Nejvíce citovaný článek - PubMed ID 18606607
Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography-tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography-tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices. Here we provide a comprehensive guide for the statistical analysis of FBMN results, focusing on the downstream analysis of the FBMN output table. We explain the data structure and principles of data cleanup and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. All code is shared in the form of Jupyter Notebooks ( https://github.com/Functional-Metabolomics-Lab/FBMN-STATS ). Additionally, the protocol is accompanied by a web application with a graphical user interface ( https://fbmn-statsguide.gnps2.org/ ) to lower the barrier of entry for new users and for educational purposes. Finally, we also show users how to integrate their statistical results into the molecular network using the Cytoscape visualization tool. Throughout the protocol, we use a previously published environmental metabolomics dataset for demonstration purposes. Together, the protocol, code and web application provide a complete guide and toolbox for FBMN data integration, cleanup and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking and can be easily adapted to other mass spectrometry feature detection, annotation and networking tools.
Lipidomics and metabolomics communities comprise various informatics tools; however, software programs handling multimodal mass spectrometry (MS) data with structural annotations guided by the Lipidomics Standards Initiative are limited. Here, we provide MS-DIAL 5 for in-depth lipidome structural elucidation through electron-activated dissociation (EAD)-based tandem MS and determining their molecular localization through MS imaging (MSI) data using a species/tissue-specific lipidome database containing the predicted collision-cross section values. With the optimized EAD settings using 14 eV kinetic energy, the program correctly delineated lipid structures for 96.4% of authentic standards, among which 78.0% had the sn-, OH-, and/or C = C positions correctly assigned at concentrations exceeding 1 μM. We showcased our workflow by annotating the sn- and double-bond positions of eye-specific phosphatidylcholines containing very-long-chain polyunsaturated fatty acids (VLC-PUFAs), characterized as PC n-3-VLC-PUFA/FA. Using MSI data from the eye and n-3-VLC-PUFA-supplemented HeLa cells, we identified glycerol 3-phosphate acyltransferase as an enzyme candidate responsible for incorporating n-3 VLC-PUFAs into the sn1 position of phospholipids in mammalian cells, which was confirmed using EAD-MS/MS and recombinant proteins in a cell-free system. Therefore, the MS-DIAL 5 environment, combined with optimized MS data acquisition methods, facilitates a better understanding of lipid structures and their localization, offering insights into lipid biology.
- MeSH
- data mining * metody MeSH
- fosfatidylcholiny metabolismus chemie MeSH
- HeLa buňky MeSH
- hmotnostní spektrometrie metody MeSH
- lidé MeSH
- lipidomika * metody MeSH
- lipidy chemie analýza MeSH
- metabolomika metody MeSH
- nenasycené mastné kyseliny metabolismus chemie MeSH
- software MeSH
- tandemová hmotnostní spektrometrie metody MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- fosfatidylcholiny MeSH
- lipidy MeSH
- nenasycené mastné kyseliny MeSH
Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. We further verified the EAC-enriched expression of GPA33 in an external cohort of 115 patients and confirm this as an attractive diagnostic and therapeutic target. To further extend the insights gained from our proteomic data, an integrated analysis of protein and RNA expression in EAC and normal tissues revealed several genes with poorly correlated protein and RNA abundance, suggesting posttranscriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, only rarely demonstrated somatic mutation, suggesting post-transcriptional drivers for this EAC-specific phenotype. AGMAT was demonstrated to be overexpressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, posttranscriptional regulation of protein expression, which may be an exploitable vulnerability.
- Klíčová slova
- biomarker, esophageal adenocarcinoma, multiomics, proteogenomics, proteomics,
- MeSH
- adenokarcinom * genetika metabolismus patologie MeSH
- lidé MeSH
- multiomika MeSH
- nádorové biomarkery * metabolismus genetika MeSH
- nádory jícnu * genetika metabolismus patologie MeSH
- posttranskripční úpravy RNA MeSH
- proteom metabolismus MeSH
- proteomika * metody MeSH
- regulace genové exprese u nádorů * MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- nádorové biomarkery * MeSH
- proteom MeSH
We present Mass Spectrometry-Data Independent Analysis software version 4 (MS-DIAL 4), a comprehensive lipidome atlas with retention time, collision cross-section and tandem mass spectrometry information. We formulated mass spectral fragmentations of lipids across 117 lipid subclasses and included ion mobility tandem mass spectrometry. Using human, murine, algal and plant biological samples, we annotated and semiquantified 8,051 lipids using MS-DIAL 4 with a 1-2% estimated false discovery rate. MS-DIAL 4 helps standardize lipidomics data and discover lipid pathways.
