Isolamento e caracterização de cepas de Saccharomyces cerevisiae de interesse em produção de vinho

Despite the availability of several Saccharomyces cerevisiae commercial strains intended for wine production, strains isolated from winery regions are usually more adapted to their own climatic conditions, grapes and also partially responsible for particular characteristics that frequently identify specific wines and regions. Thus the microbiota of an important winery region (Colombo) was studied in order to isolate and characterize S. cerevisiae strains that could be used on wine production. From 61 yeasts isolated, 14 were identified as S. cerevisiae. Some of them showed fermentative characteristics even better than commercial strains indicating that they could be applied on wine production in order to increase the quality and assure the particular wine characteristics of that region

Phenotype Sequencing: Identifying the Genes That Cause a Phenotype Directly from Pooled Sequencing of Independent Mutants

Random mutagenesis and phenotype screening provide a powerful method for dissecting microbial functions, but their results can be laborious to analyze experimentally. Each mutant strain may contain 50–100 random mutations, necessitating extensive functional experiments to determine which one causes the selected phenotype. To solve this problem, we propose a “Phenotype Sequencing” approach in which genes causing the phenotype can be identified directly from sequencing of multiple independent mutants. We developed a new computational analysis method showing that 1. causal genes can be identified with high probability from even a modest number of mutant genomes; 2. costs can be cut many-fold compared with a conventional genome sequencing approach via an optimized strategy of library-pooling (multiple strains per library) and tag-pooling (multiple tagged libraries per sequencing lane). We have performed extensive validation experiments on a set of E. coli mutants with increased isobutanol biofuel tolerance. We generated a range of sequencing experiments varying from 3 to 32 mutant strains, with pooling on 1 to 3 sequencing lanes. Our statistical analysis of these data (4099 mutations from 32 mutant genomes) successfully identified 3 genes (acrB, marC, acrA) that have been independently validated as causing this experimental phenotype. It must be emphasized that our approach reduces mutant sequencing costs enormously. Whereas a conventional genome sequencing experiment would have cost $7,200 in reagents alone, our Phenotype Sequencing design yielded the same information value for only$1200. In fact, our smallest experiments reliably identified acrB and marC at a cost of only $110–$340

Influência da segregação granulométrica e do emprego de aditivos de moagem na adequação de cinzas de casca de arroz como coproduto

RESUMO A cinza de casca de arroz (CCA) é um resíduo proveniente da combustão da casca de arroz utilizada como biomassa na produção de energia. Esta cinza é gerada em grandes quantidades e possui baixa massa específica, o que dificulta o seu gerenciamento, pois demanda muito espaço para o devido armazenamento e descarte. A CCA possui um elevado teor de sílica em sua composição, fator este que pode torná-la um material atrativo para vários segmentos industriais. Neste contexto, este trabalho tem como objetivo avaliar a influência do beneficiamento físico da cinza de casca de arroz, por meio de processos de segregação granulométrica e moagem, com e sem o uso de aditivos, nas características deste material e na sua adequação como coproduto. A metodologia experimental utilizada para o desenvolvimento deste trabalho envolveu a segregação e moagem da CCA (com e sem aditivos de moagem), caracterização química, física e estrutural das amostras de CCA bruta, segregadas e moídas. Os resultados obtidos indicam que a segregação granulométrica se apresenta como fator determinante para a utilização da CCA como coproduto. Com relação à moagem, pode-se verificar que o diâmetro médio das partículas diminui e a massa específica das amostras aumenta, com o aumento do tempo de moagem. Entretanto, verifica-se que os aditivos usados neste trabalho, nas concentrações testadas, não influenciam significativamente na redução do diâmetro das partículas

Schematic diagram of phenotype sequencing and key parameters.

<p>Overview of phenotype sequencing stages: mutagenesis, screening, and sequencing. Conventional unpooled sequencing of individual strains (left), is contrasted with pooled sequencing of multiple strains per library (right), comparing the expected frequency of observation of a real mutation in each case.</p

Phenotype sequencing of 32 isobutanol tolerant <i>E. coli</i> strains (top 21 hits by raw SNP counts).

<p>Phenotype sequencing of 32 isobutanol tolerant <i>E. coli</i> strains (top 21 hits by raw SNP counts).</p

Top 20 hits ranked by Bonferroni corrected p-value computed on non-synonymous SNPs.

<p>Top 20 hits ranked by Bonferroni corrected p-value computed on non-synonymous SNPs.</p