Development of an in vivo active,dual EP1 and EP3 selective antagonist based on a novel acyl sulfonamide bioisostere

Recent preclinical studies demonstrate a role for the prostaglandin E₂ (PGE₂) subtype 1 (EP1) receptor in mediating, at least in part, the pathophysiology of hypertension and diabetes mellitus. A series of amide and N-acylsulfonamide analogs of a previously described picolinic acid-based human EP1 receptor antagonist (7) were prepared. Each analog had improved selectivity at the mouse EP1 receptor over the mouse thromboxane receptor (TP). A subset of analogs gained affinity for the mouse PGE₂ subtype 3 (EP3) receptor, another potential therapeutic target. One analog (17) possessed equal selectivity for EP1 and EP3, displayed a sufficient in vivo residence time in mice, and lacked the potential for acyl glucuronide formation common to compound 7. Treatment of mice with 17 significantly attenuated the vasopressor activity resulting from an acute infusion of EP1 and EP3 receptor agonists. Compound 17 represents a potentially novel therapeutic in the treatment of hypertension and diabetes mellitus.     

Recurrent Tissue-Specific mtDNA Mutations Are Common in Humans

Mitochondrial DNA (mtDNA) variation can affect phenotypic variation; therefore, knowing its distribution within and among individuals is of importance to understanding many human diseases. Intra-individual mtDNA variation (heteroplasmy) has been generally assumed to be random. We used massively parallel sequencing to assess heteroplasmy across ten tissues and demonstrate that in unrelated individuals there are tissue-specific, recurrent mutations. Certain tissues, notably kidney, liver and skeletal muscle, displayed the identical recurrent mutations that were undetectable in other tissues in the same individuals. Using RFLP analyses we validated one of the tissue-specific mutations in the two sequenced individuals and replicated the patterns in two additional individuals. These recurrent mutations all occur within or in very close proximity to sites that regulate mtDNA replication, strongly implying that these variations alter the replication dynamics of the mutated mtDNA genome. These recurrent variants are all independent of each other and do not occur in the mtDNA coding regions. The most parsimonious explanation of the data is that these frequently repeated mutations experience tissue-specific positive selection, probably through replication advantage.     

Evidence for a dinuclear active site in the metallo-beta-lactamase BcII with substoichiometric Co(II). A new model for metal uptake

Metallo-beta-lactamases are zinc-dependent enzymes that constitute one of the main resistance mechanisms to beta-lactam antibiotics. Metallo-beta-lactamases have been characterized both in mono- and dimetallic forms. Despite many studies, the role of each metal binding site in substrate binding and catalysis is still unclear. This is mostly due to the difficulties in assessing the metal content and site occupancy in solution. For this reason, Co(II) has been utilized as a useful probe of the active site structure. We have employed UV-visible, EPR, and NMR spectroscopy to study Co(II) binding to the metallo-beta-lactamase BcII from Bacillus cereus. The spectroscopic features were attributed to the two canonical metal binding sites, the 3H (His(116), His(118), and His(196)) and DCH (Asp(120), Cys(221), and His(263)) sites. These data clearly reveal the coexistence of mononuclear and dinuclear Co(II)-loaded forms at Co(II)/enzyme ratios as low as 0.6. This picture is consistent with the macroscopic dissociation constants here determined from competition binding experiments. A spectral feature previously assigned to the DCH site in the dinuclear species corresponds to a third, weakly bound Co(II) site. The present work emphasizes the importance of using different spectroscopic techniques to follow the metal content and localization during metallo-beta-lactamase turnover.     

MCMC implementation of the optimal Bayesian classifier for non-Gaussian models: model-based RNA-Seq classification

Background

Sequencing datasets consist of a finite number of reads which map to specific regions of a reference genome. Most effort in modeling these datasets focuses on the detection of univariate differentially expressed genes. However, for classification, we must consider multiple genes and their interactions.

