A Critical Assessment of Vector Control for Dengue Prevention

Recently, the Vaccines to Vaccinate (v2V) initiative was reconfigured into the Partnership for Dengue Control (PDC), a multi-sponsored and independent initiative. This redirection is consistent with the growing consensus among the dengue-prevention community that no single intervention will be sufficient to control dengue disease. The PDC''s expectation is that when an effective dengue virus (DENV) vaccine is commercially available, the public health community will continue to rely on vector control because the two strategies complement and enhance one another. Although the concept of integrated intervention for dengue prevention is gaining increasingly broader acceptance, to date, no consensus has been reached regarding the details of how and what combination of approaches can be most effectively implemented to manage disease. To fill that gap, the PDC proposed a three step process: (1) a critical assessment of current vector control tools and those under development, (2) outlining a research agenda for determining, in a definitive way, what existing tools work best, and (3) determining how to combine the best vector control options, which have systematically been defined in this process, with DENV vaccines. To address the first step, the PDC convened a meeting of international experts during November 2013 in Washington, DC, to critically assess existing vector control interventions and tools under development. This report summarizes those deliberations.     

CAPRI: a Critical Assessment of PRedicted Interactions

CAPRI is a communitywide experiment to assess the capacity of protein-docking methods to predict protein-protein interactions. Nineteen groups participated in rounds 1 and 2 of CAPRI and submitted blind structure predictions for seven protein-protein complexes based on the known structure of the component proteins. The predictions were compared to the unpublished X-ray structures of the complexes. We describe here the motivations for launching CAPRI, the rules that we applied to select targets and run the experiment, and some conclusions that can already be drawn. The results stress the need for new scoring functions and for methods handling the conformation changes that were observed in some of the target systems. CAPRI has already been a powerful drive for the community of computational biologists who development docking algorithms. We hope that this issue of Proteins will also be of interest to the community of structural biologists, which we call upon to provide new targets for future rounds of CAPRI, and to all molecular biologists who view protein-protein recognition as an essential process.     

Intracerebral Microdialysis: Electrophysiological Evidence of a Critical Pitfall

Abstract: Using microdialysis probes incorporating an electrode for the recording of extracellular field potentials, we have found that microdialysis markedly inhibited the propagation of spreading depression. This effect was independent of the microdialysis flow rate and did not result from tissue injury following probe implantation. Increasing the K⁺ concentration in the perfused artificial CSF dose-dependently restored the propagation of spreading depression and revealed a large, synchronous transient increase in extracellular glutamate. These findings clearly illustrate that microdialysis can influence the experimental or pathological conditions under study, by buffering transient changes in the extracellular fluid composition. Epileptic seizures and ischaemia are two important conditions that may be prone to such a detrimental interaction.     

Metalloproteins and the Pyrite-based Origin of Life: A Critical Assessment

We critically examine the proposal by Wächtershäuser (Prokaryotes 1:275?C283, 2006a, Philos Trans R Soc Lond B Biol Sci 361: 787?C1808, 2006b) that putative transition metal binding sites in protein components of the translation machinery of hyperthermophiles provide evidence of a direct relationship with the FeS clusters of pyrite and thus indicate an autotrophic origin of life in volcanic environments. Analysis of completely sequenced cellular genomes of Bacteria, Archaea and Eucarya does not support the suggestion by Wächtershäuser (Prokaryotes 1:275?C283, 2006a, Philos Trans R Soc Lond B Biol Sci 361: 787?C1808, 2006b) that aminoacyl-tRNA synthetases and ribosomal proteins bear sequence signatures typical of strong covalent metal bonding whose absence in mesophilic species reveals a process of adaptation towards less extreme environments.     

Tryptophan-Independent Indole-3-Acetic Acid Synthesis: Critical Evaluation of the Evidence

