Untargeted Metabolite Profiling of Abalone Using Gas Chromatography Mass Spectrometry

Venter, Leonie; Rensburg, Peet Jansen van; Loots, Du Toit; Vosloo, André; Lindeque, Jeremie Zander

doi:10.1007/s12161-015-0285-5

Cited by 15 publications

(11 citation statements)

References 23 publications

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“…; Venter et al . ). Also, glucose‐6‐phosphate was successfully measured in the shell adductor and foot muscle of Haliotis lamellose (Gäde ), supporting glucose breakdown via glycolysis.…”

Section: Basic Metabolism and How We Apply It To Abalonementioning

confidence: 83%

“…Interestingly, a study performed by Venter et al . () showed comparatively low organic acids to be present in various GC‐MS analysed tissue samples of abalone, in comparison with their amino acid content, which is a rather unique occurrence, because these levels are usually very similar in other animal tissue samples analysed via the same approach (Lindeque et al . ).…”

Section: Basic Metabolism and How We Apply It To Abalonementioning

confidence: 97%

“…Enough evidence exists to suggest that glucose in abalone follows the traditional glycolysis route used in other organisms. A number of studies have focused on the quantification of glucose in abalone as summarised in Table 1 (Carefoot et al 2000;Braid et al 2005;Rosenblum et al 2005Rosenblum et al , 2006Laas & Vosloo 2010;Sheedy et al 2015;Zhou et al 2015;Venter et al 2016). Also, glucose-6-phosphate was successfully measured in the shell adductor and foot muscle of Haliotis lamellose (G€ ade 1988), supporting glucose breakdown via glycolysis.…”

Section: Carbohydrate Metabolismmentioning

confidence: 99%

“…It is important to note that the TCA cycle of abalone has as yet not been fully characterised, making this an important point for future research. Interestingly, a study performed by Venter et al (2016) showed comparatively low organic acids to be present in various GC-MS analysed tissue samples of abalone, in comparison with their amino acid content, which is a rather unique occurrence, because these levels are usually very similar in other animal tissue samples analysed via the same approach (Lindeque et al 2013). The fact that the TCA cycle intermediates in abalone are often below the detection limits of such analytical approaches supports the hypothesis that these animals make little use of mitochondrial metabolism and most likely have fewer than expected mitochondria per cell.…”

Section: Tricarboxylic Acid Cyclementioning

confidence: 99%

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Abalone growth and associated aspects: now from a metabolic perspective

Venter

Loots

Vosloo

et al. 2016

Reviews in Aquaculture

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Worldwide, there are approximately 100 Haliotis species, more commonly known as abalone or ‘Paua’ in New Zealand, ‘Venus's‐ears’ in Greece, ‘Awabi’ in Japan, ‘Perlemoen’ in South Africa and ‘Ormers’ in Europe. Regardless of what they are called in any part of the world, a high monetary value is coupled to this animal, because it is largely considered a seafood delicacy. Subsequently, a great deal of research primarily focused on improving the health and growth rates of abalone were carried out to maximise productivity of the commercial farming efforts in various countries. In this review, we comprehensively describe the most recent available scientific literature on abalone biology, and those aspects related to the growth of this organism; more specifically, those factors related to the uptake and breakdown of metabolic products which ensures long‐term growth. We subsequently discuss this in terms of basic animal design, farming outcomes, feeding, cellular growth mechanisms and the unique metabolic processes that exist in these species. Using this information and the knowledge of the metabolic processes in other organisms, we additionally make a number of new hypotheses regarding how these metabolic processes may function in terms of abalone growth. Based on the information presented in this review, we also identify major research opportunities and gaps in the existing knowledge of abalone metabolism, which when elucidated may not only serve the purpose of better understanding these organisms growth but also could potentially lead to increased productivity of the abalone commercial farming sector.

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Section: Basic Metabolism and How We Apply It To Abalonementioning

confidence: 83%

Section: Basic Metabolism and How We Apply It To Abalonementioning

confidence: 97%

Section: Carbohydrate Metabolismmentioning

confidence: 99%

Section: Tricarboxylic Acid Cyclementioning

confidence: 99%

See 2 more Smart Citations

Abalone growth and associated aspects: now from a metabolic perspective

Venter

Loots

Vosloo

et al. 2016

Reviews in Aquaculture

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“…It is a popular, suitable and fruitful method in generating metabolite fingerprints due to its high separation power, reproducible retention times, and selective mass detection (Castro-Puyana et al 2013, Venter et al 2016. When it comes to gas chromatographic determinations of carbohydrates in complex mixtures, such as plant flour extracts, trimethylsilyl-oxime derivatives of simple sugars proved to be very suitable for this kind of analysis, presenting good GC properties and providing relatively simple chromatograms.…”

mentioning

confidence: 99%

Relationship between GC/EI-qMS disaccharide profiles and corresponding genomes of wheat, rye and triticale cultivars

Pastor¹,

Ačanski²,

Vujić³

et al. 2017

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Summary:Cultivars of small grain species: wheat (Triticum aestivum), rye (Secale cereale) and triticale (Triticosecale) were selected because of their specific biochemical composition of carbohydrates for gas chromatographic analysis. Samples were grounded to flour and extracted with 96% ethanol solution. Extracted mono-and disaccharides were first derivatized into corresponding trimethylsilyl-oximes (TMSO) and analyzed on a GC/EI-qMS device. Four eluting peaks at specific retention times (18.57 min, 18.80 min, 20.85 min, and 21.39 min), were identified as trimethylsilyloximes of turanose, melibiose and two peaks of sucrose using Wiley 275 and NIST 14 mass spectra libraries, and were further selected as discrimination factors. Their presence/absence in certain small grain cultivar was labeled with 1/0 thus creating binary numerical matrices, introduced into multivariate analysis. Exploratory data analysis techniques were applied, thus providing a successful background for wheat, rye and triticale species differentiation, regardless of the specific cultivar they belong to, avoiding quantitative determinations of defined discrimination markers. Higher similarities between wheat and triticale cultivars, in comparison with rye species, may be due to the fact that most of the triticale genome structure originates from wheat species.

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