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1.
Nat Commun ; 12(1): 6144, 2021 Oct 22.
Artigo em Inglês | MEDLINE | ID: mdl-34686667

RESUMO

RIPK1 is a crucial regulator of cell death and survival. Ripk1 deficiency promotes mouse survival in the prenatal period while inhibits survival in the early postnatal period without a clear mechanism. Metabolism regulation and autophagy are critical to neonatal survival from severe starvation at birth. However, the mechanism by which RIPK1 regulates starvation resistance and survival remains unclear. Here, we address this question by discovering the metabolic regulatory role of RIPK1. First, metabolomics analysis reveals that Ripk1 deficiency specifically increases aspartate levels in both mouse neonates and mammalian cells under starvation conditions. Increased aspartate in Ripk1-/- cells enhances the TCA  flux and ATP production. The energy imbalance causes defective autophagy induction by inhibiting the AMPK/ULK1 pathway. Transcriptional analyses demonstrate that Ripk1-/- deficiency downregulates gene expression in aspartate catabolism by inactivating SP1. To summarize, this study reveals that RIPK1 serves as a metabolic regulator responsible for starvation resistance.

2.
Metabolomics ; 17(10): 87, 2021 Sep 20.
Artigo em Inglês | MEDLINE | ID: mdl-34542717

RESUMO

INTRODUCTION: Untargeted metabolomics based on liquid chromatography-mass spectrometry is inevitably affected by batch effects that are caused by non-biological systematic bias. Previously, we developed a novel method called WaveICA to remove batch effects for untargeted metabolomics data. To detect batch effect information, the method relies on a batch label. However, it cannot be used in the scenario in which there is only one batch of data or the batch label is unknown. OBJECTIVES: We aim to improve the WaveICA method to remove batch effects for untargeted metabolomics data without using batch information. METHODS: We improved the WaveICA method by developing WaveICA 2.0 to remove batch effects for metabolomics data, and provided an R package WaveICA_2.0 to implement this method. RESULTS: The performance of the WaveICA 2.0 method was evaluated on real metabolomics data. For metabolomics data with three batches, the performance of the WaveICA 2.0 method was similar to that of the WaveICA method in terms of gathering quality control samples (QCSs) and subject samples together in principle component analysis score plots, increasing the similarity of QCSs, increasing differential peaks, and improving classification accuracy. For metabolomics data with only one batch, the WaveICA 2.0 method had a strong ability to remove intensity drift and reveal more biological information and outperformed the QC-RLSC and QC-SVRC methods in our study using our metabolomics data. CONCLUSION: Our results demonstrated that the WaveICA 2.0 method can be used in practice to remove batch effects for untargeted metabolomics data without batch information.

3.
Bioinformatics ; 2021 Aug 25.
Artigo em Inglês | MEDLINE | ID: mdl-34432001

RESUMO

SUMMARY: Accurate and efficient compound annotation is a long-standing challenge for LC-MS-based data (e.g., untargeted metabolomics and exposomics). Substantial efforts have been devoted to overcoming this obstacle, whereas current tools are limited by the sources of spectral information used (in-house and public databases) and are not automated and streamlined. Therefore, we developed metID, an R package that combines information from all major databases for comprehensive and streamlined compound annotation. metID is a flexible, simple, and powerful tool that can be installed on all platforms, allowing the compound annotation process to be fully automatic and reproducible. A detailed tutorial and a case study are provided in Supplementary Materials. AVAILABILITY AND IMPLEMENTATION: https://jaspershen.github.io/metID. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

