A strategy for clone selection under different production conditions

Top performing clones have failed at the manufacturing scale while the true best performer may have been rejected early in the screening process. Therefore, the ability to screen multiple clones in complex fed-batch processes using multiple process variations can be used to assess robustness and to identify critical factors. This dynamic ranking of clones' strategy requires the execution of many parallel experiments than traditional approaches. Therefore, this approach is best suited for micro-bioreactor models which can perform hundreds of experiments quickly and efficiently. In this study, a fully monitored and controlled small scale platform was used to screen eight CHO clones producing a recombinant monoclonal antibody across several process variations, including different feeding strategies, temperature shifts and pH control profiles. The first screen utilized 240 micro-bioreactors were run for two weeks for this assessment of the scale-down model as a high-throughput tool for clone evaluation. The richness of the outcome data enable to clearly identify the best and worst clone as well as process in term of maximum monoclonal antibody titer. The follow-up comparison study utilized 180 micro-bioreactors in a full factorial design and a subset of 12 clone/process combinations was selected to be run parallel in duplicate shake flasks. Good correlation between the micro-bioreactor predictions and those made in shake flasks with a Pearson correlation value of 0.94. The results also demonstrate that this micro-scale system can perform clone screening and process optimization for gaining significant titer improvements simultaneously. This dynamic ranking strategy can support better choices of production clones.     

One-year clinical follow-up of a registry evaluating a percutaneous revascularisation strategy combining a pre-specified simple selection process with the use of a new thin-strut bare cobalt-chromium stent

Objectives. To evaluate clinical events in a specifically selected cohort of patients with obstructive coronary artery disease (CAD), using a new generation thin-strut bare cobalt-chromium coronary stent. Methods. Patients with single- or multi-vessel, stable or unstable CAD eligible for percutaneous implantation of at least one bare cobalt-chromium stent were evaluated in a single-centre registry. Prospective pre-specified criteria for bare cobalt-chromium stent implantation in our centre were: any acute ST-elevation myocardial infarction (MI), otherwise 1) de novo coronary lesion, and 2) lesion length <20 mm, and 3) reference vessel diameter >2.6 mm, and 4) no diabetes, unless reference vessel diameter >3.5 mm. Endpoints, retrospectively collected, were death, MI and clinically driven target-lesion revascularisation (TLR) and target-vessel revascularisation (TVR) after 12 months. Results. Between September 2005 and June 2007, 712 patients (48.7% one-vessel, 29.9% two-vessel, 20% three-vessel and 1.4% left main disease; 7.9% diabetics) were treated with 800 bare cobalt-chromium stents, for stable angina (40.9%), unstable angina (20.9%) or acute ST-elevation MI (38.2%). The procedural success rate was 99.3%. Peri-procedural MI rate was 2.2% in the semi-elective group. At 12 months there were 17 deaths (2.4%), of which nine non-cardiac, 20 (2.8%) MI, 19 (2.7%) TLR and 29 (4.1%) TVR. Early and late definite stent thrombosis occurred in four (0.6%) and three (0.4%) patients, respectively. Conclusion. A strategy aimed at minimising drug-eluting stent use and combining a pre-specified simple selection process with the use of a new thin-strut bare cobalt-chromium stent is safe and effective at one-year clinical follow-up. (Neth Heart J 2010;18:486-92.)     

Successful strategy for the selection of new strawberry-associated rhizobacteria antagonistic to Verticillium wilt

In order to isolate and characterize new strawberry-associated bacteria antagonistic to the soil-borne pathogenic fungus Verticillium dahliae Kleb., rhizobacterial populations from two different strawberry species, Greenish Strawberry (Fragaria viridis) and Garden Strawberry (F. x ananassa) obtained after plating onto King's B and glycerol-arginine agar, were screened for in vitro antagonism toward V. dahliae. The proportion of isolates with antifungal activity determined in in vitro assay against V. dahliae was higher for the Garden Strawberry than for the Greenish Strawberry. From 300 isolates, 20 isolates with strong antifungal activity were selected characterized by physiological profiling and molecular fingerprinting methods. Diversity among the isolates was characterized with molecular fingerprints using amplified ribosomal DNA restriction analysis (ARDRA) and the more discriminating BOX-PCR fingerprint method. The physiological profiles were well correlated with molecular fingerprinting pattern analysis. Significant reduction of Verticillium wilt by bacterial dipping bath treatment was shown in the greenhouse and in fields naturally infested by V. dahliae. The relative increase of yield ranged from 117% (Streptomyces albidoflavus S1) to 344% (Pseudomonas fluorescens P10) in greenhouse trials, and 113% (Streptomyces albidoflavus S1) to 247% (Pseudomonas fluorescens P6) in field trials. Evaluation resulted in the selection of three effective biocontrol agents (Pseudomonas fluorescens P6, P10, and Streptomyces diastatochromogenes S9) antagonistic to the Verticillium wilt pathogen.     

Population genetics: the signature of selection

There is hope that the structure of molecular variation within populations can give evidence for recent adaptive evolution. New work on Drosophila genes that seem to have been subject to adaptive changes illustrates the difficulties in calculating the statistical significance of data trends that seem to show this.     

A new practical tool for deriving a functional signature for herbaceous vegetation

Hypothesis: For any one time and place a ‘functional signature’ can be derived for a sample of herbaceous vegetation in a way that concisely represents the balance between the different clusters of functional attributes that are present among component species. Methods: We developed a spreadsheet‐based tool for calculating functional signatures within the context of the C‐S‐R system of plant functional types. We used the tool to calculate and compare signatures for specimen British vegetation samples which differed in management regime and location in time. Conclusion: The integrative power of the ‘C‐S‐R signature’ is useful in comparative studies involving widely differing samples. Movements in the signature can be used to indicate degree of resistance, resilience, eutrophication and dereliction. Systems of plant functional types other than C‐S‐R might also be approached in this way. Availability: The tool can be downloaded free of charge from the first author's web pages or from the journal's electronic archive.     

Genetic heterogeneity and selection signature at the KIT gene in pigs showing different coat colours and patterns

Mutations in the porcine KIT gene (Dominant white locus) have been shown to affect coat colours and colour distribution in pigs. We analysed this gene in several pig breeds and populations (Sicilian black, completely black or with white patches; Cinta Senese; grey local population; Large White; Duroc; Hampshire; Pietrain; wild boar; Meishan) with different coat colours and patterns, genotyping a few polymorphisms. The 21 exons and parts of the intronic regions were sequenced in these pigs and 69 polymorphisms were identified. The grey-roan coat colour observed in a local grey population was completely associated with a 4-bp deletion of intron 18 in a single copy KIT gene, providing evidence that this mutation characterizes the I^d allele described in the early genetic literature. The white patches observed in black Sicilian pigs were not completely associated with the presence of a duplicated KIT allele (I^p), suggesting that genetic heterogeneity is a possible cause of different coat colours in this breed. Selection signature was evident at the KIT gene in two different belted pig breeds, Hampshire and Cinta Senese. The same mutation(s) may cause the belted phenotype in these breeds that originated in the 18th–19th centuries from English pigs (Hampshire) and in Tuscany (Italy) in the 14th century (Cinta Senese). Phylogenetic relationships of 28 inferred KIT haplotypes indicated two clades: one of Asian origin that included Meishan and a few Sicilian black haplotypes and another of European origin.     

Plasmid DNA microgels for a therapeutical strategy combining the delivery of genes and anticancer drugs

Plasmid DNA (pDNA) is encapsulated into biocompatible microgels by an inverse microemulsion polymerization method. Plasmid DNA and doxorubicin are successfully released from pDNA microgels and their release profiles are characterized by appropriate release models. The co-delivery of genes and drugs from the microgels is evaluated as an enhancer of clinical treatment. Moreover, the release of the encapsulated pDNA is capable of transfection in vitro resulting in the expression of p53 protein. As a whole, a novel pDNA-based system is described that may find biomedical uses, especially in the cancer treatment through the combined action of chemotherapy and gene delivery approach.     

On optimal selection of summary statistics for approximate Bayesian computation

How best to summarize large and complex datasets is a problem that arises in many areas of science. We approach it from the point of view of seeking data summaries that minimize the average squared error of the posterior distribution for a parameter of interest under approximate Bayesian computation (ABC). In ABC, simulation under the model replaces computation of the likelihood, which is convenient for many complex models. Simulated and observed datasets are usually compared using summary statistics, typically in practice chosen on the basis of the investigator's intuition and established practice in the field. We propose two algorithms for automated choice of efficient data summaries. Firstly, we motivate minimisation of the estimated entropy of the posterior approximation as a heuristic for the selection of summary statistics. Secondly, we propose a two-stage procedure: the minimum-entropy algorithm is used to identify simulated datasets close to that observed, and these are each successively regarded as observed datasets for which the mean root integrated squared error of the ABC posterior approximation is minimized over sets of summary statistics. In a simulation study, we both singly and jointly inferred the scaled mutation and recombination parameters from a population sample of DNA sequences. The computationally-fast minimum entropy algorithm showed a modest improvement over existing methods while our two-stage procedure showed substantial and highly-significant further improvement for both univariate and bivariate inferences. We found that the optimal set of summary statistics was highly dataset specific, suggesting that more generally there may be no globally-optimal choice, which argues for a new selection for each dataset even if the model and target of inference are unchanged.     

Model-based rational strategy for chromatographic resin selection

A model-based rational strategy for the selection of chromatographic resins is presented. The main question being addressed is that of selecting the most optimal chromatographic resin from a few promising alternatives. The methodology starts with chromatographic modeling,parameters acquisition, and model validation, followed by model-based optimization of the chromatographic separation for the resins of interest. Finally, the resins are rationally evaluated based on their optimized operating conditions and performance metrics such as product purity, yield, concentration, throughput, productivity, and cost. Resin evaluation proceeds by two main approaches. In the first approach, Pareto frontiers from multi-objective optimization of conflicting objectives are overlaid for different resins, enabling direct visualization and comparison of resin performances based on the feasible solution space. The second approach involves the transformation of the resin performances into weighted resin scores, enabling the simultaneous consideration of multiple performance metrics and the setting of priorities. The proposed model-based resin selection strategy was illustrated by evaluating three mixed mode adsorbents (ADH, PPA, and HEA) for the separation of a ternary mixture of bovine serum albumin, ovalbumin, and amyloglucosidase. In order of decreasing weighted resin score or performance, the top three resins for this separation were ADH [PPA[HEA. The proposed model-based approach could be a suitable alternative to column scouting during process development, the main strengths being that minimal experimentation is required and resins are evaluated under their ideal working conditions, enabling a fair comparison. This work also demonstrates the application of column modeling and optimization to mixed mode chromatography.     

Opposite responses to selection and where to find them

We generally expect traits to evolve in the same direction as selection. However, many organisms possess traits that appear to be costly for individuals, while plant and animal breeding experiments reveal that selection may lead to no response or even negative responses to selection. We formalize both of these instances as cases of “opposite responses to selection.” Using quantitative genetic models for the response to selection, we outline when opposite responses to selection should be expected. These typically occur when social selection opposes direct selection, when individuals interact with others less related to them than a random member of the population, and if the genetic covariance between direct and indirect effects is negative. We discuss the likelihood of each of these occurring in nature and therefore summarize how frequent opposite responses to selection are likely to be. This links several evolutionary phenomena within a single framework.     

A feature selection approach for identification of signature genes from SAGE data

Background  

One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements.     

