Identification of Low-Molecular-Weight Compounds in Goat Epididymis Using Multinuclear Nuclear Magnetic Resonance

Patel, Anant B.; Srivastava, Sudha; Phadke, Ratna S.; Govil, Girjesh

doi:10.1006/abio.1998.2888

Cited by 14 publications

(21 citation statements)

References 28 publications

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“…Before the NMR analysis, the samples were lyophilized and resuspended in deuterium oxide. Figure 1 shows the NMR proton spectrum of a human seminal plasma sample in D 2 O solution acquired at 600 MHz and 298 K. The assignment reported in detail in Table 1 was obtained by bidimensional NMR spectra (data not shown) according to previous papers [Gupta et al, 2011a,b;Averna et al 2005;Gupta et al 2013;Lynch et al 1994;Patel et al 1999;Seaglen et al 1995]. The enlarged signals at 7.18, 6.92, 6.89, and 6.75 ppm, marked with an asterisk in Figure 1, in the region of aromatic protons of phenylalanine, tyrosine, and histidine, show a characteristic line width broadening of proton resonances.…”

Section: Resultsmentioning

confidence: 99%

Discrimination of human semen specimens by NMR data, sperm parameters, and statistical analysis

Bonechi

Collodel

Donati

et al. 2015

Systems Biology in Reproductive Medicine

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Human seminal fluid is a complex mixture of secretions originated from epididymis and the male accessory sex glands. It contains a variety of both inorganic and organic components, among which proteins are a major part of the high molecular-mass substances. In this study, 83 human seminal plasma samples were analyzed using a combined Nuclear Magnetic Resonance (NMR) Spectroscopy and Principal Component Analysis (PCA) approach to discriminate patients in relation to semen characteristics and/or conditions affecting the fertility status. Results showed a discrimination between patients with leukocytospermia and with the concomitant presence of varicocele/ex varicocele and leukocytospermia. Patients with testicular cancer, necrozoospermia, and azoospermia were separated from the other patient clusters. In addition, a differentiation of semen quality was also possible. This study represents to first use of sperm parameters together with NMR data as variables in the PCA analysis. Furthermore, this methodology allows the identification of the metabolites which play the most important role in identifying differences among human seminal plasma samples.

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Section: Resultsmentioning

confidence: 99%

Discrimination of human semen specimens by NMR data, sperm parameters, and statistical analysis

Bonechi

Collodel

Donati

et al. 2015

Systems Biology in Reproductive Medicine

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“…3). In goat a high content of free amino acids was found in the ejaculate and the epididymal fluid, where these molecules could serve as chelating agents, in particular for toxic metals, and/or as oxidizable substrates for spermatozoa (Patel et al, 1998(Patel et al, , 1999. Amino acids could also serve as endogenous substrates in human sperm cells, but further studies are needed to validate this assumption.…”

Section: Discussionmentioning

confidence: 99%

“…contrast to the substantial proportion of proteins identified, so far a relatively small number of around 20 metabolites have been identified in sperm cells of different model species (Oliva et al, 1982;Patel et al, 1999;Dreanno et al, 2000;Jones & Bubb, 2000;Marin et al, 2003;Hung et al, 2009;Lin et al, 2009). This smaller number of metabolites is in part because of the fact that the number of metabolites in cells is much lower than that of proteins (Kouskoumvekaki & Panagiotou, 2011;Wishart et al, 2013).…”

Section: Introductionmentioning

confidence: 89%

“…Metabolomic studies have been performed in sperm cells from different species, such as goat (Patel et al, 1998(Patel et al, , 1999, boar (Jones & Bubb, 2000;Marin et al, 2003), turbot (Dreanno et al, 2000) and rhesus macaque Lin et al, 2009). Rat testicular tissue (Griffin et al, 2000) and human seminal plasma have also been subjected to metabolomic analyses (Hamamah et al, 1993;Gupta et al, 2011aGupta et al, ,b, 2013.…”