4.
Nat Commun ; 12(1): 4826, 2021 08 10.
Artigo em Inglês | MEDLINE | ID: mdl-34376696

RESUMO

Loss-of-function mutations in NEK1 gene, which encodes a serine/threonine kinase, are involved in human developmental disorders and ALS. Here we show that NEK1 regulates retromer-mediated endosomal trafficking by phosphorylating VPS26B. NEK1 deficiency disrupts endosomal trafficking of plasma membrane proteins and cerebral proteome homeostasis to promote mitochondrial and lysosomal dysfunction and aggregation of α-synuclein. The metabolic and proteomic defects of NEK1 deficiency disrupts the integrity of blood-brain barrier (BBB) by promoting lysosomal degradation of A20, a key modulator of RIPK1, thus sensitizing cerebrovascular endothelial cells to RIPK1-dependent apoptosis and necroptosis. Genetic inactivation of RIPK1 or metabolic rescue with ketogenic diet can prevent postnatal lethality and BBB damage in NEK1 deficient mice. Inhibition of RIPK1 reduces neuroinflammation and aggregation of α-synuclein in the brains of NEK1 deficient mice. Our study identifies a molecular mechanism by which retromer trafficking and metabolism regulates cerebrovascular integrity, cerebral proteome homeostasis and RIPK1-mediated neuroinflammation.


Assuntos
Barreira Hematoencefálica/metabolismo , Glucose/metabolismo , Complexos Multiproteicos/metabolismo , Quinase 1 Relacionada a NIMA/metabolismo , Proteína Serina-Treonina Quinases de Interação com Receptores/metabolismo , Animais , Animais Recém-Nascidos , Linhagem Celular , Células Cultivadas , Citocinas/genética , Citocinas/metabolismo , Ativação Enzimática , Células HEK293 , Humanos , Camundongos Endogâmicos C57BL , Camundongos Knockout , Microglia/citologia , Microglia/metabolismo , Quinase 1 Relacionada a NIMA/genética , Necroptose/genética , Fosforilação , Transporte Proteico , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , Proteína Serina-Treonina Quinases de Interação com Receptores/genética , Proteínas de Transporte Vesicular/genética , Proteínas de Transporte Vesicular/metabolismo
5.
Nat Commun ; 12(1): 4343, 2021 07 15.
Artigo em Inglês | MEDLINE | ID: mdl-34267224

RESUMO

Aberrant sterol lipid metabolism is associated with physiological dysfunctions in the aging brain and aging-dependent disorders such as neurodegenerative diseases. There is an unmet demand to comprehensively profile sterol lipids spatially and temporally in different brain regions during aging. Here, we develop an ion mobility-mass spectrometry based four-dimensional sterolomics technology leveraged by a machine learning-empowered high-coverage library (>2000 sterol lipids) for accurate identification. We apply this four-dimensional technology to profile the spatially resolved landscapes of sterol lipids in ten functional regions of the mouse brain, and quantitatively uncover ~200 sterol lipids uniquely distributed in specific regions with concentrations spanning up to 8 orders of magnitude. Further spatial analysis pinpoints age-associated differences in region-specific sterol lipid metabolism, revealing changes in the numbers of altered sterol lipids, concentration variations, and age-dependent coregulation networks. These findings will contribute to our understanding of abnormal sterol lipid metabolism and its role in brain diseases.


Assuntos
Química Encefálica , Encéfalo/metabolismo , Lipídeos/química , Esteróis/análise , Envelhecimento/fisiologia , Animais , Feminino , Isomerismo , Lipidômica/métodos , Lipídeos/análise , Aprendizado de Máquina , Camundongos Endogâmicos C57BL , Esteróis/química , Esteróis/metabolismo , Espectrometria de Massas em Tandem/métodos
7.
Arthritis Rheumatol ; 73(9): 1738-1748, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-33760368

