Is there a transcription factor code? First steps towards assessing temporal changes in the landscape of post-transcriptional modifications during cellular differentiation

Abstract

Covalent post-translational modifications (PTMs) serve to expand the complexity of the proteome beyond the DNA encoded genetic information, providing an extra layer of control over cellular function. Thus, observing and decoding patterns of PTMs should reveal important regulatory pathways and networks in the cell.

The research in this proof of principle thesis designs and optimizes a protocol for observing the changing PTM landscape of key transcription factors (TF) throughout erythropoiesis – with a focus on lysine acetylation.

CRISPR gene editing of G1E-ER4 (inducible erythroid progenitor) cells was used to generate cell lines each with a unique FLAG tagged transcription factor (TF). These G1E-TF cell lines were evaluated by RT qPCR to determine globin gene expression (Hba-a1 and Hbb-b1) for the comparison of parental cell maturation with that of G1E-TF cell lines. TF protein expression was evaluated by Western blotting to determine whether the addition of the FLAG tag caused any expression change when compared with G1E-ER4 parental cells.

Protocols to purify TF proteins, prepare peptide samples and establish an LC-MS/MS data acquisition protocol for the detection of acetylated TF peptides were developed and modified. These included isobaric tags and boosting to amplify signal with isobaric labelling, to enhance signal intensity for LC-MS/MS, along with a workflow that incorporated data independent analysis and parallel reaction monitoring data acquisition modes of LC MS/MS for the detection and capture of MS1 and MS2 spectra.

These techniques when applied to (m)TAL1 proved successful. These data suggest that the protocols developed could be used as a basis for analysis of lysine acetylation landscape in erythroid TFs during their developmental trajectory and more generally for the temporally resolved analysis of PTM profiles in sets of endogenous proteins. Such data should provide a wealth of information regarding the PTM-induced control of cellular processes.