Leishmania-sandfly interactions: an empirical field study

Phlebotomus papatasi is the sandfly vector of Leishmania major in the Jordan Valley. The objective of this study was to characterize vector-parasite relations in an active zoonotic focus. Seasonality and intensity of promastigote infection rates in female sandflies and the developmental stage of these hosts were established. On 153 trap-nights, 641 female P. papatasi were caught and examined. Of these, 48 (7.4%, range 12.9-4.8%) were infected with L. major promastigotes. Correlating the number of parasites with the gonotrophic age of the vector revealed that most infections initially are light ones, and those that survive in the vector generally prosper and proliferate. Comparing infection rates in parous and gravid flies revealed that similar proportions of gravid and parous flies are found infected. Thus, Leishmania infections do not appear to affect sandfly survival.     

On the theoretical and empirical framework for studying genetic interactions within and among species

We present a quantitative genetic (QG) interpretation of the Bateson-Dobzhansky-Muller (BDM) genetic model of speciation in order to unify the theoretical framework for understanding how the genetic differentiation of populations is associated with the process of speciation. Specifically, we compare the QG theory of joint scaling with the Turelli-Orr mathematical formulation of the BDM model. By formally linking the two models, we show that a wealth of empirical methods from QG can be brought to bear on the study of the genetic architecture of hybrid phenotypes to better understand the connections, if any, between microevolution within populations and macroevolution in the origin of species. By integrating the two theories, we make additional novel predictions that enrich the opportunities for empirically testing speciation genetic theory or facets of it, such as Haldane's rule. We show that the connection between the two theories is simple and straightforward for autosomal genes but not for sex-linked genes. Differences between the two approaches highlight key conceptual issues concerning the relevance of epistasis to evolution within and among lineages and to differences in the process of speciation in hermaphrodites and in organisms with separate sexes.     

Expression cloning screening of a unique and full-length set of cDNA clones is an efficient method for identifying genes involved in Xenopus neurogenesis

Functional screens, where a large numbers of cDNA clones are assayed for certain biological activity, are a useful tool in elucidating gene function. In Xenopus, gain of function screens are performed by pool screening, whereby RNA transcribed in vitro from groups of cDNA clones, ranging from thousands to a hundred, are injected into early embryos. Once an activity is detected in a pool, the active clone is identified by sib-selection. Such screens are intrinsically biased towards potent genes, whose RNA is active at low quantities. To improve the sensitivity and efficiency of a gain of function screen we have bioinformatically processed an arrayed and EST sequenced set of 100,000 gastrula and neurula cDNA clones, to create a unique and full-length set of approximately 2500 clones. Reducing the redundancy and excluding truncated clones from the starting clone set reduced the total number of clones to be screened, in turn allowing us to reduce the pool size to just eight clones per pool. We report that the efficiency of screening this clone set is five-fold higher compared to a redundant set derived from the same libraries. We have screened 960 cDNA clones from this set, for genes that are involved in neurogenesis. We describe the overexpression phenotypes of 18 single clones, the majority of which show a previously uncharacterised phenotype and some of which are completely novel. In situ hybridisation analysis shows that a large number of these genes are specifically expressed in neural tissue. These results demonstrate the effectiveness of a unique full-length set of cDNA clones for uncovering players in a developmental pathway.     

An empirical Bayesian approach for identifying differential coexpression in high-throughput experiments

A common goal of microarray and related high-throughput genomic experiments is to identify genes that vary across biological condition. Most often this is accomplished by identifying genes with changes in mean expression level, so called differentially expressed (DE) genes, and a number of effective methods for identifying DE genes have been developed. Although useful, these approaches do not accommodate other types of differential regulation. An important example concerns differential coexpression (DC). Investigations of this class of genes are hampered by the large cardinality of the space to be interrogated as well as by influential outliers. As a result, existing DC approaches are often underpowered, exceedingly prone to false discoveries, and/or computationally intractable for even a moderately large number of pairs. To address this, an empirical Bayesian approach for identifying DC gene pairs is developed. The approach provides a false discovery rate controlled list of significant DC gene pairs without sacrificing power. It is applicable within a single study as well as across multiple studies. Computations are greatly facilitated by a modification to the expectation-maximization algorithm and a procedural heuristic. Simulations suggest that the proposed approach outperforms existing methods in far less computational time; and case study results suggest that the approach will likely prove to be a useful complement to current DE methods in high-throughput genomic studies.     

Mutagenesis strategies in zebrafish for identifying genes involved in development and disease

It has been nearly a decade since the completion of two large-scale chemical mutagenesis screens in zebrafish, and two years since the completion of a large-scale insertional mutagenesis. In this article, we use the accumulated data from these screens to compare the efficiency of each mutagen to isolate mutants and to identify mutated genes, and argue that the two mutagens target the same set of genes. We then review how both forward genetic screens and reverse genetic techniques, such as morpholinos and TILLING, and transgenics are being used to develop models of human disease.     

