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1.
2.

Introduction

Breast cancer is the most frequent diagnosed cancer among women with a mortality rate of 15% of all cancer related deaths in women. Breast cancer is heterogeneous in nature and produces plethora of metabolites allowing its early detection using molecular diagnostic techniques like magnetic resonance spectroscopy.

Objectives

To evaluate the variation in metabolic profile of breast cancer focusing on lipids as triglycerides (TG) and free fatty acids (FFA) that may alter in malignant breast tissues and lymph nodes from adjacent benign breast tissues by HRMAS 1H NMR spectroscopy.

Methods

The 1H NMR spectra recorded on 173 tissue specimens comprising of breast tumor tissues, adjacent tissues, few lymph nodes and overlying skin tissues obtained from 67 patients suffering from breast cancer. Multivariate statistical analysis was employed to identify metabolites acting as major confounders for differentiation of malignancy.

Result

Reduction in lipid content were observed in malignant breast tissues along with a higher fraction of FFA. Four small molecule metabolites e.g., choline containing compounds (Chocc), taurine, glycine, and glutamate were also identified as major confounders. The test set for prediction provided sensitivity and specificity of more than 90% excluding the lymph nodes and skin tissues.

Conclusion

Fatty acids composition in breast cancer using in vivo magnetic resonance spectroscopy (MRS) is gaining its importance in clinical settings (Coum et al. in Magn Reson Mater Phys Biol Med 29:1–4, 2016). The present study may help in future for precise evaluation of lipid classification including small molecules as a source of early diagnosis of invasive ductal carcinoma by employing in vivo magnetic resonance spectroscopic methods.
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3.

Introduction

Adoption of automatic profiling tools for 1H-NMR-based metabolomic studies still lags behind other approaches in the absence of the flexibility and interactivity necessary to adapt to the properties of study data sets of complex matrices.

Objectives

To provide an open source tool that fully integrates these needs and enables the reproducibility of the profiling process.

Methods

rDolphin incorporates novel techniques to optimize exploratory analysis, metabolite identification, and validation of profiling output quality.

Results

The information and quality achieved in two public datasets of complex matrices are maximized.

Conclusion

rDolphin is an open-source R package (http://github.com/danielcanueto/rDolphin) able to provide the best balance between accuracy, reproducibility and ease of use.
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4.

Introduction

Human arylamine N-acetyltransferase 1 (NAT1) is a phase II xenobiotic metabolizing enzyme found in almost all tissues. Expression of NAT1 is elevated in several cancers including breast cancer. However, the exact mechanism by which NAT1 expression affects cancer risk and progression remains unclear.

Objective

This study explored polar metabolome differences between MDA-MB-231 breast cancer cells expressing varying levels of NAT1 activity using an untargeted approach.

Methods

Three MDA-MB-231 breast adenocarcinoma cell lines that stably express wild-type, increased, and decreased levels of human NAT1 were investigated for differences in polar metabolic profile using a comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) system.

Results

Increased levels of human NAT1 in the transformed cell lines resulted in a statistically significant decreased abundance of the metabolite palmitoleic acid (q = 0.0006), when compared to normal and decreased levels of human NAT1. The fatty acid synthesis pathway utilizes acetyl coenzyme A (acetyl-CoA) in the first two reactions of the pathway and eventually leads to the synthesis of palmitoleic acid.

Conclusion

These data suggest a link between increased levels of NAT1 activity and decreased flux of acetyl-CoA through this portion of the fatty acid synthesis pathway.
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5.

Introduction

Metabolite identification in biological samples using Nuclear Magnetic Resonance (NMR) spectra is a challenging task due to the complexity of the biological matrices.

Objectives

This paper introduces a new, automated computational scheme for the identification of metabolites in 1D 1H NMR spectra based on the Human Metabolome Database.

Methods

The methodological scheme comprises of the sequential application of preprocessing, data reduction, metabolite screening and combination selection.

Results

The proposed scheme has been tested on the 1D 1H NMR spectra of: (a) an amino acid mixture, (b) a serum sample spiked with the amino acid mixture, (c) 20 blood serum, (d) 20 human amniotic fluid samples, (e) 160 serum samples from publicly available database. The methodological scheme was compared against widely used software tools, exhibiting good performance in terms of correct assignment of the metabolites.

