Protocols for data generation for predictive modeling

Summary Essential to the development of useful predictive models for foods is the collection of appropriate data. Within the UK Predictive Food Microbiology Program, a series of documents have been produced to aid the standardization of data collection by a number of laboratories. Documents include a protocols form, notes on experimental design, notes on the accuracy of counts by plating, the preferred method of calculating a plate count value, preferred MPN tables and the preferred methods of recording data values. These documents have proven useful in aiding collaboration between laboratories.     

Design of experiments for predictive microbial modeling

Summary Good predictive microbial models can be built with appropriate data from well-designed experiments. Anyone setting up an experiment should consider the sources of variability, possible screening experiments, optimum spacing between points on a continuous scale, and the most appropriate type of design, e.g. factorial, screening, or central composite.     

Metabolic ensemble modeling for strain engineers

Previous mathematical modeling efforts have made significant contributions to the development of systems biology for predicting biological behavior quantitatively. However, dynamic metabolic model construction remains challenging due to uncertainties in mechanistic structures and parameters. In addition, parameter estimation and model validation often require designated experiments conducted only for purpose of modeling. Such difficulties have hampered the progress of modeling in biology and biotechnology. To circumvent these problems, ensemble approaches have been used to account for uncertainties in model structure and parameters. Specifically, this review focuses on approaches that utilize readily available fermentation data for parameter screening and model validation. Time course data for metabolite measurements, if available, can further calibrate the model. The basis for this approach is explained in non-mathematical terms accessible to experimentalists. Information gained from such an approach has been shown to be useful in designing Escherichia coli strains for metabolic engineering and synthetic biology.     

Conductance measurements for data generation in predictive modeling

Summary The electrical resistance of a growth medium inoculated with bacteria may be automatically recorded throughout an incubation period without the necessity for sampling. The rate of change in conductance is dependent on the bacteria studied, the medium composition and the prevailing growth conditions.The effect of growth medium composition, growth conditions and inoculum level on the conductance response was studied forYersinia enterocolitica O:3. A large number of combinations of factors affecting the growth/activity of the bacteria could be studied simultaneously due to the large instrumental capacity of the Malthus 2000. A polynomial model based on conductance measurements was developed forY. enterocolitica describing the effect of temperature, pH andl-lactate level on conductance response curve parameters. The model was used for predicting growth rates. Growth rates calculated from bacterial counts ofY. enterocolitica growing in minced pork corresponded to growth rates predicted using the polynomial conductance models.     

Genome sequence of Propionibacterium acnes type II strain ATCC 11828

Propionibacterium acnes is an anaerobic Gram-positive bacterium that forms part of the normal human cutaneous microbiota and is occasionally associated with inflammatory diseases (I. Kurokawa et al., Exp. Dermatol. 18:821-832, 2009). Here we present the complete genome sequence for the commercially available P. acnes type II reference strain ATCC 11828 (I. Nagy et al., Microbes Infect. 8:2195-2205, 2006) recovered from a subcutaneous abscess.     

Complete genome sequence of Propionibacterium acnes type IB strain 6609

Propionibacterium acnes is an anaerobic Gram-positive bacterium that forms part of the normal human cutaneous microbiota and is thought to play a central role in acne vulgaris, a chronic inflammatory disease of the pilosebaceous unit (I. Kurokawa et al., Exp. Dermatol. 18:821-832, 2009). Here we present the whole genome sequence of P. acnes type IB strain 6609, which was recovered from a skin sample from a woman with no recorded acne history and is thus considered a nonpathogenic strain (I. Nagy, Microbes Infect. 8:2195-2205, 2006).     

Bayesian predictive identification and cumulative classification of bacteria

In this paper we give a mathematically precise formulation of an old idea in bacterial taxonomy, namely cumulative classification, where the taxonomy is continuously updated and possibly augmented as new strains are identified. Our formulation is based on Bayesian predictive probability distributions. The criterion for founding a new taxon is given a firm theoretical foundation based on prediction and it is given a clear-cut interpretation. We formulate an algorithm for cumulative classification and apply it to a large database of bacteria belonging to the family Enterobacteriaceae. The resulting taxonomy makes microbiological sense.     