Evidence for Trp-independent IAA synthesis is critically reevaluated in the light of tryptophan synthase proteome data, local IAA synthesis and Trp, indole-3-pyruvate, and IAA turnover.Trp-independent synthesis of indole-3-acetic acid (IAA) was proposed back in the early 1990s based on observations from Trp auxotrophs in maize (Zea mays; Wright et al., 1991) and Arabidopsis (Arabidopsis thaliana; Normanly et al., 1993). Recently, Wang et al. (2015) published new data suggesting that a cytosolic indole synthase (INS) may catalyze the first step separating the Trp-dependent and Trp-independent pathways in Arabidopsis. If this is the case, it would be a major breakthrough; however, in this article, I critically evaluate both recent and older evidence for the Trp-independent route and suggest that the INS is more likely to participate in Trp-dependent IAA production.The original work supporting Trp-independent IAA production was carried out prior to the availability of genome/proteome data and before the discovery that the final step of Trp-dependent IAA synthesis is carried out by a large number of YUCCA homologs operating in a highly localized manner (Zhao, 2008). I argue that experimental data supporting the Trp-independent route needs to be reconsidered in light of complete proteome data. Further, the evidence from feeding labeled compounds should be critically evaluated in light of recent data on the highly localized nature of IAA synthesis as well as older quantitative data on Trp, indole-3-pyruvic acid (IPA), and IAA turnover from my own laboratory (Cooney and Nonhebel, 1991). I conclude that evidence for the Trp-independent route is at best equivocal, and that it is not a conserved source of IAA in angiosperms.Figure 1 shows the major Trp-dependent route for IAA production whereby Trp, produced by the concerted action of Trp synthase α- and β-subunits, is converted to IAA in a further two steps catalyzed by Trp aminotransferase and the flavin monooxygenases commonly known as YUCCA (Mashiguchi et al., 2011; Won et al., 2011). This is compared with the Trp-independent route in which IAA may be produced from free indole by an unknown route (Ouyang et al., 2000; Wang et al., 2015).Open in a separate windowFigure 1.Outline of the major pathway for Trp-dependent IAA synthesis and the proposed Trp-independent route. The role proposed for Trp synthase beta (TSB) homologs discussed in the present paper is also shown. For clarity, reactions are simplified to show only the major compounds relevant to IAA synthesis.The Trp-independent route was originally based on data from Trp auxotrophs that have mutations in genes encoding either the α- or β-subunits of Trp synthase. The α-subunit catalyzes the removal of the side chain from indole-3-glycerol phosphate, passing the indole product directly to the β-subunit where the Trp side chain is created from a Ser substrate (Pan et al., 1997). In plants, this is a chloroplast-localized enzyme. Elevated levels of IAA have been reported in Trp auxotrophs of both maize and Arabidopsis. However, the trp3-1 and trp2-1 mutants of Arabidopsis, deficient in the α- and β-subunits, respectively, only showed an increase in total IAA measured following conjugate hydrolysis. No difference in free IAA levels was found (Normanly et al., 1993). The orange pericarp (orp) maize mutant was reported to have 50 times more IAA than the wild type (Wright et al., 1991). However, this was also total IAA; no data on free IAA were published. Work by Müller and Weiler (2000) indicated that IAA measured following conjugate hydrolysis could have originated via the degradation of indole-3-glycerol phosphate that accumulates in trp3-1 mutants. Further doubt regarding the accuracy of IAA measurements following conjugate hydrolysis has recently been published. Yu et al. (2015) have shown that conjugate hydrolysis treatment substantially overestimates the actual conjugated IAA due to degradation of glucobrassicin and proteins. In addition, neither report (Wright et al., 1991; Normanly et al., 1993) described a high auxin phenotype for the Trp auxotrophs. This contrasts with the superroot1 (sur1) and sur2 mutants, where the accumulation of indole intermediates resulted in a high level of free IAA as well as a high auxin phenotype (Boerjan et al., 1995; Delarue et al., 1998). It is therefore doubtful that Trp auxotrophs actually accumulate more IAA than the wild-type plants.In addition, proteome data have revealed new homologs of TSB in both Arabidopsis and maize that may contribute to Trp production in TSB mutants; these have not been considered in arguments supporting Trp-independent IAA synthesis. Maize orp has mutations in two TSB genes, resulting in a seedling lethal phenotype with high levels of accumulated indole. However, proteome sequence information now indicates that maize has three TSB genes. Plants and bacteria have divergent forms of TSB, type 1 and type 2 (Xie et al., 2001); the major TSB genes responsible for Trp synthase activity in maize and Arabidopsis are type 1. The third maize TSB gene, maize locus ID GRMZM2G054465, is a member of the TSB type 2 group. Its product is reported not to interact directly with a Trp synthase alpha (TSA) subunit but has experimentally demonstrated catalytic activity converting indole and Ser to Trp (Yin et al., 2010). This type 2 TSB may allow orp plants to make sufficient Trp for IAA production from the accumulated free indole.When the original work on