Differential Functional Constraints Cause Strain-Level Endemism in Polynucleobacter Populations.

The adaptation of bacterial lineages to local environmental conditions creates the potential for broader genotypic diversity within a species, which can enable a species to dominate across ecological gradients because of niche flexibility. The genus Polynucleobacter maintains both free-living and symbiotic ecotypes and maintains an apparently ubiquitous distribution in freshwater ecosystems. Subspecies-level resolution supplemented with metagenome-derived genotype analysis revealed that differential functional constraints, not geographic distance, produce and maintain strain-level genetic conservation in Polynucleobacter populations across three geographically proximal riverine environments. Genes associated with cofactor biosynthesis and one-carbon metabolism showed habitat specificity, and protein-coding genes of unknown function and membrane transport proteins were under positive selection across each habitat. Characterized by different median ratios of nonsynonymous to synonymous evolutionary changes (dN/dS ratios) and a limited but statistically significant negative correlation between the dN/dS ratio and codon usage bias between habitats, the free-living and core genotypes were observed to be evolving under strong purifying selection pressure. Highlighting the potential role of genetic adaptation to the local environment, the two-component system protein-coding genes were highly stable (dN/dS ratio, < 0.03). These results suggest that despite the impact of the habitat on genetic diversity, and hence niche partition, strong environmental selection pressure maintains a conserved core genome for Polynucleobacter populations. IMPORTANCE Understanding the biological factors influencing habitat-wide genetic endemism is important for explaining observed biogeographic patterns. Polynucleobacter is a genus of bacteria that seems to have found a way to colonize myriad freshwater ecosystems and by doing so has become one of the most abundant bacteria in these environments. We sequenced metagenomes from locations across the Chicago River system and assembled Polynucleobacter genomes from different sites and compared how the nucleotide composition, gene codon usage, and the ratio of synonymous (codes for the same amino acid) to nonsynonymous (codes for a different amino acid) mutations varied across these population genomes at each site. The environmental pressures at each site drove purifying selection for functional traits that maintained a streamlined core genome across the Chicago River Polynucleobacter population while allowing for site-specific genomic adaptation. These adaptations enable Polynucleobacter to become dominant across different riverine environmental gradients

ClassTR: Classifying Within-Host Heterogeneity Based on Tandem Repeats with Application to Mycobacterium tuberculosis Infections.

Genomic tools have revealed genetically diverse pathogens within some hosts. Within-host pathogen diversity, which we refer to as "complex infection", is increasingly recognized as a determinant of treatment outcome for infections like tuberculosis. Complex infection arises through two mechanisms: within-host mutation (which results in clonal heterogeneity) and reinfection (which results in mixed infections). Estimates of the frequency of within-host mutation and reinfection in populations are critical for understanding the natural history of disease. These estimates influence projections of disease trends and effects of interventions. The genotyping technique MLVA (multiple loci variable-number tandem repeats analysis) can identify complex infections, but the current method to distinguish clonal heterogeneity from mixed infections is based on a rather simple rule. Here we describe ClassTR, a method which leverages MLVA information from isolates collected in a population to distinguish mixed infections from clonal heterogeneity. We formulate the resolution of complex infections into their constituent strains as an optimization problem, and show its NP-completeness. We solve it efficiently by using mixed integer linear programming and graph decomposition. Once the complex infections are resolved into their constituent strains, ClassTR probabilistically classifies isolates as clonally heterogeneous or mixed by using a model of tandem repeat evolution. We first compare ClassTR with the standard rule-based classification on 100 simulated datasets. ClassTR outperforms the standard method, improving classification accuracy from 48% to 80%. We then apply ClassTR to a sample of 436 strains collected from tuberculosis patients in a South African community, of which 92 had complex infections. We find that ClassTR assigns an alternate classification to 18 of the 92 complex infections, suggesting important differences in practice. By explicitly modeling tandem repeat evolution, ClassTR helps to improve our understanding of the mechanisms driving within-host diversity of pathogens like Mycobacterium tuberculosis

Changes in metabolic phenotypes of Plasmodium falciparum in vitro cultures during gametocyte development.

BACKGROUND: Gametocytes are the Plasmodium life stage that is solely responsible for malaria transmission. Despite their important role in perpetuating malaria, gametocyte differentiation and development is poorly understood. METHODS: To shed light on the biochemical changes that occur during asexual and gametocyte development, metabolic characterization of media from in vitro intra-erythrocytic Plasmodium falciparum cultures was performed throughout gametocyte development by applying 1H nuclear magnetic spectroscopy, and using sham erythrocyte cultures as controls. Spectral differences between parasite and sham cultures were assessed via principal component analyses and partial-least squares analyses, and univariate statistical methods. RESULTS: Clear parasite-associated changes in metabolism were observed throughout the culture period, revealing differences between asexual parasites and gametocyte stages. With culture progression and development of gametocytes, parasitic release of the glycolytic end products lactate, pyruvate, alanine, and glycerol, were found to be dramatically reduced whilst acetate release was greatly increased. Also, uptake of lipid moieties CH(2), CH(3), and CH = CH-CH(2)-CH(2) increased throughout gametocyte development, peaking with maturity. CONCLUSIONS: This study uniquely presents an initial characterization of the metabolic exchange between parasite and culture medium during in vitro P. falciparum gametocyte culture. Results suggest that energy metabolism and lipid utilization between the asexual stages and gametocytes is different. This study provides new insights for gametocyte-specific nutritional requirements to aid future optimization and standardization of in vitro gametocyte cultivation, and highlights areas of novel gametocyte cell biology that deserve to be studied in greater detail and may yield new targets for transmission-blocking drugs

A mammalian circadian clock model incorporating daytime expression elements

Models of the mammalian clock have traditionally been based around two feedback loops-the self-repression of Per/Cry by interfering with activation by BMAL/CLOCK, and the repression of Bmal/Clock by the REV-ERB proteins. Recent experimental evidence suggests that the D-box, a transcription factor binding site associated with daytime expression, plays a larger role in clock function than has previously been understood. We present a simplified clock model that highlights the role of the D-box and illustrate an approach for finding maximum-entropy ensembles of model parameters, given experimentally imposed constraints. Parameter variability can be mitigated using prior probability distributions derived from genome-wide studies of cellular kinetics. Our model reproduces predictions concerning the dual regulation of Cry1 by the D-box and Rev-ErbA/ROR response element (RRE) promoter elements and allows for ensemble-based predictions of phase response curves (PRCs). Nonphotic signals such as Neuropeptide Y (NPY) may act by promoting Cry1 expression, whereas photic signals likely act by stimulating expression from the E/E' box. Ensemble generation with parameter probability restraints reveals more about a model's behavior than a single optimal parameter set

Optimal Partial Harvesting Schedule for Aquaculture Operations

Abstract When growth is density dependent, partial harvest of the standing stock of cultured species (fish or shrimp) over the course of the growing season (i.e., partial harvesting) would decrease competition and thereby increase individual growth rates and total yield. Existing studies in optimal harvest management of aquaculture operations, however, have not provided a rigorous framework for determining "discrete" partial harvesting (i.e., partially harvest the cultured species at several discrete points until the final harvest). In this paper, we develop a partial harvesting model that is capable of addressing discrete partial harvesting and other partial harvesting using impulsive control theory. We derive necessary conditions of the efficient partial harvesting scheme for a single production cycle. We also present a numerical example to illustrate how partial harvesting can improve the profitability of an aquaculture enterprise compared to single-batch harvesting and gradual thinning. The study results indicate that well-designed partial harvesting schemes can enhance the profitability of aquaculture operations.Partial harvesting, impulsive control theory, aquaculture., Livestock Production/Industries, C61, Q22,

A modified bats echolocation-based algorithm for solving constrained optimisation problems

A modified adaptive bats sonar algorithm (MABSA) is presented that utilises the concept of echolocation of a colony of bats to find prey. The proposed algorithm is applied to solve the constrained optimisation problems coupled with penalty function method as constraint handling technique. The performance of the algorithm is verified through rigorous tests with four constrained optimisation benchmark test functions. The acquired results show that the proposed algorithm performs better to find optimum solution in terms of accuracy and convergence speed. The statistical results of MABSA to solve all the test functions also has been compared with the results from several existing algorithms taken from literature on similar test functions. The comparative study has shown that MABSA outperforms other establish algorithms, and thus, it can be an efficient alternative method in the solving constrained optimisation problems