Phylogenetics and biogeography of a spectacular Old World radiation of butterflies: the subtribe Mycalesina (Lepidoptera: Nymphalidae: Satyrini)

Background  

Butterflies of the subtribe Mycalesina (Nymphalidae: Satyrinae) are important model organisms in ecology and evolution. This group has radiated spectacularly in the Old World tropics and presents an exciting opportunity to better understand processes of invertebrate rapid radiations. However, the generic-level taxonomy of the subtribe has been in a constant state of flux, and relationships among genera are unknown. There are six currently recognized genera in the group. Mycalesis, Lohora and Nirvanopsis are found in the Oriental region, the first of which is the most speciose genus among mycalesines, and extends into the Australasian region. Hallelesis and Bicyclus are found in mainland Africa, while Heteropsis is primarily Madagascan, with a few species in Africa. We infer the phylogeny of the group with data from three genes (total of 3139 bp) and use these data to reconstruct events in the biogeographic history of the group.     

Analysis of antigenically important residues in human influenza A virus in terms of B-cell epitopes

In this paper we undertake an analysis of the antigenicity of influenza A virus hemagglutinin. We developed a novel computational approach to the identification of antigenically active regions and showed that the amino acid substitutions between successive predominant seasonal strains form clusters that are consistent, in terms of both their location and their size, with the properties of B-cell epitopes in general and with those epitopes that have been identified experimentally in influenza A virus hemagglutinin to date. Such an interpretation provides a biologically plausible framework for an understanding of the location of antigenically important substitutions that is more specific than the canonical "antigenic site" model and provides an effective basis for deriving models that predict antigenic escape in the H3N2 subtype. Our results support recent indications that antibodies binding to the "stalk" region of hemagglutinin are found in the human population and exert evolutionary pressure on the virus. Our computational approach provides a possible method for identifying antigenic escape through evolution in this region, which in some cases will not be identified by the hemagglutinin inhibition assay.     

Environmental Transmission of Human Noroviruses in Shellfish Waters

Human noroviruses (NoV) are the most common cause of epidemic gastroenteritis following consumption of bivalve shellfish contaminated with fecal matter. NoV levels can be effectively reduced by some sewage treatment processes such as activated sludge and membrane bioreactors. However, tertiary sewage treatment and substantial sewage dilution are usually required to achieve low concentrations of virus in shellfish. Most outbreaks have been associated with shellfish harvested from waters affected by untreated sewage from, for example, storm overflows or overboard disposal of feces from boats. In coastal waters, NoV can remain in suspension or associate with organic and inorganic matter and be accumulated by shellfish. Shellfish take considerably longer to purge NoV than fecal indicator bacteria when transferred from sewage-polluted estuarine waters to uncontaminated waters. The abundance and distribution of NoV in shellfish waters are influenced by the levels of sewage treatment, proximity of shellfish beds to sewage sources, rainfall, river flows, salinity, and water temperature. Detailed site-specific information on these factors is required to design measures to control the viral risk.     

Isocitrate dehydrogenase 1 R132C mutation occurs exclusively in microsatellite stable colorectal cancers with the CpG island methylator phenotype

The CpG Island Methylator Phenotype (CIMP) is fundamental to an important subset of colorectal cancer; however, its cause is unknown. CIMP is associated with microsatellite instability but is also found in BRAF mutant microsatellite stable cancers that are associated with poor prognosis. The isocitrate dehydrogenase 1 (IDH1) gene causes CIMP in glioma due to an activating mutation that produces the 2-hydroxyglutarate oncometabolite. We therefore examined IDH1 alteration as a potential cause of CIMP in colorectal cancer. The IDH1 mutational hotspot was screened in 86 CIMP-positive and 80 CIMP-negative cancers. The entire coding sequence was examined in 81 CIMP-positive colorectal cancers. Forty-seven cancers varying by CIMP-status and IDH1 mutation status were examined using Illumina 450K DNA methylation microarrays. The R132C IDH1 mutation was detected in 4/166 cancers. All IDH1 mutations were in CIMP cancers that were BRAF mutant and microsatellite stable (4/45, 8.9%). Unsupervised hierarchical cluster analysis identified an IDH1 mutation-like methylation signature in approximately half of the CIMP-positive cancers. IDH1 mutation appears to cause CIMP in a small proportion of BRAF mutant, microsatellite stable colorectal cancers. This study provides a precedent that a single gene mutation may cause CIMP in colorectal cancer, and that this will be associated with a specific epigenetic signature and clinicopathological features.     

Mathematical and computational modeling in biology at multiple scales

A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined.     

Transplanting Supersites of HIV-1 Vulnerability

One strategy for isolating or eliciting antibodies against a specific target region on the envelope glycoprotein trimer (Env) of the human immunodeficiency virus type 1 (HIV-1) involves the creation of site transplants, which present the target region on a heterologous protein scaffold with preserved antibody-binding properties. If the target region is a supersite of HIV-1 vulnerability, recognized by a collection of broadly neutralizing antibodies, this strategy affords the creation of “supersite transplants”, capable of binding (and potentially eliciting) antibodies similar to the template collection of effective antibodies. Here we transplant three supersites of HIV-1 vulnerability, each targeted by effective neutralizing antibodies from multiple donors. To implement our strategy, we chose a single representative antibody against each of the target supersites: antibody 10E8, which recognizes the membrane-proximal external region (MPER) on the HIV-1 gp41 glycoprotein; antibody PG9, which recognizes variable regions one and two (V1V2) on the HIV-1 gp120 glycoprotein; and antibody PGT128 which recognizes a glycopeptide supersite in variable region 3 (glycan V3) on gp120. We used a structural alignment algorithm to identify suitable acceptor proteins, and then designed, expressed, and tested antigenically over 100-supersite transplants in a 96-well microtiter-plate format. The majority of the supersite transplants failed to maintain the antigenic properties of their respective template supersite. However, seven of the glycan V3-supersite transplants exhibited nanomolar affinity to effective neutralizing antibodies from at least three donors and recapitulated the mannose₉-N-linked glycan requirement of the template supersite. The binding of these transplants could be further enhanced by placement into self-assembling nanoparticles. Essential elements of the glycan V3 supersite, embodied by as few as 3 N-linked glycans and ∼25 Env residues, can be segregated into acceptor scaffolds away from the immune-evading capabilities of the rest of HIV-1 Env, thereby providing a means to focus the immune response on the scaffolded supersite.     

Integration of biological data by kernels on graph nodes allows prediction of new genes involved in mitotic chromosome condensation

The advent of genome-wide RNA interference (RNAi)–based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function—mitotic chromosome condensation—and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest.