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1.
J Agric Food Chem ; 69(36): 10741-10748, 2021 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-34478301

RESUMO

Plantaricin Q7 is a bacteriocin produced by Lactobacillus plantarum Q7 with food preservation potential. Low yield is one of the bottlenecks of the wide application of plantaricin Q7. Nontargeted metabolomics was performed to reveal the mechanism of plantaricin Q7 biosynthesis. The results showed that the composition and abundance of intracellular metabolites varied significantly at key time points of plantaricin Q7 synthesis. Differential metabolic pathways were purine metabolism; pyrimidine metabolism; alanine, aspartate, and glutamate metabolism; amino acid biosynthesis; aminoacyl-tRNA biosynthesis; and ABC transporters. Differential metabolites were xanthine, deoxyadenosine, uracil, 5-methylcytosine, α-ketoglutarate, γ-aminobutyric acid, glutamate, glutamine, and tryptophan. Based on metabolomics information, the putative metabolic synthesis pathway of plantaricin Q7 was proposed. Glutamine, glutamate, and 5-methylcytosine could be critical metabolites and simulate plantaricin Q7 biosynthesis significantly (P < 0.05). Bacteriocin production was investigated by comparative metabolomics in this report, which could help to achieve higher plantaricin Q7 yield by metabolic regulation.


Assuntos
Bacteriocinas , Lactobacillus plantarum , Bacteriocinas/metabolismo , Vias Biossintéticas , Conservação de Alimentos , Lactobacillus plantarum/metabolismo , Metabolômica
2.
BMC Bioinformatics ; 22(1): 423, 2021 Sep 07.
Artigo em Inglês | MEDLINE | ID: mdl-34493210

RESUMO

BACKGROUND: Assessing the reproducibility of measurements is an important first step for improving the reliability of downstream analyses of high-throughput metabolomics experiments. We define a metabolite to be reproducible when it demonstrates consistency across replicate experiments. Similarly, metabolites which are not consistent across replicates can be labeled as irreproducible. In this work, we introduce and evaluate the use (Ma)ximum (R)ank (R)eproducibility (MaRR) to examine reproducibility in mass spectrometry-based metabolomics experiments. We examine reproducibility across technical or biological samples in three different mass spectrometry metabolomics (MS-Metabolomics) data sets. RESULTS: We apply MaRR, a nonparametric approach that detects the change from reproducible to irreproducible signals using a maximal rank statistic. The advantage of using MaRR over model-based methods that it does not make parametric assumptions on the underlying distributions or dependence structures of reproducible metabolites. Using three MS Metabolomics data sets generated in the multi-center Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPD) study, we applied the MaRR procedure after data processing to explore reproducibility across technical or biological samples. Under realistic settings of MS-Metabolomics data, the MaRR procedure effectively controls the False Discovery Rate (FDR) when there was a gradual reduction in correlation between replicate pairs for less highly ranked signals. Simulation studies also show that the MaRR procedure tends to have high power for detecting reproducible metabolites in most situations except for smaller values of proportion of reproducible metabolites. Bias (i.e., the difference between the estimated and the true value of reproducible signal proportions) values for simulations are also close to zero. The results reported from the real data show a higher level of reproducibility for technical replicates compared to biological replicates across all the three different datasets. In summary, we demonstrate that the MaRR procedure application can be adapted to various experimental designs, and that the nonparametric approach performs consistently well. CONCLUSIONS: This research was motivated by reproducibility, which has proven to be a major obstacle in the use of genomic findings to advance clinical practice. In this paper, we developed a data-driven approach to assess the reproducibility of MS-Metabolomics data sets. The methods described in this paper are implemented in the open-source R package marr, which is freely available from Bioconductor at http://bioconductor.org/packages/marr .


Assuntos
Metabolômica , Espectrometria de Massas , Reprodutibilidade dos Testes
3.
World J Gastroenterol ; 27(31): 5171-5180, 2021 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-34497442

RESUMO

Pancreatic ductal adenocarcinoma (PDAC) represents a challenging pathology with very poor outcomes and is increasing in incidence within the general population. The majority of patients are diagnosed incidentally with insidious symptoms and hence present late in the disease process. This significantly affects patient outcomes: the only cure is surgical resection but only up to 20% of patients present with resectable disease at the time of clinical presentation. The use of "omic" technology is expanding rapidly in the field of personalised medicine - using genomic, proteomic and metabolomic approaches allows researchers and clinicians to delve deep into the core molecular processes of this difficult disease. This review gives an overview of the current findings in PDAC using these "omic" approaches and summarises useful markers in aiding clinicians treating PDAC. Future strategies incorporating these findings and potential application of these methods are presented in this review article.


Assuntos
Adenocarcinoma , Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Carcinoma Ductal Pancreático/genética , Humanos , Metabolômica , Neoplasias Pancreáticas/genética , Proteômica
4.
Zhongguo Yi Xue Ke Xue Yuan Xue Bao ; 43(4): 536-544, 2021 Aug.
Artigo em Chinês | MEDLINE | ID: mdl-34494523

RESUMO

Objective To obtain the metabolome profiles in liver and serum of mice during normal aging. Methods The liver and serum samples of ten 2-month-old mice and ten 18-month-old C57BL/6J mice under physiological conditions were collected.Metabolites were identified and quantified by liquid chromatography-tandem mass spectrometry.The overall assessment,differential screening,and functional analysis were performed with the filtered high-quality data. Results In the negative-ion mode and positive-ion mode,242 and 399 metabolites were identified in the liver and 265 and 230 in serum,respectively.The difference of metabolome between young and old mice was moderate.The upregulated metabolites identified in aging liver were related to the metabolism of riboflavin,glucose,and arachidonic acid,while the downregulated ones were associated with the metabolism of pyrimidine,purine,glycerophospholipid,glutathione,and nicotinamide.Altered metabolites in serum during aging were involved in a variety of nucleic acid metabolism-related pathways,such as pyrimidine metabolism,purine metabolism,one carbon pool by folate,and amino sugar and nucleotide sugar metabolism. Conclusions The metabolome profiles of mouse liver and serum both revealed dysregulated nucleic acid metabolism pathways during normal aging.This study provides metabolome data for further research on aging-associated mechanism and may support the discovery of intervention methods for aging.


Assuntos
Metaboloma , Metabolômica , Envelhecimento , Animais , Fígado , Camundongos , Camundongos Endogâmicos C57BL
5.
Int J Mol Sci ; 22(17)2021 Sep 02.
Artigo em Inglês | MEDLINE | ID: mdl-34502454

RESUMO

COVID-19 is a global threat that has spread since the end of 2019, causing severe clinical sequelae and deaths, in the context of a world pandemic. The infection of the highly pathogenetic and infectious SARS-CoV-2 coronavirus has been proven to exert systemic effects impacting the metabolism. Yet, the metabolic pathways involved in the pathophysiology and progression of COVID-19 are still unclear. Here, we present the results of a mass spectrometry-based targeted metabolomic analysis on a cohort of 52 hospitalized COVID-19 patients, classified according to disease severity as mild, moderate, and severe. Our analysis defines a clear signature of COVID-19 that includes increased serum levels of lactic acid in all the forms of the disease. Pathway analysis revealed dysregulation of energy production and amino acid metabolism. Globally, the variations found in the serum metabolome of COVID-19 patients may reflect a more complex systemic perturbation induced by SARS-CoV-2, possibly affecting carbon and nitrogen liver metabolism.


Assuntos
Biomarcadores/sangue , Carbono/metabolismo , Fígado/metabolismo , Metaboloma , Nitrogênio/metabolismo , Aminoácidos/metabolismo , COVID-19/sangue , COVID-19/patologia , COVID-19/virologia , Citocinas/sangue , Análise Discriminante , Humanos , Análise dos Mínimos Quadrados , Redes e Vias Metabólicas/genética , Metabolômica/métodos , SARS-CoV-2/isolamento & purificação , Índice de Gravidade de Doença
6.
Nat Commun ; 12(1): 5229, 2021 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-34471142

RESUMO

The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Here, we introduce DEEP Picker, a deep neural network (DNN)-based approach for peak picking and spectral deconvolution which semi-automates the analysis of two-dimensional NMR spectra. DEEP Picker includes 8 hidden convolutional layers and was trained on a large number of synthetic spectra of known composition with variable degrees of crowdedness. We show that our method is able to correctly identify overlapping peaks, including ones that are challenging for expert spectroscopists and existing computational methods alike. We demonstrate the utility of DEEP Picker on NMR spectra of folded and intrinsically disordered proteins as well as a complex metabolomics mixture, and show how it provides access to valuable NMR information. DEEP Picker should facilitate the semi-automation and standardization of protocols for better consistency and sharing of results within the scientific community.


Assuntos
Aprendizado Profundo , Espectroscopia de Ressonância Magnética/métodos , Redes Neurais de Computação , Algoritmos , Automação , Imageamento por Ressonância Magnética/métodos , Metabolômica/métodos , Ressonância Magnética Nuclear Biomolecular/métodos , Proteínas/análise
7.
Zhongguo Zhong Yao Za Zhi ; 46(12): 3133-3143, 2021 Jun.
Artigo em Chinês | MEDLINE | ID: mdl-34467705

RESUMO

To study the effect of mineral Chloriti Lapis on pulmonary metabolites and metabolic pathways in lung tissues of rats with acute exacerbation of chronic obstructive pulmonary disease(AECOPD). The AECOPD rat model of phlegm heat syndrome was replicated by the method of smoking combined with Klebsiella pneumoniae infection. Except for using UPLC-Q-TOF-MS analysis, SPSS 18.0, SIMCA 13.0 and other software were also used for statistical analysis. Through literature search and online database comparison, the differential metabolites were identified, and the possible metabolic pathways were analyzed. After 15 days of administration, PLS-DA analysis was carried out on lung tissue samples of rats in each group. The results showed that the metabolic profiles of lung tissues of rats in each group could be well separated, which indicated that Chloriti Lapis and aminophylline had significant intervention effect on the lung metabolic profile of rats with AECOPD. Moreover, the metabolic profile of Chloriti Lapis group was closer to that of control group, and the intervention effect was better than that of aminophylline group. As a result, 15 potential differential metabolites were identified: phytosphingosine, sphinganine, tetradecanoylcarnitine, L-palmitoylcarnitine, elaidic carnitine, lysoPC[18∶2(9Z,12Z)], lysoPC(16∶0), lysoPC[18∶1(9Z)], lysoPC(18∶0), stearic acid, lysoPC(15∶0), arachidonic acid, docosapentaenoic acid, linoleic acid and palmitic acid. Among them, Chloriti Lapis could significantly improve the levels of 10 differential metabolites of phytosphingosine, tetradecanoylcarnitine, L-palmitoylcarnitine, elaidic carnitine, lysoPC[18∶2(9Z,12Z)], lysoPC(16∶0), lysoPC[18∶1(9Z)], stearic acid, lysoPC(15∶0), and palmitic acid(P<0.05). The intervention effect of Chloriti Lapis group was better than that of aminophylline group. Analysis of metabolic pathways showed that there were 8 possible metabolic pathways that could be affected, and three of the most important metabolic pathways(pathway impact>0.1) were involved: linoleic acid metabolism, arachidonic acid metabolism, and sphingolipid metabolism. Chloriti Lapis had obvious intervention effects on lung tissue-related metabolites and metabolic pathways in rats with AECOPD, and the effect was better than that of aminophyllinne.


Assuntos
Medicina Tradicional Chinesa , Doença Pulmonar Obstrutiva Crônica , Animais , Pulmão , Metabolômica , Minerais , Ratos
8.
Zhonghua Gan Zang Bing Za Zhi ; 29(8): 788-793, 2021 Aug 20.
Artigo em Chinês | MEDLINE | ID: mdl-34517462

RESUMO

Objective: To study the changes of urinary metabolic profile, screen metabolic ions characterization with clinical diagnostic value, and a disease differentiation model establishment, in an attempt to help the clinical diagnosis of hepatocellular carcinoma patients. Methods: A case-control study was conducted. Ultra-performance liquid chromatography/mass spectrometry (UPLC-MS) were used to analyze urine samples of 32 patients with hepatocellular carcinoma, 28 patients with liver cirrhosis and 28 healthy persons, respectively. The orthogonal partial least squares discriminant analysis (OPLS-DA) and the principal component analysis (PCA) model were constructed using MZmine2.0 and SIMCA-P + 12.0.1.0 software for preliminary screening of metabolites. The metabolic ions selected in the final test were analyzed by SPSS, and the markers were analyzed and screened by one-way analysis of variance. Finally, the sensitivity and specificity of the selected markers were analyzed by calculating the area under the receiver operating characteristic (ROC) curve. One-way analysis of variance was used to compare quantitative indicators between groups. Results: OPLS-DA model parameters were R2X = 35.3%, R2Y = 86.9%, and Q2 = 72.2%, which had a good identification value. A total of 26 characteristic ions were screened, of which 17 were identified. 14, 19-Dihydroaspidospermatine had a high value in distinguishing healthy person with hepatocellular carcinoma patients, and the area under the receiver operating characteristic curve was higher than 0.9. The area under the ROC curve for distinguishing liver cancer with liver cirrhosis patients was 0.88, which was higher than the ROC curve of alpha-fetoprotein (0.75). Conclusion: Based on the UPLC-MS platform, the PCA and OPLS-DA models were successfully constructed, and the characteristic metabolic ions in the urine were extracted and identified, which has a certain value in assisting clinical screening of hepatocellular carcinoma patients.


Assuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , Biomarcadores , Carcinoma Hepatocelular/diagnóstico , Estudos de Casos e Controles , Cromatografia Líquida , Humanos , Metaboloma , Metabolômica , Espectrometria de Massas em Tandem
9.
Talanta ; 235: 122720, 2021 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-34517588

RESUMO

Inborn errors of metabolism, also known as inherited metabolic diseases (IMDs), are related to genetic mutations and cause corresponding biochemical metabolic disorder of newborns and even sudden infant death. Timely detection and diagnosis of IMDs are of great significance for improving survival of newborns. Here we propose a strategy for simultaneously detecting six types of IMDs via combining GC-MS technique with the random forest algorithm (RF). Clinical urine samples from IMD and healthy patients are analyzed using GC-MS for acquiring metabolomics data. Then, the RF model is established as a multi-classification tool for the GC-MS data. Compared with the models built by artificial neural network and support vector machine, the results demonstrated the RF model has superior performance of high specificity, sensitivity, precision, accuracy, and matthews correlation coefficients on identifying all six types of IMDs and normal samples. The proposed strategy can afford a useful method for reliable and effective identification of multiple IMDs in clinical diagnosis.


Assuntos
Doenças Metabólicas , Algoritmos , Cromatografia Gasosa-Espectrometria de Massas , Humanos , Lactente , Recém-Nascido , Metabolômica
10.
Talanta ; 235: 122729, 2021 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-34517597

RESUMO

Thyroid cancer is a malignant disease with dramatically low advanced-stage 10-year survival. Meanwhile, the metabolites in saliva are becoming a wealthy source of disease biomarkers. However, there is a lack of non-invasive analytical methods for the identification of biomarkers in saliva for the preoperative diagnosis of thyroid cancer. Therefore, we developed an ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) method to simultaneously determine the metabolic levels of 10 amino acids in saliva, aiming to study the amino acid metabolism profile to promote early diagnosis of thyroid cancer. We tested unstimulated whole saliva from patients with papillary thyroid carcinoma (PTC; n = 61) and healthy controls (HC; n = 61), and used receiver operating characteristic (ROC) curves to establish the diagnostic value of potential markers. The method validation results showed good precision, linearity (R2 > 0.99), recovery (92.2 %-110.3 %), intra- and inter-day precision (RSD < 7 % and RSD < 9 %, respectively). The concentration of 10 amino acids was significantly different between PTC and HC in human salivary analysis (P < 0.05), the area under the curve (AUC) values of a single marker for the diagnosis of PTC were ranging from 0.678 to 0.833. A panel of alanine, valine, proline, phenylalanine was selected in combination yielded the AUC of 0.936, which will improve the accuracy of early diagnosis of thyroid cancer (sensitivity: 91.2 %; specificity: 85.2 %). This study proved the possibility of salivary amino acid biomarkers for PTC early diagnosis, providing a simple auxiliary way for the non-invasive diagnosis of thyroid cancer.


Assuntos
Saliva , Neoplasias da Glândula Tireoide , Aminoácidos , Cromatografia Líquida , Humanos , Espectrometria de Massas , Metabolômica , Neoplasias da Glândula Tireoide/diagnóstico
11.
Talanta ; 235: 122786, 2021 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-34517644

RESUMO

In this study, we identify 11 mouse pup volatiles putatively involved in maternal care induction in adult females. For this purpose, we have adapted the dynamic headspace methodology to extract the volatolome of whole alive animals. Untargeted metabolomic methodology was used to compare the volatolome of neonatal (4-6 days) with elder pups until the age of weaning (21-23 days old). Pup volatolome was analyzed by gas chromatography (GC) coupled to single quadrupole mass spectrometry (MS) using automated thermal desorption for sample introduction. After data processing and multivariate statistical analysis, comparison with NIST spectral library allowed identifying compounds secreted preferentially by neonatal pups: di(propylen glycol) methyl ether, 4-nonenal, di(ethylene glycol) monobutyl ether, 2-phenoxyethanol, isomethyl ionone, tridecanal, 1,3-diethylbenzene, 1,2,4,5-tetramethylbenzene, 2-ethyl-p-xylene and tri(propylene glycol) methyl ether. Palmitic acid was enriched in the volatolome of fourth week youngsters compared to neonatal pups. The results demonstrated the great potential of the new sampling procedure combined with GC-MS based untargeted volatolomics to identify volatile pheromones in mammals.


Assuntos
Compostos Orgânicos Voláteis , Animais , Cromatografia Gasosa-Espectrometria de Massas , Espectrometria de Massas , Metabolômica , Camundongos , Feromônios , Compostos Orgânicos Voláteis/análise
12.
Anal Chem ; 93(32): 11099-11107, 2021 08 17.
Artigo em Inglês | MEDLINE | ID: mdl-34347447

RESUMO

As a vital hub, a mitochondrion houses metabolic pathways that play important roles in cellular physiology. Aberrant metabolites occurring in mitochondria are closely associated with the emergence and progression of various mitochondria-related diseases. Therefore, a simple and versatile approach to efficiently purify intact mitochondria is urgently needed to precisely and comprehensively characterize the composition and abundance of the mitochondrial metabolome in different physiological and pathological states. In this work, novel immunoaffinitive magnetic composites MagG@PD@Avidin@TOM20 were prepared to achieve highly selective isolation of intact mitochondria from three different hepatocytes (LO2, HepG2, and Huh7). The prepared composites inherit combined merits, including strong magnetic responsiveness, excellent stability, and specific and high affinity between antibody TOM20 and mitochondrial outer membrane protein. These mitochondria attached on MagG@PD@Avidin@TOM20 were characterized by the western blot and fluorescence microscopy to confirm their purity and integrity, which are vital for reliable mitochondrial metabolic analysis. Subsequently, ultrahigh-performance liquid chromatography-high-resolution mass spectrometry-based untargeted metabolomics analysis was conducted to characterize the metabolomes in the immunopurified mitochondria and whole cells. Notably, the metabolite profiles of whole cells and mitochondria including itaconic acid, acetylcarnitine, malic acid, etc., were significantly different. These data underscore the importance of determining metabolites at the mitochondrial level, which would supplement us new knowledge at the subcellular level.


Assuntos
Metaboloma , Metabolômica , Grafite , Indóis , Fenômenos Magnéticos , Mitocôndrias/metabolismo , Polímeros
13.
Food Res Int ; 147: 110519, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34399497

RESUMO

The short term micro-flowing purification system (STMFPS) has been shown to improve the flesh quality of freshwater fish. However, few studies have focused on the involved underlying mechanisms. This study explored the effect of STMFPS on the flesh quality of market-size freshwater fish based on the combination of metabolomics and transcriptomics methods. The UPLC-QTOF/MS based metabolomics method was utilized to screen metabolites and predict the possible major metabolic pathways during different STMFPS treatment periods (0 d, 1 d, 5 d and 9 d). Furthermore, the transcriptomic data demonstrated that the differentially expressed genes detected in crucian carp muscle were 2915, 7852 and 7183 after 1 d, 5 d and 9 d STMFPS treatment. Results showed that the TCA cycle, ornithine cycle, purine metabolism and amino acid catabolism play important roles in improving the flesh quality of crucian carp. This study may help to understand the mechanism of improving the flesh quality of aquatic products using STMFPS.


Assuntos
Carpas , Animais , Carpas/genética , Carpa Dourada , Metabolômica , Transcriptoma , Água
14.
Talanta ; 234: 122688, 2021 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-34364485

