Totoro: Identifying Active Reactions During the Transient State for Metabolic Perturbations

International audienceMotivation: The increasing availability of metabolomic data and their analysis are improving the understanding of cellular mechanisms and how biological systems respond to different perturbations. Currently, there is a need for novel computational methods that facilitate the analysis and integration of increasing volume of available data. Results: In this paper, we present Totoro a new constraint-based approach that integrates quantitative non-targeted metabolomic data of two different metabolic states into genome-wide metabolic models and predicts reactions that were most likely active during the transient state. We applied Totoro to real data of three different growth experiments (pulses of glucose, pyruvate, succinate) from Escherichia coli and we were able to predict known active pathways and gather new insights on the different metabolisms related to each substrate. We used both the E. coli core and the iJO1366 models to demonstrate that our approach is applicable to both smaller and larger networks. Availability: Totoro is an open source method (available at https://gitlab.inria.fr/erable/totoro ) suitable for any organism with an available metabolic model. It is implemented in C++ and depends on IBM CPLEX which is freely available for academic purposes

A methodology to infer gene networks from spatial patterns of expression: an application to fluorescence in situ hybridization images

The proper functional development of a multicellular organism depends on an intricate network of interacting genes that are expressed in accurate temporal and spatial patterns across different tissues. Complex inhibitory and excitatory interactions among genes control the territorial differences that explain specialized cell fates, embryo polarization and tissues architecture in metazoans. Given the nature of the regulatory gene networks, similarity of expression patterns can identify genes with similar roles. The inference and analysis of the gene interaction networks through complex network tools can reveal important aspects of the biological system modeled. Here we suggest an image analysis pipeline to quantify co-localization patterns in in situ hybridization images of Drosophila embryos and, based on these patterns, infer gene networks. We analyze the spatial dispersion of the gene expression and show the gene interaction networks for different developmental stages. Our results suggest that the inference of developmental networks based on spatial expression data is biologically relevant and represents a potential tool for the understanding of animal development.FAPESP (99/12765-2, 05/00587-5, 09/16799-2, 11/22639-8)CNPq (301303/06-1)Human Frontier Science Program (RGP39/2002)Medical Research Council (U105185859

Níveis de Concentrado na Terminação de Bovinos de Corte em Confinamento

A maior parte dos custos de produção da terminação de bovinos em confinamento é decorrente da alimentação resultando na necessidade desenvolvimento de estudos tecnológicos nutricionais que contemplem a eficiência econômica e biológica do sistema de produção de carne. Com o objetivo de diminuir o tempo necessário para que os animais alcancem o peso de abate e conformação de carcaça adequada e para que possam ser comercializados na entressafra, o setor produtivo pode utilizar o sistema de confinamento, que é uma alternativa que pode ser utilizada para melhorar o desempenho econômico e biológico desses animais, com um nível nutricional adequado. O ganho em peso médio diário, o consumo de ração, a conversão alimentar bem como o rendimento de carcaça e a qualidade da carne são os parâmetros normalmente utilizados na avaliação do desempenho dos animais terminados em confinamento. Torna-se necessária a avaliação de alternativas tecnológicas inovadoras, compatíveis com as novas demandas, adequadas à  nova ótica de aumento de eficiência do setor e a conseqüente reestruturação da cadeia produtiva de carne bovina

1D and 2D Fourier-based approaches to numeric curvature estimation and their comparative performance assessment.

A careful comparison of three numeric techniques for estimation of the curvature along spatially quantized contours is reported. Two of the considered techniques are based on the Fourier transform (operating over 1D and 2D signals) and Gaussian regularization required to attenuate the spatial quantization noise. While the 1D approach has been reported before and used in a series of applications, the 2D Fourier transform-based method is reported in this article for the first time. The third approach, based on splines, represents a more traditional alternative. Three classes of parametric curves are investigated: analytical, B-splines, and synthesized in the Fourier domain. Four quantization schemes are considered: grid intersect quantization, square box quantization, a table scanner, and a video camera. The performances of the methods are evaluated in terms of their execution speed, curvature error, and sensitivity to the involved parameters. The third approach resulted the fastest, but implied larger errors; the Fourier methods allowed higher accuracy and were robust to parameter configurations. The 2D Fourier method provides the curvature values along the whole image, but exhibits interference in some situations. Such results are important not only for characterizing the relative performance of the considered methods, but also for providing practical guidelines for those interested in applying those techniques to real problems

Soybean meal replaced by slow release urea in finishing diets for beef cattle

Eight crossbred steers (average body weight of 418 kg) fitted with ruminal and abomasal cannula were used to evaluate the effects of replacing soybean meal (SBM) with slow-release urea (SRU) in beef cattle diets containing two concentrate levels. The experimental design included two 4×4 Latin squares, which were run simultaneously. Each Latin square received one level of concentrate [400 or 800 g/kg on a dry matter (DM) basis]. Within each Latin square, the four replacement levels of soybean meal protein with slow-release urea were applied to the animals (0%, 33%, 66% and 100% of substitution on N basis). The DM intake as well as organic matter (OM) intake and crude protein (CP) intake decreased linearly (P0.10). A lower intake of DM, OM, and CP was observed when cattle were fed SRU compared to SBM. However, the use of SRU did not change the digestibility and digestion rate (kd) and kp of DM, OM, CP and neutral detergent fiber corrected for ash and protein (NDFap). In summary, SRU provides higher concentrations of NH3–N throughout a day than SBM in cattle fed low concentrate diets

Automatic detection of the parasite Trypanosoma cruzi in blood smears using a machine learning approach applied to mobile phone images

Chagas disease is a life-threatening illness caused by the parasite Trypanosoma cruzi. The diagnosis of the acute form of the disease is performed by trained microscopists who detect parasites in blood smear samples. Since this method requires a dedicated high-resolution camera system attached to the microscope, the diagnostic method is more expensive and often prohibitive for low-income settings. Here, we present a machine learning approach based on a random forest (RF) algorithm for the detection and counting of T. cruzi trypomastigotes in mobile phone images. We analyzed micrographs of blood smear samples that were acquired using a mobile device camera capable of capturing images in a resolution of 12 megapixels. We extracted a set of features that describe morphometric parameters (geometry and curvature), as well as color, and texture measurements of 1,314 parasites. The features were divided into train and test sets (4:1) and classified using the RF algorithm. The values of precision, sensitivity, and area under the receiver operating characteristic (ROC) curve of the proposed method were 87.6%, 90.5%, and 0.942, respectively. Automating image analysis acquired with a mobile device is a viable alternative for reducing costs and gaining efficiency in the use of the optical microscope