Heavy water labeling

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Proteomics (319)
Transcriptomics (281)
Unknown (48)
Genomics (13)
Metabolomics (6)

Organisms

Mus musculus (72)
Homo sapiens (65)
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Organisms

mouse gut metagenome (3)
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Decreased fumarate hydratase activity (3)
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Internal Carotid Artery Stenosis (NCI Metathesaurus C0340569) has DiseaseStaging Asymptomatic (1)
Carotid artery disease: ASYMPTOMATIC high-grade inner carotid artery stenosis (1)
Hodgkin lymphoma, mixed cellularity, stage IV (1)
Liposarcoma (1)
Breast adenocarcinoma (1)
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Reference (1)
Acute myeloid leukemia (1)
Alzheimer's disease (1)

Technology Type

Mass Spectrometry (308)
Shotgun proteomics (222)
Bottom-up proteomics (33)
Affinity purification coupled with mass spectrometry proteomics (32)
Gel-based experiment (21)
Data-dependent acquisition (17)
Top-down proteomics (8)
SRM/MRM (7)
Mass spectrometry (5)
SWATH MS (5)
Chemical cross-linking coupled with mass spectrometry proteomics (4)
Data-independent acquisition (4)
All-ion fragmentation (3)
Proteogenomics (3)
HDMSE (2)
MSE (2)
Mass spectrometry assay (1)
DiaPASEF (1)
RNA mass spectrometry (1)

Instrument Platform

Axon GenePix 4000B scanning hardware (4)
G2565BA DNA microarray scanner [Agilent] (3)
Illumina NovaSeq 6000 (3)
ScanArray Lite [PerkinElmer] (2)
GenePix 4000A [Axon Instruments] (2)
418 [Affymetrix] (2)
GenePix 4000B [Axon Instruments] (2)
Liquid Chromatography MS - negative - reverse phase (2)
Axon GenePix 4000B scanner (1)
Axon Instruments GenePix 4000B scanner (1)
Agilent G2565AA and G2565BA Microarray Scanner (1)
GeneChip Scanner 3000 [Affymetrix] (1)
NanoDrop (1)
ScanArray 4000XL [PerkinElmer] (1)
Illumina MiSeq (1)
Illumina HiSeq 2500 (1)
Illumina HiSeq 2000 (1)
Orbitrap Fusion Lumos (1)
Gas Chromatography MS - (1)
Apex-ultra hybrid Qq-FTMS (Bruker) (1)
6540 Q-TOF LC/MS (Agilent) (1)
Liquid Chromatography MS - negative - reverse-phase (1)
Liquid Chromatography MS - positive - reverse phase (1)

Publication Date

2010 (40)
2021 (39)
2020 (37)
2015 (37)
2017 (35)
2022 (34)
2023 (33)
2018 (33)
2025 (32)
2014 (32)
2024 (28)
2013 (28)
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2008 (26)
2007 (25)
2011 (23)
2009 (23)
2012 (22)
2019 (18)
2004 (14)
2005 (13)
2026 (11)
2006 (4)

CHEBI ID

CHEBI:229503 (1)
CHEBI:229499 (1)
CHEBI:229498 (1)
CHEBI:229497 (1)
CHEBI:229493 (1)
CHEBI:229500 (1)
CHEBI:229494 (1)
CHEBI:229501 (1)
CHEBI:229502 (1)
CHEBI:229495 (1)
CHEBI:199577 (1)
CHEBI:229496 (1)
CHEBI:28125 (1)
CHEBI:87798 (1)
CHEBI:37624 (1)
CHEBI:29985 (1)
CHEBI:27551 (1)
CHEBI:16695 (1)
CHEBI:16708 (1)
CHEBI:19138 (1)
CHEBI:72639 (1)
CHEBI:64017 (1)
CHEBI:15428 (1)
CHEBI:17821 (1)
CHEBI:15727 (1)
CHEBI:17115 (1)
CHEBI:17203 (1)
CHEBI:15843 (1)
CHEBI:28364 (1)
CHEBI:28728 (1)

Metabolite Name

Ethanolamine (2)
Glycine (2)
D-Lac-Hcy (1)
D-Lac-Gln (1)
D-Lac-Phe (1)
D-Lac-Thr (1)
D-Lac-Leu (1)
D-Lac-Met (1)
D-Lac-Glu (1)
D-Lac-Val (1)
MG-H1 (1)
L-Lac-Cys (1)
D-Lac-Cys peak 2 (1)
D-Lac-Cys peak 1 (1)
<small>L</small>-serine (1)
<small>L</small>-methionine (1)
Hydrazine (1)
AA (1)
CEA (1)
5-methylcytosine (1)
Methanol (1)
Ethanol (1)
DHA (1)
Hydroxylamine (1)
TXB2 (1)
Cytidine 5'-monophosphate disodium salt (1)
Uridylic acid (1)
Adenosine 5'-monophosphate (1)
L-Glucose (1)
Phosphoenolpyruvate (1)

