Biology subjects

Budnik, B.

Publications and source records attributed to Budnik, B..

6 recordsLinked to original sources

bioRxiv2018

Automated sample preparation for high-throughput single-cell proteomics

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.

systems biology↗

bioRxiv2018

Cohesin interacts with a panoply of splicing factors required for cell cycle progression and genomic organization

The cohesin complex regulates sister chromatid cohesion, chromosome organization, gene expression, and DNA repair. Here we report that endogenous human cohesin interacts with a panoply of splicing factors and RNA binding proteins, including diverse components of the U4/U6.U5 tri-snRNP complex and several splicing factors that are commonly mutated in cancer. The interactions are enhanced during mitosis, and the interacting splicing factors and RNA binding proteins follow the cohesin cycle and prophase pathway of regulated interactions with chromatin. Depletion of cohesin-interacting splicing factors results in stereotyped cell cycle arrests and alterations in genomic organization. These data support the hypothesis that splicing factors and RNA binding proteins control cell cycle progression and genomic organization via regulated interactions with cohesin and chromatin.\n\nOne Sentence SummaryEndogenous tagging reveals that cohesin interacts with diverse chromatin-bound splicing factors that regulate cell cycle progression and genomic organization in human cells.

cell biology↗

bioRxiv2018

Catalysis of cataract-associated human γD crystallin aggregation via dynamic disulfide exchange

Several mutations in human {gamma}D-crystallin (H{gamma}D), a long-lived eye lens protein, cause misfolding and aggregation, leading to cataract. Surprisingly, wild-type H{gamma}D catalyzes aggregation of its cataract related W42Q variant while itself remaining soluble - the inverse of the classical prion-like scenario whereby misfolded polypeptides catalyze aggregation of natively folded ones. The search for a biochemical mechanism of catalysis of W42Q aggregation by WT has revealed that WT H{gamma}D can transfer a disulfide bond to the W42Q variant. The transferred disulfide kinetically traps an aggregation-prone intermediate made accessible by the W42Q mutation, facilitating light-scattering aggregation of the W42Q variant. The aggregating variant thus becomes a disulfide sink, removing the disulfides from solution. Such redox \"hot potato\" competitions among wild-type and mutant or modified polypeptides may be relevant for many long-lived proteins that function in oxidizing environments. In these cases aggregation may be forestalled by inhibiting disulfide flow toward damaged polypeptides.

biochemistry↗

bioRxiv2017

Quantifying homologous proteins and proteoforms

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. A HIquant server is implemented at: https://web.northeastern.edu/slavov/2014_HIquant/

systems biology↗

bioRxiv2017

Pervasive Discordance Between mRNA And Protein Expression During Embryonic Stem Cell Differentiation

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 singlecell 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.

systems biology↗

bioRxiv2017

Mass-spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation

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.

systems biology↗