A new improved strategy for the selection of cold-adapted antagonist yeasts to control postharvest pear diseases

Postharvest diseases cause considerable losses of harvested fruits during transportation and storage. Many yeast species have been reported as good antagonists against postharvest pear pathogens. In this work, we used a novel selection strategy that involves the isolation of yeasts from washing fluids, showing biocontrol activity against a regional Penicillium expansum strain (primary screening), originally obtained from fruit wounds after long time storage at ?1/0°C. About 26 isolates representative of the 11 yeast species identified in the 27 selected washing waters were chosen to be evaluated in a secondary screening against a regional Botrytis cinerea strain on pear wounds. Among yeasts tested, 38% showed complete control of P. expansum, but only 15% reduced the decay incidence of B. cinerea to 60–80% at ?1/0°C. These results reveal that some of the yeasts found can be biological alternatives to fungicides in the control of P. expansum and B. cinerea infections. Based on the data obtained, our strategy seems to be much more effective than the previously reported methods in obtaining successful biocontrol agents.     

Evolutionarily stable strategy in a sex- and frequency-dependent selection model

In this paper, a sex-dependent matrix game haploid model is investigated. For this model, since the phenotypes of female and male individuals are determined by alleles located at a single locus and are sex dependent, any given genotype corresponds to a strategy pair. Thus, a strategy pair is an ESS if and only if the allele corresponding to this strategy pair cannot be invaded by any mutant allele. We show that an ESS equilibrium must be locally asymptotically stable if it exists.     

The signature of positive selection at randomly chosen loci

In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequency alleles drift to fixation and no longer contribute to polymorphism, while linkage disequilibrium is broken down by recombination. As a result, loci chosen without independent evidence of recent selection are not expected to exhibit either of these features, even if they have been affected by numerous sweeps in their genealogical history. How then can we explain the patterns in the data? One possibility is population structure, with unequal sampling from different subpopulations. Alternatively, positive selection may not operate as is commonly modeled. In particular, the rate of fixation of advantageous mutations may have increased in the recent past.     

Micro-scale signature of purifying selection in Marburg virus genomes

In the seven protein-coding genes in the Marburg virus (MARV) genome, the synonymous nucleotide diversity substantially exceeded the nonsynonymous nucleotide diversity, indicating strong purifying selection. Likewise, there was evidence of purifying selection on 5'UTR and 3'UTR, where nucleotide diversity (pi) was significantly less than piS in the coding regions. Nonsynonymous polymorphic sites showed significantly reduced mean gene diversity in comparison to other polymorphic sites, indicating that purifying selection at certain slightly deleterious nonsynonymous polymorphisms is ongoing. Moreover, nonsynonymous polymorphic sites showed significantly reduced gene diversity in comparison to adjacent synonymous sites, even though the vast majority of such adjacent synonymous sites were in the same codon or an adjacent codon. Thus purifying selection, in conjunction with recombination and/or backward mutation, can act to break up linkage relationships at a micro-scale in the MARV genome. The ability of purifying selection to break up linkage between synonymous and nonsynonymous polymorphisms on such a fine scale has not been reported in any other genome.     

The signature of positive selection on standing genetic variation

Considerable interest is focused on the use of polymorphism data to identify regions of the genome that underlie recent adaptations. These searches are guided by a simple model of positive selection, in which a mutation is favored as soon as it arises. This assumption may not be realistic, as environmental changes and range expansions may lead previously neutral or deleterious alleles to become beneficial. We examine what effect this mode of selection has on patterns of variation at linked neutral sites by implementing a new coalescent model of positive directional selection on standing variation. In this model, a neutral allele arises and drifts in the population, then at frequency f becomes beneficial, and eventually reaches fixation. Depending on the value of f, this scenario can lead to a large variance in allele frequency spectra and in levels of linkage disequilibrium at linked, neutral sites. In particular, for intermediate f, the beneficial substitution often leads to a loss of rare alleles--a pattern that differs markedly from the signature of directional selection currently relied on by researchers. These findings highlight the importance of an accurate characterization of the effects of positive selection, if we are to reliably identify recent adaptations from polymorphism data.