Section: Introductionmentioning

confidence: 99%

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Identification of endogenous metabolites in human sperm cells using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS)

et al. 2015

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SUMMARYThe objective of this study was to contribute to the first comprehensive metabolomic characterization of the human sperm cell through the application of two untargeted platforms based on proton nuclear magnetic resonance ( 1 H-NMR) spectroscopy and gas chromatography coupled to mass spectrometry (GC-MS). Using these two complementary strategies, we were able to identify a total of 69 metabolites, of which 42 were identified using NMR, 27 using GC-MS and 4 by both techniques. The identity of some of these metabolites was further confirmed by two-dimensional C heteronuclear single-quantum correlation (HSQC) spectroscopy. Most of the metabolites identified are reported here for the first time in mature human spermatozoa. The relationship between the metabolites identified and the previously reported sperm proteome was also explored. Interestingly, overrepresented pathways included not only the metabolism of carbohydrates, but also of lipids and lipoproteins. Of note, a large number of the metabolites identified belonged to the amino acids, peptides and analogues super class. The identification of this initial set of metabolites represents an important first step to further study their function in male gamete physiology and to explore potential reasons for dysfunction in future studies. We also demonstrate that the application of NMR and MS provides complementary results, thus constituting a promising strategy towards the completion of the human sperm cell metabolome.

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“…The assignments of metabolites in the [ 13 C, 1 H] HSQC spectra were made by comparing the carbon and proton chemical shifts with literature values (Gribbestad et al 1994(Gribbestad et al , 1999Pal et al 2005;Patel et al 1999;Sharma et al 2003Sharma et al , 2004, by comparison with spectra of authentic compounds and by spiking the samples. A homonuclear two-dimensional total correlation spectrum (TOCSY; 75 ms of mixing time) was also recorded for the assignments of 1 H resonances.…”

Section: Identification and Quantification Of Metabolites In Nmr Spectramentioning

confidence: 99%

Profiling of central metabolism in human cancer cells by two-dimensional NMR, GC-MS analysis, and isotopomer modeling

et al. 2007

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Tracking metabolic profiles has the potential to reveal crucial enzymatic steps that could be targeted in the drug discovery process. It is of special importance for various types of cancer known to be associated with substantial rewiring of metabolic networks. Here we introduce an integrated approach for the analysis of metabolome that allows us to simultaneously assess pathway activities (fluxes) and concentrations of a large number of the key components involved in central metabolism of human cells. This is accomplished by in vivo labeling with [U-13 C]glucose followed by two-dimensional nuclear magnetic resonance (NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) analysis. A comprehensive isotopomer model was developed, which enabled us to compare fluxes through the key central metabolic pathways including glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, anaplerotic reactions, and biosynthetic pathways of fatty acids and amino acids. The validity and strength of this approach is illustrated by its application to a number of perturbations to breast cancer cells, including exposure to hypoxia, drug treatment, and tumor progression. We observed significant differences in the activities of specific metabolic pathways resulting from these perturbations and providing new mechanistic insights. Based on these findings we conclude that the developed metabolomic approach constitutes a promising analytical tool for revealing specific metabolic phenotypes in a variety of cell types and pathological conditions.

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Identification of Low-Molecular-Weight Compounds in Goat Epididymis Using Multinuclear Nuclear Magnetic Resonance

Cited by 14 publications

References 28 publications

Discrimination of human semen specimens by NMR data, sperm parameters, and statistical analysis

Discrimination of human semen specimens by NMR data, sperm parameters, and statistical analysis

Identification of endogenous metabolites in human sperm cells using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS)

Profiling of central metabolism in human cancer cells by two-dimensional NMR, GC-MS analysis, and isotopomer modeling

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Identification of Low-Molecular-Weight Compounds in Goat Epididymis Using Multinuclear Nuclear Magnetic Resonance

Cited by 14 publications

References 28 publications

Discrimination of human semen specimens by NMR data, sperm parameters, and statistical analysis

Discrimination of human semen specimens by NMR data, sperm parameters, and statistical analysis

Identification of endogenous metabolites in human sperm cells using proton nuclear magnetic resonance (1H-NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS)

Profiling of central metabolism in human cancer cells by two-dimensional NMR, GC-MS analysis, and isotopomer modeling

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Identification of endogenous metabolites in human sperm cells using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS)