Nikolai Slavov

About

Nikolai Slavov received his undergraduate education from the Massachusetts Institute of Technology (MIT) in 2004. He pursued doctoral research in the Botstein laboratory at Princeton University, aiming to understand how cells coordinate their growth, gene expression, and metabolism. He discovered a simple mechanism that can account for the growth-rate dependent transcriptional responses across a wide range of growth conditions and growth rates  (Slavov and Botstein, 2011, Slavov et al., 2011). After defending his dissertation in 2010, Nikolai Slavov began a postdoctoral project in the van Oudenaarden laboratory at MIT, aiming to understand the Warburg effect, a hallmark of cancer cells characterized by the fermentation of glucose in the presence of enough oxygen to support respiration. This work demonstrated that aerobic glycolysis can reduce the energy demands associated with respiratory metabolism and stress survival and that, contrary to expectations and decades-long assumptions, exponential growth at a constant rate can represent not a single metabolic/physiological state but a continuum of changing states characterized by different metabolic fluxes (Slavov et al., 2014). Following a lead from these experiments, Nikolai Slavov obtained direct evidence for differential stoichiometry among core ribosomal proteins in unperturbed wild-type cells (Slavov et al., 2015). His findings support the existence of ribosomes with distinct protein composition and physiological function that represent an explored layer of regulating gene expression.  Most recently, the Slavov laboratory developed methods for high-throughput Single Cell ProtEomics by Mass Spectrometry (SCoPE-MS and SCoPE2) and used them to quantify proteome heterogeneity during cell differentiation.

Selected Publications

• Slavov N.^✉ et al. (2019) Voices in methods development: Single-cell proteomics Nature Methods,  PDF
• Specht H, Emmott E, Koller T, Slavov N.✉ (2019) High-throughput single-cell proteomics quantifies the emergence of macrophage heterogeneity
  bioRxiv   DOI: 10.1101/665307   PDF   |   Data   |   SCP2019 talk   |   SCoPE2 Web
• Chen A, Franks A, Slavov N.^✉ (2019) DART-ID increases single-cell proteome coverage, PLoS Computational Biology, DOI: 10.1371/journal.pcbi.1007082  |  PDF   |   RAW Data @ MassIVE   |   GitHub |  DART-ID web
• Huffman RG, Specht H, Chen AT, Slavov N. (2019) DO-MS: Data-Driven Optimization of Mass Spectrometry Methods, J. of Proteome Res.,  DOI: 10.1021/acs.jproteome.9b00039 | DO-MS web  |  DO-MS @ GitHub 
• Budnik B., Levy E., Harmonage G., Slavov N. (2018) SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation, Genome Biology, DOI: 10.1186/s13059-018-1547-5  |  Data Web  |   SCoPE-MS blog  |  Highlight by Proteomics News | Highlight by Front Line Genomics
• Emmott EP, Jovanovic M, Slavov N.^✉ (2018) Ribosome stoichiometry: from form to function, Trends in Biomedical Sciences, DOI: 10.1016/j.tibs.2018.10.009   PDF
• Malioutov D., Chen T., Jaffe J., Airoldi E., Budnik B., Slavov N. ^✉ (2018) Quantifying homologous proteins and proteoforms, Molecular & Cellular Proteomics, DOI: 10.1101/168765 | PDF | HIquant server
• Specht H, Harmange G, Perlman DH, Emmott E, Niziolek Z, Budnik B, Slavov N.^✉Automated sample preparation for high-throughput single-cell proteomics, bioRxiv, DOI: 10.1101/399774   PDF   |   RAW Data @ MassIVE   |   SCP2018 Talk
• Specht H. & Slavov N. (2018) Transformative opportunities for single cell proteomics  J. of Proteome Res., 17 (8), 2565 – 2571
• Berg P., Budnik B., Slavov N., Semrau S. (2017) Dynamic post-transcriptional regulation during embryonic stem cell differentiation, bioRxiv, DOI: 10.1101/123497
• Franks A., Airoldi E.M., Slavov N. (2017) Post-transcriptional regulation across human tissues, PLoS Computational Biology, 13(5): e1005535, DOI: 10.1101/020206  | Highlight by The Scientist
• Slavov N. (2015) Making the most of peer review, eLife, 4:e12708
• Slavov N., Semrau S., Airoldi E., Budnik B., van Oudenaarden A., (2015) Differential Stoichiometry among Core Ribosomal Proteins, Cell Reports, 13(5), 865-873. (TiBS Spotlight)
• Malioutov D., Slavov N. (2014) Convex Total Least Squares, Journal of Machine Learning Research, W&CP, 32(1), 109-117.
• Slavov N., Budnik B., Schwab D., Airoldi E., van Oudenaarden A. (2014) Constant Growth Rate Can Be Supported by Decreasing Energy Flux and Increasing Aerobic Glycolysis, Cell Reports 7(3), 705-714.
• Slavov N., Carey, J., Linse, S. (2013) Calmodulin transduces Ca⁺² oscillations into differential regulation of its target proteins, ACS Chemical Neuroscience, 4, 601-612.
• Slavov N., Botstein D. (2013) Decoupling Nutrient Signaling from Growth Rate Causes Aerobic Glycolysis and Deregulation of Cell Size and Gene Expression, Molecular Biology of the Cell, 24(2), 157-168,
• Slavov N., van Oudenaarden A. (2012) How to Regulate a Gene: To Repress or to Activate?, Molecular Cell, 46(5), 551-552.
• Slavov N., Airoldi E.M., van Oudenaarden A., 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
• Slavov N., Macinskas J., Caudy A., Botstein D. (2011) Metabolic Cycling without Cell Division Cycling in Respiring Yeast, PNAS, vol. 108, 19090-19095
• Slavov N., Botstein D. (2011) Coupling among Growth Rate Response, Metabolic Cycle and Cell Division Cycle in Yeast, Mol. Biol. Cell, vol. 22
• Slavov N. (2010) Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks, JMLR, W&CP vol. 9
• Slavov, N., Dawson, K. (2009) Correlation Signature of the Macroscopic States of the Gene Regulatory Network in Cancer, PNAS, vol. 106, no. 11   PDF

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