Publications

2019
Emmott E, Jovanovic M, Slavov N. Approaches for Studying Ribosome Specialization. Trends in Biochemical Sciences [Internet]. 2019;44 (5) :478 - 479. Publisher's VersionAbstract
Contrary to the textbook model, recent measurements demonstrated unexpected diversity in ribosomal composition that likely enables specialized translational functions. Methods based on liquid chromatography coupled to tandem mass-spectrometry (LC-MS/MS) enable direct quantification of ribosomal proteins with high specificity, accuracy, and throughput. LC-MS/MS can be ‘top-down’, analyzing intact proteins, or more commonly ‘bottom-up’, where proteins are digested to peptides prior to analysis. Changes to rRNA can be examined using either LC-MS/MS or sequencing-based approaches. The regulation of protein synthesis by specialized ribosomes can be examined by multiple methods. These include the popular ‘Ribo-Seq’ method for analyzing ribosome density on a given mRNA, as well as LC-MS/MS approaches incorporating pulse-labelling with stable isotopes (SILAC) to monitor protein synthesis and degradation.
Emmott E, Jovanovic M, Slavov N. Ribosome stoichiometry: from form to function. Trends in Biochemical Sciences [Internet]. 2019;44 :95–109. Publisher's VersionAbstract
The existence of eukaryotic ribosomes with distinct ribosomal protein (RP) stoichiometry and regulatory roles in protein synthesis has been speculated for over 60 years. Recent advances in mass spectrometry (MS) and high-throughput analysis have begun to identify and characterize distinct ribosome stoichiometry in yeast and mammalian systems. In addition to RP stoichiometry, ribosomes host a vast array of protein modifications, effectively expanding the number of human RPs from 80 to many thousands of distinct proteoforms. Is it possible that these proteoforms combine to function as a ‘ribosome code’ to tune protein synthesis? We outline the specific benefits that translational regulation by specialized ribosomes can offer and discuss the means and methodologies available to correlate and characterize RP stoichiometry with function. We highlight previous research with a focus on formulating hypotheses that can guide future experiments and crack the ribosome code.
Malioutov D, Chen T, Airoldi E, Jaffe J, Budnik B, Slavov N. Quantifying Homologous Proteins and Proteoforms. Molecular & Cellular Proteomics [Internet]. 2019;18 (1) :162–168. Publisher's VersionAbstract
Many proteoforms—arising from alternative splicing, post-translational modifications (PTM), or paralogous genes—have distinct biological functions, such as histone PTM proteoforms. However, their quantification by existing bottom-up mass-spectrometry (MS) methods is undermined by peptide-specific biases. To avoid these biases, we developed and implemented a first-principles model (HIquant) for quantifying proteoform stoichiometries. We characterized when MS data allow inferring proteoform stoichiometries by HIquant and derived an algorithm for optimal inference. We applied this algorithm to infer proteoform stoichiometries in two experimental systems that supported rigorous bench-marking: alkylated proteoforms spiked-in at known ratios and endogenous histone 3 PTM proteoforms quantified relative to internal heavy standards. When compared with the benchmarks, the proteoform stoichiometries interfered by HIquant without using external standards had relative error of 5–15% for simple proteoforms and 20–30% for complex proteoforms. A HIquant server is implemented at: https://web.northeastern.edu/slavov/2014_HIquant/
Huffman G, Specht H, Chen AT, Slavov N. DO-MS: Data-Driven Optimization of Mass Spectrometry Methods. bioRxiv [Internet]. 2019. Publisher's VersionAbstract