trp2 mutants of Arabidopsis was carried out, two TSB genes were known (Last et al., 1991). As the trp2 plants were deficient only in TSB1, they were able to make sufficient Trp to survive under low-light conditions. Full proteome data now indicate that Arabidopsis has four TSB-like genes; in addition to TSB1 and TSB2, there is a third type 1 TSB gene, Arabidopsis locus ID AT5G28237. The product of this gene has not been experimentally characterized. The fourth gene, AT5G38530, encodes a type 2 TSB with demonstrated catalytic activity similar to ZmTSB type 2 mentioned above (Yin et al., 2010). Thus, the trp2 plants may also make enough Trp for IAA production. It is even possible that one of the minor forms of TSB has a specific role in IAA production. Type 2 TSBs are conserved throughout the plant kingdom, and the biological role for this protein is not known (Xie et al., 2001).A phylogenetic analysis of type 1 TSBs is shown in Figure 2. This indicates that the product of AT5G28237 belongs to a eudicot-conserved TSB type 1-like clade, divergent from that containing major experimentally characterized TSBs. A multiple sequence alignment (not shown) reveals that members of this divergent clade have a shortened N terminus with respect to the major chloroplast-localized TSB proteins. A localization prediction carried out in CELLO (Yu et al., 2006) suggests a cytosolic location for these proteins. Examination of EST databases indicates that the genes encoding these proteins are expressed. It is possible that the product of AT5G28237 could interact with the cytosolic INS studied by Wang et al. (2015), or separately with its indole product, to produce Trp that is further converted to IAA.Open in a separate windowFigure 2.Phylogeny of TSB type 1 homologs from Oryza sativa (LOC_Os), Sorghum bicolor (Sobic), Z. mays (GRMZM), Arabidopsis (AT), Brassica rapa (Brara), Solanum lycopersicum (Solyc), Populus trichocarpa (Potri), and Physcomitrella patens (Phpat). Protein sequences were downloaded from Phytozome v10.2 (Goodstein et al., 2012). The phylogenetic analysis was conducted in MEGA6 (http://megasoftware.net; Tamura et al., 2013) with multiple sequence alignment by MUSCLE (Edgar, 2004) and evolutionary history inferred using the neighbor-joining method (Saitou and Nei, 1987). The optimal tree is shown; the percentage of replicate trees in which the associated sequences clustered together in the bootstrap test (500 replicates) is shown next to the branches (Felsenstein, 1985). The tree is drawn to scale; the scale bar indicates the number of amino acid substitutions per site. It is rooted with type 1 TSBs from the moss P. patens.The second major line of evidence for Trp-independent IAA synthesis comes from isotopic labeling experiments. Wright et al. (1991) observed greater incorporation of ²H into IAA than Trp in orp seedlings grown on ²H₂O. Normanly et al. (1993) reported higher enrichment of ¹⁵N in IAA than Trp in trp2-1 mutants of Arabidopsis grown on ¹⁵N anthranilate; very poor incorporation of deuterium from ²H-Trp into IAA was reported in the trp2-1 plants. A number of similar reports relating to other plants have been published showing differences in the incorporation of label from Trp into IAA depending on experimental tissue and environmental conditions (e.g. Michalczuk et al., 1992; Rapparini et al., 2002; Sztein et al., 2002). This evidence has been persuasive; however, it assumes a single pool of Trp to which ¹⁵N anthranilate and ²H-Trp contribute and from which IAA is made. If Trp is made at different rates in different parts of the plant, and/or exogenous ²H-Trp does not equilibrate with newly synthesized Trp, then the ratio of ¹⁵N to ²H in Trp will vary in different plant organs/tissues/cells. Trp turnover and thus incorporation of label from ¹⁵N anthranilate are likely to differ substantially throughout the plant, with the highest rates of labeling occurring in cells with high rates of protein synthesis. This would not be a problem for the experiment if IAA is made at equal rates in different parts of the plant, but we know it is not. The Trp aminotransferase/YUCCA pathway of IAA synthesis elegantly shown to be responsible for the bulk of IAA synthesis (Mashiguchi et al., 2011; Won et al., 2011) appears to be locally controlled in Arabidopsis via 11 different YUCCA-encoding genes that have highly localized expression (Zhao, 2008). Adding to the complication is the need for ¹⁵N anthranilate and ²H-Trp to move into and through the plant to regions of Trp and IAA synthesis, respectively. This is likely to occur at different rates due to differing transporter requirements.Data from my own laboratory (Cooney and Nonhebel, 1991) is particularly relevant to this discussion. We monitored incorporation of ²H from deuterated water into IAA and Trp in tomato (S. lycopersicum) shoots. Unlike the other studies, we also measured the incorporation of label into IPA. Our data showed that IPA became labeled at a rate consistent with this compound acting as the major/sole precursor of IAA. Crucially, the proportion of labeled Trp was lower than ²H-IPA. Our interpretation of these data was that IPA and IAA were produced from newly synthesized Trp, and that Trp was not uniformly labeled throughout the shoot. At the time, we suggested different subcellular pools of Trp; this may be the case, but in light of new knowledge of localized IAA synthesis, it is most likely that substantial differences in Trp and IAA