RESUMO

Untargeted metabolomics has been widely used for studies with zebrafish embryos. Until now, the number of analytical approaches to determine metabolites in zebrafish is limited, and there is a lack of consensus on the best platforms for comprehensive metabolomics analysis of zebrafish embryos. In addition, the capacity of these methods to detect metabolites is unsatisfactory and the confidence level for identifying compounds is relatively low. To improve the metabolome coverage, we mainly focused on the optimization of separation mechanisms, mobile phase additives, and resuspension solvents based on liquid chromatography (LC) coupling to high-resolution mass spectrometry (HRMS) techniques. Moreover, the procedures for optimizing methods were assessed when taking metabolite profiles in both positive and negative ionization modes into account. Four LC columns were studied: C18, T3, PFP, and HILIC. In positive ionization mode, it was strongly recommended to employ the HILIC approach operated at the neutral condition, which led to the presence of more than 4700 features and the annotation of 151 metabolites, mainly zwitterionic and basic compounds, in comparison to reverse phase (RP)-based methods with less than 1000 features. In negative ionization mode, the PFP column operated at 0.02% acetic acid showed the best performance in terms of metabolite coverage: 3100 metabolic features were detected and 218 metabolites were annotated in zebrafish embryos. Metabolite profiles mainly contained acidic and zwitterionic compounds. HILIC-based platforms were complementary to RP columns when analyzing highly polar metabolites. Additionally, it was preferable to reconstitute zebrafish extracts in 100% water for analysis of metabolites on RP columns, with a 20-30% increase in the number of identified metabolites compared to a 50% water in methanol solution. However, water/methanol (1:9, v/v), as resuspension solution, was advantageous over water/methanol (1:1, v/v) for HILIC analysis showing an 8-15% increase in detected metabolites. In total 336 polar metabolites were annotated by the combination of the optimized HILIC (positive) and PFP (negative) approaches. The largest metabolome coverage of polar metabolites in zebrafish embryos was obtained when three approaches were combined (negative PFP and HILIC, and HILIC positive) resulting in more than 420 annotated compounds.


Assuntos
Metaboloma , Peixe-Zebra , Animais , Cromatografia Líquida , Metabolômica , Solventes
17.
Planta ; 254(3): 59, 2021 Aug 24.
Artigo em Inglês | MEDLINE | ID: mdl-34427790

RESUMO

MAIN CONCLUSION: Through combined analysis of the transcriptome and targeted metabolome of lily bulbs, the possible molecular mechanism of dormancy release was revealed. Regulation of bulb dormancy is critical for ensuring annual production and high-quality cultivation. The application of low temperatures is the most effective method for breaking bulb dormancy, but the molecular mechanism underlying this response is unclear. Herein, targeted metabolome and transcriptome analyses were performed on Lilium davidii var. unicolor bulbs stored for 0, 50, and 100 days at 4 °C. Dormancy release mainly depended on the accumulation of gibberellins GA4 and GA7, which are synthesized by the non-13-hydroxylation pathway, rather than GA3, and ABA was degraded in the process. The contents of nonbioactive GA9, GA15, and GA24, the precursors of GA4 synthesis, increased with bulb dormancy release. Altogether, 113,252 unique transcripts were de novo assembled through high-throughput transcriptome sequences, and 639 genes were continuously differentially expressed. Energy sources during carbohydrate metabolism mainly depend on glycolysis and the pentose phosphate pathway. Screening of transcription factor families involved in bulb dormancy release showed that MYB, WRKY, NAC, and TCP members were significantly correlated with the targeted metabolome. Coexpression analysis further confirmed that ABI5, PYL8, PYL4, and PP2C, which are vital ABA signaling elements, regulated GA3ox and GA20ox in the GA4 biosynthesis pathway, and XERICO may be involved in the regulation of ABA and GA4 signaling through the ubiquitination pathway. WRKY32, WRKY71, DAM14, NAC8, ICE1, bHLH93, and TCP15 also participated in the ABA/GA4 regulatory network, and ICE1 may be the key factor linking temperature signals and hormone metabolism. These results will help to reveal the bulb dormancy molecular mechanism and develop new strategies for high-quality bulb production.


Assuntos
Lilium , Regulação da Expressão Gênica de Plantas , Lilium/genética , Metabolômica , Dormência de Plantas , Sementes , Transcriptoma
18.
Anal Chem ; 93(33): 11415-11423, 2021 08 24.
Artigo em Inglês | MEDLINE | ID: mdl-34375078

