Two rapid assays for screening of patulin biodegradation

Artículo sobre distintos ensayos para comprobar la biodegradación de la patulinaThe mycotoxin patulin is produced by the blue mould pathogen Penicillium expansum in rotting apples during postharvest storage. Patulin is toxic to a wide range of organisms, including humans, animals, fungi and bacteria. Wash water from apple packing and processing houses often harbours patulin and fungal spores, which can contaminate the environment. Ubiquitous epiphytic yeasts, such as Rhodosporidium kratochvilovae strain LS11 which is a biocontrol agent of P. expansum in apples, have the capacity to resist the toxicity of patulin and to biodegrade it. Two non-toxic products are formed. One is desoxypatulinic acid. The aim of the work was to develop rapid, high-throughput bioassays for monitoring patulin degradation in multiple samples. Escherichia coli was highly sensitive to patulin, but insensitive to desoxypatulinic acid. This was utilized to develop a detection test for patulin, replacing time-consuming thin layer chromatography or high-performance liquid chromatography. Two assays for patulin degradation were developed, one in liquid medium and the other in semi-solid medium. Both assays allow the contemporary screening of a large number of samples. The liquid medium assay utilizes 96-well microtiter plates and was optimized for using a minimum of patulin. The semisolid medium assay has the added advantage of slowing down the biodegradation, which allows the study and isolation of transient degradation products. The two assays are complementary and have several areas of utilization, from screening a bank of microorganisms for biodegradation ability to the study of biodegradation pathways

Metabolomics and Age-Related Macular Degeneration

Age-related macular degeneration (AMD) leads to irreversible visual loss, therefore, early intervention is desirable, but due to its multifactorial nature, diagnosis of early disease might be challenging. Identification of early markers for disease development and progression is key for disease diagnosis. Suitable biomarkers can potentially provide opportunities for clinical intervention at a stage of the disease when irreversible changes are yet to take place. One of the most metabolically active tissues in the human body is the retina, making the use of hypothesis-free techniques, like metabolomics, to measure molecular changes in AMD appealing. Indeed, there is increasing evidence that metabolic dysfunction has an important role in the development and progression of AMD. Therefore, metabolomics appears to be an appropriate platform to investigate disease-associated biomarkers. In this review, we explored what is known about metabolic changes in the retina, in conjunction with the emerging literature in AMD metabolomics research. Methods for metabolic biomarker identification in the eye have also been discussed, including the use of tears, vitreous, and aqueous humor, as well as imaging methods, like fluorescence lifetime imaging, that could be translated into a clinical diagnostic tool with molecular level resolution

Integrating metabolomics, genomics and disease pathways in age-related macular degeneration: The EYE-RISK Consortium

Objective In the current study we aimed to identify metabolites associated with age-related macular degeneration (AMD) by performing the largest metabolome association analysis in AMD to date. In addition, we aimed to determine the effect of AMD-associated genetic variants on metabolite levels, and aimed to investigate associations between the identified metabolites and activity of the complement system, one of the main AMD-associated disease pathways. Design Case-control assocation analysis of metabolomics data. Subjects 2,267 AMD cases and 4,266 controls from five European cohorts. Methods Metabolomics was performed using a high-throughput H-NMR metabolomics platform, which allows the quantification of 146 metabolite measurements and 79 derivative values. Metabolome-AMD associations were studied using univariate logistic regression analyses. The effect of 52 AMD-associated genetic variants on the identified metabolites was investigated using linear regression. In addition, associations between the identified metabolites and activity of the complement pathway (defined by the C3d/C3 ratio) were investigated using linear regression. Main Outcome Measures Metabolites associated with AMD Results We identified 60 metabolites that were significantly associated with AMD, including increased levels of large and extra-large HDL subclasses and decreased levels of VLDL, amino acids and citrate. Out of 52 AMD-associated genetic variants, seven variants were significantly associated with 34 of the identified metabolites. The strongest associations were identified for genetic variants located in or near genes involved in lipid metabolism (ABCA1, CETP, APOE, LIPC) with metabolites belonging to the large and extra-large HDL subclasses. In addition, 57 out of 60 metabolites were significantly associated with complement activation levels, and these associations were independent of AMD status. Increased large and extra-large HDL levels and decreased VLDL and amino acid levels were associated with increased complement activation. Conclusions Lipoprotein levels were associated with AMD-associated genetic variants, while decreased essential amino acids may point to nutritional deficiencies in AMD. We observed strong associations between the vast majority of the AMD-associated metabolites and systemic complement activation levels, independent of AMD status. This may indicate biological interactions between the main AMD disease pathways, and suggests that multiple pathways may need to be targeted simultaneously for successful treatment of AMD. Abbreviations AMDAge-related macular degenerationGWASGenome-wide association studyHDLHigh density lipoproteinVLDLVery low density lipoproteinNMRNuclear magnetic resonanceACMEAverage casual effect estimatesOROdds ratiopFDRFalse discovery rate corrected p-valueCIConfindence intervalCVDCardiovascular diseasesPCAPrincipal component analysisSDStandard deviationBMIBody mass indexFDRFalse discovery rateEUGENDAEuropean Genetic DatabaseRSRotterdam StudyALIENORAntioxydants, LIpides Essentiels, Nutrition et maladies OculaiResCORRBICombined Ophthalmic Research Rotterdam BiobankMARSMünster Age and Retina Study. For all metabolite abbreviations please see supplementary table