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Soil salinization adversely affects soil fertility and plant growth in arid region worldwide. However, as the drivers of nutrient cycling, the response of microbial communities to soil salinization is poorly understood. This study characterized bacterial communities in different soil layers along a natural salinity gradient in the Karayulgun River Basin, located northwest of the Taklimakan desert in China, using the 16S rRNA Miseq-sequencing technique. The results revealed a significant filtering effect of salinity on the bacterial community in the topsoil. Only the α-diversity (Shannon index) in the topsoil (0-10 cm) significantly decreased with increasing salinity levels, and community dissimilarity in the topsoil was enhanced with increasing salinity, while there was no significant relationship in the subsoil. BugBase predictions revealed that aerobic, facultatively anaerobic, gram-positive, and stress-tolerant bacterial phenotypes in the topsoil was negatively related to salinity. The average degree and number of modules of the bacterial co-occurrence network in the topsoil were lower under higher salinity levels, which contrasted with the trends in the subsoil, suggesting an unstable bacterial network in the topsoil caused by higher salinity. The average path length among bacterial species increased in both soil layers under high salinity conditions. Plant diversity and available nitrogen were the main drivers affecting community composition in the topsoil, while available potassium largely shaped community composition in the subsoil. This study provides solid evidence that bacterial communities adapt to salinity through the adjustment of microbial composition based on soil depth. This information will contribute to the sustainable management of drylands and improved predictions and responses to changes in ecosystems caused by climate change.

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When selecting microbial strains for the production of fermented foods, various microbial phenotypes need to be taken into account to achieve target product characteristics, such as biosafety, flavor, texture, and health-promoting effects. Through continuous advances in sequencing technologies, microbial whole-genome sequences of increasing quality can now be obtained both cheaper and faster, which increases the relevance of genome-based characterization of microbial phenotypes. Prediction of microbial phenotypes from genome sequences makes it possible to quickly screen large strain collections in silico to identify candidates with desirable traits. Several microbial phenotypes relevant to the production of fermented foods can be predicted using knowledge-based approaches, leveraging our existing understanding of the genetic and molecular mechanisms underlying those phenotypes. In the absence of this knowledge, data-driven approaches can be applied to estimate genotype-phenotype relationships based on large experimental datasets. Here, we review computational methods that implement knowledge- and data-driven approaches for phenotype prediction, as well as methods that combine elements from both approaches. Furthermore, we provide examples of how these methods have been applied in industrial biotechnology, with special focus on the fermented food industry.

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Introducción. La resistencia bacteriana ha tomado importancia en salud pública, requiriendo estable-cer las relaciones existentes entre las infecciones, el manejo terapéutico y la expresión de los mecanis-mos de resistencia en microorganismos aislados en muestras hospitalarias. Objetivo. Reportar el perfil de resistencia de los microorganismos identificados en una institución prestadora de servicios de salud de tercer y cuarto nivel de atención en el Departamento de Boyacá durante un periodo de 6 meses en el año 2018. Materiales y métodos. Se llevó a cabo un estudio observacional, descriptivo y de corte transversal; los microorganismos fueron aislados de muestras clínicas de una institución prestadora de salud del departamento de Boyacá durante un periodo de 6 meses en el año 2018. Se realizó identificación, concentración mínima inhibitoria y pruebas confirmatorias de susceptibilidad según la Clinical and Laboratory Standards Institute M100-S23. Resultados. En los aislados evaluados predominaron los bacilos Gram negativos con un 86,4 % de estas 50% presentaron el fenotipo de resistencia Betalactamasas de espectro extendido, siendo Es-cherichia coli el microorganismo más frecuente. Staphylococcus aureus fue el único microorganismo Gram positivo aislado con 100% de cepas resistente a meticilina. Conclusiones. El microorganismo aislado con mayor frecuencia fue Escherichia coli y el mecanismo de resistencia más prevalente fue la producción de Betalactamasas de espectro extendido aisladas de muestras de orina

Introduction. Bacterial resistance has recently become important in public health, requiring to esta-blish some existing relationships between infections, therapeutic management and the expression of resistance mechanisms in microorganisms isolated in clinical samples. Objective. Report the resistance profile of circulating microorganisms isolated in a third and fourth level healthcare service provider institution in Boyacá Department. Materials and methods. An observational, descriptive and cross-sectional study was carried out, strains were isolated from clinical samples from a health institution of department of Boyacá in a six-month period during 2018. Identification, minimum inhibitory concentration and confirmatory test were carried out according to Clinical and Laboratory Standards Institute M100-S23. Results. In all isolated strain, Gram negative bacilli were predominated (86.4%), these isolates had a 50 % of Extended-spectrum beta-lactamases resistance phenotype, where Escherichia coli was the most frequent isolated microorganism. Staphylococcus aureus was the unique Gram positive microor-ganism isolated with 100% of Methicillin Resistant Staphylococcus aureus type strains. Conclusions. Escherichia coli was the most prevalent microorganism and Extended-spectrum be-ta-lactamases was the most frequent resistance mechanism isolated from urinary infection samples.

Introdução. A resistência bacteriana tornou-se importante na saúde pública, exigindo o estabeleci-mento das relações existentes entre infecções, gestão terapêutico e a expressão de mecanismos de resistência em microrganismos isolados em amostras hospitalares. Objetivo. Relatar o perfil de resistência dos microrganismos identificados em uma instituição de saúde de terceiro e quarto nível no Departamento de Boyacá por um período de 6 meses em 2018. Materiais e métodos. Foi realizado um estudo observacional, descritivo e transversal; os microrga-nismos foram isolados de amostras clínicas de uma instituição prestadora de serviços de saúde no departamento de Boyacá por um período de 6 meses em 2018. A identificação, a concentração inibi-tória mínima e os testes de susceptibilidade confirmatória foram realizados de acordo com o Instituto de Padrões Clínicos e Laboratoriais M100-S23b Resultados. Nos isolados avaliados, predominou o bacilo Gram-negativo com 86,4%, destes 50% apresentaram o fenótipo de resistência a betalactamases de espectro estendido, sendo Escherichia coli o microrganismo mais frequente. Staphylococcus aureus foi o único microrganismo Gram positivo isolado com cepas 100% resistentes à meticilina. Conclusões. O organismo frequentemente isolado foi Escherichia coli e o mecanismo de resistência mais prevalente foi a produção de betalactamases de espectro estendido, isolada de amostras de urina

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