Using partition designs to enhance purification process understanding

Characterization of purification processes by identifying significant input parameters and establishing predictive models is vital to developing robust processes. Current experimental design approaches restrict analysis to one process step at a time, which can severely limit the ability to identify interactions between process steps. This can be overcome by the use of partition designs which can model multiple, sequential process steps simultaneously. This paper presents the application of partition designs to a monoclonal antibody purification process. Three sequential purification steps were modeled using both traditional experimental designs and partition designs and the results compared as a proof of concept study. The partition and traditional design approaches identified the same input parameters within each process step that significantly affected the product quality output examined. The partition design also identified significant interactions between input parameters across process steps that could not be uncovered by the traditional approach. Biotechnol. Bioeng. 2010;107: 814–824. © 2010 Wiley Periodicals, Inc.     

The evolutionary dynamics of the Helena retrotransposon revealed by sequenced Drosophila genomes

Background  

Several studies have shown that genomes contain a mixture of transposable elements, some of which are still active and others ancient relics that have degenerated. This is true for the non-LTR retrotransposon Helena, of which only degenerate sequences have been shown to be present in some species (Drosophila melanogaster), whereas putatively active sequences are present in others (D. simulans). Combining experimental and population analyses with the sequence analysis of the 12 Drosophila genomes, we have investigated the evolution of Helena, and propose a possible scenario for the evolution of this element.     

Identifying a high fraction of the human genome to be under selective constraint using GERP++

Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint. One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous, highly scoring nucleotide positions. Here we present GERP++, a new tool that uses maximum likelihood evolutionary rate estimation for position-specific scoring and, in contrast to previous bottom-up methods, a novel dynamic programming approach to subsequently define constrained elements. GERP++ evaluates a richer set of candidate element breakpoints and ranks them based on statistical significance, eliminating the need for biased heuristic extension techniques. Using GERP++ we identify over 1.3 million constrained elements spanning over 7% of the human genome. We predict a higher fraction than earlier estimates largely due to the annotation of longer constrained elements, which improves one to one correspondence between predicted elements with known functional sequences. GERP++ is an efficient and effective tool to provide both nucleotide- and element-level constraint scores within deep multiple sequence alignments.     

<Emphasis Type="Italic">Post hoc</Emphasis> pattern matching: assigning significance to statistically defined expression patterns in single channel microarray data

Background  

Researchers using RNA expression microarrays in experimental designs with more than two treatment groups often identify statistically significant genes with ANOVA approaches. However, the ANOVA test does not discriminate which of the multiple treatment groups differ from one another. Thus, post hoc tests, such as linear contrasts, template correlations, and pairwise comparisons are used. Linear contrasts and template correlations work extremely well, especially when the researcher has a priori information pointing to a particular pattern/template among the different treatment groups. Further, all pairwise comparisons can be used to identify particular, treatment group-dependent patterns of gene expression. However, these approaches are biased by the researcher's assumptions, and some treatment-based patterns may fail to be detected using these approaches. Finally, different patterns may have different probabilities of occurring by chance, importantly influencing researchers' conclusions about a pattern and its constituent genes.     

Arabidopsis and cotton (Gossypium) as models for studying copia-like retrotransposon evolution

Transposable elements have likely played an important role in species evolution. Questions of transposable element evolution, therefore, are best addressed within the context of their hosts' evolutionary history. This approach requires efficient means to identify and characterize transposable elements among related species. For the copia-like retrotransposons, this has recently become possible due to the development of a polymerase chain reaction assay to identify these sequences among plants. In this paper, the evolution of copia-like retrotransposons is evaluated within the context of the evolutionary history of two plant models, Arabidopsis thaliana and cotton (Gossypium).     

A comparison of methods for adaptive treatment selection

Traditionally drug development is generally divided into three phases which have different aims and objectives. Recently so-called adaptive seamless designs that allow combination of the objectives of different development phases into a single trial have gained much interest. Adaptive trials combining treatment selection typical for Phase II and confirmation of efficacy as in Phase III are referred to as adaptive seamless Phase II/III designs and are considered in this paper. We compared four methods for adaptive treatment selection, namely the classical Dunnett test, an adaptive version of the Dunnett test based on the conditional error approach, the combination test approach, and an approach within the classical group-sequential framework. The latter two approaches have only recently been published. In a simulation study we found that no one method dominates the others in terms of power apart from the adaptive Dunnett test that dominates the classical Dunnett by construction. Furthermore, scenarios under which one approach outperforms others are described.     

