1. 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% % %
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 )
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
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)
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)
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
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
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