Elucidating the Importance and Regulation of Key Enhancers for Human MEIS1 Expression

Myeloid ecotropic virus insertion site 1 (MEIS1) is essential for normal hematopoiesis and is deregulated in a large subset of acute myeloid leukemia (AML) by yet unknown mechanisms. We previously identified 3 candidate enhancer regions: enhancer region 1 (E1) at -2 kb upstream; enhancer region 2 (E2) at +10.6 kb downstream inside intron 6; and enhancer region 3 (E3) +140 kb downstream of the translation start site. In the current study, we utilized CRISPR-Cas9 genome editing to further characterize these enhancers in a human AML cell line and identify the key transcription factors (TFs) associated with their function. To efficiently track MEIS1 expression levels, a GFP reporter, a P2A self-cleaving peptide tag and a hemagglutinin tag at its translation start site was introduced in a MEIS1 high expressing human AML cell line, U937. Then we introduced random mutations (Indels) along the MEIS1 locus utilizing a CRISPR-Cas9 mediated genome editing vector system in mono-allelic MEIS1-GFP-tagged U937 cells with special focus on the previously identified enhancer regions to find the key sequences important to the function of the MEIS1 enhancer regions. Two targeted regions yielding the highest proportion of GFP - cells corresponded to the E2 enhancer region within intron 6 and were referred to as E2.1 and E2.2. Using chromosome conformation capture (3C) assay, we detected a significantly decreased interaction (p=0.0022) between the promoter and the intron 6 region surrounding the E2 region in E2.2 targeted cells compared to the parental cells. Moreover, our data indicated that the DNA sequence within E2.2 is highly critical to this region's enhancer function which is further influenced by the larger genomic region surrounding the E2.1 gRNA targeted site. To identify TFs binding to the E2 region, we further scrutinized the E2.2 indel region for loss of TF binding sites. We performed TF prediction analysis and performed a protein pull down-mass spectrometry experiment to identify TF candidates. The overlap yielded a list of 7 TFs, each of which we targeted via CRISPR/Cas9. Reduction in GFP levels was only observed for FLI1 locus targeting but not for the other 6 TFs. Concordant reduction in MEIS1 and FLI1 levels were confirmed by immunoblotting. Additionally, chromatin immunoprecipitation (ChIP) followed by quantitative PCR revealed significant FLI1 enrichment at the promoter and at 3 sites surrounding the E2.2 region (p=0.0004) compared to 4 control regions scattered along the MEIS1 locus. Given a previous study indicating MEIS1 upregulation of FLI1 in normal hematopoiesis, we hypothesised that a positive feedback loop may exist between FLI1 and MEIS1 in AML. Since MEIS1 levels are frequently elevated in normal karyotype AML (CN-AML), we used the murine Hoxa9/Meis1 AML model as a surrogate for CN-AML and performed Meis1 ChIP-seq analysis. We detected direct Meis1 binding to the intronic region of the mouse Fli1 gene as well as other ETS factor loci, in Hoxa9/Meis1 cells. To better understand the clinical relevance of FLI1 in AML, we analyzed the Beat AML dataset. High FLI1 transcript levels correlated with adverse overall survival in CN-AML (p=0.044). Additionally, we observed a trend towards worse outcome with high FLI1 in the NPM1-mutated CN-AML subtype (p=0.069). We also observed a similar correlation in CN-AML for another ETS factor, ELF1, which we had previously shown to bind and upregulate MEIS1 expression in AML, suggesting a broader unrecognized role for ETS factors in AML. In summary, we have developed a rapid flow cytometry-based readout for the fine dissection and characterization of the cis-regulatory elements and associated TFs critical for MEIS1 transcription via CRISPR-Cas9 genetic manipulation. Our study revealed FLI1 as the candidate key regulator of MEIS1 expression and a positive correlation between FLI1 mRNA levels and worse overall survival in MEIS1-high AML subgroups. Disclosures No relevant conflicts of interest to declare.