Inferring species phylogenies from multiple genes: concatenated sequence tree versus consensus gene tree

Phylogenetic trees from multiple genes can be obtained in two fundamentally different ways. In one, gene sequences are concatenated into a super-gene alignment, which is then analyzed to generate the species tree. In the other, phylogenies are inferred separately from each gene, and a consensus of these gene phylogenies is used to represent the species tree. Here, we have compared these two approaches by means of computer simulation, using 448 parameter sets, including evolutionary rate, sequence length, base composition, and transition/transversion rate bias. In these simulations, we emphasized a worst-case scenario analysis in which 100 replicate datasets for each evolutionary parameter set (gene) were generated, and the replicate dataset that produced a tree topology showing the largest number of phylogenetic errors was selected to represent that parameter set. Both randomly selected and worst-case replicates were utilized to compare the consensus and concatenation approaches primarily using the neighbor-joining (NJ) method. We find that the concatenation approach yields more accurate trees, even when the sequences concatenated have evolved with very different substitution patterns and no attempts are made to accommodate these differences while inferring phylogenies. These results appear to hold true for parsimony and likelihood methods as well. The concatenation approach shows >95% accuracy with only 10 genes. However, this gain in accuracy is sometimes accompanied by reinforcement of certain systematic biases, resulting in spuriously high bootstrap support for incorrect partitions, whether we employ site, gene, or a combined bootstrap resampling approach. Therefore, it will be prudent to report the number of individual genes supporting an inferred clade in the concatenated sequence tree, in addition to the bootstrap support.     

Modeling of protein spatial structure using tritium planigraphy

The results of protein spatial structure modeling using the tritium planigraphy technique are presented. The knowledge of 3D structure of macromolecules is obligatory for understanding the basic mechanisms of interaction in biological systems and complex technological processes. Known limitations of the X-ray analysis (crystal state) and NMR (molecular weight) make it necessary to seek new approaches to modeling the spatial structure of proteins. Semiempirical tritium planigraphy is one of these approaches. The method is based on bombardment of the object with a beam of hot tritium atoms (E _at ≥ 0.3 eV) and computer simulation. On the example of proteins of different structural classes, we show that this integrated approach can yield a 3D model well consistent with the X-ray data. An important factor is the sequence of searching for contacts between secondary structure elements: the best fit with the native structure is achieved by assembling the elements from the N- to the C-terminus of the polypeptide chain.     

SEED SET AND SEED MASS IN IPOMOPSIS AGGREGATA: VARIANCE PARTITIONING AND INFERENCES ABOUT POSTPOLLINATION SELECTION

Events that follow pollination, such as pollen-tube growth and seed maturation, comprise an important phase of angiosperm reproduction. Differential success during this “postpollination” phase may represent phenotypic selection, including sexual selection, or interaction between parents caused, for example, by their genetic similarity. By providing a detailed partitioning of variance in success, diallel crossing designs offer great potential to determine which processes are occurring and their relative magnitudes. We performed three partial diallels with the montane herb Ipomopsis aggregata, using a large sample of parental plants (69 total). Embedded in the designs were crossing-distance treatments of 1 m, 10 m, and 100 m, reflecting a range of parental genetic similarity. We partitioned phenotypic variance in seed set per fruit into six components using restricted maximum-likelihood (REML) analysis. For one diallel, we also partitioned variance in seed mass into five components, and estimated two components of covariance between seed set and mass. Variance caused by maternal effects (V_mat) comprised 12%–35% of total variance in seed set and 62% of variance in seed mass, and there was a significant negative environmental covariance between seed set and seed mass. Parental interaction made no detectable contribution to phenotypic variance in either of our measures of postpollination success, although crossing distance did contribute slightly but significantly to fit of the model in some cases. Finally, there was no detectable paternal variance (V_pat) in seed set or seed mass. These results are in keeping with reports from other studies of natural plant populations. The finding of little or no paternal variance in particular suggests little scope for postpollination sexual selection through the male function of cosexual plants such as I. aggregata.     

Surveying Hard-to-Reach Groups Through Sampled Respondents in a Social Network

The sampling frame in most social science surveys misses members of certain groups, such as the homeless or individuals living with HIV. These groups are known as hard-to-reach groups. One strategy for learning about these groups, or subpopulations, involves reaching hard-to-reach group members through their social network. In this paper we compare the efficiency of two common methods for subpopulation size estimation using data from standard surveys. These designs are examples of mental link tracing designs. These designs begin with a randomly sampled set of network members (nodes) and then reach other nodes indirectly through questions asked to the sampled nodes. Mental link tracing designs cost significantly less than traditional link tracing designs, yet introduce additional sources of potential bias. We examine the influence of one such source of bias using simulation studies. We then demonstrate our findings using data from the General Social Survey collected in 2004 and 2006. Additionally, we provide survey design suggestions for future surveys incorporating such designs.     

Analysis of non-peptidic compounds as potential malarial inhibitors against Plasmodial cysteine proteases via integrated virtual screening workflow

Falcipain-2 (FP-2) and falcipain-3 (FP-3), haemoglobin-degrading enzymes in Plasmodium falciparum, are validated drug targets for the development of effective inhibitors against malaria. However, no commercial drug-targeting falcipains has been developed despite their central role in the life cycle of the parasites. In this work, in silico approaches are used to identify key structural elements that control the binding and selectivity of a diverse set of non-peptidic compounds onto FP-2, FP-3 and homologues from other Plasmodium species as well as human cathepsins. Hotspot residues and the underlying non-covalent interactions, important for the binding of ligands, are identified by interaction fingerprint analysis between the proteases and 2-cyanopyridine derivatives (best hits). It is observed that the size and chemical type of substituent groups within 2-cyanopyridine derivatives determine the strength of protein–ligand interactions. This research presents novel results that can further be exploited in the structure-based molecular-guided design of more potent antimalarial drugs.     