Conclusions

This new robust scheme accomplishes to automatically identify peak resonances in 1H-NMR spectra with high accuracy and less human intervention with a wide range of applications in metabolic profiling.
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6.

Introduction

The differences in fecal metabolome between ankylosing spondylitis (AS)/rheumatoid arthritis (RA) patients and healthy individuals could be the reason for an autoimmune disorder.

Objectives

The study explored the fecal metabolome difference between AS/RA patients and healthy controls to clarify human immune disturbance.

Methods

Fecal samples from 109 individuals (healthy controls 34, AS 40, and RA 35) were analyzed by 1H NMR spectroscopy. Data were analyzed with principal component analysis (PCA) and orthogonal projection to latent structure discriminant (OPLS-DA) analysis.

Results

Significant differences in the fecal metabolic profiles could distinguish AS/RA patients from healthy controls but could not distinguish between AS and RA patients. The significantly decreased metabolites in AS/RA patients were butyrate, propionate, methionine, and hypoxanthine. Significantly increased metabolites in AS/RA patients were taurine, methanol, fumarate, and tryptophan.

Conclusion

The metabolome variations in feces indicated AS and RA were two homologous diseases that could not be distinguished by 1H NMR metabolomics.
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7.

Objectives

To develop a new vector for constitutive expression in Pichia pastoris based on the endogenous glycolytic PGK1 promoter.

Results

P. pastoris plasmids bearing at least 415 bp of PGK1 promoter sequences can be used to drive plasmid integration by addition at this locus without affecting cell growth. Based on this result, a new P. pastoris integrative vector, pPICK2, was constructed bearing some features that facilitate protein production in this yeast: a ~620 bp PGK1 promoter fragment with three options of restriction sites for plasmid linearization prior to yeast transformation: a codon-optimized α-factor secretion signal, a new polylinker, and the kan marker for vector propagation in bacteria and selection of yeast transformants.

Conclusions

A new constitutive vector for P. pastoris represents an alternative platform for recombinant protein production and metabolic engineering purposes.
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8.

Objective

To develop an efficient synthetic promoter library for fine-tuned expression of target genes in Corynebacterium glutamicum.

Results

A synthetic promoter library for C. glutamicum was developed based on conserved sequences of the ??10 and ??35 regions. The synthetic promoter library covered a wide range of strengths, ranging from 1 to 193% of the tac promoter. 68 promoters were selected and sequenced for correlation analysis between promoter sequence and strength with a statistical model. A new promoter library was further reconstructed with improved promoter strength and coverage based on the results of correlation analysis. Tandem promoter P70 was finally constructed with increased strength by 121% over the tac promoter. The promoter library developed in this study showed a great potential for applications in metabolic engineering and synthetic biology for the optimization of metabolic networks.

Conclusions

To the best of our knowledge, this is the first reconstruction of synthetic promoter library based on statistical analysis of C. glutamicum.
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9.

Objective

To construct a promoter probe vector, pBE-bgaB, to screen strong promoters from Bacillus amyloliquefaciens.

Results

266 colonies containing active promoter elements from the genomic DNA of B. amyloliquefaciens were identified. Among these, promoter P41 exhibited the strongest β-Gal activity in Escherichia coli and B. amyloliquefaciens. Sequence analysis showed that promoter P41 contained P ykuN , a ykuN gene encoding flavodoxin. Optimization of the ribosome-binding site from P41 to P382 improved β-Gal activity by ~ 200%.

Conclusion

A new strong promoter for protein expression and genetic engineering of Bacillus species.
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10.

Background

The protein encoded by the gene ybgI was chosen as a target for a structural genomics project emphasizing the relation of protein structure to function.

Results

The structure of the ybgI protein is a toroid composed of six polypeptide chains forming a trimer of dimers. Each polypeptide chain binds two metal ions on the inside of the toroid.

