Oscar Dias

Correlation between sludge settling ability and image analysis information using partial least squares

In the last years there has been an increase on the research of the activated sludge processes, and mainly on the solid-liquid separation stage, considered of critical importance, due to the different problems that may arise affecting the compaction and the settling of the sludge. Furthermore, image analysis procedures are, nowadays considered to be an adequate method to characterize both aggregated and filamentous bacteria, and increasingly used to monitor bulking events in pilot plants. As a result of that, in this work, image analysis routines were developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments. Moreover, the large amount of activated sludge data collected with the image analysis implementation can be subsequently treated by multivariate statistical procedures such as PLS. In the current work the implementation of image analysis and PLS techniques has shown to provide important information for better understanding the behavior of activated sludge processes, and to predict, at some extent, the sludge volume index. As a matter of fact, the obtained results allowed explaining the strong relationships between the sludge settling properties and the free filamentous bacteria contents, aggregates size and aggregates morphology, establishing relevant relationships between macroscopic and microscopic properties of the biological system.

Monitoring of activated sludge settling ability through image analysis: validation on full-scale wastewater treatment plants

In recent years, a great deal of attention has been focused on the research of activated sludge processes, where the solid–liquid separation phase is frequently considered of critical importance, due to the different problems that severely affect the compaction and the settling of the sludge. Bearing that in mind, in this work, image analysis routines were developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments in eight different wastewater treatment plants, for a combined period of 2 years. The monitoring of the activated sludge contents allowed for the detection of bulking events proving that the developed image analysis methodology is adequate for a continuous examination of the morphological changes in microbial aggregates and subsequent estimation of the sludge volume index. In fact, the obtained results proved that the developed image analysis methodology is a feasible method for the continuous monitoring of activated sludge systems and identification of disturbances.

Reconstructing genome-scale metabolic models with merlin

The Metabolic Models Reconstruction Using Genome-Scale Information (merlin) tool is a user-friendly Java application that aids the reconstruction of genome-scale metabolic models for any organism that has its genome sequenced. It performs the major steps of the reconstruction process, including the functional genomic annotation of the whole genome and subsequent construction of the portfolio of reactions. Moreover, merlin includes tools for the identification and annotation of genes encoding transport proteins, generating the transport reactions for those carriers. It also performs the compartmentalisation of the model, predicting the organelle localisation of the proteins encoded in the genome and thus the localisation of the metabolites involved in the reactions promoted by such enzymes. The gene-proteins-reactions (GPR) associations are automatically generated and included in the model. Finally, merlin expedites the transition from genomic data to draft metabolic models reconstructions exported in the SBML standard format, allowing the user to have a preliminary view of the biochemical network, which can be manually curated within the environment provided by merlin.

iOD907, the first genome-scale metabolic model for the milk yeast Kluyveromyces lactis

We describe here the first genome-scale metabolic model of Kluyveromyces lactis, iOD907. It is partially compartmentalized (four compartments), composed of 1867 reactions and 1476 metabolites. The iOD907 model performed well when comparing the positive growth of K. lactis to Biolog experiments and to an online catalogue of strains that provides information on carbon sources in which K. lactis is able to grow. Chemostat experiments were used to adjust non-growth-associated energy requirements, and the model proved accurate when predicting the biomass, oxygen and carbon dioxide yields. When compared to published experiments, in silico knockouts accurately predicted in vivo phenotypes. The iOD907 genome-scale metabolic model complies with the MIRIAM (minimum information required for the annotation of biochemical models) standards for the annotation of enzymes, transporters, metabolites and reactions. Moreover, it contains direct links to Kyoto encyclopedia of genes and genomes (KEGG; for enzymes, metabolites and reactions) and to the Transporters Classification Database (TCDB) for transporters, allowing easy comparisons to other models. Furthermore, this model is provided in the well-established systems biology markup language (SBML) format, which means that it can be used in most metabolic engineering platforms, such as OptFlux or Cobra. The model is able to predict the behavior of K. lactis under different environmental conditions and genetic perturbations. Furthermore, by performing simulations and optimizations, it can be important in the design of minimal media and will allow insights on the milk yeasts metabolism, as well as identifying metabolic engineering targets for improving the production of products of interest.

A Comparison between bright field and phase-contrast image analysis techniques in activated sludge morphological characterization.

Different approaches using microscopy image analysis procedures were employed for characterization of activated sludge systems. The approaches varied mainly on the type of visualization and acquisition method used for collection of data. In this context, this study focused on the comparison of the two most common acquisition methods: bright field and phase-contrast microscopy. Images were acquired from seven different wastewater treatment plants for a combined period of two years. Advantages and disadvantages of each acquisition technique and the results are discussed. Bright field microscopy proved to be more simple and inexpensive and provided the best overall results.

