Changes in cell-surface expression of MHC and Thy-1.2 determinants following treatment with lipid modulating agents

Treatment of normal mouse spleen cells with lipid fluidity modulators changes the expression of cell-surface H-2 determinants. BALB/c spleen cells treated for 1 to 2 hr with cholesteryl hemisuccinate (CHS) displayed reduced levels of all tested H-2 determinants (H-2L, H-2K, and H-2D) as evaluated by flow microfluorometry and increased membrane lipid packing density as determined by 1,6-diphenyl-1,3,5-hexatriene (DPH) fluorescence polarization. In contrast, decreasing membrane lipid packing density by phosphatidylcholine treatment decreased DPH fluorescence polarization and increased the expression of MHC determinants. The effects were selective in that expression of Thy-1.2 determinants was decreased by the latter treatment and not increased by CHS. The results are discussed in terms of passive modulation of antigenic expression.     

Polymorphisms and genetic linkage of histamine receptors

Histamine is a biogenic amine that plays an essential role in controlling many physiological functions, both in the central nervous system (CNS) and the peripheral nervous system (PNS). Most of these physiological effects are mediated through interactions with four histamine receptor subtypes, all of which are members of the larger family of rhodopsin-like class A G-protein coupled receptors (GPCRs) (Leurs et al., 2011; Lim et al., 2009). Here, we focus on the genetic variations and polymorphisms localized on the genes encoding for human histamine receptors where it provides an up to date collection of all polymorphisms found on genes encoding the histamine receptor subtypes and their association to diseases.     

HIPPI: highly accurate protein family classification with ensembles of HMMs

Background

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics.

Results

We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy.

Conclusion

HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp.

     

Unidentifiable divergence times in rates-across-sites models

The rates-across-sites assumption in phylogenetic inference posits that the rate matrix governing the Markovian evolution of a character on an edge of the putative phylogenetic tree is the product of a character-specific scale factor and a rate matrix that is particular to that edge. Thus, evolution follows basically the same process for all characters, except that it occurs faster for some characters than others. To allow estimation of tree topologies and edge lengths for such models, it is commonly assumed that the scale factors are not arbitrary unknown constants, but rather unobserved, independent, identically distributed draws from a member of some parametric family of distributions. A popular choice is the gamma family. We consider an example of a clock-like tree with three taxa, one unknown edge length, a known root state, and a parametric family of scale factor distributions that contains the gamma family. This model has the property that, for a generic choice of unknown edge length and scale factor distribution, there is another edge length and scale factor distribution which generates data with exactly the same distribution, so that even with infinitely many data it will be typically impossible to make correct inferences about the unknown edge length.     

Incorporation of CpG oligonucleotide ligand into protein-loaded particle vaccines promotes antigen-specific CD8 T-cell immunity

The development of multicomponent biotherapeutic carriers is an important challenge in the field of drug delivery, particularly in the area of protein-based vaccines. While the delivery of protein antigens to antigen presenting cells (APCs) is crucial for this type of vaccination, the incorporation of additional adjuvants may be just as important in order to generate more potent immune responses. This article presents the synthesis and biological evaluation of carrier particles that both deliver a protein payload to APCs and display receptor ligands for the enhancement of APC immunostimulation. Particles displaying CpG oligonucleotide ligands for Toll-like receptor 9 were synthesized. The addition of CpG DNA to the particles led to a 45-fold increase in the secretion of interleukin-12, a cytokine that aids in T-cell activation, and a significant increase in the expression of costimulatory molecules by APCs. Moreover, vaccination with particles containing both ovalbumin (OVA) and CpG DNA induced a superior OVA-specific CD8 T-cell response in vivo, as measured by increased OVA-specific CD8 T-cell proliferation, secretion of the proinflammatory cytokine IFN-gamma, and the induction of OVA-specific cytotoxicity.     