RESUMO

Targeted, untargeted, and data-independent acquisition (DIA) metabolomics workflows are often hampered by ambiguous identification based on either MS1 information alone or relatively few MS2 fragment ions. While DIA methods have been popularized in proteomics, it is less clear whether they are suitable for metabolomics workflows due to their large precursor isolation windows and complex coisolation patterns. Here, we quantitatively investigate the conditions necessary for unique metabolite detection in complex backgrounds using precursor and fragment ion mass-to-charge (m/z) separation, comparing three benchmarked mass spectrometry (MS) methods [MS1, MRM (multiple reaction monitoring), and DIA]. Our simulations show that DIA outperformed MS1-only and MRM-based methods with regards to specificity by factors of ∼2.8-fold and ∼1.8-fold, respectively. Additionally, we show that our results are not dependent on the number of transitions used or the complexity of the background matrix. Finally, we show that collision energy is an important factor in unambiguous detection and that a single collision energy setting per compound cannot achieve optimal pairwise differentiation of compounds. Our analysis demonstrates the power of using both high-resolution precursor and high-resolution fragment ion m/z for unambiguous compound detection. This work also establishes DIA as an emerging MS acquisition method with high selectivity for metabolomics, outperforming both data-dependent acquisition (DDA) and MRM with regards to unique compound identification potential.


Assuntos
Metabolômica , Proteômica , Íons , Espectrometria de Massas , Fluxo de Trabalho
19.
Anal Chem ; 93(34): 11692-11700, 2021 08 31.
Artigo em Inglês | MEDLINE | ID: mdl-34403256

RESUMO

In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries, we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for compound-to-mass-spectrum prediction and also one of the top tools for in silico mass-spectrum-to-compound identification. This work improves CFM-ID's ability to predict ESI-MS/MS spectra from compounds by (1) learning parameters from features based on the molecular topology, (2) adding a new approach to ring cleavage that models such cleavage as a sequence of simple chemical bond dissociations, and (3) expanding its hand-written rule-based predictor to cover more chemical classes, including acylcarnitines, acylcholines, flavonols, flavones, flavanones, and flavonoid glycosides. We demonstrate that this new version of CFM-ID (version 4.0) is significantly more accurate than previous CFM-ID versions in terms of both EI-MS/MS spectral prediction and compound identification. CFM-ID 4.0 is available at http://cfmid4.wishartlab.com/ as a web server and docker images can be downloaded at https://hub.docker.com/r/wishartlab/cfmid.


Assuntos
Flavonas , Espectrometria de Massas em Tandem , Simulação por Computador , Metabolômica , Software
20.
Int J Mol Sci ; 22(16)2021 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-34445456

RESUMO

Flavonoids are representative secondary metabolites with different metabolic functions in plants. Previous study found that ectopic expression of EsMYB90 from Eutremasalsugineum could strongly increase anthocyanin content in transgenic tobacco via regulating the expression of anthocyanin biosynthesis genes. In the present research, metabolome analysis showed that there existed 130 significantly differential metabolites, of which 23 metabolites enhanced more than 1000 times in EsMYB90 transgenic tobacco leaves relative to the control, and the top 10 of the increased metabolites included caffeic acid, cyanidin O-syringic acid, myricetin and naringin. A total of 50 markedly differential flavonoids including flavones (14), flavonols (13), flavone C-glycosides (9), flavanones (7), catechin derivatives (5), anthocyanins (1) and isoflavone (1) were identified, of which 46 metabolites were at a significantly enhanced level. Integrated analysis of metabolome and transcriptome revealed that ectopic expression of EsMYB90 in transgenic tobacco leaves is highly associated with the prominent up-regulation of 16 flavonoid metabolites and the corresponding 42 flavonoid biosynthesis structure genes in phenylpropanoid/flavonoid pathways. Dual luciferase assay documented that EsMYB90 strongly activated the transcription of NtANS and NtDFR genes via improving their promoter activity in transiently expressed tobacco leaves, suggesting that EsMYB90 functions as a key regulator on anthocyanin and flavonoid biosynthesis. Taken together, the crucial regulatory role of EsMYB90 on enhancing many flavonoid metabolite levels is clearly demonstrated via modulating flavonoid biosynthesis gene expression in the leaves of transgenic tobacco, which extends our understanding of the regulating mechanism of MYB transcription factor in the phenylpropanoid/flavonoid pathways and provides a new clue and tool for further investigation and genetic engineering of flavonoid metabolism in plants.


Assuntos
Antocianinas , Brassicaceae/metabolismo , Perfilação da Expressão Gênica , Metabolômica , Proteínas de Plantas , Plantas Geneticamente Modificadas , Tabaco , Antocianinas/biossíntese , Antocianinas/genética , Brassicaceae/genética , Proteínas de Plantas/biossíntese , Proteínas de Plantas/genética , Plantas Geneticamente Modificadas/genética , Plantas Geneticamente Modificadas/metabolismo , Tabaco/genética , Tabaco/metabolismo
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