- MeSH
- analýza dat * MeSH
- chromatografie kapalinová MeSH
- lipidomika metody MeSH
- lipidy chemie genetika MeSH
- tandemová hmotnostní spektrometrie MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- lipidy MeSH
Heterocytous cyanobacteria are among the most prolific sources of bioactive secondary metabolites, including anabaenopeptins (APTs). A terrestrial filamentous Brasilonema sp. CT11 collected in Costa Rica bamboo forest as a black mat, was studied using a multidisciplinary approach: genome mining and HPLC-HRMS/MS coupled with bioinformatic analyses. Herein, we report the nearly complete genome consisting of 8.79 Mbp with a GC content of 42.4%. Moreover, we report on three novel tryptophan-containing APTs; anabaenopeptin 788 (1), anabaenopeptin 802 (2), and anabaenopeptin 816 (3). Furthermore, the structure of two homologues, i.e., anabaenopeptin 802 (2a) and anabaenopeptin 802 (2b), was determined by spectroscopic analysis (NMR and MS). Both compounds were shown to exert weak to moderate antiproliferative activity against HeLa cell lines. This study also provides the unique and diverse potential of biosynthetic gene clusters and an assessment of the predicted chemical space yet to be discovered from this genus.
- Klíčová slova
- Brasilonema, anabaenopeptins, antiproliferative activity, hexapeptides, molecular networking, tryptophan-containing peptides,
- MeSH
- cyklické peptidy * chemie genetika izolace a purifikace farmakologie MeSH
- HeLa buňky MeSH
- hmotnostní spektrometrie MeSH
- lidé MeSH
- nukleární magnetická rezonance biomolekulární MeSH
- proliferace buněk účinky léků MeSH
- sinice * chemie genetika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- cyklické peptidy * MeSH
The rapid emergence of resistance in pathogenic bacteria together with a steep decline in economic incentives has rendered a new wave in the drug development by the pharmaceutical industry and researchers. Since cyanobacteria are recognized as wide producers of pharmaceutically important compounds, we investigated thirty-four cyanobacterial extracts prepared by solvents of different polarities for their antimicrobial potential. Almost all tested cyanobacterial strains exhibited some degree of antimicrobial bioactivity, with more general effect on fungal strains compared with bacteria. Surprisingly ~50% of cyanobacterial extracts exhibited specific activity against one or few bacterial indicator strains with Gram-positive bacteria being more affected. Extracts of two most promising strains were subjected to activity-guided fractionation and determination of the minimum inhibitory concentration (MIC) against selected bacterial and fungal isolates. Multiple fractions were responsible for their antimicrobial effect with MIC reaching low-micromolar concentrations and in some of them high level of specificity was recorded. Twenty-six bioactive fractions analyzed on LC-HRMS/MS and Global Natural Product Social Molecular Networking (GNPS) online workflow using dereplication resulted in identification of only forty-nine peptide spectrum matches (PSMs) with eleven unique metabolites spectrum matches (MSMs). Interestingly, only three fractions from Nostoc calcicola Lukešová 3/97 and four fractions from Desmonostoc sp. Cc2 showed the presence of unique MSMs suggesting the presence of unknown antimicrobial metabolites among majority of bioactive fractions from both the strains. Our results highlight potential for isolation and discovery of potential antimicrobial bioactive lead molecules from cyanobacterial extracts.
General transcription factor TFIID is a key component of RNA polymerase II transcription initiation. Human TFIID is a megadalton-sized complex comprising TATA-binding protein (TBP) and 13 TBP-associated factors (TAFs). TBP binds to core promoter DNA, recognizing the TATA-box. We identified a ternary complex formed by TBP and the histone fold (HF) domain-containing TFIID subunits TAF11 and TAF13. We demonstrate that TAF11/TAF13 competes for TBP binding with TATA-box DNA, and also with the N-terminal domain of TAF1 previously implicated in TATA-box mimicry. In an integrative approach combining crystal coordinates, biochemical analyses and data from cross-linking mass-spectrometry (CLMS), we determine the architecture of the TAF11/TAF13/TBP complex, revealing TAF11/TAF13 interaction with the DNA binding surface of TBP. We identify a highly conserved C-terminal TBP-interaction domain (CTID) in TAF13, which is essential for supporting cell growth. Our results thus have implications for cellular TFIID assembly and suggest a novel regulatory state for TFIID function.
- Klíčová slova
- S. cerevisiae, TBP associated factors, TFIID, biochemistry, biophysics, core promoter DNA, gene regulation, histone fold domain, human, structural biology, transcription factors,
- MeSH
- DNA metabolismus MeSH
- faktory asociované s proteinem vázajícím TATA box chemie metabolismus MeSH
- histonacetyltransferasy metabolismus MeSH
- hmotnostní spektrometrie MeSH
- konformace proteinů MeSH
- krystalografie rentgenová MeSH
- lidé MeSH
- mapování interakce mezi proteiny MeSH
- promotorové oblasti (genetika) MeSH
- protein vázající TATA box chemie metabolismus MeSH
- transkripční faktor TFIID chemie metabolismus MeSH
- vazba proteinů MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- DNA MeSH
- faktory asociované s proteinem vázajícím TATA box MeSH
- histonacetyltransferasy MeSH
- protein vázající TATA box MeSH
- TAF11 protein, human MeSH Prohlížeč
- TAF13 protein, human MeSH Prohlížeč
- TATA-binding protein associated factor 250 kDa MeSH Prohlížeč
- TBP protein, human MeSH Prohlížeč
- transkripční faktor TFIID MeSH
