Human DDK rescues stalled forks and counteracts checkpoint inhibition at unfired origins to complete DNA replication.

Eukaryotic genomes replicate via spatially and temporally regulated origin firing. Cyclin-dependent kinase (CDK) and Dbf4-dependent kinase (DDK) promote origin firing, whereas the S phase checkpoint limits firing to prevent nucleotide and RPA exhaustion. We used chemical genetics to interrogate human DDK with maximum precision, dissect its relationship with the S phase checkpoint, and identify DDK substrates. We show that DDK inhibition (DDKi) leads to graded suppression of origin firing and fork arrest. S phase checkpoint inhibition rescued origin firing in DDKi cells and DDK-depleted Xenopus egg extracts. DDKi also impairs RPA loading, nascent-strand protection, and fork restart. Via quantitative phosphoproteomics, we identify the BRCA1-associated (BRCA1-A) complex subunit MERIT40 and the cohesin accessory subunit PDS5B as DDK effectors in fork protection and restart. Phosphorylation neutralizes autoinhibition mediated by intrinsically disordered regions in both substrates. Our results reveal mechanisms through which DDK controls the duplication of large vertebrate genomes.

Proteomic characterization of chromosomal common fragile site (CFS)-associated proteins uncovers ATRX as a regulator of CFS stability.

Common fragile sites (CFSs) are conserved genomic regions prone to break under conditions of replication stress (RS). Thus, CFSs are hotspots for rearrangements in cancer and contribute to its chromosomal instability. Here, we have performed a global analysis of proteins that recruit to CFSs upon mild RS to identify novel players in CFS stability. To this end, we performed Chromatin Immunoprecipitation (ChIP) of FANCD2, a protein that localizes specifically to CFSs in G2/M, coupled to mass spectrometry to acquire a CFS interactome. Our strategy was validated by the enrichment of many known regulators of CFS maintenance, including Fanconi Anemia, DNA repair and replication proteins. Among the proteins identified with unknown functions at CFSs was the chromatin remodeler ATRX. Here we demonstrate that ATRX forms foci at a fraction of CFSs upon RS, and that ATRX depletion increases the occurrence of chromosomal breaks, a phenotype further exacerbated under mild RS conditions. Accordingly, ATRX depletion increases the number of 53BP1 bodies and micronuclei, overall indicating that ATRX is required for CFS stability. Overall, our study provides the first proteomic characterization of CFSs as a valuable resource for the identification of novel regulators of CFS stability.

Quantitative phosphoproteomics to unravel the cellular response to chemical stressors with different modes of action.

Damage to cellular macromolecules and organelles by chemical exposure evokes activation of various stress response pathways. To what extent different chemical stressors activate common and stressor-specific pathways is largely unknown. Here, we used quantitative phosphoproteomics to compare the signaling events induced by four stressors with different modes of action: the DNA damaging agent: cisplatin (CDDP), the topoisomerase II inhibitor: etoposide (ETO), the pro-oxidant: diethyl maleate (DEM) and the immunosuppressant: cyclosporine A (CsA) administered at an equitoxic dose to mouse embryonic stem cells. We observed major differences between the stressors in the number and identity of responsive phosphosites and the amplitude of phosphorylation. Kinase motif and pathway analyses indicated that the DNA damage response (DDR) activation by CDDP occurs predominantly through the replication-stress-related Atr kinase, whereas ETO triggers the DDR through Atr as well as the DNA double-strand-break-associated Atm kinase. CsA shares with ETO activation of CK2 kinase. Congruent with their known modes of action, CsA-mediated signaling is related to down-regulation of pathways that control hematopoietic differentiation and immunity, whereas oxidative stress is the most prominent initiator of DEM-modulated stress signaling. This study shows that even at equitoxic doses, different stressors induce distinctive and complex phosphorylation signaling cascades.

A simple DNA recombination screening method by RT-PCR as an alternative to Southern blot.

The generation of genetically engineered mouse models (GEMMs), including knock-out (KO) and knock-in (KI) models, often requires genomic screening of many mouse ES cell (mESC) clones by Southern blot. The use of large targeting constructs facilitates the recombination of exogenous DNA in a specific genomic locus, but limits the detection of its correct genomic integration by standard PCR methods. Genomic Long Range PCR (LR-PCR), using primers adjacent to the homology arms, has been used as an alternative to radioactive-based Southern blot screenings. However, LR-PCRs are often difficult and render many false positive and false negative results. Here, we propose an alternative screening method based on the detection of a genetic modification at the mRNA level, which we successfully optimized in two mouse models. This screening method consists of a reverse-transcription PCR (RT-PCR) using primers that match exons flanking the targeting construct. The detection of the expected modification in this PCR product confirms the integration at the correct genomic location and shows that the mutant mRNA is expressed. This is a simple and sensitive strategy to screen locus-specific recombination of targeting constructs which can also be useful to screen KO and KI mutant mice or cell lines including those generated by CRISPR/Cas9.

TIMP-1 increases expression and phosphorylation of proteins associated with drug resistance in breast cancer cells.

