Understanding PTM Cross Talk Through a Visualization Tool, PTMViz.

The advancement of sequencing technologies has expanded our understanding of biological complexity through mechanisms such as allelic variations, alternative splicing of RNA, degradation of RNA by microRNAs, and posttranslational modifications (PTMs). In this chapter, we describe a method, PTMViz, for analyzing proteoforms identified by mass spectrometry. This interactive platform provides differential abundance analysis and visualization of protein and posttranslational modifications. We describe the detailed steps to prepare mass spectrometry database search results into the necessary format for PTMViz, how to set up the experimental conditions for differential abundance analysis, and the visualization of the results. The application is freely available at https://github.com/ByrumLab/PTMViz .

Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer.

Triple negative breast cancer (TNBC) is an aggressive type of breast cancer with very little treatment options. TNBC is very heterogeneous with large alterations in the genomic, transcriptomic, and proteomic landscapes leading to various subtypes with differing responses to therapeutic treatments. We applied a multi-omics data integration method to evaluate the correlation of important regulatory features in TNBC BRCA1 wild-type MDA-MB-231 and TNBC BRCA1 5382insC mutated HCC1937 cells compared with non-tumorigenic epithelial breast MCF10A cells. The data includes DNA methylation, RNAseq, protein, phosphoproteomics, and histone post-translational modification. Data integration methods identified regulatory features from each omics method that had greater than 80% positive correlation within each TNBC subtype. Key regulatory features at each omics level were identified distinguishing the three cell lines and were involved in important cancer related pathways such as TGFß signaling, PI3K/AKT/mTOR, and Wnt/beta-catenin signaling. We observed overexpression of PTEN, which antagonizes the PI3K/AKT/mTOR pathway, and MYC, which downregulates the same pathway in the HCC1937 cells relative to the MDA-MB-231 cells. The PI3K/AKT/mTOR and Wnt/beta-catenin pathways are both downregulated in HCC1937 cells relative to MDA-MB-231 cells, which likely explains the divergent sensitivities of these cell lines to inhibitors of downstream signaling pathways. The DNA methylation and RNAseq data is freely available via GEO GSE171958 and the proteomics data is available via the ProteomeXchange PXD025238.

PTMViz: a tool for analyzing and visualizing histone post translational modification data.

BACKGROUND: Histone post-translational modifications (PTMs) play an important role in our system by regulating the structure of chromatin and therefore contribute to the regulation of gene and protein expression. Irregularities in histone PTMs can lead to a variety of different diseases including various forms of cancer. Histone modifications are analyzed using high resolution mass spectrometry, which generate large amounts of data that requires sophisticated bioinformatics tools for analysis and visualization. PTMViz is designed for downstream differential abundance analysis and visualization of both protein and/or histone modifications. RESULTS: PTMViz provides users with data tables and visualization plots of significantly differentiated proteins and histone PTMs between two sample groups. All the data is packaged into interactive data tables and graphs using the Shiny platform to help the user explore the results in a fast and efficient manner to assess if changes in the system are due to protein abundance changes or epigenetic changes. In the example data provided, we identified several proteins differentially regulated in the dopaminergic pathway between mice treated with methamphetamine compared to a saline control. We also identified histone post-translational modifications including histone H3K9me, H3K27me3, H4K16ac, and that were regulated due to drug exposure. CONCLUSIONS: Histone modifications play an integral role in the regulation of gene expression. PTMViz provides an interactive platform for analyzing proteins and histone post-translational modifications from mass spectrometry data in order to quickly identify differentially expressed proteins and PTMs.

Multi-omics data integration considerations and study design for biological systems and disease.

With the advancement of next-generation sequencing and mass spectrometry, there is a growing need for the ability to merge biological features in order to study a system as a whole. Features such as the transcriptome, methylome, proteome, histone post-translational modifications and the microbiome all influence the host response to various diseases and cancers. Each of these platforms have technological limitations due to sample preparation steps, amount of material needed for sequencing, and sequencing depth requirements. These features provide a snapshot of one level of regulation in a system. The obvious next step is to integrate this information and learn how genes, proteins, and/or epigenetic factors influence the phenotype of a disease in context of the system. In recent years, there has been a push for the development of data integration methods. Each method specifically integrates a subset of omics data using approaches such as conceptual integration, statistical integration, model-based integration, networks, and pathway data integration. In this review, we discuss considerations of the study design for each data feature, the limitations in gene and protein abundance and their rate of expression, the current data integration methods, and microbiome influences on gene and protein expression. The considerations discussed in this review should be regarded when developing new algorithms for integrating multi-omics data.

A facile forward-genetic screen for Arabidopsis autophagy mutants reveals twenty-one loss-of-function mutations disrupting six ATG genes.