Motifs involved in protein-protein interactions

Summary Interactions between proteins are extremely variable. However, in the dimeric proteins comprised of regular motifs, interface interactions are similar to those that stabilize monomers. Additional stability is gained by converting loops within motifs or domains to linkers across interfaces. In multi-domain proteins, interactions can be greatly effected by the conformation of linkers between domains. Complex association of subunits, involving higher rotational symmetry or cubic symmetry, frequently involves motif sharing across interfaces.     

Improving the performance of an SVM-based method for predicting protein-protein interactions

Predicting the interactions between all the possible pairs of proteins in a given organism (making a protein-protein interaction map) is a crucial subject in bioinformatics. Most of the previous methods based on supervised machine learning use datasets containing approximately the same number of interacting pairs of proteins (positives) and non-interacting pairs of proteins (negatives) for training a classifier and are estimated to yield a large number of false positives. Thinking that the negatives used in previous studies cannot adequately represent all the negatives that need to be taken into account, we have developed a method based on multiple Support Vector Machines (SVMs) that uses more negatives than positives for predicting interactions between pairs of yeast proteins and pairs of human proteins. We show that the performance of a single SVM improved as we increased the number of negatives used for training and that, if more than one CPU is available, an approach using multiple SVMs is useful not only for improving the performance of classifiers but also for reducing the time required for training them. Our approach can also be applied to assessing the reliability of high-throughput interactions.     

Development of an immunological technique for identifying multiple predator–prey interactions in a complex arthropod assemblage

A simplified but highly effective approach for the post‐mortem evaluation of predation on several targeted members of an arthropod assemblage that does not require the development of pest‐specific enzyme‐linked immunosorbent assay (ELISA) (e.g. pest‐specific monoclonal antibodies) or PCR assays (DNA primers) is described. Laboratory feeding studies were conducted to determine if predation events could be detected from predators that consumed prey marked with foreign protein. I determined that large and small rabbit immunoglobulin G (IgG)‐marked prey can be detected by a rabbit‐IgG‐specific ELISA in the guts of chewing and piercing–sucking type predators. I then conducted multifaceted inclusion and exclusion field cage studies to qualify the degree of interguild and intraguild predation occurring among a complex arthropod assemblage during four separate light phase treatments. The field cages contained an arthropod assemblage consisting of 11 or 12 species of predaceous arthropods and three pest species. The three pests introduced into the cages included third instar Trichoplusia ni marked with rabbit IgG, third instar Lygus hesperus marked with chicken IgG and Pectinophora gossypiella sentinel egg masses. The inclusion cages allowed foraging fire ants, Solenopis xyloni, to freely enter the cages while the exclusion cages contained barriers that prevented ant entry. The results obtained using the conventional inclusion/exclusion field cage methodology revealed that there was substantial interguild and intraguild predation occurring on the majority of the arthropods in the assemblage, particularly in those cages that included ants. I then precisely identified which predators in the assemblage were feeding on the three targeted pests by conducting three post‐mortem gut content analyses on each individual predator (1503 individuals) in the assemblage. Specifically, P. gossypiella egg predation events were detected using an established P. gossypiella‐egg‐specific ELISA, and third instar T. ni and L. hesperus predation events were detected using rabbit‐IgG‐specific and chicken‐IgG‐specific ELISAs, respectively. Generally, the gut ELISAs revealed that Collops vittatus, Spanagonicus albofasciatus and Geocoris punctipes readily preyed on P. gossypiella eggs; Nabis alternatus, Zelus renardii and spiders (primarily Misumenops celer) readily preyed on marked L. hesperus nymphs, and spiders, S. albofasciatus and N. alternatus readily preyed on T. ni larvae. Furthermore, the cage methods and the post‐mortem predator gut ELISAs revealed very few distinctive patterns of predation with regard to the light cycle the assemblage was exposed to.     

A mechanism of dynamical interactions for two-person social dilemmas

We propose a new mechanism of interactions between game-theoretical agents in which the weights of the connections between interacting individuals are dynamical, payoff-dependent variables. Their evolution depends on the difference between the payoff of the agents from a given type of encounter and their average payoff. The mechanism is studied in the frame of two models: agents distributed on a random graph, and a mean field model. Symmetric and asymmetric connections between the agents are introduced. Long time behavior of both systems is discussed for the Prisoner's Dilemma and the Snow Drift games.     

Use of an immunoblotting method for identifying the individual proteins in the antigenic complexes of Bordetella pertussis

The composition of antigenic complexes isolated from the supernatant fluid of B. pertussis culture has been studied by means of immunoblotting techniques. In preparations obtained from B. pertussis strains 305 and 475 fragments of the molecule of fimbrial hemagglutinin, three subunits of B. pertussis toxin and agglutinogens 2 and 3 have been detected with the use of antisera to B. pertussis protective substances.     