Green fluorescent protein gene as a tool to examine the efficacy of Agrobacterium-delivered CRISPR/Cas9 reagents to generate targeted mutations in the potato genome

CRISPR/Cas9 has emerged as a simple, yet efficient gene editing tool to generate targeted mutations in desired genes in crops plants. Agrobacterium tumefaciens, a reliable and inexpensive DNA-delivery mechanism into plant cells, has been used for the generation of CRISPR/Cas9-mediated mutations in crop plants, including potato. However, little information is available as to the progression of gene knockout during various stages of culture following the introduction of CRISPR components in this species. In the current study, the green fluorescent protein (gfp) transgene was first introduced in the genome of a potato variety, Yukon Gold. Two GFP-expressing lines, one with a single gfp copy integrated and another with four gfp copies integrated, were subjected to CRISPR/Cas9-mediated mutations in the transgene(s) using three different gRNAs. Disappearance of GFP fluorescence was monitored during the entire culture/regeneration process. Although all three gRNAs successfully knocked out the transgene(s), their efficiencies differed greatly and did not completely match the predicted scores by some guide RNA prediction tools. The nature of mutations in various knockout events was analyzed. Several lines containing four gfp-copies showed four different types of mutations. These findings suggest that it is possible to target all four alleles of a desired native gene in the tetraploid potato.

     

The discovery and structure-activity relationships of pyrano[3,4-b]indole-based inhibitors of hepatitis C virus NS5B polymerase

We describe the structure-activity relationship of the C7-position of pyrano[3,4-b]indole-based inhibitors of HCV NS5B polymerase. Further exploration of the allosteric binding site led to the discovery of the significantly more potent compounds 13 and 14.     

Algorithms for MDC-based multi-locus phylogeny inference: beyond rooted binary gene trees on single alleles

One of the criteria for inferring a species tree from a collection of gene trees, when gene tree incongruence is assumed to be due to incomplete lineage sorting (ILS), is Minimize Deep Coalescence (MDC). Exact algorithms for inferring the species tree from rooted, binary trees under MDC were recently introduced. Nevertheless, in phylogenetic analyses of biological data sets, estimated gene trees may differ from true gene trees, be incompletely resolved, and not necessarily rooted. In this article, we propose new MDC formulations for the cases where the gene trees are unrooted/binary, rooted/non-binary, and unrooted/non-binary. Further, we prove structural theorems that allow us to extend the algorithms for the rooted/binary gene tree case to these cases in a straightforward manner. In addition, we devise MDC-based algorithms for cases when multiple alleles per species may be sampled. We study the performance of these methods in coalescent-based computer simulations.     

Suppression of statin effectiveness by copper and zinc in yeast and human cells

Lovastatin and other statins inhibit HMG-CoA reductase, which carries out an early step in the sterol biosynthesis pathway. Statins lower cholesterol and are widely prescribed to prevent heart disease, but like many drugs, they can interact with nutritionally acquired metabolites. To probe these interactions, we explored the effect of a diverse library of metabolites on statin effectiveness using a Saccharomyces cerevisiae model. In yeast, treatment with lovastatin results in reduced growth. We combined lovastatin with the library of metabolites, and found that copper and zinc ions impaired the ability of the statin to inhibit yeast growth. Using an integrated genomic and metabolomic approach, we found that lovastatin plus metal synergistically upregulated some sterol biosynthesis genes. This altered pattern of gene expression resulted in greater flux through the sterol biosynthesis pathway and an increase in ergosterol levels. Each sterol intermediate level was correlated with expression of the upstream gene. Thus, the ergosterol biosynthetic response induced by statin is enhanced by copper and zinc. In cultured mammalian cells, these metals also rescued statin growth inhibition. Because copper and zinc impair the ability of statin to reduce sterol biosynthesis, dietary intake of these metals could have clinical relevance for statin treatment in humans.     

Requirement of mouse BCCIP for neural development and progenitor proliferation

Multiple DNA repair pathways are involved in the orderly development of neural systems at distinct stages. The homologous recombination (HR) pathway is required to resolve stalled replication forks and critical for the proliferation of progenitor cells during neural development. BCCIP is a BRCA2 and CDKN1A interacting protein implicated in HR and inhibition of DNA replication stress. In this study, we determined the role of BCCIP in neural development using a conditional BCCIP knock-down mouse model. BCCIP deficiency impaired embryonic and postnatal neural development, causing severe ataxia, cerebral and cerebellar defects, and microcephaly. These development defects are associated with spontaneous DNA damage and subsequent cell death in the proliferative cell populations of the neural system during embryogenesis. With in vitro neural spheroid cultures, BCCIP deficiency impaired neural progenitor's self-renewal capability, and spontaneously activated p53. These data suggest that BCCIP and its anti-replication stress functions are essential for normal neural development by maintaining an orderly proliferation of neural progenitors.