The performance of ultrasensitive LC-MS/MS methods, such as Single-Cell Proteomics by Mass Spectrometry (SCoPE-MS), depends on multiple interdependent parameters. This interdependence makes it challenging to specifically pinpoint bottlenecks in the LC-MS/MS methods and approaches for resolving them. For example, low signal at MS2 level can be due to poor LC separation, ionization, apex targeting, ion transfer, or ion detection. We sought to specifically diagnose such bottlenecks by interactively visualizing data from all levels of bottom-up LC-MS/MS analysis. Many search engines, such as MaxQuant, already provide such data, and we developed an open source platform for their interactive visualization and analysis: Data-driven Optimization of MS (DO-MS). We found that in many cases DO-MS not only specifically diagnosed bottlenecks but also enabled us to rationally optimize them. For example, we used DO-MS to diagnose poor sampling of the elution peak apex and to optimize it, which increased the efficiency of delivering ions for MS2 analysis by 370 %. DO-MS is easy to install and use, and its GUI allows for interactive data subsetting and high-quality figure generation. The modular design of DO-MS facilitates customization and expansion. DO-MS is available for download from GitHub: https://github.com/SlavovLab/DO-MS
2018
Budnik B, Levy E, Harmange G, Slavov N. SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation. Genome Biology [Internet]. 2018;19 (1) :161. Publisher's VersionAbstract
Some exciting biological questions require quantifying thousands of proteins in single cells. To achieve this goal, we develop Single Cell ProtEomics by Mass Spectrometry (SCoPE-MS) and validate its ability to identify distinct human cancer cell types based on their proteomes. We use SCoPE-MS to quantify over a thousand proteins in differentiating mouse embryonic stem cells. The single-cell proteomes enable us to deconstruct cell populations and infer protein abundance relationships. Comparison between single-cell proteomes and transcriptomes indicates coordinated mRNA and protein covariation, yet many genes exhibit functionally concerted and distinct regulatory patterns at the mRNA and the protein level.
Malioutov D, Chen T, Airoldi E, Jaffe JD, Budnik B, Slavov N. Quantifying homologous proteins and proteoforms. Molecular & Cellular Proteomics [Internet]. 2018. Publisher's VersionAbstract
Many proteoforms – arising from alternative splicing, post-translational modifications (PTM), or paralogous genes – have distinct biological functions, such as histone PTM proteoforms. However, their quantification by existing bottom-up mass–spectrometry (MS) methods is undermined by peptide-specific biases. To avoid these biases, we developed and implemented a first-principles model (HIquant ) for quantifying proteoform stoichiometries. We characterized when MS data allow inferring proteoform stoichiometries by HIquant and derived an algorithm for optimal inference. We applied this algorithm to infer proteoform stoichiometries in two experimental systems that supported rigorous bench-marking: alkylated proteoforms spiked-in at known ratios and endogenous histone 3 PTM proteoforms quantified relative to internal heavy standards. When compared to the benchmarks, the proteoform stoichiometries interfered by HIquant without using external standards had relative error of 5 - 15% for simple proteoforms and 20 - 30% for complex proteoforms. A HIquant server is implemented at: https://web.northeastern.edu/slavov/2014_HIquant/
Specht H, Harmange G, Perlman DH, Emmott E, Niziolek Z, Budnik B, Slavov N. Automated sample preparation for high-throughput single-cell proteomics. bioRxiv [Internet]. 2018. Publisher's VersionAbstract
A major limitation to applying quantitative LC-MS/MS proteomics to small samples, such as single cells, are the losses incured during sample cleanup. To relieve this limitation, we developed a Minimal ProteOmic sample Preparation (mPOP) method for culture-grown mammalian cells. mPOP obviates cleanup and thus eliminates cleanup-related losses while expediting sample preparation and simplifying its automation. Bulk SILAC samples processed by mPOP or by conventional urea-based methods indicated that mPOP results in complete cell lysis and accurate relative quantification. We integrated mPOP lysis with the Single Cell ProtEomics by Mass Spectrometry (SCoPE-MS) sample preparation, and benchmarked the quantification of such samples on a Q-exactive instrument. The results demonstrate low noise and high technical reproducibility. Then, we FACS sorted single U-937, HEK-293, and mouse ES cells into 96-well plates and analyzed them by automated mPOP and SCoPE-MS. The quantified proteins enabled separating the single cells by cell-type and cell-division-cycle phase.