Conclusion

The toroidal structure is comparable to that of some proteins that are involved in DNA metabolism. The di-nuclear metal site could imply that the specific function of this protein is as a hydrolase-oxidase enzyme.
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11.

Background

Recent studies showed that long non-coding RNA (lncRNA) plays an important role in many life activities. RPPH1 is one of the lncRNA genes that are expressed differently between breast cancer and normal tissues by the lncRNA gene chip. Our study was conducted to examine the regulation of lncRNA RPPH1 in breast cancer.

Methods

Two cell lines, MCF-7 and MDA-MB-231, were selected to be the research objects in this study; RPPH1 overexpression and knockdown models were established by transforming vectors. Real-time polymerase chain reaction, MTT assay, clone formation and cell flow cytometer assay were used to test the function of RPPH1. Dual-luciferase assay was used to detect a target relationship between RPPH1 and miR-122.

Results

RPPH1 overexpression promoted cell cycle and proliferation and increased colony formation. In the RPPH1 overexpression model, there was a target relationship between RPPH1 and miR-122, and some of the downstream genes of miR-122, including ADAM10, PKM2, NOD2 and IGF1R, were increased. Moreover, we found that lentivirus-mediated interference of lncRNA RPPH1 inhibited tumour growth in nude mice.

Conclusion

Breast cancer progression can be promoted by directly targeting miR-122 through lncRNA RPPH1. This study provided evidence that can serve as the molecular basis for improving treatment options for patients.
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12.

Introduction

Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.

Objective

To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.

Methods

Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.

Results

Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.

Conclusion

Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.
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13.

Introduction

Although it is still at a very early stage compared to its mass spectrometry (MS) counterpart, proton nuclear magnetic resonance (NMR) lipidomics is worth being investigated as an original and complementary solution for lipidomics. Dedicated sample preparation protocols and adapted data acquisition methods have to be developed to set up an NMR lipidomics workflow; in particular, the considerable overlap observed for lipid signals on 1D spectra may hamper its applicability.

Objectives

The study describes the development of a complete proton NMR lipidomics workflow for application to serum fingerprinting. It includes the assessment of fast 2D NMR strategies, which, besides reducing signal overlap by spreading the signals along a second dimension, offer compatibility with the high-throughput requirements of food quality characterization.

Method

The robustness of the developed sample preparation protocol is assessed in terms of repeatability and ability to provide informative fingerprints; further, different NMR acquisition schemes—including classical 1D, fast 2D based on non-uniform sampling or ultrafast schemes—are evaluated and compared. Finally, as a proof of concept, the developed workflow is applied to characterize lipid profiles disruption in serum from β-agonists diet fed pigs.

Results

Our results show the ability of the workflow to discriminate efficiently sample groups based on their lipidic profile, while using fast 2D NMR methods in an automated acquisition framework.

Conclusion

This work demonstrates the potential of fast multidimensional 1H NMR—suited with an appropriate sample preparation—for lipidomics fingerprinting as well as its applicability to address chemical food safety issues.
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14.

Introduction

Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients.

Objectives

We performed 1H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC.

Methods

1H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n?=?40), LNM-negative GC patients (n?=?40) and normal controls (n?=?40).

Results

There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM.

Conclusion

To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.
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15.

Introduction

Aqueous–methanol mixtures have successfully been applied to extract a broad range of metabolites from plant tissue. However, a certain amount of material remains insoluble.

Objectives

To enlarge the metabolic compendium, two ionic liquids were selected to extract the methanol insoluble part of trunk from Betula pendula.

Methods

The extracted compounds were analyzed by LC/MS and GC/MS.

Results

The results show that 1-butyl-3-methylimidazolium acetate (IL-Ac) predominantly resulted in fatty acids, whereas 1-ethyl-3-methylimidazolium tosylate (IL-Tos) mostly yielded phenolic structures. Interestingly, bark yielded more ionic liquid soluble metabolites compared to interior wood.

Conclusion

From this one can conclude that the application of ionic liquids may expand the metabolic snapshot.
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16.

Introduction

Botanicals containing iridoid and phenylethanoid/phenylpropanoid glycosides are used worldwide for the treatment of inflammatory musculoskeletal conditions that are primary causes of human years lived with disability, such as arthritis and lower back pain.

Objectives

We report the analysis of candidate anti-inflammatory metabolites of several endemic Scrophularia species and Verbascum thapsus used medicinally by peoples of North America.

Methods

Leaves, stems, and roots were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and partial least squares-discriminant analysis (PLS-DA) was performed in MetaboAnalyst 3.0 after processing the datasets in Progenesis QI.

Results

Comparison of the datasets revealed significant and differential accumulation of iridoid and phenylethanoid/phenylpropanoid glycosides in the tissues of the endemic Scrophularia species and Verbascum thapsus.

Conclusions

Our investigation identified several species of pharmacological interest as good sources for harpagoside and other important anti-inflammatory metabolites.
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17.
18.

Introduction

Experiments in metabolomics rely on the identification and quantification of metabolites in complex biological mixtures. This remains one of the major challenges in NMR/mass spectrometry analysis of metabolic profiles. These features are mandatory to make metabolomics asserting a general approach to test a priori formulated hypotheses on the basis of exhaustive metabolome characterization rather than an exploratory tool dealing with unknown metabolic features.

Objectives

In this article we propose a method, named ASICS, based on a strong statistical theory that handles automatically the metabolites identification and quantification in proton NMR spectra.

Methods

A statistical linear model is built to explain a complex spectrum using a library containing pure metabolite spectra. This model can handle local or global chemical shift variations due to experimental conditions using a warping function. A statistical lasso-type estimator identifies and quantifies the metabolites in the complex spectrum. This estimator shows good statistical properties and handles peak overlapping issues.

Results

The performances of the method were investigated on known mixtures (such as synthetic urine) and on plasma datasets from duck and human. Results show noteworthy performances, outperforming current existing methods.

Conclusion

ASICS is a completely automated procedure to identify and quantify metabolites in 1H NMR spectra of biological mixtures. It will enable empowering NMR-based metabolomics by quickly and accurately helping experts to obtain metabolic profiles.
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19.

Objectives

To enhance the efficiency of influenza virosome-mediated gene delivery by engineering this virosome.

Results

A novel chimeric influenza virosome was constructed containing the glycoprotein of Vesicular stomatitis virus (VSV-G), along with its own hemagglutinin protein. To optimize the transfection efficiency of both chimeric and influenza cationic virosomes, HEK cells were transfected with plasmid DNA and virosomes and the transfection efficiency was assessed by FACS analysis. The chimeric virosome was significantly more efficient in mediating transfection for all amounts of DNA and virosomes compared to the influenza virosome.

Conclusions

Chimeric influenza virosome, including VSV-G, is superior to the conventional influenza virosome for gene delivery.
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20.

Introduction

Fish feed formulations are constantly evolving to improve the quality of diets for farmed fish and to ensure the sustainability of the aquaculture sector. Nowadays, insect, microalgae and yeast are feedstuff candidates for new feeds. However, the characterization of aquafeed is still based on proximate and targeted analyses which may not be sufficient to assess feed quality.

Objectives

Our aim was to highlight the soluble compounds that specifically differ between selected plant-based feeds complemented with alternative feedstuffs and discuss their origin and potential for fish nutrition.

Methods

A growth trial was carried out to evaluate growth performances and feed conversion ratios of fish fed plant-based, commercial, insect, spirulina and yeast feeds. 1H NMR metabolomics profiling of each feed was performed using a CPMG sequence on polar extracts. Spectra were processed, and data were analyzed using multivariate and univariate analyses to compare alternative feeds to a plant-based feed.

Results

Fish fed insect or yeast feed showed the best growth performances associated with the lowest feed conversion ratios compared to plant-based feed. Soluble compound 1H NMR profiles of insect and spirulina alternative feeds differed significantly from the plant-based one that clustered with yeast feed. In insect and spirulina feeds, specific differences compared to plant-based feed concerned glycerol and 3-hydroxybutyrate, respectively.

Conclusion

This strategy based on compositional differences between plant-based and alternative feeds can be useful for detecting compounds unsuspected until now that could impact fish metabolism.
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