turnover in different cells/tissues may be the reason for these observations.The arguments above cast doubt on the existence of the Trp-independent route; however, a recent publication by Wang et al. (2015) claims to provide new evidence for its importance. They present the interesting finding that Arabidopsis plants with a null mutation in INS, a cytosolic TSA homolog previously shown to have indole-3-glycerol phosphate lyase (IGL) activity (Zhang et al., 2008), had reduced levels of IAA. The mutation particularly affected early embryo development. I suggest that the INS may make a contribution to IAA synthesis, but the only specific evidence that it does so via a Trp-independent route is the observation that the ins-1 mutation has an additive effect with the weakly ethylene insensitive8-1 Trp aminotransferase mutation. This evidence is indicative rather than conclusive. The possibility that INS may act in concert with a minor TSB homolog, as suggested in Figure 1, needs to be considered.In addition, Wang et al. (2015) focus on Arabidopsis alone. If INS has a key role in IAA synthesis, then evolutionary theory predicts a conserved protein with wide taxonomic distribution. On the contrary, an exhaustive BLAST search (Altschul et al., 1997) of diverse taxa in Phytozome v10.2 (Goodstein et al., 2012) and GenBank (Benson et al., 2013) revealed that INS orthologs with cytosolic prediction and shortened N terminus occur only in members of the Brassicaceae (Eutrema salsugineum, Arabis alpina, Camelina sativa, Capsella rubella, Brassica napus, Boechera stricta, Arabidopsis lyrata, B. rapa) and in Tarenaya hassleriana from the Brassicaceae sister family, the Cleomaceae. The phylogenetic tree in Figure 3 shows relationships between INS and TSA homologs from several plant species and indicates the separate clade of cytosolic INS homologs in the Brassicaceae. In this diagram, the sequence most closely related to INS from another group is that from tomato. This protein is the only TSA found in tomato and has an unambiguous chloroplast signal peptide. P. trichocarpa and M. truncatula as well as other eudicots outside the Brassicaeae and Cleomaceae also lack cytosolic TSA homologs. Furthermore, INS and its orthologs are phylogenetically distinct from the other experimentally characterized indole-3-glycerol phosphate lyases benzoxazin1 and IGL (Frey et al., 2000) and their orthologs. The latter are restricted to the grasses where they are involved in the production of cyclic hydroxamic acid defense compounds (Frey et al., 2000). The grasses also have an additional separate clade of cytosolic TSA homologs, although work by Kriechbaumer et al. (2008) did not detect any catalytic activity for the product of GRMZM2G046191_T01. The phylogeny of INS and its orthologs would suggest the major role of these proteins may be the production of lineage-specific metabolites such as the indole-derived defense compounds produced in grasses; any role in IAA synthesis may be incidental and restricted to the Brassicaeae and Cleomaceae.Open in a separate windowFigure 3.Phylogeny of TSA homologs from O. sativa (LOC_Os), S. bicolor (Sobic), Z. mays (GRMZM), Arabidopsis (AT), A. lyrata (Alyrata), B. rapa (Brara), S. lycopersicum (Solyc), Medicago truncatula (Medtr), P. trichocarpa (Potri), and P. patens (Phpat). Protein sequences were downloaded from Phytozome v10.2 (Goodstein et al., 2012). The phylogenetic analysis was conducted in MEGA6 (Tamura et al., 2013) with multiple sequence alignment by MUSCLE (Edgar, 2004) and evolutionary history inferred using the neighbor-joining method (Saitou and Nei, 1987). The rooted optimal tree is shown; the percentage of replicate trees in which the associated sequences clustered together in the bootstrap test (500 replicates) is shown next to the branches (Felsenstein, 1985). The tree is drawn to scale; the scale bar indicates the number of amino acid substitutions per site. It is rooted with the TSA ortholog from the moss P. patens.In conclusion, I contend that experimental data relating to IAA synthesis in Arabidopsis, including that suggesting the involvement of a cytosolic INS, can be explained by the Trp-dependent IAA synthesis pathway. I show that INS and its orthologs are not found outside the Brassicaceae and a closely related sister clade; any alternative IAA synthesis pathway in which they may be involved is likely to have similar limited taxonomic occurrence. Furthermore, Arabidopsis and its relatives contain two additional TSB homologs that could convert free indole into Trp. Curiously, both of these proteins have a wider taxonomic distribution. A priority for further experimental work should be testing the involvement of minor TSB homologs in IAA synthesis, including the highly conserved type 2 TSBs as well as a eudicot-specific clade of possibly cytosolic type 1 TSBs. Work would also have to establish whether free indole exists in plants other than the Brassicaceae and the grasses. Finally, I argue that isotope-labeling experiments do not provide strong support for the Trp-independent route, as IAA production is highly localized. Previously published data from my laboratory clearly show that the main Trp-dependent IAA precursor IPA becomes more highly labeled from ²H₂O than Trp, even though the latter is produced from Trp in a single reaction. Thus, it cannot be argued that differences in isotope enrichment between Trp and IAA demonstrate the existence of a Trp-independent route.     