Chen A, Franks A, Slavov N. DART-ID increases single-cell proteome coverage. bioRxiv [Internet]. 2018. Publisher's VersionAbstract
Analysis by liquid chromatography and tandem mass spectrometry (LC-MS/MS) can identify and quantify thousands of proteins in microgram-level samples, such as those comprised of thousands of cells. Identifying proteins by LC-MS/MS proteomics, however, remains challenging for lowly abundant samples, such as the proteomes of single mammalian cells. To increase the identification rate of peptides in such small samples, we developed DART-ID. This method implements a data-driven, global retention time (RT) alignment process to infer peptide RTs across experiments. DART-ID then incorporates the global RT-estimates within a principled Bayesian framework to increase the confidence in correct peptide-spectrum-matches. Applying DART-ID to hundreds of samples prepared by the Single Cell Proteomics by Mass Spectrometry (SCoPE-MS) design increased the peptide and proteome coverage by 30 - 50% at 1% FDR. The newly identified peptides and proteins were further validated by demonstrating that their quantification is consistent with the quantification of peptides identified from high-quality spectra. DART-ID can be applied to various sets of experimental designs with similar sample complexities and chromatography conditions, and is freely available online.
Levy E, Slavov N. Single cell protein analysis for systems biology. Essays In Biochemistry [Internet]. 2018;62. Publisher's VersionAbstract
The cellular abundance of proteins can vary even between isogenic single cells. This variability between single-cell protein levels can have regulatory roles, such as controlling cell fate during apoptosis induction or the proliferation/quiescence decision. Here, we review examples connecting protein levels and their dynamics in single cells to cellular functions. Such findings were made possible by the introduction of antibodies, and subsequently fluorescent proteins, for tracking protein levels in single cells. However, in heterogeneous cell populations, such as tumors or differentiating stem cells, cellular decisions are controlled by hundreds, even thousands of proteins acting in concert. Characterizing such complex systems demands measurements of thousands of proteins across thousands of single cells. This demand has inspired the development of new methods for single-cell protein analysis, and we discuss their trade-offs, with an emphasis on their specificity and coverage. We finish by highlighting the potential of emerging mass-spec methods to enable systems-level measurement of single-cell proteomes with unprecedented coverage and specificity. Combining such methods with methods for quantitating the transcriptomes and metabolomes of single cells will provide essential data for advancing quantitative systems biology.
Specht H, Slavov N. Transformative opportunities for single-cell proteomics. Journal of Proteome Research [Internet]. 2018;17 :2563 - 2916. Publisher's VersionAbstract
Many pressing medical challenges, such as diagnosing disease, enhancing directed stem-cell differentiation, and classifying cancers, have long been hindered by limitations in our ability to quantify proteins in single cells. Mass spectrometry (MS) is poised to transcend these limitations by developing powerful methods to routinely quantify thousands of proteins and proteoforms across many thousands of single cells. We outline specific technological developments and ideas that can increase the sensitivity and throughput of single-cell MS by orders of magnitude and usher in this new age. These advances will transform medicine and ultimately contribute to understanding biological systems on an entirely new level.
2018_specht_slavov_single-cell-proteomics.pdf
Levy E, Slavov N. Single cell protein analysis for systems biology. PeerJ Preprints [Internet]. 2018;6 :e26965v1. Publisher's VersionAbstract
The cellular abundance of proteins can vary even between isogenic single cells. This variability between single-cell protein levels can have functional roles, such as controlling cell fate during apoptosis induction or the proliferation/quiescence decision. Here, we review such examples of connecting protein levels and their dynamics in single cells to cellular functions. Such findings were made possible by the introduction of antibodies, and subsequently fluorescent proteins, for tracking protein levels in single cells. However, in heterogeneous cell populations, such as tumors or differentiating stem cells, cellular decisions are controlled by hundreds, even thousands of proteins acting in concert. Characterizing such complex systems demands measurements of thousands of proteins across thousands of single cells. This demand has inspired the development of new methods for single cell protein analysis, and we discuss their trade-offs, with emphasis on their specificity and coverage. We finish by highlighting the potential of emerging mass-spec methods to enable systems-level measurement of single-cell proteomes with unprecedented coverage and specificity. Combining such methods with methods for quantifying the trasncriptomes and metabolomes of single cells will provide essential data for advancing quantitative systems biology.