Peak Filtering, Peak Annotation, and Wildcard Search for Glycoproteomics

Glycopeptides in peptide or digested protein samples pose a number of analytical and bioinformatics challenges beyond those posed by unmodified peptides or peptides with smaller posttranslational modifications. Exact structural elucidation of glycans is generally beyond the capability of a single mass spectrometry experiment, so a reasonable level of identification for tandem mass spectrometry, taken by several glycopeptide software tools, is that of peptide sequence and glycan composition, meaning the number of monosaccharides of each distinct mass, for example HexNAc(2)Hex(5) rather than man5. Even at this level, however, glycopeptide analysis poses challenges: finding glycopeptide spectra when they are a tiny fraction of the total spectra; assigning spectra with unanticipated glycans, not in the initial glycan database; and finding, scoring, and labeling diagnostic peaks in tandem mass spectra. Here we discuss recent improvements to Byonic, a glycoproteomics search program, that address these three issues. Byonic now supports filtering spectra by m/z peaks, so that the user can limit attention to spectra with diagnostic peaks, for example, at least two out of three of 204.087 for HexNAc, 274.092 for NeuAc (with water loss), and 366.139 for HexNAc-Hex, all within a set mass tolerance, for example, ± 0.01 Daltons. Also new is glycan “wildcard” search, which allows an unspecified mass within a user-set mass range to be applied to N- or O-linked glycans and enables assignment of spectra with unanticipated glycans. Finally the next release of Byonic supports user-specified peak annotations from user-defined posttranslational modifications. We demonstrate the utility of these new software features by finding previously unrecognized glycopeptides in publicly available data, including glycosylated neuropeptides from rat brain.

Combining Information from Crosslinks and Monolinks in the Modelling of Protein Structures

SUMMARYMonolinks are produced in a Chemical Crosslinking Mass Spectrometry experiment and are more abundant than crosslinks. They convey residue exposure information, but so far have not been used in the modelling of protein structures. Here we present the Monolink Depth Score (MoDS), for assessing structural models based on the depth of monolinked residues, corresponding to their distance to the nearest bulk water. Using simulated and reprocessed experimental data from the Proteomic Identification Database, we compare the performance of MoDS to MNXL - our previously-developed score for assessing models based on crosslinking data. Our results show that MoDS can be used to effectively score model structures based on monolinks, and that combining it with MNXL leads to overall higher scoring performance. The work strongly supports the use of monolink data in the context of integrative structure determination. We also present XLM-Tools, a programme to assist in this effort, available at: https://github.com/Topf-Lab/XLM-Tools.

HpaP Sequesters HrpJ, an Essential Component of Ralstonia solanacearum Virulence That Triggers Necrosis in Arabidopsis

The Gram-negative bacterium Ralstonia solanacearum, the causal agent of bacterial wilt, is a worldwide major crop pathogen whose virulence strongly relies on a type III secretion system (T3SS). This extracellular apparatus allows the translocation of proteins, called type III effectors (T3Es), directly into the host cells. To date, very few data are available in plant-pathogenic bacteria concerning the role played by type III secretion (T3S) regulators at the posttranslational level. We have demonstrated that HpaP, a putative T3S substrate specificity switch protein of R. solanacearum, controls T3E secretion. To better understand the role of HpaP on T3S control, we analyzed the secretomes of the GMI1000 wild-type strain as well as the hpaP mutant using a mass spectrometry experiment (liquid chromatography tandem mass spectrometry). The secretomes of both strains appeared to be very similar and highlighted the modulation of the secretion of few type III substrates. Interestingly, only one type III-associated protein, HrpJ, was identified as specifically secreted by the hpaP mutant. HrpJ appeared to be an essential component of the T3SS, essential for T3S and pathogenicity. We further showed that HrpJ is specifically translocated in planta by the hpaP mutant and that HrpJ can physically interact with HpaP. Moreover, confocal microscopy experiments demonstrated a cytoplasmic localization for HrpJ once in planta. When injected into Arabidopsis thaliana leaves, HrpJ is able to trigger a necrosis on 16 natural accessions. A genome-wide association mapping revealed a major association peak with 12 highly significant single-nucleotide polymorphisms located on a plant acyl-transferase.