Two distinct cis-acting elements are involved in light-dependent activation of the pea elip promoter

Light activation of the pea (Pisum sativum) elip gene promoter was analysed in transgenic plants and in transiently transfected plant protoplasts. A series of promoter deletions fused to the gusA reporter was tested, and the results obtained by the two experimental approaches were in good agreement. We identified two nucleotide sequence elements involved in light-regulated expression of the elip gene. One element is similar to the GT1 binding site of the rbcS-3A gene, and the other resembles a G-box-like ACGT element. The region containing both elements was able to confer light responsiveness on a heterologous basic promoter. Electrophoretic mobility shift assays demonstrated that each element is specifically recognized by DNA-binding proteins present in nuclear extracts from pea seedlings. The G-box-like ACGT element is necessary but not sufficient for light inducibility, indicating that the two elements act together in confering light responsiveness.     

The pogo transposable element family of Drosophila melanogaster.

Summary A 190 by insertion is associated with the white-eosin mutation in Drosophila melanogaster. This insertion is a member of a family of transposable elements, pogo elements, which is of the same class as the P and hobo elements of D. melanogaster. Strains typically have many copies of a 190 by element, 10–15 elements 1.1–1.5 kb in size and several copies of a 2.1 kb element. The smaller elements all appear to be derived from the largest by single internal deletions so that all elements share terminal sequences. They either always insert at the dinucleotide TA and have perfect 21 bp terminal inverse repeats, or have 22 by inverse repeats and produce no duplication upon insertion. Analysis by DNA blotting of their distribution and occupancy of insertion sites in different strains suggests that they may be less mobile than P or hobo. The DNA sequence of the largest element has two long open reading frames on one strand which are joined by splicing as indicated by cDNA analysis. RNAs of this strand are made, whose sizes are similar to the major size classes of elements. A protein predicted by the DNA sequence has significant homology with a human centrosomal-associated protein, CENP-B. Homologous sequences were not detected in other Drosophila species, suggesting that this transposable element family may be restricted to D. melanogaster.     

Reinterpreting Responsiveness for Health Systems Research in Low and Middle‐Income Countries

The ethical concept of responsiveness has largely been interpreted in the context of international clinical research. In light of the increasing conduct of externally funded health systems research (HSR) in low‐ and middle‐income countries (LMICs), this article examines how responsiveness might be understood for such research and how it can be applied. It contends that four features (amongst others) set HSR in LMICs apart from international clinical research: a focus on systems; being context‐driven; being policy‐driven; and being closely linked to development objectives. These features support reinterpreting responsiveness for HSR in LMICs as responsiveness to systems needs, where health system performance assessments can be relied upon to identify systems needs, and/or responsiveness to systems priorities, which entails aligning research with HSR priorities set through country‐owned processes involving national and sub‐national policymakers from host countries. Both concepts may be difficult to achieve in practice. Country ownership is not an established fact for many countries and alignment to their priorities may be meaningless without it. It is argued that more work is, therefore, needed to identify strategies for how the responsiveness requirement can be ethically fulfilled for HSR in LMICs under non‐ideal conditions such as where host countries have not set HSR priorities via country‐owned processes. Embeddedness is proposed as one approach that could be the focus of further development.     

Uncovering QTL for resistance and survival time to Philasterides dicentrarchi in turbot (Scophthalmus maximus)

Disease resistance‐related traits have received increasing importance in aquaculture breeding programs worldwide. Currently, genomic information offers new possibilities in breeding to address the improvement of this kind of traits. The turbot is one of the most promising European aquaculture species, and Philasterides dicentrarchi is a scuticociliate parasite causing fatal disease in farmed turbot. An appealing approach to fight against disease is to achieve a more robust broodstock, which could prevent or diminish the devastating effects of scuticociliatosis on farmed individuals. In the present study, a genome scan for quantitative trait loci (QTL) affecting resistance and survival time to P. dicentrarchi in four turbot families was carried out. The objectives were to identify QTL using different statistical approaches [linear regression (LR) and maximum likelihood (ML)] and to locate significantly associated markers for their application in genetic breeding strategies. Several genomic regions controlling resistance and survival time to P. dicentrarchi were detected. When analyzing each family separately, significant QTL for resistance were identified by the LR method in two linkage groups (LG1 and LG9) and for survival time in LG1, while the ML methodology identified QTL for resistance in LG9 and LG23 and for survival time in LG6 and LG23. The analysis of the total data set identified an additional significant QTL for resistance and survival time in LG3 with the LR method. Significant association between disease resistance‐related traits and genotypes was detected for several markers, a single one explaining up to 22% of the phenotypic variance. Obtained results will be essential to identify candidate genes for resistance and to apply them in marker‐assisted selection programs to improve turbot production.