A Critical Assessment of Feature Selection Methods for Biomarker Discovery in Clinical Proteomics

In this paper, we compare the performance of six different feature selection methods for LC-MS-based proteomics and metabolomics biomarker discovery—t test, the Mann–Whitney–Wilcoxon test (mww test), nearest shrunken centroid (NSC), linear support vector machine–recursive features elimination (SVM-RFE), principal component discriminant analysis (PCDA), and partial least squares discriminant analysis (PLSDA)—using human urine and porcine cerebrospinal fluid samples that were spiked with a range of peptides at different concentration levels. The ideal feature selection method should select the complete list of discriminating features that are related to the spiked peptides without selecting unrelated features. Whereas many studies have to rely on classification error to judge the reliability of the selected biomarker candidates, we assessed the accuracy of selection directly from the list of spiked peptides. The feature selection methods were applied to data sets with different sample sizes and extents of sample class separation determined by the concentration level of spiked compounds. For each feature selection method and data set, the performance for selecting a set of features related to spiked compounds was assessed using the harmonic mean of the recall and the precision (f-score) and the geometric mean of the recall and the true negative rate (g-score). We conclude that the univariate t test and the mww test with multiple testing corrections are not applicable to data sets with small sample sizes (n = 6), but their performance improves markedly with increasing sample size up to a point (n > 12) at which they outperform the other methods. PCDA and PLSDA select small feature sets with high precision but miss many true positive features related to the spiked peptides. NSC strikes a reasonable compromise between recall and precision for all data sets independent of spiking level and number of samples. Linear SVM-RFE performs poorly for selecting features related to the spiked compounds, even though the classification error is relatively low.Biomarkers play an important role in advancing medical research through the early diagnosis of disease and prognosis of treatment interventions (1, 2). Biomarkers may be proteins, peptides, or metabolites, as well as mRNAs or other kinds of nucleic acids (e.g. microRNAs) whose levels change in relation to the stage of a given disease and which may be used to accurately assign the disease stage of a patient. The accurate selection of biomarker candidates is crucial, because it determines the outcome of further validation studies and the ultimate success of efforts to develop diagnostic and prognostic assays with high specificity and sensitivity. The success of biomarker discovery depends on several factors: consistent and reproducible phenotyping of the individuals from whom biological samples are obtained; the quality of the analytical methodology, which in turn determines the quality of the collected data; the accuracy of the computational methods used to extract quantitative and molecular identity information to define the biomarker candidates from raw analytical data; and finally the performance of the applied statistical methods in the selection of a limited list of compounds with the potential to discriminate between predefined classes of samples. De novo biomarker research consists of a biomarker discovery part and a biomarker validation part (3). Biomarker discovery uses analytical techniques that try to measure as many compounds as possible in a relatively low number of samples. The goal of subsequent data preprocessing and statistical analysis is to select a limited number of candidates, which are subsequently subjected to targeted analyses in large number of samples for validation.Advanced technology, such as high-performance liquid chromatography–mass spectrometry (LC-MS),¹ is increasingly applied in biomarker discovery research. Such analyses detect tens of thousands of compounds, as well as background-related signals, in a single biological sample, generating enormous amounts of multivariate data. Data preprocessing workflows reduce data complexity considerably by trying to extract only the information related to compounds resulting in a quantitative feature matrix, in which rows and columns correspond to samples and extracted features, respectively, or vice versa. Features may also be related to data preprocessing artifacts, and the ratio of such erroneous features to compound-related features depends on the performance of the data preprocessing workflow (4). Preprocessed LC-MS data sets contain a large number of features relative to the sample size. These features are characterized by their m/z value and retention time, and in the ideal case they can be combined and linked to compound identities such as metabolites, peptides, and proteins. In LC-MS-based proteomics and metabolomics studies, sample analysis is so time consuming that it is practically impossible to increase the number of samples to a level that balances the number of features in a data set. Therefore, the success of biomarker discovery depends on powerful feature selection methods that can deal with a low sample size and a high number of features. Because of the unfavorable statistical situation and the risk of overfitting the data, it is ultimately pivotal to validate the selected biomarker candidates in a larger set of independent samples, preferably in a double-blinded fashion, using targeted analytical methods (1).Biomarker selection is often based on classification methods that are preceded by feature selection methods (filters) or which have built-in feature selection modules (wrappers and embedded methods) that can be used to select a list of compounds/peaks/features that provide the best classification performance for predefined sample groups (e.g. healthy versus diseased) (5). Classification methods are able to classify an unknown sample into a predefined sample class. Univariate feature selection methods such as filters (t test or Wilcoxon–Mann–Whitney tests) cannot be used for sample classification. Other classification methods such as the nearest shrunken centroid method have intrinsic feature selection ability, whereas other classification methods such as principal component discriminant analysis (PCDA) and partial least squares regression coupled with discriminant analysis (PLSDA) should be augmented with a feature selection method. There are classifiers having no feature selection option that perform the classification using all variables, such as support vector machines that use non-linear kernels (6). Classification methods without the ability to select features cannot be used for biomarker discovery, because these methods aim to classify samples into predefined classes but cannot identify the limited number of variables (features or compounds) that form the basis of the classification (6, 7). Different statistical methods with feature selection have been developed according to the complexity of the analyzed data, and these have been extensively reviewed (5, 6, 8, 9). Ways of optimizing such methods to improve sensitivity and specificity are a major topic in current biomarker discovery research and in the many “omics-related” research areas (6, 10, 11). Comparisons of classification methods with respect to their classification and learning performance have been initiated. Van der Walt et al. (12) focused on finding the most accurate classifiers for simulated data sets with sample sizes ranging from 20 to 100. Rubingh et al. (13) compared the influence of sample size in an LC-MS metabolomics data set on the performance of three different statistical validation tools: cross validation, jack-knifing model parameters, and a permutation test. That study concluded that for small sample sets, the outcome of these validation methods is influenced strongly by individual samples and therefore cannot be trusted, and the validation tool cannot be used to indicate problems due to sample size or the representativeness of sampling. This implies that reducing the dimensionality of the feature space is critical when approaching a classification problem in which the number of features exceeds the number of samples by a large margin. Dimensionality reduction retains a smaller set of features to bring the feature space in line with the sample size and thus allow the application of classification methods that perform with acceptable accuracy only when the sample size and the feature size are similar.In this study we compared different classification methods focusing on feature selection in two types of spiked LC-MS data sets that mimic the situation of a biomarker discovery study. Our results provide guidelines for researchers who will engage in biomarker discovery or other differential profiling “omics” studies with respect to sample size and selecting the most appropriate feature selection method for a given data set. We evaluated the following approaches: univariate t test and Mann–Whitney–Wilcoxon test (mww test) with multiple testing correction (14), nearest shrunken centroid (NSC) (15, 16), support vector machine–recursive features elimination (SVM-RFE) (17), PLSDA (18), and PCDA (19). PCDA and PLSDA were combined with the rank-product as a feature selection criterion (20). These methods were evaluated with data sets having three characteristics: different biological background, varying sample size, and varying within- and between-class variability of the added compounds. Data were acquired via LC-MS from human urine and porcine cerebrospinal fluid (CSF) samples that were spiked with a set of known peptides (true positives) at different concentration levels. These samples were then combined in two classes containing peptides spiked at low and high concentration levels. The performance of the classification methods with feature selection was measured based on their ability to select features that were related to the spiked peptides. Because true positives were known in our data set, we compared performance based on the f-score (the harmonic mean of precision and recall) and the g-score (the geometric mean of accuracy).     