Emmott EP, Jovanovic M, Slavov N. Ribosome stoichiometry: from form to function. PeerJ Preprints [Internet]. 2018;6 :e26991v1. Publisher's VersionAbstract
The existence of eukaryotic ribosomes with distinct ribosomal protein (RP) stoichiometry and regulatory roles in protein synthesis been speculated for over sixty years. Recent advances in mass spectrometry and high throughput analysis have begun to identify and characterize distinct ribosome stoichiometry in yeast or mammalian systems. In addition to RP stoichiometry, ribosomes play host to a vast array of protein modifications, effectively expanding the number of human RPs from 80 to many thousands of distinct proteoforms. Is it possible these proteoforms combine to function as a ‘ribosome code’ to tune protein synthesis? We outline the specific benefits that translational regulation by specialized ribosomes can offer and discuss the means and methodologies available to correlate and characterize RP stoichiometry with function. We highlight previous research with a focus on formulating hypotheses that can guide future experiments and crack the ‘ribosome code’.
Budnik B, Levy E, Harmange G, Slavov N. Mass-spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation. bioRxiv [Internet]. 2018. Publisher's VersionAbstract
Cellular heterogeneity is important to biological processes, including cancer and development. However, proteome heterogeneity is largely unexplored because of the limitations of existing methods for quantifying protein levels in single cells. To alleviate these limitations, we developed Single Cell ProtEomics by Mass Spectrometry (SCoPE-MS), and validated its ability to identify distinct human cancer cell types based on their proteomes. We used SCoPE-MS to quantify over a thousand proteins in differentiating mouse embryonic stem (ES) cells. The single-cell proteomes enabled us to deconstruct cell populations and infer protein abundance relationships. Comparison between single-cell proteomes and transcriptomes indicated coordinated mRNA and protein covariation. Yet many genes exhibited functionally concerted and distinct regulatory patterns at the mRNA and the protein levels, suggesting that post-transcriptional regulatory mechanisms contribute to proteome remodeling during lineage specification, especially for developmental genes. SCoPE-MS is broadly applicable to measuring proteome configurations of single cells and linking them to functional phenotypes, such as cell type and differentiation potentials.
Specht H, Slavov N. Routinely quantifying single cell proteomes: A new age in quantitative biology and medicine. PeerJ Preprints [Internet]. 2018;6 :e26821v1. Publisher's VersionAbstract
Many pressing medical challenges – such as diagnosing disease, enhancing directed stem cell differentiation, and classifying cancers – have long been hindered by limitations in our ability to quantify proteins in single cells. Mass-spectrometry (MS) is poised to transcend these limitations by developing powerful methods to routinely quantify thousands of proteins and proteoforms across many thousands of single cells. We outline specific technological developments and ideas that can increase the sensitivity and throughput of single cell MS by orders of magnitude and usher in this new age. These advances will transform medicine and ultimately contribute to understanding biological systems on an entirely new level.
2017
van den Berg PR, Budnik B, Slavov N, Semrau S. Dynamic post-transcriptional regulation during embryonic stem cell differentiation. bioRxiv [Internet]. 2017. Publisher's VersionAbstract
During in vitro differentiation, pluripotent stem cells undergo extensive remodeling of their gene expression profile. While studied extensively at the transcriptome level, much less is known about protein dynamics. Here, we measured mRNA and protein levels of 7459 genes during differentiation of embryonic stem cells (ESCs). This comprehensive data set revealed pervasive discordance between mRNA and protein. The high temporal resolution of the data made it possible to determine protein turnover rates genome-wide by fitting a kinetic model. This model further enabled us to systematically identify dynamic post-transcriptional regulation. Moreover, we linked different modes of regulation to the function of specific gene sets. Finally, we showed that the kinetic model can be applied to single-cell transcriptomics data to predict protein levels in differentiated cell types. In conclusion, our comprehensive data set, easily accessible through a web application, is a valuable resource for the discovery of post-transcriptional regulation in ESC differentiation.