Propionic acid production by immobilized cells of a propionate-tolerant strain of Propionibacterium acidipropionici

Cells of the propionate-tolerant strain Propionibacterium acidipropionici P200910, immobilized in calcium alginate beads, were tested for propionic and acetic acid production both in a semidefined laboratory medium and in corn steep liquor in batch, fed-batch, and continuous fermentation. Cell density was about 9.8 × 10⁹ cells/g (wet weight) of beads, and beads were added to the medium at 0.1 g (wet weight) beads/ml. Beads could be reused for several consecutive batch fermentations; propionic acid production in the tenth cycle was about 50%–70% of that in the first cycle. In batch culture complete substrate consumption (glucose in semidefined medium, lactate in corn steep liquor) and maximum acid production were seen within 36 h, and acid yields from the substrate were higher than in free-cell fermentations. Fed-batch fermentations were incubated up to 250 h. Maximum propionic acid concentrations obtained were 45.6 g/l in corn steep liquor and 57 g/l in semidefined medium; this is the highest concentration achieved to date in our laboratory. Maximum acetic acid concentrations were 17 g/l and 12 g/l, respectively. In continuous fermentation of semidefined medium, dilution rates up to 0.31 h^–1 could be used, which gave higher volumetric productivities (0.96 g l^–1 h^–1 for propionic acid and 0.26 g l^–1 h^–1 for acetic acid) than we have obtained with free cells. Corn steep liquor shows promise as an inexpensive medium for production of both acids by immobilized cells of propionibacteria.Journal paper no. J- 15614 of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa. Project no. 3122     

A simple method for differentiation of Propionibacterium acnes and Propionibacterium propionicum

Abstract TLC glycolipid profiles of several culture collection and clinical strains of Propionibacterium acnes and Propionibacterium propionicum were examined. The former were characterized by weak orcinol-positive minor glycolipids of type g, while the others had mainly strong orcinol-positive major glycolipids of type G. The simple and rapid small scale procedure seemed to be useful for differentiation of these phenotypically similar and genotypically closely related species irrespective of their serotypes.     

Structure of acidic polysaccharide from cell wall of Propionibacterium acnes strain C7

The structure of polysaccharide prepared by lysozyme digestion from the cell wall of Propionibacterium acnes strain C7 was examined. The polysaccharide fraction was composed of glucose, galactose, mannose, galactosamine, and diaminomannuronic acid in a molar ratio of 1:1:0.3:1:2. By Smith degradation of the polysaccharide, diaminouronic acid-containing fractions were obtained, and the configuration of diaminouronic acid was identified as 2,3-diacetamido-2,3-dideoxymannuronic acid [Man(NAc)2A] by means of 1H-NMR and 13C-NMR spectroscopic analyses. The results of analyses involving methylation and partial acid hydrolysis led to the conclusion that the polysaccharide has the repeating unit----6)Gal(alpha 1----4)Man(NAc)2A(beta 1----6)Glc(alpha 1----4)Man(NAc)2A (beta 1----3)GalNAc(beta 1--. In addition, a portion of the galactose residues were substituted at C-4 by alpha 1----2 linked mannotriose.     

Cardiac arrhythmia classification using autoregressive modeling

Background  

Computer-assisted arrhythmia recognition is critical for the management of cardiac disorders. Various techniques have been utilized to classify arrhythmias. Generally, these techniques classify two or three arrhythmias or have significantly large processing times. A simpler autoregressive modeling (AR) technique is proposed to classify normal sinus rhythm (NSR) and various cardiac arrhythmias including atrial premature contraction (APC), premature ventricular contraction (PVC), superventricular tachycardia (SVT), ventricular tachycardia (VT) and ventricular fibrillation (VF).     

Entropy-based gene ranking without selection bias for the predictive classification of microarray data

Background

We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process).

Results

With E-RFE, we speed up the recursive feature elimination (RFE) with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles.

Conclusions

Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

     

Corn stover feedstock trials to support predictive modeling

To be sustainable, feedstock harvest must neither degrade soil, water, or air resources nor negatively impact productivity or subsequent crop yields. Simulation modeling will help guide the development of sustainable feedstock production practices, but not without field validation. This paper introduces field research being conducted in six states to support Sun Grant Regional Partnership modeling. Our objectives are to (1) provide a fundamental understanding of limiting factor(s) affecting corn (Zea mays L.) stover harvest, (2) develop tools (e.g., equations, models, etc.) that account for those factors, and (3) create a multivariant analysis framework to combine models for all limiting factors. Sun Grant modelers will use this information to improve regional estimates of feedstock availability. A minimum data set, including soil organic carbon (SOC), total N, pH, bulk density (BD), and soil‐test phosphorus (P), and potassium (K) concentrations, is being collected. Stover yield for three treatments (0%, 50%, and 90% removal) and concentrations of N, P, and K in the harvested stover are being quantified to assess the impact of stover harvest on soil resources. Grain yield at a moisture content of 155 g kg^?1 averaged 9.71 Mg ha^?1, matching the 2008 national average. Stover dry matter harvest rates ranged from 0 to 7 Mg ha^?1. Harvesting stover increased N–P–K removal by an average of 42, 5, and 45 kg ha^?1 compared with harvesting only grain. Replacing those three nutrients would cost $53.68 ha^?1 based on 2009 fertilizer prices. This first‐year data and that collected in subsequent years is being used to develop a residue management tool that will ultimately link multiple feedstock supplies together in a landscape vision to help develop a comprehensive carbon management plan, quantify corn stover harvest effects on soil quality, and predict regional variability in feedstock supplies.