Evidence for a Critical Role of Catecholamines for Cardiomyocyte Lineage Commitment in Murine Embryonic Stem Cells

Catecholamine release is known to modulate cardiac output by increasing heart rate. Although much is known about catecholamine function and regulation in adults, little is known about the presence and role of catecholamines during heart development. The present study aimed therefore to evaluate the effects of different catecholamines on early heart development in an in vitro setting using embryonic stem (ES) cell-derived cardiomyocytes. Effects of catecholamine depletion induced by reserpine were examined in murine ES cells (line D3, αPIG44) during differentiation. Cardiac differentiation was assessed by immunocytochemistry, qRT-PCR, quantification of beating clusters, flow cytometry and pharmacological approaches. Proliferation was analyzed by EB cross-section measurements, while functionality of cardiomyocytes was studied by extracellular field potential (FP) measurements using microelectrode arrays (MEAs). To further differentiate between substance-specific effects of reserpine and catecholamine action via α- and β-receptors we proved the involvement of adrenergic receptors by application of unspecific α- and β-receptor antagonists. Reserpine treatment led to remarkable down-regulation of cardiac-specific genes, proteins and mesodermal marker genes. In more detail, the average ratio of ∼40% spontaneously beating control clusters was significantly reduced by 100%, 91.1% and 20.0% on days 10, 12, and 14, respectively. Flow cytometry revealed a significant reduction (by 71.6%, n = 11) of eGFP positive CMs after reserpine treatment. By contrast, reserpine did not reduce EB growth while number of neuronal cells in reserpine-treated EBs was significantly increased. MEA measurements of reserpine-treated EBs showed lower FP frequencies and weak responsiveness to adrenergic and muscarinic stimulation. Interestingly we found that developmental inhibition after α- and β-adrenergic blocker application mimicked developmental changes with reserpine. Using several methodological approaches our data suggest that reserpine inhibits cardiac differentiation. Thus catecholamines play a critical role during development.     

