ArticleAnalytical and bioanalytical chemistry2008
Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry.
Article in Analytical and bioanalytical chemistry, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 69 citations in OpenAlex.
- Progressive drought alters the root exudate metabolome and differentially activates metabolic pathways in cotton (Frontiers in plant science · 2023Article
- Improved Sample Preparation for Untargeted Metabolomics Profiling of Escherichia coli.Microbiology spectrum · 2021Article
- UPLC-MS-Based Non-targeted Analysis of Endogenous Metabolite Changes in the Leaves ofFrontiers in plant science · 2021Article
- Metabolic Pathway Profiling in Intracellular and Extracellular Environments ofFrontiers in microbiology · 2019Article
- Metabolic footprint analysis of metabolites that discriminate single and mixed yeast cultures at two key time-points during mixed culture alcoholic fermentations.Metabolomics : Official journal of the Metabolomic Society · 2018Article
- Exo-metabolome of Pseudovibrio sp. FO-BEG1 analyzed by ultra-high resolution mass spectrometry and the effect of phosphate limitation.PloS one · 2014Article
- High-performance metabolic profiling with dual chromatography-Fourier-transform mass spectrometry (DC-FTMS) for study of the exposome.Metabolomics : Official journal of the Metabolomic Society · 2013Article
- Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology.Computational and structural biotechnology journal · 2013Review
- AMDORAP: non-targeted metabolic profiling based on high-resolution LC-MS.BMC bioinformatics · 2011Article
- Mass spectra-based framework for automated structural elucidation of metabolome data to explore phytochemical diversity.Frontiers in plant science · 2011Article
- "Lossless" compression of high resolution mass spectra of small molecules.Metabolomics : Official journal of the Metabolomic Society · 2010Article
- Metabolic pathway relationships revealed by an integrative analysis of the transcriptional and metabolic temperature stress-response dynamics in yeast.Omics : a journal of integrative biology · 2010Article
- AtMetExpress development: a phytochemical atlas of Arabidopsis development.Plant physiology · 2010Article
- Assessment of metabolome annotation quality: a method for evaluating the false discovery rate of elemental composition searches.PloS one · 2009Article
- Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'.BMC bioinformatics · 2009Article
- MS/MS spectral tag-based annotation of non-targeted profile of plant secondary metabolites.The Plant journal : for cell and molecular biology · 2009Article
- Dynamics of time-lagged gene-to-metabolite networks of Escherichia coli elucidated by integrative omics approach.Omics : a journal of integrative biologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS) is the best MS technology for obtaining exact mass measurements owing to its great resolution and accuracy, and several outstanding FT-ICR/MS-based metabolomics approaches have been reported. A reliable annotation scheme is needed to deal with direct-infusion FT-ICR/MS metabolic profiling. Correlation analyses can help us not only uncover relations between the ions but also annotate the ions originated from identical metabolites (metabolite derivative ions). In the present study, we propose a procedure for metabolite annotation on direct-infusion FT-ICR/MS by taking into consideration the classification of metabolite-derived ions using correlation analyses. Integrated analysis based on information of isotope relations, fragmentation patterns by MS/MS analysis, co-occurring metabolites, and database searches (KNApSAcK and KEGG) can make it possible to annotate ions as metabolites and estimate cellular conditions based on metabolite composition. A total of 220 detected ions were classified into 174 metabolite derivative groups and 72 ions were assigned to candidate metabolites in the present work. Finally, metabolic profiling has been able to distinguish between the growth stages with the aid of PCA. The constructed model using PLS regression for OD(600) values as a function of metabolic profiles is very useful for identifying to what degree the ions contribute to the growth stages. Ten phospholipids which largely influence the constructed model are highly abundant in the cells. Our analyses reveal that global modification of those phospholipids occurs as E. coli enters the stationary phase. Thus, the integrated approach involving correlation analyses, metabolic profiling, and database searching is efficient for high-throughput metabolomics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.