RESUMO

OBJECTIVE: To systematically profile metabolic alterations and dysregulated metabolic pathways in hyperuricemia and gout, and to identify potential metabolite biomarkers to discriminate gout from asymptomatic hyperuricemia. METHODS: Serum samples from 330 participants, including 109 with gout, 102 with asymptomatic hyperuricemia, and 119 normouricemic controls, were analyzed by high-resolution mass spectrometry-based metabolomics. Multivariate principal components analysis and orthogonal partial least squares discriminant analysis were performed to explore differential metabolites and pathways. A multivariate methods with Unbiased Variable selection in R (MUVR) algorithm was performed to identify potential biomarkers and build multivariate diagnostic models using 3 machine learning algorithms: random forest, support vector machine, and logistic regression. RESULTS: Univariate analysis demonstrated that there was a greater difference between the metabolic profiles of patients with gout and normouricemic controls than between the metabolic profiles of individuals with hyperuricemia and normouricemic controls, while gout and hyperuricemia showed clear metabolomic differences. Pathway enrichment analysis found diverse significantly dysregulated pathways in individuals with hyperuricemia and patients with gout compared to normouricemic controls, among which arginine metabolism appeared to play a critical role. The multivariate diagnostic model using MUVR found 13 metabolites as potential biomarkers to differentiate hyperuricemia and gout from normouricemia. Two-thirds of the samples were randomly selected as a training set, and the remainder were used as a validation set. Receiver operating characteristic analysis of 7 metabolites yielded an area under the curve of 0.83-0.87 in the training set and 0.78-0.84 in the validation set for distinguishing gout from asymptomatic hyperuricemia by 3 machine learning algorithms. CONCLUSION: Gout and hyperuricemia have distinct serum metabolomic signatures. This diagnostic model has the potential to improve current gout care through early detection or prediction of progression to gout from hyperuricemia.


Assuntos
Gota/metabolismo , Hiperuricemia/metabolismo , Metabolômica , Adulto , Algoritmos , Doenças Assintomáticas , Biomarcadores/metabolismo , Estudos de Casos e Controles , Feminino , Gota/diagnóstico , Humanos , Hiperuricemia/diagnóstico , Aprendizado de Máquina , Masculino , Espectrometria de Massas , Redes e Vias Metabólicas , Pessoa de Meia-Idade , Sensibilidade e Especificidade , Adulto Jovem
8.
Anal Chim Acta ; 1142: 108-117, 2021 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-33280688

RESUMO

Sterols are an important type of lipids, and play many important roles in physiological and pathological processes. However, comprehensive analysis of sterols especially identification of unknown sterols is challenging. In this work, LC-MS with all ion fragmentation (AIF) technology was developed for untargeted analysis of sterols in biological samples. AIF technology provided holistic and multi-dimensional characterization for both knowns and unknowns sterols, including accurate m/z, isotope pattern, retention time (RT), and co-eluted peak profiles between MS1 and MS2 ions in one analysis. We further developed an analysis strategy by integrating the multi-dimensional properties to support unambiguous identification of sterols, including distinguishing sterol isomers. The developed strategy enabled to identify a total of 23 sterols in mouse samples, and quantified 19 sterols in mouse liver tissues. More importantly, we demonstrated that AIF based multi-dimensional analysis provided a possibility to identify sterols without chemical standards and facilitated to discover novel compounds with sterol-like structures in biological samples. In summary, we employed the LC-MS based AIF technology to develop multi-dimensional characterization and identification of both known and unknown sterols in complex biological samples. The comprehensive analysis of sterols facilitates to provide molecular insights to many physiological and pathological activities in biology.


Assuntos
Esteróis , Espectrometria de Massas em Tandem , Animais , Cromatografia Líquida , Íons , Camundongos , Tecnologia
9.
Anal Chim Acta ; 1136: 115-124, 2020 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-33081935