Bisphosphonates and Connexin 43: A Critical Review of Evidence

Abstract

Bisphosphonates (BPs) are drugs commonly used in the treatment of various disease arising or affecting bone tissue. There is a standard use in bone neoplasia and metastasis, hormonal and developmental disorders as well as for compensation of adverse effects in several medical therapies. Many in-vivo and in-vitro studies have assessed the efficacy of this drug and its function in cellular scale. In this concern, BPs are described to inhibit the resorptive function of osteoclasts and to prevent apoptosis of osteoblasts and osteocytes. They can preserve the osteocytic network, reduce fracture rate, and increase the bone mineral content, which is therapeutically used. Connexin 43 (Cx43) is a crucial molecule for basal regulation of bone homeostasis, development, and differentiation. It is described for signal transduction in many physiological and pathological stimuli and recently to be involved in BP action.     

Evidence for the Critical Role of Sucrose Synthase for Anoxic Tolerance of Maize Roots using a Double Mutant

The induction of the sucrose synthase (SuSy) gene (SuSy) by low O₂, low temperature, and limiting carbohydrate supply suggested a role in carbohydrate metabolism under stress conditions. The isolation of a maize (Zea mays L.) line mutant for the two known SuSy genes but functionally normal showed that SuSy activity might not be required for aerobic growth and allowed the possibility of investigating its importance during anaerobic stress. As assessed by root elongation after return to air, hypoxic pretreatment improved anoxic tolerance, in correlation with the number of SuSy genes and the level of SuSy expression. Furthermore, root death in double-mutant seedlings during anoxic incubation could be attributed to the impaired utilization of sucrose (Suc). Collectively, these data provide unequivocal evidence that Suc is the principal C source and that SuSy is the main enzyme active in Suc breakdown in roots of maize seedlings deprived of O₂. In this situation, SuSy plays a critical role in anoxic tolerance.     

A Critical Assessment of the Role of Potassium and Osmolarity in Stomatal Opening

An attempt has been made to separate the osmotic effect fromthe ionic effect of KCI in stomatal responses. For this purposeisolated illuminated epidermis from species with and withoutsubsidiary cells were treated with KCI (0-250 mOs kg^–1)and with mannitol (0-250 mOs kg^–1). Since osmolarity wasmade the basis of comparison, the effect of mannitol had tobe observed immediately, before guard cell contents could haveleached into the incubation medium. When plotting aperturesagainst osmolarity sigmoid curves were obtained with KCI, butwith mannitol straight lines resulted provided that prior tostripping and incubation leaves were briefly illuminated. Whilst in lower concentrations (60 mOs kg^–1 for Viciafaba; 90 mOs kg^–1 for Zantedeschia aethiopica; 190 mOskg^–1 for Commelina communis) pores were wider in mannitolthan in KCI, in concentrations above these values the situationwas reversed. It appeared therefore that KCI had either an inhibitoryor a promoting effect. Inhibition was most pronounced when atthe beginning of incubation stomata were closed; the inhibitoryeffect on stomata without subsidiary cells occurred at low concentrations(0-60 mOs kg^–1) whereas when subsidiary cells were presentinhibition occurred at up to 190mOs kg^–1. Other experiments started with KCI solutions of 50 mOs kg^–1for Vicia faba, 85 mOs kg^–1 for Zantedeschia aethiopicaand 115 mOs kg^–1 for Commelina communism; mannitol wasadditionally used to give the progressive increases in osmolarity.Degrees of opening were then reached which with KCI alone couldonly be attained at the very highest concentrations. Starch disappearance was followed using the periodic-acid-silvertest; by using either ⁸⁶Rb or ⁴³K it was shown that ion uptakewas restricted to guard cells alone only at osmolarities exceeding200 mOs kg^–1. On the basis of these observations it was concluded that K transportdoes not represent the major mechanism of stomatal regulation. Key words: Stomata, Potassium, Osmolarity     

Critical Assessment of Methods and Concepts in Nonphotic Phase Shifting

This paper concerns methodological limitations in research on nonphotic resetting of circadian rhythms. There are problems in producing phase responses curves for arousing activity-inducing stimuli when locomotor activity is also used as a phase marker. It is also difficult to define the nature of these nonphotic inputs. Dose-response curves relating amount of wheel running to phase shifts have been overinterpreted, and the measurement of phase shifts is complicated by concomitant changes in period. Some of these points also apply sometimes to chronobiological experiments with light.     

Critical Assessment of Methods and Concepts in Nonphotic Phase Shifting

This paper concerns methodological limitations in research on nonphotic resetting of circadian rhythms. There are problems in producing phase responses curves for arousing activity-inducing stimuli when locomotor activity is also used as a phase marker. It is also difficult to define the nature of these nonphotic inputs. Dose-response curves relating amount of wheel running to phase shifts have been overinterpreted, and the measurement of phase shifts is complicated by concomitant changes in period. Some of these points also apply sometimes to chronobiological experiments with light.     

A Critical Assessment of Putative Gatekeeper Interactions in the Villin Headpiece Helical Subdomain

The helical subdomain of the villin headpiece (HP36) is one of the smallest naturally occurring proteins that folds cooperatively. Its small size, rapid folding, and simple three-helix topology have made it an extraordinary popular model system for computational, theoretical, and experimental studies of protein folding. Aromatic-proline interactions involving Trp64 and Pro62 have been proposed to play a critical role in specifying the subdomain fold by acting as gatekeeper residues. Note that the numbering corresponds to full-length headpiece. Mutation of Pro62 has been shown to lead to a protein that does not fold, but this may arise for two different reasons: The residue may make interactions that are critical for the specificity of the fold or the mutation may simply destabilize the domain. In the first case, the protein cannot fold, while in the second, the small fraction of molecules that do fold adopt the correct structure. The modest stability of the wild type prevents a critical analysis of these interactions because even moderately destabilizing mutations lead to a very small folded state population. Using a hyperstable variant of HP36, denoted DM HP36, as our new wild type, we characterized a set of mutants designed to assess the role of the putative gatekeeper interactions. Four single mutants, DM Pro62Ala, DM Trp64Leu, DM Trp64Lys, and DM Trp64Ala, and a double mutant, DM Pro62Ala Trp64Leu, were prepared. All mutants are less stable than DM HP36, but all are well folded as judged by CD and ¹H NMR. All of the mutants display sigmoidal thermal unfolding and urea-induced unfolding curves. Double-mutant cycle analysis shows that the interactions between Pro62 and Trp64 are weak but favorable. Interactions involving Pro62 and proline-aromatic interactions are, thus, not required for specifying the subdomain fold. The implications for the design and thermodynamics of miniature proteins are discussed.     

Assessment of the Toxicity of CuO Nanoparticles by Using Saccharomyces cerevisiae Mutants with Multiple Genes Deleted

To develop applicable and susceptible models to evaluate the toxicity of nanoparticles, the antimicrobial effects of CuO nanoparticles (CuO-NPs) on various Saccharomyces cerevisiae (S. cerevisiae) strains (wild type, single-gene-deleted mutants, and multiple-gene-deleted mutants) were determined and compared. Further experiments were also conducted to analyze the mechanisms associated with toxicity using copper salt, bulk CuO (bCuO), carbon-shelled copper nanoparticles (C/Cu-NPs), and carbon nanoparticles (C-NPs) for comparisons. The results indicated that the growth inhibition rates of CuO-NPs for the wild-type and the single-gene-deleted strains were comparable, while for the multiple-gene deletion mutant, significantly higher toxicity was observed (P < 0.05). When the toxicity of the CuO-NPs to yeast cells was compared with the toxicities of copper salt and bCuO, we concluded that the toxicity of CuO-NPs should be attributed to soluble copper rather than to the nanoparticles. The striking difference in adverse effects of C-NPs and C/Cu-NPs with equivalent surface areas also proved this. A toxicity assay revealed that the multiple-gene-deleted mutant was significantly more sensitive to CuO-NPs than the wild type. Specifically, compared with the wild-type strain, copper was readily taken up by mutant strains when cell permeability genes were knocked out, and the mutants with deletions of genes regulated under oxidative stress (OS) were likely producing more reactive oxygen species (ROS). Hence, as mechanism-based gene inactivation could increase the susceptibility of yeast, the multiple-gene-deleted mutants should be improved model organisms to investigate the toxicity of nanoparticles.