Rapid Peptides Generator: fast and efficient in silico protein digestion

Recent developments in mass spectrometry techniques used in proteomics and proteogenomics have led to a constantly increasing interest in proteases. These proteases are used in different mass spectrometry analyses requiring protein digestions. To perform such digestions, one or multiple proteases are used. Few software exist that predict cleavage sites of proteases and simulate in silico digestions. In this work, Rapid Peptides Generator (RPG), a new software developed in order to predict proteases-induced cleavage sites on sequences, is presented. RPG offers extra features and overcomes most issues of existing software in different ways. First, for each generated peptide, RPG gives its sequence, length and estimation of mass, measurements already provided by other software, as well as the peptide’s isoelectric point. Moreover, contrary to existing software that limit the option of proteases to be used to a predefined list, users of RPG are able to easily define new proteases using a simple yet powerful grammar. This feature allows users to stay up-to-date to new or more specific proteases available on the market and optimizes time and effort before the actual mass spectrometry experiment. RPG is freely available through the well established package management system ‘pip’ and follows the standards for software development.

Chemical proteomics reveals target selectivity of clinical Jak inhibitors in human primary cells

Kinobeads are a set of promiscuous kinase inhibitors immobilized on sepharose beads for the comprehensive enrichment of endogenously expressed protein kinases from cell lines and tissues. These beads enable chemoproteomics profiling of kinase inhibitors of interest in dose-dependent competition studies in combination with quantitative mass spectrometry. We present improved bead matrices that capture more than 350 protein kinases and 15 lipid kinases from human cell lysates, respectively. A multiplexing strategy is suggested that enables determination of apparent dissociation constants in a single mass spectrometry experiment. Miniaturization of the procedure enabled determining the target selectivity of the clinical BCR-ABL inhibitor dasatinib in peripheral blood mononuclear cell (PBMC) lysates from individual donors. Profiling of a set of Jak kinase inhibitors revealed kinase off-targets from nearly all kinase families underpinning the need to profile kinase inhibitors against the kinome. Potently bound off-targets of clinical inhibitors suggest polypharmacology, e.g. through MRCK alpha and beta, which bind to decernotinib with nanomolar affinity.

Integrative proteomic and phosphoproteomic profiling of prostate cell lines

ABSTRACTBackgroundProstate cancer is a major public health issue, mainly because patients relapse after androgen deprivation therapy. Proteomic strategies, aiming to reflect the functional activity of cells, are nowadays among the leading approaches to tackle the challenges not only of better diagnosis, but also of unraveling mechanistic details related to disease etiology and progression.MethodsWe conducted here a large SILAC-based Mass Spectrometry experiment to map the proteomes and phosphoproteomes of four widely used prostate cell lines, namely PNT1A, LNCaP, DU145 and PC3, representative of different cancerous and hormonal status.ResultsWe identified more than 3000 proteins and phosphosites, from which we quantified more than 1000 proteins and 500 phosphosites after stringent filtering. Extensive exploration of this proteomics and phosphoproteomics dataset allowed characterizing housekeeping as well as cell-line specific proteins, phosphosites and functional features of each cell line. In addition, by comparing the sensitive and resistant cell lines, we identified protein and phosphosites differentially expressed in the resistance context. Further data integration in a molecular network highlighted the differentially expressed pathways, in particular migration and invasion, RNA splicing, DNA damage repair response and transcription regulation.ConclusionsOverall, this study proposes a valuable resource toward the characterization of proteome and phosphoproteome of four widely used prostate cell lines and reveals candidates to be involved in prostate cancer progression for further experimental validation.

Detecting single amino acids and small peptides by combining isobaric tags and peptidomics

Single amino acids and small endogenous peptides play important roles in maintaining a properly functioning organism. These molecules are however currently only routinely identified in targeted approaches. In a small proof-of-concept mass spectrometry experiment, we found that by combining isobaric tags and peptidomics, and by targeting singly charged molecules, we were able to identify a significant amount of single amino acids and small endogenous peptides using a basic mass-based identification approach. While there is still room for improvement, our simple test indicates that a limited amount of extra work when setting up the mass spectrometry experiment could potentially lead to a wealth of additional information.