RESUMO

Lipids are an important class of biomolecules, and play many essential functions in biology. Ion mobility-mass spectrometry (IM-MS) has emerged as a promising technology for lipidomics by providing a holistic and multi-dimensional characterization of lipid structures. However, the lipid identification using the multi-dimensional match (i.e., MS1, retention time, collision cross section, and MS/MS spectra) gives multiple lipid candidates, and often over-reports the structural information. Here, we developed a lipid identification strategy that integrated library-based match and rule-based refinement for accurate lipid structural elucidation in IM-MS based lipidomics. The new strategy took the advantage of multi-dimensional information for high-coverage identification, while it also utilized the fragmentation rules to determine the accurate structural information. We demonstrated that the combined strategy accurately determined the lipid structures as lipid species level, fatty acyl level, or fatty acyl position level for different lipid classes in the lipid standard mixture and various biological samples. The combined strategy efficiently reduced the redundancy and improved the accuracy for different lipid classes, and identified a total of 440-960 lipid species in various biological samples. Finally, we performed quantitative lipidomics analysis of NIST SRM 1950 human plasma using IM-MS technology. The measured concentrations of most quantified lipids (>80%) were highly consistent with values reported from other independent laboratories. In summary, the developed lipid identification strategy allowed for the accurate identification of lipid structures, and facilitated accurate lipid quantification in IM-MS based untargeted lipidomics.


Assuntos
Lipidômica , Espectrometria de Massas em Tandem , Humanos , Espectrometria de Mobilidade Iônica , Lipídeos
10.
Nat Commun ; 11(1): 4334, 2020 08 28.
Artigo em Inglês | MEDLINE | ID: mdl-32859911

RESUMO

The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobility - mass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here, we curate an ion mobility CCS atlas, namely AllCCS, and develop an integrated strategy for metabolite annotation using known or unknown chemical structures. The AllCCS atlas covers vast chemical structures with >5000 experimental CCS records and ~12 million calculated CCS values for >1.6 million small molecules. We demonstrate the high accuracy and wide applicability of AllCCS with medium relative errors of 0.5-2% for a broad spectrum of small molecules. AllCCS combined with in silico MS/MS spectra facilitates multi-dimensional match and substantially improves the accuracy and coverage of both known and unknown metabolite annotation from biological samples. Together, AllCCS is a versatile resource that enables confident metabolite annotation, revealing comprehensive chemical and metabolic insights towards biological processes.


Assuntos
Espectrometria de Mobilidade Iônica/métodos , Metaboloma/fisiologia , Metabolômica/métodos , Algoritmos , Fenômenos Biológicos , Confiabilidade dos Dados , Bases de Dados Factuais , Redes e Vias Metabólicas , Software , Espectrometria de Massas em Tandem
11.
Nat Biotechnol ; 38(10): 1159-1163, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32541957

RESUMO

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.


Assuntos
Análise de Dados , Lipidômica/métodos , Lipídeos/genética , Cromatografia Líquida , Lipídeos/química , Espectrometria de Massas em Tandem
12.
Anal Chem ; 92(7): 5082-5090, 2020 04 07.
Artigo em Inglês | MEDLINE | ID: mdl-32207605

RESUMO

Untargeted metabolomics based on liquid chromatography-mass spectrometry is affected by nonlinear batch effects, which cover up biological effects, result in nonreproducibility, and are difficult to be calibrate. In this study, we propose a novel deep learning model, called Normalization Autoencoder (NormAE), which is based on nonlinear autoencoders (AEs) and adversarial learning. An additional classifier and ranker are trained to provide adversarial regularization during the training of the AE model, latent representations are extracted by the encoder, and then the decoder reconstructs the data without batch effects. The NormAE method was tested on two real metabolomics data sets. After calibration by NormAE, the quality control samples (QCs) for both data sets gathered most closely in a PCA score plot (average distances decreased from 56.550 and 52.476 to 7.383 and 14.075, respectively) and obtained the highest average correlation coefficients (from 0.873 and 0.907 to 0.997 for both). Additionally, NormAE significantly improved biomarker discovery (median number of differential peaks increased from 322 and 466 to 1140 and 1622, respectively). NormAE was compared with four commonly used batch effect removal methods. The results demonstrated that using NormAE produces the best calibration results.