Macroautophagy is a process through which eukaryotic cells degrade large substrates including organelles, protein aggregates, and invading pathogens. Over 40 autophagy-related (ATG) genes have been identified through forward-genetic screens in yeast. Although homology-based analyses have identified conserved ATG genes in plants, only a few atg mutants have emerged from forward-genetic screens in Arabidopsis thaliana. We developed a screen that consistently recovers Arabidopsis atg mutations by exploiting mutants with defective LON2/At5g47040, a protease implicated in peroxisomal quality control. Arabidopsis lon2 mutants exhibit reduced responsiveness to the peroxisomally-metabolized auxin precursor indole-3-butyric acid (IBA), heightened degradation of several peroxisomal matrix proteins, and impaired processing of proteins harboring N-terminal peroxisomal targeting signals; these defects are ameliorated by preventing autophagy. We optimized a lon2 suppressor screen to expedite recovery of additional atg mutants. After screening mutagenized lon2-2 seedlings for restored IBA responsiveness, we evaluated stabilization and processing of peroxisomal proteins, levels of several ATG proteins, and levels of the selective autophagy receptor NBR1/At4g24690, which accumulates when autophagy is impaired. We recovered 21 alleles disrupting 6 ATG genes: ATG2/At3g19190, ATG3/At5g61500, ATG5/At5g17290, ATG7/At5g45900, ATG16/At5g50230, and ATG18a/At3g62770. Twenty alleles were novel, and 3 of the mutated genes lack T-DNA insertional alleles in publicly available repositories. We also demonstrate that an insertional atg11/At4g30790 allele incompletely suppresses lon2 defects. Finally, we show that NBR1 is not necessary for autophagy of lon2 peroxisomes and that NBR1 overexpression is not sufficient to trigger autophagy of seedling peroxisomes, indicating that Arabidopsis can use an NBR1-independent mechanism to target peroxisomes for autophagic degradation. Abbreviations: ATG: autophagy-related; ATI: ATG8-interacting protein; Col-0: Columbia-0; DSK2: dominant suppressor of KAR2; EMS: ethyl methanesulfonate; GFP: green fluorescent protein; IAA: indole-3-acetic acid; IBA: indole-3-butyric acid; ICL: isocitrate lyase; MLS: malate synthase; NBR1: Next to BRCA1 gene 1; PEX: peroxin; PMDH: peroxisomal malate dehydrogenase; PTS: peroxisomal targeting signal; thiolase: 3-ketoacyl-CoA thiolase; UBA: ubiquitin-associated; WT: wild type.

Ursodeoxycholate inhibits mast cell activation and reverses biliary injury and fibrosis in Mdr2-/- mice and human primary sclerosing cholangitis.

Ursodeoxycholic acid (UDCA) is used to treat biliary disorders; and, bile acids alter mast cell (MC) histamine release. MCs infiltrate Mdr2-/- mice liver (model of primary sclerosing cholangitis (PSC)). MC-derived histamine increases inflammation, hepatic stellate cell (HSC) activation and fibrosis. The objective was to determine the effects of UDCA treatment on MC infiltration, biliary damage, inflammation and fibrosis in Mdr2-/- mice and human PSC. Wild-type and Mdr2-/- mice were fed bile acid control diet or UDCA (0.5% wt/wt). Human samples were collected from control and PSC patients treated with placebo or UDCA (15 mg/kg/BW). MC infiltration was measured by immunhistochemistry and quantitative polymerase chain reaction (qPCR) for c-Kit, chymase, and tryptase. The HDC/histamine/histamine receptor (HR)-axis was evaluated by EIA and qPCR. Intrahepatic bile duct mass (IBDM) and biliary proliferation was evaluated by CK-19 and Ki-67 staining. Fibrosis was detected by immunostaining and qPCR for fibrotic markers. Inflammatory components were measured by qPCR. HSC activation was measured by SYP-9 staining. Inflammation was detected by qPCR for CD68. In vitro, MCs were treated with UDCA (40 µM) prior to HA secretion evaluation and coculturing with cholangiocytes or HSCs. BrDU incorporation and fibrosis by qPCR was performed. UDCA reduced MC number, the HDC/histamine/HR-axis, IBDM, HSC activation, inflammation, and fibrosis in Mdr2-/- mice and PSC patients. In vitro, UDCA decreases MC-histamine release, which was restored by blocking ASBT and FXRß. Proliferation and fibrosis decreased after treatment with UDCA-treated MCs. We conclude that UDCA acts on MCs reducing histamine levels and decreases the inflammatory/hyperplastic/fibrotic reaction seen in PSC. Ursodeoxycholic acid (UDCA) is used to treat biliary disorders; and, bile acids alter mast cell (MC) histamine release. Following liver injury like primary sclerosing cholangitis in mice and humans, MCs infiltrate. MC-derived histamine increases biliary damage, fibrosis, and inflammation. UDCA treatment decreases these parameters via reduced MC activation.