Genome-wide metabolic (re-) annotation of Kluyveromyces lactis

BackgroundEven before having its genome sequence published in 2004, Kluyveromyces lactis had long been considered a model organism for studies in genetics and physiology. Research on Kluyveromyces lactis is quite advanced and this yeast species is one of the few with which it is possible to perform formal genetic analysis. Nevertheless, until now, no complete metabolic functional annotation has been performed to the proteins encoded in the Kluyveromyces lactis genome.ResultsIn this work, a new metabolic genome-wide functional re-annotation of the proteins encoded in the Kluyveromyces lactis genome was performed, resulting in the annotation of 1759 genes with metabolic functions, and the development of a methodology supported by merlin (software developed in-house). The new annotation includes novelties, such as the assignment of transporter superfamily numbers to genes identified as transporter proteins. Thus, the genes annotated with metabolic functions could be exclusively enzymatic (1410 genes), transporter proteins encoding genes (301 genes) or have both metabolic activities (48 genes). The new annotation produced by this work largely surpassed the Kluyveromyces lactis currently available annotations. A comparison with KEGG’s annotation revealed a match with 844 (~90%) of the genes annotated by KEGG, while adding 850 new gene annotations. Moreover, there are 32 genes with annotations different from KEGG.ConclusionsThe methodology developed throughout this work can be used to re-annotate any yeast or, with a little tweak of the reference organism, the proteins encoded in any sequenced genome. The new annotation provided by this study offers basic knowledge which might be useful for the scientific community working on this model yeast, because new functions have been identified for the so-called metabolic genes. Furthermore, it served as the basis for the reconstruction of a compartmentalized, genome-scale metabolic model of Kluyveromyces lactis, which is currently being finished.

Merlin: Metabolic Models Reconstruction using Genome-Scale Information ?

This article describes Merlin, a user-friendly program that performs functional genomic annotations of lists of genes. Merlin retrieves information of each homologue and automatically scores the results, allowing the user to change the score selection, and dynamically (re-)annotate the genome. Merlin expedites the transition from genome-scale data to SBML metabolic models, allowing the user to have a preliminary view of the biochemical network.

Dilution and Magnification Effects on Image Analysis Applications in Activated Sludge Characterization

The properties of activated sludge systems can be characterized using image analysis procedures. When these systems operate with high biomass content, accurate sludge characterization requires samples to be diluted. Selection of the best image acquisition magnification is directly related to the amount of biomass screened. The aim of the present study was to survey the effects of dilution and magnification on the assessment of aggregated and filamentous bacterial content and structure using image analysis procedures. Assessments of biomass content and structure were affected by dilutions. Therefore, the correct operating dilution requires careful consideration. Moreover, the acquisition methodology comprising a 100× magnification allowed data on aggregated and filamentous biomass to be determined and smaller aggregates to be identified and characterized, without affecting the accuracy of lower magnifications regarding biomass representativeness.

Genome-wide metabolic re-annotation of Ashbya gossypii: new insights into its metabolism through a comparative analysis with Saccharomyces cerevisiae and Kluyveromyces lactis

BackgroundAshbya gossypii is an industrially relevant microorganism traditionally used for riboflavin production. Despite the high gene homology and gene order conservation comparatively with Saccharomyces cerevisiae, it presents a lower level of genomic complexity. Its type of growth, placing it among filamentous fungi, questions how close it really is from the budding yeast, namely in terms of metabolism, therefore raising the need for an extensive and thorough study of its entire metabolism. This work reports the first manual enzymatic genome-wide re-annotation of A. gossypii as well as the first annotation of membrane transport proteins.ResultsAfter applying a developed enzymatic re-annotation pipeline, 847 genes were assigned with metabolic functions. Comparatively to KEGG’s annotation, these data corrected the function for 14% of the common genes and increased the information for 52 genes, either completing existing partial EC numbers or adding new ones. Furthermore, 22 unreported enzymatic functions were found, corresponding to a significant increase in the knowledge of the metabolism of this organism. The information retrieved from the metabolic re-annotation and transport annotation was used for a comprehensive analysis of A. gossypii’s metabolism in comparison to the one of S. cerevisiae (post-WGD – whole genome duplication) and Kluyveromyces lactis (pre-WGD), suggesting some relevant differences in several parts of their metabolism, with the majority being found for the metabolism of purines, pyrimidines, nitrogen and lipids. A considerable number of enzymes were found exclusively in A. gossypii comparatively with K. lactis (90) and S. cerevisiae (13). In a similar way, 176 and 123 enzymatic functions were absent on A. gossypii comparatively to K. lactis and S. cerevisiae, respectively, confirming some of the well-known phenotypes of this organism.ConclusionsThis high quality metabolic re-annotation, together with the first membrane transporters annotation and the metabolic comparative analysis, represents a new important tool for the study and better understanding of A. gossypii’s metabolism.

Data Integration Issues in the Reconstruction of the Genome-Scale Metabolic Model of Zymomonas Mobillis

Genome-scale model reconstruction represents a major tool in the field of Metabolic Engineering .This paper reports on a study about data integration issues in the process of genome-scale reconstruction of the metabolic model of the bacterium Zymomonas mobilis, a promising organism for bioethanol production. Data is retrieved from the Entrez Gene, KEGG, BioCyc and Brenda databases, and the several processes involved in data integration from these sources are described, as well as the data quality issues.