Assuntos
Aprendizado Profundo , Metabolômica , Calibragem , Cromatografia Líquida , Espectrometria de Massas , Controle de Qualidade
13.
Nat Commun ; 11(1): 1531, 2020 03 24.
Artigo em Inglês | MEDLINE | ID: mdl-32210233

RESUMO

Vesicle associated membrane protein 2 (VAMP2/synaptobrevin2), a core SNARE protein residing on synaptic vesicles (SVs), forms helix bundles with syntaxin-1 and SNAP25 for the SNARE assembly. Prior to the SNARE assembly, the structure of VAMP2 is unclear. Here, by using in-cell NMR spectroscopy, we describe the dynamic membrane association of VAMP2 SNARE motif in mammalian cells, and the structural change of VAMP2 upon the change of intracellular lipid environment. We analyze the lipid compositions of the SV membrane by mass-spectrometry-based lipidomic profiling, and further reveal that VAMP2 forms distinctive conformations in different membrane regions. In contrast to the non-raft region, the membrane region of cholesterol-rich lipid raft markedly weakens the membrane association of VAMP2 SNARE motif, which releases the SNARE motif and facilitates the SNARE assembly. Our work reveals the regulation of different membrane regions on VAMP2 structure and sheds light on the spatial regulation of SNARE assembly.


Assuntos
Lipídeos de Membrana/metabolismo , Microdomínios da Membrana/metabolismo , Proteínas SNARE/metabolismo , Vesículas Sinápticas/metabolismo , Proteína 2 Associada à Membrana da Vesícula/metabolismo , Linhagem Celular Tumoral , Colesterol/metabolismo , Células HEK293 , Humanos , Microscopia Intravital , Metabolismo dos Lipídeos , Lipidômica , Espectroscopia de Ressonância Magnética , Fusão de Membrana , Domínios Proteicos/genética , Multimerização Proteica , Proteínas Recombinantes/genética , Proteínas Recombinantes/metabolismo , Análise Espacial , Proteína 2 Associada à Membrana da Vesícula/genética
14.
Methods Mol Biol ; 2104: 139-148, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31953816

RESUMO

Liquid chromatography-mass spectrometry (LC-MS) is one of the most popular technologies in metabolomics. The large-scale and unambiguous identification of metabolite structures remains a challenging task in LC-MS based metabolomics. Tandem mass spectral databases provide experimental and in silico MS/MS spectra to facilitate the identification of both known and unknown metabolites, which has become a gold standard method in metabolomics. In addition, metabolite knowledge databases offer valuable biological and pathway information of metabolites. In this chapter, we have briefly reviewed the most common and important tandem mass spectral and metabolite databases, and illustrated how they could be used for metabolite identification.


Assuntos
Bases de Dados Factuais , Metabolômica , Espectrometria de Massas em Tandem , Biologia Computacional/métodos , Humanos , Lipidômica/métodos , Metaboloma , Metabolômica/métodos , Espectrometria de Massas em Tandem/métodos , Navegador
15.
Neuron ; 105(4): 621-629.e4, 2020 02 19.
Artigo em Inglês | MEDLINE | ID: mdl-31831331

RESUMO

A balance between synaptic excitation and inhibition (E/I balance) maintained within a narrow window is widely regarded to be crucial for cortical processing. In line with this idea, the E/I balance is reportedly comparable across neighboring neurons, behavioral states, and developmental stages and altered in many neurological disorders. Motivated by these ideas, we examined whether synaptic inhibition changes over the 24-h day to compensate for the well-documented sleep-dependent changes in synaptic excitation. We found that, in pyramidal cells of visual and prefrontal cortices and hippocampal CA1, synaptic inhibition also changes over the 24-h light/dark cycle but, surprisingly, in the opposite direction of synaptic excitation. Inhibition is upregulated in the visual cortex during the light phase in a sleep-dependent manner. In the visual cortex, these changes in the E/I balance occurred in feedback, but not feedforward, circuits. These observations open new and interesting questions on the function and regulation of the E/I balance.


