Non-oxidative and oxidative degradation of d-galacturonic acid with alkali

Niemelä, Klaus; Sjöström, Eero

doi:10.1016/0008-6215(85)85010-2

Cited by 17 publications

(8 citation statements)

References 18 publications

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“…Compound 2 then undergoes a 1,2-hydride transfer similar to the benzylic acid rearrangement to produce 3-deoxy- d - xylo -hexarate or 3-deoxy- d - lyxo -hexarate (Figure 11 , compound 3 ). 21 The mechanism of this reaction was not investigated.…”

Section: Results and Discussionmentioning

confidence: 99%

Evolution of Enzymatic Activities in the Enolase Superfamily: Galactarate Dehydratase III from Agrobacterium tumefaciens C58

et al. 2014

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The genome of Agrobacterium tumefaciens C58 encodes 12 members of the enolase superfamily (ENS), eight of which are members of the mandelate racemase (MR) subgroup and, therefore, likely to be acid sugar dehydratases. Using a library of 77 acid sugars for high-throughput screening, one protein (UniProt entry A9CG74; locus tag Atu4196) showed activity with both m-galactarate and d-galacturonate. Two families of galactarate dehydratases had been discovered previously in the ENS, GalrD/TalrD [Yew, W. S., et al. (2007) Biochemistry46, 9564–9577] and GalrD-II [Rakus, J. F., et al. (2009) Biochemistry48, 11546–11558]; these have different active site acid/base catalysis and have no activity with d-galacturonate. A9CG74 dehydrates m-galactarate to form 2-keto-3-deoxy-galactarate but does not dehydrate d-galacturonate as expected. Instead, when A9CG74 is incubated with d-galacturonate, 3-deoxy-d-xylo-hexarate or 3-deoxy-d-lyxo-hexarate is formed. In this reaction, instead of abstracting the C5 proton α to the carboxylate group, the expected reaction for a member of the ENS, the enzyme apparently abstracts the proton α to the aldehyde group to form 3-deoxy-d-threo-hexulosuronate that undergoes a 1,2-hydride shift similar to the benzylic acid rearrangement to form the observed product. A. tumefaciens C58 does not utilize m-galactarate as a carbon source under the conditions tested in this study, although it does utilize d-galacturonate, which is a likely precursor to m-galactarate. The gene encoding A9CG74 and several genome proximal genes were upregulated with d-galacturonate as the carbon source. One of these, a member of the dihydrodipicolinate synthase superfamily, catalyzes the dehydration and subsequent decarboxylation of 2-keto-3-deoxy-d-galactarate to α-ketoglutarate semialdehyde, thereby providing a pathway for the conversion of m-galactarate to α-ketoglutarate semialdehyde.

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Section: Results and Discussionmentioning

confidence: 99%

Evolution of Enzymatic Activities in the Enolase Superfamily: Galactarate Dehydratase III from Agrobacterium tumefaciens C58

et al. 2014

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“… 61 Very scarce data is available on the biochemistry of 2,4-dihydroxybutanoic acid. In one report, this metabolite was overproduced under low oxygen conditions from D-galacturonic acid, 63 a uronic acid, which is a stereoisomer of glucoronic acid. Concentration of glucoronic acid was decreased at a marginal significance level in the P-MCI group in our study ( P =0.10).…”

Section: Discussionmentioning

confidence: 99%

Metabolome in progression to Alzheimer's disease

et al. 2011

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Mild cognitive impairment (MCI) is considered as a transition phase between normal aging and Alzheimer's disease (AD). MCI confers an increased risk of developing AD, although the state is heterogeneous with several possible outcomes, including even improvement back to normal cognition. We sought to determine the serum metabolomic profiles associated with progression to and diagnosis of AD in a prospective study. At the baseline assessment, the subjects enrolled in the study were classified into three diagnostic groups: healthy controls (n=46), MCI (n=143) and AD (n=47). Among the MCI subjects, 52 progressed to AD in the follow-up. Comprehensive metabolomics approach was applied to analyze baseline serum samples and to associate the metabolite profiles with the diagnosis at baseline and in the follow-up. At baseline, AD patients were characterized by diminished ether phospholipids, phosphatidylcholines, sphingomyelins and sterols. A molecular signature comprising three metabolites was identified, which was predictive of progression to AD in the follow-up. The major contributor to the predictive model was 2,4-dihydroxybutanoic acid, which was upregulated in AD progressors (P=0.0048), indicating potential involvement of hypoxia in the early AD pathogenesis. This was supported by the pathway analysis of metabolomics data, which identified upregulation of pentose phosphate pathway in patients who later progressed to AD. Together, our findings primarily implicate hypoxia, oxidative stress, as well as membrane lipid remodeling in progression to AD. Establishment of pathogenic relevance of predictive biomarkers such as ours may not only facilitate early diagnosis, but may also help identify new therapeutic avenues.

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“…If, for example, we consider an alkaline extraction of seaweeds, alginates will be partially converted to carboxylic acids ( Niemela and Sjostrom, 1985 ) and their identification and quantification can be carried out by GC-MS; during the same extraction procedure, polyphenols, such as phloroethols, will be rearranged as complex dibenzofurans ( Ragan and Glombitza, 1986 ), and HPLC-DAD will be a good analytical tool to separate, qualitatively identify and quantify them against a suitable internal standard. Fucoidans will undergo hydrolysis in oligomers and constituent sugars.…”

Section: From Raw Materials To Biostimulants: a Step-by-step Procedurmentioning

confidence: 99%

A Systematic Approach to Discover and Characterize Natural Plant Biostimulants

Povero¹,

Mejía²,

Tommaso³

et al. 2016

Front. Plant Sci.

141

100

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The use of natural plant biostimulants is proposed as an innovative solution to address the challenges to sustainable agriculture, to ensure optimal nutrient uptake, crop yield, quality, and tolerance to abiotic stress. However, the process of selection and characterization of plant biostimulant matrices is complex and involves a series of rigorous evaluations customized to the needs of the plant. Here, we propose a highly differentiated plant biostimulant development and production platform, which involves a combination of technology, processes, and know-how. Chemistry, biology and omic concepts are combined/integrated to investigate and understand the specific mode(s) of action of bioactive ingredients. The proposed approach allows to predict and characterize the function of natural compounds as biostimulants. By managing and analyzing massive amounts of complex data, it is therefore possible to discover, evaluate and validate new product candidates, thus expanding the uses of existing products to meet the emerging needs of agriculture.

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Non-oxidative and oxidative degradation of d-galacturonic acid with alkali

Cited by 17 publications

References 18 publications

Evolution of Enzymatic Activities in the Enolase Superfamily: Galactarate Dehydratase III from Agrobacterium tumefaciens C58

Evolution of Enzymatic Activities in the Enolase Superfamily: Galactarate Dehydratase III from Agrobacterium tumefaciens C58

Metabolome in progression to Alzheimer's disease

A Systematic Approach to Discover and Characterize Natural Plant Biostimulants

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