Saleh D, Najjar M, Zelic M, Shah S, Nogusa S, Polykratis A, Paczosa MK, Gough PJ, Bertin J, Whalen M, et al. Kinase Activities of RIPK1 and RIPK3 Can Direct IFN-beta Synthesis Induced by Lipopolysaccharide. The Journal of Immunology. 2017;198 (11) :4435–4447.
Malioutov D, Chen T, Jaffe J, Airoldi E, Carr S, Budnik B, Slavov N. Quantifying homologous proteins and proteoforms. bioRxiv [Internet]. 2017. Publisher's VersionAbstract
Many proteoforms - arising from alternative splicing, post-translational modifications (PTMs), or paralogous genes - have distinct biological functions, such as histone PTM proteoforms. However, their quantification by existing bottom-up mass-spectrometry (MS) methods is undermined by peptide-specific biases. To avoid these biases, we developed and implemented a first-principles model (HIquant) for quantifying proteoform stoichiometries. We characterized when MS data allow inferring proteoform stoichiometries by HIquant, derived an algorithm for optimal inference, and demonstrated experimentally high accuracy in quantifying fractional PTM occupancy without using external standards, even in the challenging case of the histone modification code. HIquant server is implemented at: https://web.northeastern.edu/slavov/2014_HIquant/
Franks A, Airoldi E, Slavov N. Post-transcriptional regulation across human tissues. PLOS Computational Biology [Internet]. 2017;13 (5) :1-20. Publisher's VersionAbstract
Author Summary The identity of human tissues depends on their protein levels. Are tissue protein levels set largely by corresponding mRNA levels or by other (post-transcriptional) regulatory mechanisms? We revisit this question based on statistical analysis of mRNA and protein levels measured across human tissues. We find that for any one gene, its protein levels across tissues are poorly predicted by its mRNA levels, suggesting tissue-specific post-transcriptional regulation. In contrast, the overall protein levels are well predicted by scaled mRNA levels. We show how these speciously contradictory findings are consistent with each other and represent the two sides of Simpson’s paradox.
Budnik B, Levy E, Harmange G, Slavov N. Mass-spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation. bioRxiv [Internet]. 2017. Publisher's VersionAbstract
Cellular heterogeneity is important to biological processes, including cancer and development. However, proteome heterogeneity is largely unexplored because of the limitations of existing methods for quantifying protein levels in single cells. To alleviate these limitations, we developed Single Cell ProtEomics by Mass Spectrometry (SCoPE-MS), and validated its ability to identify distinct human cancer cell types based on their proteomes. We used SCoPE-MS to quantify over a thousand proteins in differentiating mouse embryonic stem (ES) cells. The single-cell proteomes enabled us to deconstruct cell populations and infer protein abundance relationships. Comparison between single-cell proteomes and transcriptomes indicated coordinated mRNA and protein covariation. Yet many genes exhibited functionally concerted and distinct regulatory patterns at the mRNA and the protein levels, suggesting that post-transcriptional regulatory mechanisms contribute to proteome remodeling during lineage specification, especially for developmental genes. SCoPE-MS is broadly applicable to measuring proteome configurations of single cells and linking them to functional phenotypes, such as cell type and differentiation potentials.
2015
Slavov N. Point of View: Making the most of peer review. eLife [Internet]. 2015;4 :e12708. Publisher's VersionAbstract
Journals should publish referee reports and respond to well-founded concerns about papers after publication.

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