Assuntos
Ritmo Circadiano/fisiologia , Potenciais Pós-Sinápticos Excitadores/fisiologia , Potenciais Pós-Sinápticos Inibidores/fisiologia , Rede Nervosa/fisiologia , Córtex Visual/fisiologia , Vias Visuais/fisiologia , Animais , Feminino , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Transgênicos , Rede Nervosa/citologia , Inibição Neural/fisiologia , Técnicas de Cultura de Órgãos , Células Piramidais/fisiologia , Córtex Visual/citologia , Vias Visuais/citologia
16.
Methods Mol Biol ; 2084: 269-282, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31729667

RESUMO

Untargeted lipidomics aims to comprehensively measure and characterize all lipid species in biological systems. Ion mobility-mass spectrometry (IM-MS) has showed a great potential for untargeted lipidomic analysis. Coupling with liquid chromatography and data-independent tandem MS techniques, acquired IM-MS data set contains four-dimensional information for lipid identification, including m/z of MS1 ion, retention time (RT), collision cross section (CCS), and MS/MS spectra. In this protocol, we introduced a data processing workflow using an integrative web server, namely, LipidIMMS Analyzer, to support accurate lipid identification. The protocol demonstrated the integration of all four dimensional information to achieve unambiguous identifications of lipids in complex biological samples.


Assuntos
Espectrometria de Mobilidade Iônica , Lipidômica , Lipídeos/análise , Análise de Dados , Bases de Dados Factuais , Lipidômica/métodos , Software , Navegador
17.
Anal Chem ; 91(18): 11897-11904, 2019 09 17.
Artigo em Inglês | MEDLINE | ID: mdl-31436405

RESUMO

SWATH-MS-based data-independent acquisition mass spectrometry (DIA-MS) technology has been recently developed for untargeted metabolomics due to its capability to acquire all MS2 spectra with high quantitative accuracy. However, software tools for deconvolving multiplexed MS/MS spectra from SWATH-MS with high efficiency and high quality are still lacking in untargeted metabolomics. Here, we developed a new software tool, namely, DecoMetDIA, to deconvolve multiplexed MS/MS spectra for metabolite identification and support the SWATH-based untargeted metabolomics. In DecoMetDIA, multiple model peaks are selected to model the coeluted and unresolved chromatographic peaks of fragment ions in multiplexed spectra and decompose them into a linear combination of the model peaks. DecoMetDIA enabled us to reconstruct the MS2 spectra of metabolites from a variety of different biological samples with high coverages. We also demonstrated that the deconvolved MS2 spectra from DecoMetDIA were of high accuracy through comparison to the experimental MS2 spectra from data-dependent acquisition (DDA). Finally, about 90% of deconvolved MS2 spectra in various biological samples were successfully annotated using software tools such as MetDNA and Sirius. The results demonstrated that the deconvolved MS2 spectra obtained from DecoMetDIA were accurate and valid for metabolite identification and structural elucidation. The comparison of DecoMetDIA to other deconvolution software such as MS-DIAL demonstrated that it performs very well for small polar metabolites. DecoMetDIA software is freely available at https://github.com/ZhuMSLab/DecoMetDIA .


Assuntos
Metabolômica , Software , Espectrometria de Massas em Tandem
18.
Nature ; 569(7757): 581-585, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-31043749

