Isolation and characterization of potential phytase-producing fungi from environmental samples of antioquia (colombia) / aislamiento y caracterización de hongos productores de fitasa a partir de muestras ambientales de antioquia (colombia)

Abstract. Phytases are enzymes used as feed additive that enhance the phosphorus and mineral uptake in monogastric animals and reduce the level of phosphate excretion in their manure. Due to their easy cultivation and high production of extracellular enzymes, filamentous fungi are one of best sources of phytase for use in the feed industry. Phytase has been found principally in the genera Aspergillus, Penicillium, Mucor and Rhizopus. In this work, we report the isolation and characterization of environmental fungi producers of phytase with potential use as feed additives. Samples were collected from soils, fruits and cereals in Antioquia (Colombia). A total of 26 fungal strains were isolated and identified using ITS sequencing and morphological analysis. Strains belonged to the following genera: Penicillium, Aspergillus, Fusarium, Mortierella, Pestalotiopsis, Phoma, Paecilomyces and Rigidoporus. Fifty percent of isolates exhibited halos in phytase screening agar indicating that acidic phytases are common enzymes secreted by environmental fungi. Ten isolates were also able to grow in liquid phytase screening medium revealing their potential use for enzyme production in submerged fermentations. Molecular detection of the PhyA gene from Aspergillus was achieved. Partial sequence of the phyA gene from one A. niger isolate was obtained and analyzed. / Resumen. Las fitasas son enzimas utilizadas como aditivo en productos de alimentación animal, con el fin de mejorar la asimilación de fósforo y minerales en animales monogástricos y disminuir la excreción de fósforo al ambiente. Los hongos filamentosos son una de las mejores fuentes de fitasas debido a su facilidad de cultivo y altos niveles de producción de enzimas extracelulares. Los principales productores de fitasas corresponden a miembros de los géneros Aspergillus, Penicillium, Mucor y Rhizopus. En este trabajo se reporta el aislamiento y caracterización de hongos ambientales productores de fitasas con aplicación potencial en la industria de alimentación animal. Se obtuvieron e identificaron un total de 26 aislamientos; caracterizados por secuenciación de la región ITS-ADNr y análisis morfológico. Los aislamientos pertenecieron a los siguientes géneros: Penicillium, Aspergillus, Fusarium, Mortierella, Pestalotiopsis, Phoma, Paecilomyces y Rigidoporus. Se observó la secreción de fitasas en 50% de los aislamientos sugiriendo la ubiquidad de esta enzima en hongos ambientales. Diez aislamientos crecieron eficientemente en medio líquido con fitato como única fuente de fósforo. Estos últimos cumplen con los requisitos para la producción de enzimas mediante fermentación sumergida. Se diseñaron cebadores para la detección molecular del gen PhyA en los aislamientos del género Aspergillus. Se obtuvo y analizó la secuencia parcial del gen PhyA de un aislamiento de A. nige

Aislamiento y Caracterización de Hongos Productores de Fitasa a partir de Muestras Ambientales de Antioquia (Colombia)

Abstract. Phytases are enzymes used as feed additive that enhance the phosphorus and mineral uptake in monogastric animals and reduce the level of phosphate excretion in their manure. Due to their easy cultivation and high production of extracellular enzymes, filamentous fungi are one of best sources of phytase for use in the feed industry. Phytase has been found principally in the genera Aspergillus, Penicillium, Mucor and Rhizopus. In this work, we report the isolation and characterization of environmental fungi producers of phytase with potential use as feed additives. Samples were collected from soils, fruits and cereals in Antioquia (Colombia). A total of 26 fungal strains were isolated and identified using ITS sequencing and morphological analysis. Strains belonged to the following genera: Penicillium, Aspergillus, Fusarium, Mortierella, Pestalotiopsis, Phoma, Paecilomyces and Rigidoporus. Fifty percent of isolates exhibited halos in phytase screening agar indicating that acidic phytases are common enzymes secreted by environmental fungi. Ten isolates were also able to grow in liquid phytase screening medium revealing their potential use for enzyme production in submerged fermentations. Molecular detection of the PhyA gene from Aspergillus was achieved. Partial sequence of the phyA gene from one A. niger isolate was obtained and analyzed. / Resumen. Las fitasas son enzimas utilizadas como aditivo en productos de alimentación animal, con el fin de mejorar la asimilación de fósforo y minerales en animales monogástricos y disminuir la excreción de fósforo al ambiente. Los hongos filamentosos son una de las mejores fuentes de fitasas debido a su facilidad de cultivo y altos niveles de producción de enzimas extracelulares. Los principales productores de fitasas corresponden a miembros de los géneros Aspergillus, Penicillium, Mucor y Rhizopus. En este trabajo se reporta el aislamiento y caracterización de hongos ambientales productores de fitasas con aplicación potencial en la industria de alimentación animal. Se obtuvieron e identificaron un total de 26 aislamientos; caracterizados por secuenciación de la región ITS-ADNr y análisis morfológico. Los aislamientos pertenecieron a los siguientes géneros: Penicillium, Aspergillus, Fusarium, Mortierella, Pestalotiopsis, Phoma, Paecilomyces y Rigidoporus. Se observó la secreción de fitasas en 50% de los aislamientos sugiriendo la ubiquidad de esta enzima en hongos ambientales. Diez aislamientos crecieron eficientemente en medio líquido con fitato como única fuente de fósforo. Estos últimos cumplen con los requisitos para la producción de enzimas mediante fermentación sumergida. Se diseñaron cebadores para la detección molecular del gen PhyA en los aislamientos del género Aspergillus. Se obtuvo y analizó la secuencia parcial del gen PhyA de un aislamiento de A. nige

Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach

Introduction Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings.Research design and methods We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999–2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup.Results SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89).Conclusions Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications