Identification of the high-yield monacolin K strain from Monascus spp. and its submerged fermentation using different medicinal plants

Metabolites of intestinal fora can be used as diagnostic and progressive markers for mild cognitive impairment

Purpose

The aim of the work was to analyze the metabolites of the intestinal microbiota from the patients with mild cognitive impairment (MCI) and progressive MCI due to Alzheimer's disease (AD).

Method

Two cohorts were established. The first one included 87 subjects with 30 healthy controls (NC), 22 patients with MCI due to AD, and 35 patients with AD. The second cohort included 87 patients with MCI due to AD, who were followed up for 2 years and finally were divided into progressive MCI due to AD group (P-G) and unprogressive MCI due to AD group (U-G) according their cognitive levels. Fecal samples were collected to all patients at the baseline time point. Differential metabolites were subjected to pathway analysis by MetaboAnalyst.

Results

In the first cohort, we found 21 different metabolites among the three groups (AD, MCI, and NC). In the second cohort, we identified 19 differential metabolites between the P-G and U-G groups. By machine learning analysis, we found that seven characteristic metabolites [Erythrodiol, alpha-Curcumene, Synephrine, o-Hydroxylaminobenzoate, 3-Amino-4-hydroxybenzoic acid, 2-Deoxystreptamine, and 9(S] were of characteristic significance for the diagnosis of MCI due to AD, and six metabolites (Indolelactate, Indole-3-acetaldehyde, L-Proline, Perillyl, Mesaconate, and Sphingosine) were the characteristic metabolites of early warning for the progression of MCI due to AD. D-Glucuronic acid was negatively correlated with Apolipoprotein E4 (APOE4). Perillyl alcohol was negatively correlated with all of the five biomarkers [P-tau181, Neurofilament light chain (NF-light), Aβ1-42, Aβ1-40, and glial fibrillary acidic protein (GFAP)], but Indoleacetaldehyde was positively correlated with three biomarkers (P-tau181, Aβ1-42, and GFAP). Three characteristic metabolites (3-Amino-4-hydroxybenzoate, 2-Deoxystreptamine, and p-Synephrine) were positively correlated with Aβ1-42. 2-Deoxystreptamine, 9(S)-HPOT, and Indoleacetaldehyde were positively correlated with GFAP. L-Proline and Indoleacetaldehyde were positively correlated with NF-light.

Conclusion

Specific metabolites of intestinal fora can be used as diagnostic and progressive markers for MCI.

Whole genome sequence characterization of Aspergillus terreus ATCC 20541 and genome comparison of the fungi A. terreus

Aspergillus terreus is well-known for lovastatin and itaconic acid production with biomedical and commercial importance. The mechanisms of metabolite formation have been extensively studied to improve their yield through genetic engineering. However, the combined repertoire of carbohydrate-active enzymes (CAZymes), cytochrome P450s (CYP) enzymes, and secondary metabolites (SMs) in the different A. terreus strains has not been well studied yet, especially with respect to the presence of biosynthetic gene clusters (BGCs). Here we present a 30 Mb whole genome sequence of A. terreus ATCC 20541 in which we predicted 10,410 protein-coding genes. We compared the CAZymes, CYPs enzyme, and SMs across eleven A. terreus strains, and the results indicate that all strains have rich pectin degradation enzyme and CYP52 families. The lovastatin BGC of lovI was linked with lovF in A. terreus ATCC 20541, and the phenomenon was not found in the other strains. A. terreus ATCC 20541 lacked a non-ribosomal peptide synthetase (AnaPS) participating in acetylaszonalenin production, which was a conserved protein in the ten other strains. Our results present a comprehensive analysis of CAZymes, CYPs enzyme, and SM diversities in A. terreus strains and will facilitate further research in the function of BGCs associated with valuable SMs.