RESUMO

Methylation of cytosine to 5-methylcytosine (5mC) is a prevalent DNA modification found in many organisms. Sequential oxidation of 5mC by ten-eleven translocation (TET) dioxygenases results in a cascade of additional epigenetic marks and promotes demethylation of DNA in mammals1,2. However, the enzymatic activity and function of TET homologues in other eukaryotes remains largely unexplored. Here we show that the green alga Chlamydomonas reinhardtii contains a 5mC-modifying enzyme (CMD1) that is a TET homologue and catalyses the conjugation of a glyceryl moiety to the methyl group of 5mC through a carbon-carbon bond, resulting in two stereoisomeric nucleobase products. The catalytic activity of CMD1 requires Fe(II) and the integrity of its binding motif His-X-Asp, which is conserved in Fe-dependent dioxygenases3. However, unlike previously described TET enzymes, which use 2-oxoglutarate as a co-substrate4, CMD1 uses L-ascorbic acid (vitamin C) as an essential co-substrate. Vitamin C donates the glyceryl moiety to 5mC with concurrent formation of glyoxylic acid and CO2. The vitamin-C-derived DNA modification is present in the genome of wild-type C. reinhardtii but at a substantially lower level in a CMD1 mutant strain. The fitness of CMD1 mutant cells during exposure to high light levels is reduced. LHCSR3, a gene that is critical for the protection of C. reinhardtii from photo-oxidative damage under high light conditions, is hypermethylated and downregulated in CMD1 mutant cells compared to wild-type cells, causing a reduced capacity for photoprotective non-photochemical quenching. Our study thus identifies a eukaryotic DNA base modification that is catalysed by a divergent TET homologue and unexpectedly derived from vitamin C, and describes its role as a potential epigenetic mark that may counteract DNA methylation in the regulation of photosynthesis.


Assuntos
5-Metilcitosina/metabolismo , Proteínas de Algas/metabolismo , Ácido Ascórbico/metabolismo , Biocatálise , Chlamydomonas reinhardtii/enzimologia , DNA/química , DNA/metabolismo , 5-Metilcitosina/química , Dióxido de Carbono/metabolismo , Metilação de DNA , Glioxilatos/metabolismo , Nucleosídeos/química , Nucleosídeos/metabolismo , Fotossíntese
19.
Nat Commun ; 10(1): 1516, 2019 04 03.
Artigo em Inglês | MEDLINE | ID: mdl-30944337

RESUMO

Large-scale metabolite annotation is a challenge in liquid chromatogram-mass spectrometry (LC-MS)-based untargeted metabolomics. Here, we develop a metabolic reaction network (MRN)-based recursive algorithm (MetDNA) that expands metabolite annotations without the need for a comprehensive standard spectral library. MetDNA is based on the rationale that seed metabolites and their reaction-paired neighbors tend to share structural similarities resulting in similar MS2 spectra. MetDNA characterizes initial seed metabolites using a small library of MS2 spectra, and utilizes their experimental MS2 spectra as surrogate spectra to annotate their reaction-paired neighbor metabolites, which subsequently serve as the basis for recursive analysis. Using different LC-MS platforms, data acquisition methods, and biological samples, we showcase the utility and versatility of MetDNA and demonstrate that about 2000 metabolites can cumulatively be annotated from one experiment. Our results demonstrate that MetDNA substantially expands metabolite annotation, enabling quantitative assessment of metabolic pathways and facilitating integrative multi-omics analysis.


Assuntos
Redes e Vias Metabólicas , Metabolômica/métodos , Modelos Biológicos , Algoritmos , Animais , Cromatografia Líquida/métodos , Bases de Dados Factuais , Drosophila/metabolismo , Regulação da Expressão Gênica , Gluconeogênese , Metaboloma , Metabolômica/instrumentação , Espectrometria de Massas em Tandem/métodos , Transcriptoma
20.
Anal Bioanal Chem ; 411(19): 4349-4357, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-30847570

RESUMO

Metabolomics quantitatively measures metabolites in a given biological system and facilitates the understanding of physiological and pathological activities. With the recent advancement of mass spectrometry (MS) technology, liquid chromatography-mass spectrometry (LC-MS) with data-independent acquisition (DIA) has been emerged as a powerful technology for untargeted metabolomics due to its capability to acquire all MS2 spectra and high quantitative accuracy. In this trend article, we first introduced the basic principles of several common DIA techniques including MSE, all ion fragmentation (AIF), SWATH, and MSX. Then, we summarized and compared the data analysis strategies to process DIA-based untargeted metabolomics data, including metabolite identification and quantification. We think the advantages of the DIA technique will enable its broad application in untargeted metabolomics.


Assuntos
Metabolômica/métodos , Espectrometria de Massas em Tandem/métodos , Algoritmos
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