First Public Date

2017 (4)
2025 (2)
2026 (1)
2020 (1)
2013 (1)

Modification

4x(15)N labeled L-arginine (8)
2x(15)N labeled L-lysine (6)
4x(2)H labeled dimethylated residue (3)
4x(2)H labeled dimethylated L-lysine (2)
Heavy form - site K (1)
Light form - site K (1)

Study type

Transcription profiling by array (248)
Other (6)
Transcription profiling by tiling array (4)
Comparative genomic hybridization by array (4)
ChIP-seq (4)
Proteomic profiling by array (4)
Methylation profiling by array (3)
RNA-seq of coding RNA (3)
RNAi profiling by array (2)
ChIP-chip by array (2)
MicroRNA profiling by array (2)
RNA-seq of coding RNA from single cells (2)
Differential (1)
Human - High-throughput sequencing (1)
Translation profiling (1)
Antigen profiling (1)
Transcription profiling by RT-PCR (1)

Release Date

2010 (41)
2014 (29)
2013 (28)
2008 (26)
2007 (25)
2009 (24)
2012 (23)
2011 (23)
2015 (21)
2016 (17)
2005 (14)
2004 (14)
2023 (12)
2022 (8)
2018 (6)
2017 (6)
2020 (5)
2024 (4)
2006 (4)
2021 (4)
2025 (3)
2026 (2)
2019 (1)

Lab affiliation

Cellzome (10)
Department of Biochemistry and Functional Proteomics, Institute of Biology II, Faculty of Biology and BIOSS Centre for Biological Signalling Studies, University of Freiburg, 79104 Freiburg im Breisgau, Germany (7)
CRUK - Beatson Institute for Cancer Research - Switchback Rd, Bearsden, Glasgow G61 1BD - United Kingdom (3)
Department of Biochemistry and Molecular Biology, University of Calgary, Alberta, Canada; Department of Physiology and Pharmacology, University of Calgary, Alberta, Canada; The Hotchkiss Brain Institute, University of Calgary, Alberta, Canada; McCaig Institute for Bone and Joint Health, University of Calgary, Alberta, Canada (3)
Molecular and Cell Biology Laboratory, The Salk Institute for Biological Studies, 10010 N. Torrey Pines Rd, La Jolla, CA 92037 (3)
Yazhouwan National Laboratory, Sanya 572024, China (3)
Alkali Soil Natural Environmental Science Center, Northeast Forestry University, Harbin 150040, China (2)
Biological Chemistry Department, David Geffen School of Medicine, UCLA (2)
Boston College (2)
Department of Experimental Medicine, University of Tor Vergata, Rome, Italy (2)
Department of Immunobiology, University of Lausanne, Switzerland (2)
Department of Laboratory Medicine and Pathology, Mayo Clinic (2)
Department of Neuro- and Sensory Physiology University Medical Center Göttingen Humboldtallee 23 37073 Göttingen (2)
Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, China (2)
Diabetes and Circadian Rhythms Department, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland (2)
Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong SAR, China (2)
Genome Biology Unit and Proteomics Core Facility, European Molecular Biology Laboratory, 69117 Heidelberg, Germany (2)
Institut Pasteur Unité des Interactions Bactéries-Cellules, Inserm U604, INRA USC2020 25 rue du Dr. Roux 75015 Paris France (2)
Institute for Biochemistry and Molecular Biology, Faculty of Medicine, University of Bonn (2)
Lund Stem Cell Center, Division of Molecular Hematology, Lund University, Lund, Sweden (2)
McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205 USA (2)
(1) German Center for Neurodegenerative Diseases (DZNE), 72076 Tübingen, Germany (2) University of Tübingen, Center for Ophthalmology, Institute for Ophthalmic Research, 72074 Tübingen, Germany (1)
1. Center for Molecular Medicine Cologne, University of Cologne, Robert-Koch-Str. 21, D- 50931 Cologne, Germany 2. Inst. for Neurophysiology, University of Cologne, Robert-Koch-Str. 39, D-50931 Cologne, Germany 3. CECAD; Cologne Cluster of Excellence in Cellular Stress Responses in Ageing-associated Diseases, University of Cologne, Joseph-Stelzmann-Str. 26, D-50931 Cologne, Germany (1)
1. Institute of Chemical Biology, Shenzhen Bay Laboratory, 518107 Shenzhen, China; 2. School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055, China (1)
1. Laboratory of Protein and Peptide Pharmaceuticals & Laboratory of Proteomics, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China 2. University of Chinese Academy of Sciences, Beijing 100049, China (1)
1.Center for Translational Vision Research, Gavin Herbert Eye Institute, Department of Ophthalmology, University of California-Irvine, Irvine, CA 92697, USA 2.Department of Ophthalmic Research, Cleveland Clinic, Cleveland, OH 44195, USA 3.Department of Physiology & Biophysics, School of Medicine, University of California-Irvine, Irvine, CA 92697, USA (1)
1Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China 2Academy of Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China 3Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China (1)
733 N. Broadway Miller Research Building room 527 Johns Hopkins University Baltimore, MD 21205 (1)
AMU, CNRS, INSERM, Institut Paoli-Calmettes, CRCM (1)
Age-related Inflammation and Degeneration Research Unit, Chulalongkorn University, Bangkok 10330, Thailand (1)

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Matrix Effect on Chemical Isotope Labeling and Its Implication in Metabolomic Sample Preparation for Quantitative Metabolomics

Matrix effect from various constituents in biological samples can reduce the accuracy of quantitative metabolomics. Differential chemical isotope labeling liquid chromatography mass spectrometry (CIL LC-MS) can overcome the matrix effect on MS detection based on measuring the intensity ratios of met...

2015-07-01 | MTBLS194 | MetaboLights

D2Ome - rate constant estimation from heavy water metabolic labeling and LC-MS

We developed a software for extraction of protein decay rate constants from heavy water labeling followed by LC-MS experiments. We illustrate the program on application to normal diet and western diet fed LDLR-/- mice. We demonstrate that proteins subunits of 40S ribosomal complex have reduced stabi...

ORGANISM(S): Mus musculus (Mouse)

2019-04-10 | PXD009493 | Pride

Two-Channel Chemical Isotope Labeling Metabolomics Analysis of Human Fecal Samples

Global metabolomics study of the amine and carboxyl submetabolomes of 16 human fecal samples.

2026-09-23 | MTBLS13531 | MetaboLights

geoRge: A Computational Tool To Detect the Presence of Stable Isotope Labeling in LC/MS-Based Untargeted Metabolomics

Studying the flow of chemical moieties through the complex set of metabolic reactions that happen in the cell is essential to understanding the alterations in homeostasis that occur in disease. Recently, LC/MS-based untargeted metabolomics and isotopically labeled metabolites have been used to facil...

2015-09-15 | MTBLS213 | MetaboLights

Amino acid and heavy water labelling to obtain protein turnover rates in intact adult animals

Both labelling studies were conducted with C57/BL6J adult male mice, derived from the same supplier and maintained under identical conditions. Eleven adult male C57BL/6JOlaHsd mice (Harlan UK Ltd., Shardlow, UK) of over 12 months of age at the start of the experiment were housed individually in 48 x...

ORGANISM(S): Mus Musculus (mouse)

2021-12-13 | PXD029639 | JPOST Repository

Heavy metal resistance in Cupriavidus metallidurans CH34 is governed by an intricate transcriptional network.

Background: The high number of heavy metal resistance genes in the soil bacterium Cupriavidus metallidurans CH34 makes it an interesting model organism to study microbial responses to heavy metals. Results: In this study the transcriptional response of this bacterium was measured after challenging i...

ORGANISM(S): Cupriavidus metallidurans CH34

2011-06-28 | E-GEOD-23876 | biostudies-arrayexpress

Human serum proteome dynamics in type 2 diabetes using heavy water labeling mass spectrometry

Control subjects and type 2 diabetic patients were given deuterium-labeled (heavy) water for a seven-day period and their plasma serum proteins were analyzed by high-resolution mass spectrometry. Using an in-house-developed software, fractional synthesis rates were calculated for proteins of interes...

ORGANISM(S): Homo sapiens (Human)

2017-11-02 | PXD005755 | Pride

Proteome dynamics Mass spectrometry Serum Type 2 diabetes Heavy water T2d Human

Using Heavy Mass Isotopomers for Protein Turnover in Heavy Water Metabolic Labeling.

Not available

S-EPMC8167932 | biostudies-literature

Protein turnover models for LC-MS data of heavy water metabolic labeling.

Not available

S-EPMC8921656 | biostudies-literature

Transcription profiling of wheat to identify genotypic differences in water soluble carbohydrate metabolism in stem

Water soluble carbohydrates (WSC, composed of mainly fructans, sucrose, glucose and fructose) deposited in wheat stems are important carbon sources for grain filling. Variation in stem WSC concentrations among wheat genotypes is one of the genetic factors influencing grain weight and yield under wat...

ORGANISM(S): Triticum aestivum

2008-10-26 | E-GEOD-9767 | biostudies-arrayexpress

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