Insights into the genome and proteome of <i>Sphingomonas paucimobilis</i> strain 20006FA involved in the regulation of polycyclic aromatic hydrocarbon degradation

In order to study the mechanisms regulating the phenanthrene degradation pathway and the intermediate-metabolite accumulation in strain S. paucimobilis 20006FA, we sequenced the genome and compared the genome-based predictions to experimental proteomic analyses. Physiological studies indicated that the degradation involved the salicylate and protocatechuate pathways, reaching 56.3% after 15 days. Furthermore, the strain degraded other polycyclic aromatic hydrocarbons (PAH) such as anthracene (13.1%), dibenzothiophene (76.3%), and fluoranthene. The intermediate metabolite 1-hydroxy2-naphthoic acid (HNA) accumulated during phenanthrene catabolism and inhibited both bacterial growth and phenanthrene degradation, but exogenous-HNA addition did not affect further degradation. Genomic analysis predicted 126 putative genes encoding enzymes for all the steps of phenanthrene degradation, which loci could also participate in the metabolism of other PAH. Proteomic analysis identified enzymes involved in 19 of the 23 steps needed for the transformation of phenanthrene to trichloroacetic-acid intermediates that were upregulated in phenanthrene cultures relative to the levels in glucose cultures. Moreover, the protein-induction pattern was temporal, varying between 24 and 96 h during phenanthrene degradation, with most catabolic proteins being overexpressed at 96 h—e. g., the biphenyl dioxygenase and a multispecies (2Fe–2S)-binding protein. These results provided the first clues about regulation of expression of phenanthrene degradative enzymes in strain 20006FA and enabled an elucidation of the metabolic pathway utilized by the bacterium. To our knowledge the present work represents the first investigation of genomic, proteomic, and physiological studies of a PAH-degrading Sphingomonas strain.Centro de Investigación y Desarrollo en Fermentaciones Industriale

Exatidão dos dados do sistema de vigilância epidemiológica da malária no estado do Amazonas

The Epidemiological Surveillance System for Malaria (SIVEP-Malaria) is the Brazilian governmental program that registers all information about compulsory reporting of detected cases of malaria by all medical units and medical practitioners. The objective of this study is to point out the main sources of errors in the SIVEP-Malaria database by applying a data cleaning method to assist researchers about the best way to use it and to report the problems to authorities. The aim of this study was to assess the quality of the data collected by the surveillance system and its accuracy. The SIVEP-Malaria data base used was for the state of Amazonas, Brazil, with data collected from 2003 to 2014. A data cleaning method was applied to the database to detect and remove erroneous records. It was observed that the collecting procedure of the database is not homogeneous among the municipalities and over the years. Some of the variables had different data collection periods, missing data, outliers and inconsistencies. Variables depending on the health agents showed a good quality but those that rely on patients were often inaccurate. We showed that a punctilious preprocessing is needed to produce statistically correct data from the SIVEP-Malaria data base. Fine spatial scale and multi-temporal analysis are of particular concern due to the local concentration of uncertainties and the data collecting seasonality observed. This assessment should help to enhance the quality of studies and the monitoring of the use of the SIVEP database.O Sistema de Vigilância Epidemiológica de Malária (SIVEP-Malária) é um programa governamental brasileiro que arquiva automaticamente todas as informações sobre casos de malária registrados em todas as unidades de saúde e consultórios medicos. O objetivo deste estudo foi avaliar a qualidade dos dados coletados pelo sistema de vigilância e sua precisão. Foram utilizados os dados do SIVEP-Malária para o estado do Amazonas, Brasil, de 2003 a 2014. Um método de limpeza de dados foi aplicado para detectar e remover registros errôneos. Observamos que a coleta de dados não é homogênea entre os municipios e ao longo dos anos. Algumas variaveis tinham diferentes padrões de coleta, falta de dados, dados discrepantes e inconsistências. Dados que dependem do agente de saúde possuem boa qualidade mas aqueles que dependem dos pacientes são frequentemente imprecisos. Mostramos que um pre-processamento meticuloso é necessário para produzir dados estatisticamente corretos a partir do SIVEP-Malária. Analises em escala espacial detalhada ou multi-temporais são particularmente afetadas devido à concentração local de incertezas e a sazonalidade observada na coleta de dados. Esta avaliação deve auxiliar a melhorar os estudos e monitoramentos que fazem uso dos dados do SIVEP