculations based on quantitative rRNA depletion experiments (ribo-zero, triplicates) 0.12 0.2 0.3 0.12 0.2 0.3 Growth rate (hour-1) C-controlled chemostats N2-controlled C-controlled Growth rate (GR, hour-1) D. RNA degradation rates are a function of GR C. mRNA levels co-vary with GR 2. Other RNA classes Measurements from RNA-seq using the “Global spike-in population profile normalization method” (Method box at bottom) Distribution of mRNA degradation rates (RATE-seq) Response of individual mRNA degradation rates to the cell’s growth rate Distribution of the mRNA abundance response to GR GO term enrichment of mRNAs not responding to GR (negative slopes, ~17% of all) C N2 GR 0.12 0.2 0.3 1.4 1.0 0.6 0.2 Growth rate (hour-1) 0.12 0.2 0.3 N2-controlled log-RNA degradation rate (min-1) 0.07 0.06 0.05 0.04 0.03 0.02 0.01 -log(p-value) log-RNA response to GR (slope) Degradation rate (min-1) C N2 E. Conclusions and future directions 0.10 0.15 0.20 0.25 0.30 1. GR-dependent baseline transcription 2. Global RNA absolute abundance measurements Growth rate (hour-1) Synthesis rates calculated by the formula: Abundance = Synthesis - Degradation 5 -5 -10 log2-Molecules/cell 0.12 0.2 0.3 Growth rate (hour-1) Holstege et al. N2 C Method RATE-seq measures global RNA degradation rates (Neymotin et al. 2014) The concurrent positive response of absolute RNA abundance and RNA degradation rates to growth rate can be explained by an even bigger global increase in transcription. With our method we are able to measure absolute transcript abundance in molecule/cell units. Our absolute abundance measurements are consistent with previous studies (Holstege et al.). F. References Method Common normalization methods The problem with normalization Global spike-in population profile normalization method A B RNA extraction Modeling approach x: molecules/cell Method Measured unit Normalization Southern Pixels, AU (Bq) housekeeping, rRNA , total RNA (q)PCR Cycle, Ct housekeeping, std curve microarrays AU (hv) total RNA, various housekeeping RNA-seq Reads length, total RNA Global changes on transcription violate the assumption of constant mean expression levels. Darzynkiewicz, D., P. Evenson, L. Staiano-Coico, T. K. Sharpless, M.L. Melamed (1979) Journal of Cellular physiology, 100:425 Holstege FC, Jennings EG, Wyrick JJ, Lee TI, Hengartner CJ, Green MR, Golub TR, Lander ES, Young RA (1998) Cell, 95:717 Karpinets,T. V., Greenwood, D. J, Sams,C. E., Ammons, J. T. (2006) BMC Biology, 4:30 Lovén, J., Orlando, D. A., Sigova, A. A., Lin, C. Y., Rahl, P. B., Burge, C. B.,Young, R. A. (2012) Cell, 151:476. Neymotin, B., Athanasiadou R., Gresham D. (2014) RNA, 20:1645 Low GR High GR (1x RNA/cell) (5x RNA/cell) Cellular RNA External RNA spike-in Fixed no. of cells/tube Fixed vol. spike-in Experimental Black Box Transcript length Transcript thermodynamic parameters Random PCR effects Random sampling at sequencing Random post-processing artifacts EBB A B Expression levels f(x): fragment counts