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Steen, H.

Publications and source records attributed to Steen, H..

3 recordsLinked to original sources
bioRxiv2018

Degradation of the extracellular matrix is part of the pathology of ulcerative colitis

The scientific value of re-analyzing existing datasets is often proportional to the complexity of the data. Proteomics data are inherently complex and can be analyzed at many levels, including proteins, peptides, and post-translational modifications to verify and/or develop new hypotheses. In this paper, we present our re-analysis of a previously published study comparing colon biopsy samples from ulcerative colitis (UC) patients to non-affected controls. In addition to confirming and reinforcing the original finding of upregulation of neutrophil extracellular traps (NETs), we report novel findings, including that Extracellular Matrix (ECM) degradation and neutrophil maturation are involved in the pathology of UC. The pharmaceutically most relevant differential protein expressions were confirmed using immunohistochemistry as an orthogonal method. As part of this study, we also compared proteomics data to previously published mRNA expression data. These comparisons indicated compensatory regulation at transcription levels of the ECM proteins we identified and open possible new venues for drug discovery.

molecular biology↗
bioRxiv2017

PIQED: Automated Identification And Quantification Of Protein Modifications From DIA-MS Data

Label-free quantification using data-independent acquisition (DIA) is a robust method for deep and accurate proteome quantification1,2. However, when lacking a pre-existing spectral library, as is often the case with studies of novel post-translational modifications (PTMs), samples are typically analyzed several times: one or more data dependent acquisitions (DDA) are used to generate a spectral library followed by DIA for quantification. This type of multi-injection analysis results in significant cost with regard to sample consumption and instrument time for each new PTM study, and may not be possible when sample amount is limiting and/or studies require a large number of biological replicates. Recently developed software (e.g. DIA-Umpire) has enabled combined peptide identification and quantification from a data-independent acquisition without any pre-existing spectral library3,4. Still, these tools are designed for protein level quantification. Here we demonstrate a software tool and workflow that extends DIA-Umpire to allow automated identification and quantification of PTM peptides from DIA. We accomplish this using a custom, open-source graphical user interface DIA-Pipe (https://github.com/jgmeyerucsd/PIQEDia/releases/tag/v0.1.2) (figure 1a).\n\nO_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC=\"FIGDIR/small/141382_fig1.gif\" ALT=\"Figure 1\">\nView larger version (46K):\norg.highwire.dtl.DTLVardef@41b8f3org.highwire.dtl.DTLVardef@d59733org.highwire.dtl.DTLVardef@b9a722org.highwire.dtl.DTLVardef@8be50c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1:C_FLOATNO Automated Qualitative and Quantitative Analysis of Post-Translational Modifications using DIA-Pipe. (a) Workflow of the all-DIA strategy for identification and quantification of PTMs. Modified peptides enriched from biological samples are analyzed by data-independent acquisition. All data analysis steps starting from instrument. wiff files, acquired on a TripleTOF 5600, can be completed using the DIA-Pipe GUI, including: (1) file conversion and pseudo-MS/MS spectra generation using DIA-Umpire, (2) database searching by MS-GF+, X! Tandem, and Comet followed by results refinement and combination using PeptideProphet/iProphet/PTMProphet, (3) automated spectral library generation and fragment area extraction using SkylineRunner, and finally, (4) Skyline report filtering and formatting for significance testing with mapDIA. (b) mProphet composite score distributions of target and second-best peaks picked by Skylineshowing essentially error-free peak picking by Skyline of peptides identified using pseudo-MS/MS spectra. (c) Distribution of coefficient of variations observed from three technical replicates for 1,182 acetylation sites. (d) Observed distributions of log2(fold change) computed by mapDIA using three technical replicates of 1X injection volume compared to three technical replicates of 0.5X injection volume; expected log2(fold change) value =1. (e) Number of identified peptides from each single replicate injection and from the combination of two or three replicates. An average of 1,655 acetylated peptides were identified per replicate. The combination of two or three replicates increased the number of identifications by 19% or 29%, respectively.\n\nC_FIG

systems biology↗
bioRxiv2017

Human PGBD5 DNA transposase promotes site-specific oncogenic mutations in rhabdoid tumors

Genomic rearrangements are a hallmark of childhood solid tumors, but their mutational causes remain poorly understood. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as an enzymatically active human DNA transposase expressed in the majority of rhabdoid tumors, a lethal childhood cancer. Using assembly-based whole-genome DNA sequencing, we observed previously unknown somatic genomic rearrangements in primary human rhabdoid tumors. These rearrangements were characterized by deletions and inversions involving PGBD5-specific signal (PSS) sequences at their breakpoints, with some recurrently targeting tumor suppressor genes, leading to their inactivation. PGBD5 was found to be physically associated with human genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. We found that ectopic expression of PGBD5 in primary immortalized human cells was sufficient to promote penetrant cell transformation in vitro and in immunodeficient mice in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain, as well as end-joining DNA repair, and induced distinct structural rearrangements, involving PSS-associated breakpoints, similar to those found in primary human rhabdoid tumors. This defines PGBD5 as an oncogenic mutator and provides a plausible mechanism for site-specific DNA rearrangements in childhood and adult solid tumors.

cancer biology↗