Tissue inhibitor of metalloproteinase 1 (TIMP-1) is a protein with a potential biological role in drug resistance. To elucidate the unknown molecular mechanisms underlying the association between high TIMP-1 levels and increased chemotherapy resistance, we employed SILAC-based quantitative mass spectrometry to analyze global proteome and phosphoproteome differences of MCF-7 breast cancer cells expressing high or low levels of TIMP-1. In TIMP-1 high expressing cells, 312 proteins and 452 phosphorylation sites were up-regulated. Among these were the cancer drug targets topoisomerase 1, 2A, and 2B, which may explain the resistance phenotype to topoisomerase inhibitors that was observed in cells with high TIMP-1 levels. Pathway analysis showed an enrichment of proteins from functional categories such as apoptosis, cell cycle, DNA repair, transcription factors, drug targets and proteins associated with drug resistance or sensitivity, and drug transportation. The NetworKIN algorithm predicted the protein kinases CK2a, CDK1, PLK1, and ATM as likely candidates involved in the hyperphosphorylation of the topoisomerases. Up-regulation of protein and/or phosphorylation levels of topoisomerases in TIMP-1 high expressing cells may be part of the mechanisms by which TIMP-1 confers resistance to treatment with the widely used topoisomerase inhibitors in breast and colorectal cancer.

The dual methyltransferase METTL13 targets N terminus and Lys55 of eEF1A and modulates codon-specific translation rates.

Eukaryotic elongation factor 1 alpha (eEF1A) delivers aminoacyl-tRNA to the ribosome and thereby plays a key role in protein synthesis. Human eEF1A is subject to extensive post-translational methylation, but several of the responsible enzymes remain unknown. Using a wide range of experimental approaches, we here show that human methyltransferase (MTase)-like protein 13 (METTL13) contains two distinct MTase domains targeting the N terminus and Lys55 of eEF1A, respectively. Our biochemical and structural analyses provide detailed mechanistic insights into recognition of the eEF1A N terminus by METTL13. Moreover, through ribosome profiling, we demonstrate that loss of METTL13 function alters translation dynamics and results in changed translation rates of specific codons. In summary, we here unravel the function of a human MTase, showing that it methylates eEF1A and modulates mRNA translation in a codon-specific manner.

Proteomics Reveals Global Regulation of Protein SUMOylation by ATM and ATR Kinases during Replication Stress.

The mechanisms that protect eukaryotic DNA during the cumbersome task of replication depend on the precise coordination of several post-translational modification (PTM)-based signaling networks. Phosphorylation is a well-known regulator of the replication stress response, and recently an essential role for SUMOs (small ubiquitin-like modifiers) has also been established. Here, we investigate the global interplay between phosphorylation and SUMOylation in response to replication stress. Using SUMO and phosphoproteomic technologies, we identify thousands of regulated modification sites. We find co-regulation of central DNA damage and replication stress responders, of which the ATR-activating factor TOPBP1 is the most highly regulated. Using pharmacological inhibition of the DNA damage response kinases ATR and ATM, we find that these factors regulate global protein SUMOylation in the protein networks that protect DNA upon replication stress and fork breakage, pointing to integration between phosphorylation and SUMOylation in the cellular systems that protect DNA integrity.

Search Databases and Statistics: Pitfalls and Best Practices in Phosphoproteomics.

Advances in mass spectrometric instrumentation in the past 15 years have resulted in an explosion in the raw data yield from typical phosphoproteomics workflows. This poses the challenge of confidently identifying peptide sequences, localizing phosphosites to proteins and quantifying these from the vast amounts of raw data. This task is tackled by computational tools implementing algorithms that match the experimental data to databases, providing the user with lists for downstream analysis. Several platforms for such automated interpretation of mass spectrometric data have been developed, each having strengths and weaknesses that must be considered for the individual needs. These are reviewed in this chapter. Equally critical for generating highly confident output datasets is the application of sound statistical criteria to limit the inclusion of incorrect peptide identifications from database searches. Additionally, careful filtering and use of appropriate statistical tests on the output datasets affects the quality of all downstream analyses and interpretation of the data. Our considerations and general practices on these aspects of phosphoproteomics data processing are presented here.

Systems Analysis for Interpretation of Phosphoproteomics Data.

Global phosphoproteomics investigations yield overwhelming datasets with up to tens of thousands of quantified phosphosites. The main challenge after acquiring such large-scale data is to extract the biological meaning and relate this to the experimental question at hand. Systems level analysis provides the best means for extracting functional insights from such types of datasets, and this has primed a rapid development of bioinformatics tools and resources over the last decade. Many of these tools are specialized databases that can be mined for annotation and pathway enrichment, whereas others provide a platform to generate functional protein networks and explore the relations between proteins of interest. The use of these tools requires careful consideration with regard to the input data, and the interpretation demands a critical approach. This chapter provides a summary of the most appropriate tools for systems analysis of phosphoproteomics datasets, and the considerations that are critical for acquiring meaningful output.

From Phosphosites to Kinases.

Kinases play a pivotal role in propagating the phosphorylation-mediated signaling networks in living cells. With the overwhelming quantities of phosphoproteomics data being generated, the number of identified phosphorylation sites (phosphosites) is ever increasing. Often, proteomics investigations aim to understand the global signaling modulation that takes place in different biological conditions investigated. For phosphoproteomics data, identifying the kinases central to mediating this response is key. This has prompted several efforts to catalogue the immense amounts of phosphorylation data and known or predicted kinases responsible for the modifications. However, barely 20 % of the known phosphosites are assigned to a kinase, initiating various bioinformatics efforts that attempt to predict the responsible kinases. These algorithms employ different approaches to predict kinase consensus sequence motifs, mostly based on large scale in vivo and in vitro experiments. The context of the kinase and the phosphorylated proteins in a biological system is equally important for predicting association between the enzymes and substrates, an aspect that is also being tackled with available bioinformatics tools. This chapter summarizes the use of the larger phosphorylation databases, and approaches that can be applied to predict kinases that phosphorylate individual sites or that are globally modulated in phosphoproteomics datasets.