Selecting representative model micro-organisms

Background

The sexually transmitted disease, gonorrhea, is a serious health problem in developed as well as in developing countries, for which treatment continues to be a challenge. The recent completion of the genome sequence of the causative agent, Neisseria gonorrhoeae, opens up an entirely new set of approaches for studying this organism and the diseases it causes. Here, we describe the initial phases of the construction of an expression-capable clone set representing the protein-coding ORFs of the gonococcal genome using a recombination-based cloning system.

Results

The clone set thus far includes 1672 of the 2250 predicted ORFs of the N. gonorrhoeae genome, of which 1393 (83%) are sequence-validated. Included in this set are 48 of the 61 ORFs of the gonococcal genetic island of strain MS11, not present in the sequenced genome of strain FA1090. L-arabinose-inducible glutathione-S-transferase (GST)-fusions were constructed from random clones and each was shown to express a fusion protein of the predicted size following induction, demonstrating the use of the recombination cloning system. PCR amplicons of each ORF used in the cloning reactions were spotted onto glass slides to produce DNA microarrays representing 2035 genes of the gonococcal genome. Pilot experiments indicate that these arrays are suitable for the analysis of global gene expression in gonococci.

Conclusion

This archived set of Gateway^® entry clones will facilitate high-throughput genomic and proteomic studies of gonococcal genes using a variety of expression and analysis systems. In addition, the DNA arrays produced will allow us to generate gene expression profiles of gonococci grown in a wide variety of conditions. Together, the resources produced in this work will facilitate experiments to dissect the molecular mechanisms of gonococcal pathogenesis on a global scale, and ultimately lead to the determination of the functions of unknown genes in the genome.     

Gyrotaxis: A plume model for self-focusing micro-organisms

We consider the phenomenon of self-focusing pattern formation of motile micro-organisms (“streamer”). The focusing mechanism is based on gyrotaxis, a physical phenomenon, and it results from the balance between viscous and gravitational moments on the organisms. Under particular circumstances such streamers are stabilized and sink, resulting in vertical transport of micro-organisms as well as horizontal heterogeneity in cell concentration. We develop a plume model for the streamer, which consists of the equations of continuity, momentum, and cell concentration. These equations are further simplified to three basic equations representing volume, momentum and concentration fluxes of the steady-state plume. Asymptotic analytical solutions for the plume are obtained. From numerical solutions we find the shape of the plume which takes the form of a vertical string with lengths ranging from 1 to 10 cm. The streamer formation can be related to algal blooms occurring in the sea and to algal cultures grown in the laboratory.     

Selecting the best-fit model of nucleotide substitution

Despite the relevant role of models of nucleotide substitution in phylogenetics, choosing among different models remains a problem. Several statistical methods for selecting the model that best fits the data at hand have been proposed, but their absolute and relative performance has not yet been characterized. In this study, we compare under various conditions the performance of different hierarchical and dynamic likelihood ratio tests, and of Akaike and Bayesian information methods, for selecting best-fit models of nucleotide substitution. We specifically examine the role of the topology used to estimate the likelihood of the different models and the importance of the order in which hypotheses are tested. We do this by simulating DNA sequences under a known model of nucleotide substitution and recording how often this true model is recovered by the different methods. Our results suggest that model selection is reasonably accurate and indicate that some likelihood ratio test methods perform overall better than the Akaike or Bayesian information criteria. The tree used to estimate the likelihood scores does not influence model selection unless it is a randomly chosen tree. The order in which hypotheses are tested, and the complexity of the initial model in the sequence of tests, influence model selection in some cases. Model fitting in phylogenetics has been suggested for many years, yet many authors still arbitrarily choose their models, often using the default models implemented in standard computer programs for phylogenetic estimation. We show here that a best-fit model can be readily identified. Consequently, given the relevance of models, model fitting should be routine in any phylogenetic analysis that uses models of evolution.     

A biased random walk model for the trajectories of swimming micro-organisms

The motion of swimming micro-organisms that have a preferred direction of travel, such as single-celled algae moving upwards (gravitaxis) or towards a light source (phototaxis), is modelled as the continuous limit of a correlated and biased random walk as the time step tends to zero. This model leads to a Fokker-Planck equation for the probability distribution function of the orientation of the cells, from which macroscopic parameters such as the mean cell swimming direction and the diffusion coefficient due to cell swimming can be calculated. The model is tested on experimental data for gravitaxis and phototaxis and used to derive values for the macroscopic parameters for future use in theories of bioconvection, for example.     

Usefulness of different groups of bacteriophages as model micro-organisms for evaluating chlorination

AIMS: To assess the usefulness of bacterial and viral indicators in chlorination processes and to collect quantitative information necessary for risk assessment analysis in water disinfection processes based on chlorination. METHODS AND RESULTS: Naturally occurring bacterial indicators, bacteriophages and enteroviruses were determined to evaluate the effect of chlorination in groundwater and secondary sewage effluents. Additionally, the effect of chlorinating on selected bacteriophages, enteroviruses and Escherichia coli was also tested in spiked samples of bottled water and sewage effluents. Results indicate that chlorination inactivates more efficiently bacteria than phages and enteroviruses. Among the human viruses, phages infecting Bacteroides fragilis and selected somatic coliphages belonging to the Siphoviridae family were the most persistent to chlorination. CONCLUSIONS: The three groups of bacteriophages studied were all more resistant to chlorination than bacteria and some of the phages were more resistant than enteroviruses. Results presented here indicate that it is very risky to generalize from information obtained with inactivation experiments done with single isolates of any phage or virus. If possible, inactivation studies should be done with naturally occurring populations. Phages offer a good opportunity for studying naturally occurring populations. Thus, the bacteriophages offer a range of resistance to chlorination that may represent most of the viruses that can be found in water. SIGNIFICANCE AND IMPACT OF THE STUDY: Data reported in this study support the inclusion of bacteriophages as additional indicators of the efficiency of water chlorination processes and water quality.     

Effects of the high pressure of homogenization on some spoiling micro-organisms, representative of fruit juice microflora, inoculated in saline solution

Aims:  This study was aimed to investigate the effects of a high-pressure homogenization (HPH) treatment on some micro-organisms, involved in the spoilage of fruit juices.
Methods and Results:  Lactobacillus plantarum , Lactobacillus brevis , Bacillus coagulans cells, Saccharomyces bayanus , Pichia membranaefaciens and Rhodotorula bacarum were separately inoculated in a saline solution (0·9% NaCl); the initial inoculum was ca. 5 log CFU ml⁻¹. Then, the samples were processed through a homogenizer at 10–150 MPa for 1, 2 or 3 times. Yeasts were completely inactivated at 50–110 MPa with a single pass treatment, while lactic acid bacteria counts were reduced to approximately 1 log CFU ml⁻¹ after a three-steps HPH processing.
Conclusions:  Yeasts were the most sensitive micro-organisms, followed by B. coagulans . On the other hand, lactic acid bacteria appeared resistant to HPH.
Significance and Impact of the Study:  The results of this study provided some useful information on the susceptibility of microflora of juices to homogenization; moreover, they suggested that HPH could be used successfully to inactivate yeasts.     

A representative model of the hierarchic structure of human populations]

The paper deals with the concept of a hierarchy population. The population is hierarchial, if it can be divided into a certain amount of subpopulations in such a way that the set may naturally break into classes (levels). A migration may exist from each sub-population or into a higher one. Such population structures are frequently encountered among the human populations. It is shown that in a hierarchial population a selection is more efficient than in a non-subdivided one. In this respect the role of small populations in evolution is suggested. It was possible to demonstrate that in a hierarchial population there was a higher degree of polymorphism, a higher velocity of the evolutional process, that in a non-subdivided population of the same size. Besides, the level of polymorphism in the hierarchial population increases monotomously with the growth of the amount of generations during rather a long period of time.     

A class representative model for Pure Parsimony Haplotyping under uncertain data

The Pure Parsimony Haplotyping (PPH) problem is a NP-hard combinatorial optimization problem that consists of finding the minimum number of haplotypes necessary to explain a given set of genotypes. PPH has attracted more and more attention in recent years due to its importance in analysis of many fine-scale genetic data. Its application fields range from mapping complex disease genes to inferring population histories, passing through designing drugs, functional genomics and pharmacogenetics. In this article we investigate, for the first time, a recent version of PPH called the Pure Parsimony Haplotype problem under Uncertain Data (PPH-UD). This version mainly arises when the input genotypes are not accurate, i.e., when some single nucleotide polymorphisms are missing or affected by errors. We propose an exact approach to solution of PPH-UD based on an extended version of Catanzaro et al.[1] class representative model for PPH, currently the state-of-the-art integer programming model for PPH. The model is efficient, accurate, compact, polynomial-sized, easy to implement, solvable with any solver for mixed integer programming, and usable in all those cases for which the parsimony criterion is well suited for haplotype estimation.