User:Nikolai Slavov

Contact Info

Nikolai Slavov

• Nikolai Slavov
• van Oudenaarden Lab
• Massachusetts Institute of Technology, 68-359
• 77 Massachusetts Ave Cambridge, MA 02139
• http://www.people.fas.harvard.edu/~nslavov/
• http://mit.edu/nslavov/www/
• http://alum.mit.edu/www/nslavov
• Email me through OpenWetWare

Education

• 2010, PhD, Botstein Lab, Princeton University
• 2006, MS, Princeton University
• 2004, BS, Massachusetts Institute of Technology

Research interests

All living cells must coordinate protein synthesis, degradation and metabolism with fundamental biological processes, such as cell growth, division and differentiation. Gaps in our understanding of this coordination limit our ability to treat deregulated cell growth in cancer and to influence stem cell differentiation for regenerative therapies. To address these gaps, I aim to understand quantitatively, conceptually, and mechanistically the dynamics of this coordination with emphasis on ribosome specialization and direct precision measurements of metabolic and protein translation and degradation rates in absolute units, molecules per cell per hours.

I am also interested in the dynamics of cell growth, metabolic and regulatory processes during the eukaryotic cell division cycle (CDC), across a wide range of CDC periods. In particular, I study how the growth rate signal - which is function of the availability of nutrients and growth factors - regulates the switch between respiration and fermentation and changes the duration of phases of the cell growth and division cycles.

Publications

1. Slavov N., Botstein D., Caudy A. (2014)

   Extensive Regulation of Metabolism and Growth during the Cell Division Cycle. bioRxiv

   PDF

   Under review

2. Slavov N., Semrau S., Airoldi E.M., Budnik B., van Oudenaarden A. (2014)

   Variable stoichiometry among core ribosomal proteins. bioRxiv

   PDF

   Under review

3. Malioutov D., Slavov N. (2014)

   Convex Total Least Squares.

   JMLR, W&CP vol. 32, PDF

   The ordinary-least-squares, commonly known as regression, assumes that the independent variables are measured without error. However, most empirical measurements have varying degree of noise. Ignoring such variable noise in the the independent variables can result in large systematic errors in the inference even in the limit of infinite data. This article describes a principled solution (inference algorithm) for such problems, known as structured total-least-squares.

4. Slavov N., Budnik B., Schwab D., Airoldi E.M., van Oudenaarden A. (2014)

   Constant Growth Rate Can Be Supported by Decreasing Energy Flux and Increasing Aerobic Glycolysis.

   Cell Reports, vol. 7 PDF

   We find that exponential growth at a constant rate can represent not a single metabolic/physiological state but a continuum of changing states and that aerobic glycolysis can reduce the energy demands associated with respiratory metabolism and stress survival.

5. Slavov, N., Carey, J., Linse S. (2013)

   Calmodulin transduces Ca+2 oscillations into differential regulation of its target proteins.

   ACS Chemical Neuroscience, vol. 4, issue 2 PDF

   The molecular and network properties of the calmodulin signaling network, combined with its lignad-binding dynamics, can transduce a common signal (calcium levels) through a common signaling hub (calmodulin) and yet send different signals to many downstream proteins.

6. Slavov N. and Botstein D. (2012)

   Decoupling Nutrient Signaling from Growth Rate Causes Aerobic Glycolysis and Deregulation of Cell Size and Gene Expression

   Mol. Biol. Cell, vol. 24, no. 2 PDF

   The nutrition and the growth rate of a cell are two interacting factors with pervasive physiological effects. Our experiments decouple these factors and demonstrate the role of a growth rate signal, independent of the actual rate of biomass increase, on gene regulation, the cell division cycle, and the switch to a respiro-fermentative metabolism.

7. Slavov N., van Oudenaarden A.*(2012) How to Regulate a Gene: To Repress or to Activate? Mol. Cell, vol. 46, issue 5, 551-552

   PDF

8. Slavov N., Airoldi E., van Oudenaarden A., and Botstein D. (2012)

   A Conserved Cell Growth Cycle Can Account for the Environmental Stress Responses of Divergent Eukaryotes

   Mol. Biol. Cell, vol. 23, no. 10, 1986-1997 PDF

   We find that transitions between the two phases of the cell growth cycle can account for the environmental stress response, the growth-rate response, and the cross protection between slow growth and various types of stress factors. We suggest that this mechanism is conserved across budding and fission yeast, and normal human cells.

9. Slavov N., Macinskas J., Caudy A., Botstein D. (2011)

   Metabolic Cycling without Cell Division Cycling in Respiring Yeast

   PNAS, vol. 108, no. 47, 19090-19095 PDF

10. Slavov N. and Botstein D. (2011)

    Coupling among Growth Rate Response, Metabolic Cycle and Cell Division Cycle in Yeast

    Mol. Biol. Cell, vol. 22, 1997-2009 PDF

    We discovered that the relative durations of the phases of the yeast metabolic cycle change with the growth rate. These changes can explain mechanistically the transcriptional growth-rate responses of all yeast genes (25% of the genome) that we find to be the same across all studied nutrient limitations in either ethanol or glucose carbon source.

11. Slavov N. (2010)

    Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks, JMLR, vol. 9

    PDF

12. Silverman SJ, Petti AA, Slavov N, Parsons L, Briehof R, Thiberge SY, Zenklusen D, Gandhi SJ, Larson DR, Singer RH, and Botstein D. Metabolic cycling in single yeast cells from unsynchronized steady-state populations limited on glucose or phosphate. Proc Natl Acad Sci U S A. 2010 Apr 13;107(15):6946-51. DOI:10.1073/pnas.1002422107 |

    F1000 Review

13. Slavov N and Dawson KA. Correlation signature of the macroscopic states of the gene regulatory network in cancer. Proc Natl Acad Sci U S A. 2009 Mar 17;106(11):4079-84. DOI:10.1073/pnas.0810803106 |

Protocols

• Phosphate-Limited Medium with Ethanol as a Sole Source of Carbon and Energy[1]
• Glucose-Limited Mineral Medium[2]
• Ethanol-Limited Mineral Medium[3]