Time-course microarray analysis for identifying candidate genes involved in obesity-associated pathological changes in the mouse colon

Background

Obesity is known to increase the risk of colorectal cancer. However, mechanisms underlying the pathogenesis of obesity-induced colorectal cancer are not completely understood. The purposes of this study were to identify differentially expressed genes in the colon of mice with diet-induced obesity and to select candidate genes as early markers of obesity-associated abnormal cell growth in the colon.

Methods

C57BL/6N mice were fed normal diet (11% fat energy) or high-fat diet (40% fat energy) and were euthanized at different time points. Genome-wide expression profiles of the colon were determined at 2, 4, 8, and 12 weeks. Cluster analysis was performed using expression data of genes showing log₂ fold change of ≥1 or ≤?1 (twofold change), based on time-dependent expression patterns, followed by virtual network analysis.

Results

High-fat diet-fed mice showed significant increase in body weight and total visceral fat weight over 12 weeks. Time-course microarray analysis showed that 50, 47, 36, and 411 genes were differentially expressed at 2, 4, 8, and 12 weeks, respectively. Ten cluster profiles representing distinguishable patterns of genes differentially expressed over time were determined. Cluster 4, which consisted of genes showing the most significant alterations in expression in response to high-fat diet over 12 weeks, included Apoa4 (apolipoprotein A-IV), Ppap2b (phosphatidic acid phosphatase type 2B), Cel (carboxyl ester lipase), and Clps (colipase, pancreatic), which interacted strongly with surrounding genes associated with colorectal cancer or obesity.

Conclusions

Our data indicate that Apoa4, Ppap2b, Cel, and Clps are candidate early marker genes associated with obesity-related pathological changes in the colon. Genome-wide analyses performed in the present study provide new insights on selecting novel genes that may be associated with the development of diseases of the colon.

     

The Bead blot: a method for identifying ligand-protein and protein-protein interactions using combinatorial libraries of peptide ligands

Small molecules that bind proteins can be used as ligands for protein purification and for investigating protein-protein and protein-drug interactions. Unfortunately, many methods used to identify new ligands to desired proteins suffer from common shortcomings, including the requirement that the target protein be purified and/or the requirement that the ligands be selected under conditions different from those under which it will be used. We have developed a new method called the Bead blot that can (i) select ligands to unpurified proteins, including trace proteins, present in complex materials (e.g., unfractionated plasma); (ii) select ligands to multiple proteins under a variety of conditions in a single experiment; and (iii) be used with libraries of different types of ligands. In the Bead blot, a library of ligands, synthesized on chromatography resin beads, is incubated with a starting material containing a target protein for which a ligand is sought. The proteins in the material bind to their complementary ligands according to specific affinity interactions. Then the protein-loaded beads are immobilized in a porous matrix, and the proteins are directionally eluted from the beads and captured on a membrane superimposed on the beads. The location of the target protein on the membrane is determined, and because the position of the protein(s) on the membrane reflects the position of the bead(s) in the matrix, the bead that originally bound the protein is identified, with subsequent elucidation of the ligand sequence. Ligands to several targets can be identified in one experiment. Here we demonstrate the broad utility of this method by the selection of ligands that purify plasma protein complexes or that remove pathogens from whole blood with very high affinity constants. We also select ligands to a protein based on competitive elution.     

Validation and development of an immunofluorescence method for isolating and identifying mycobacteria L forms

The complement fixation test and the immunofluorescence test have demonstrated that the L-forms of mycobacteria retain their species-specific and genus-specific determinants and possess serological activity. The L-variants obtained by different methods differ in size, depending on the degree of the destruction of their cell wall. Specific antisera to the L-forms of mycobacteria, suitable for use in the indirect immunofluorescence test, have been obtained. These antisera are highly specific and permit not only the rapid detection, but also identification of the L-forms.     

On the use of genetic divergence for identifying species

Degree of genetic divergence is frequently used to infer that two populations belong to separate species, or that several populations belong to a single species. I explore the logical framework of this approach, including the following assumptions: (i) speciation takes place over very long periods of time; (ii) reproductive isolation is based on the slow accumulation many genetic differences throughout the genome; (iii) genetic divergence automatically leads to reproductive isolation between species; and (iv) pre-mating and post-mating reproductive isolation have a similar genetic basis. I argue that so many exceptions to these assumptions have been demonstrated that they cannot be used with any reliability to distinguish different species. In addition, genetic distance as a species criterion is mostly used within the framework of Mayr's Biological Species Concept and is not free of assumptions about the nature of species or of speciation. The use of genetic distance to infer separate species (or the lack of these) is not parsimonious, its theoretical foundations are not well understood, and it cannot be applied over a wide range of plants and animals. I explore alternative approaches towards solving the species problems normally solved using genetic distance. © 2002 The Linnean Society of London, Biological Journal of the Linnean Society , 2002, 75 , 509–516.