Results

Thus, we introduce a hierarchical multivariate Poisson model (MP) and the associated optimal Bayesian classifier (OBC) for classifying samples using sequencing data. Lacking closed-form solutions, we employ a Monte Carlo Markov Chain (MCMC) approach to perform classification. We demonstrate superior or equivalent classification performance compared to typical classifiers for two synthetic datasets and over a range of classification problem difficulties. We also introduce the Bayesian minimum mean squared error (MMSE) conditional error estimator and demonstrate its computation over the feature space. In addition, we demonstrate superior or leading class performance over an RNA-Seq dataset containing two lung cancer tumor types from The Cancer Genome Atlas (TCGA).

Conclusions

Through model-based, optimal Bayesian classification, we demonstrate superior classification performance for both synthetic and real RNA-Seq datasets. A tutorial video and Python source code is available under an open source license at http://bit.ly/1gimnss.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0401-3) contains supplementary material, which is available to authorized users.     

Accurate,Fully-Automated NMR Spectral Profiling for Metabolomics

Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites) that appear in a person’s biofluids, which means such diseases can often be readily detected from a person’s “metabolic profile"—i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR) spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person’s metabolic profile. Given a 1D ¹H NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid), BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the “signatures” of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF), defined mixtures and realistic computer generated spectra; involving > 50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (~ 90% correct identification and ~ 10% quantification error), in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively—with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of NMR in clinical settings. BAYESIL is accessible at http://www.bayesil.ca.     

RAPID EVOLUTION OF REPRODUCTIVE ISOLATION BETWEEN INCIPIENT OUTCROSSING AND SELFING CLARKIA SPECIES

A major goal of speciation research is to understand the processes involved in the earliest stages of the evolution of reproductive isolation (RI). One important challenge has been to identify systems where lineages have very recently diverged and opportunities for hybridization are present. We conducted a comprehensive examination of the components of RI across the life cycle of two subspecies of Clarkia xantiana, which diverged recently (ca. 65,000 bp). One subspecies is primarily outcrossing, but self‐compatible, whereas the other is primarily selfing. The subspecies co‐occur in a zone of sympatry but hybrids are rarely observed. Premating barriers resulted in nearly complete isolation in both subspecies with flowering time and pollinator preference (for the outcrosser over the selfer) as the strongest barriers. We found that the outcrosser had consistently more competitive pollen, facilitating hybridization in one direction, but no evidence for pollen–pistil interactions as an isolating barrier. Surprisingly, postzygotic isolation was detected at the stage of hybrid seed development, but in no subsequent life stages. This crossing barrier was asymmetric with crosses from the selfer to outcrosser most frequently failing. Collectively, the results provide evidence for rapid evolution of multiple premating and postzygotic barriers despite a very recent divergence time.     

Localized hypoxia may have caused coral reef mortality at the Flower Garden Banks

Coral Reefs - On July 25, 2016, turbid water and dead corals, sponges and other invertebrates were discovered at the East Bank (EB) of the Flower Garden Banks (FGB) National Marine Sanctuary....     

Identification of novel potentially toxic oligomers formed in vitro from mammalian-derived expanded huntingtin exon-1 protein

Huntington disease is a genetic neurodegenerative disorder that arises from an expanded polyglutamine region in the N terminus of the HD gene product, huntingtin. Protein inclusions comprised of N-terminal fragments of mutant huntingtin are a characteristic feature of disease, though are likely to play a protective role rather than a causative one in neurodegeneration. Soluble oligomeric assemblies of huntingtin formed early in the aggregation process are candidate toxic species in HD. In the present study, we established an in vitro system to generate recombinant huntingtin in mammalian cells. Using both denaturing and native gel analysis, we have identified novel oligomeric forms of mammalian-derived expanded huntingtin exon-1 N-terminal fragment. These species are transient and were not previously detected using bacterially expressed exon-1 protein. Importantly, these species are recognized by 3B5H10, an antibody that recognizes a two-stranded hairpin conformation of expanded polyglutamine believed to be associated with a toxic form of huntingtin. Interestingly, comparable oligomeric species were not observed for expanded huntingtin shortstop, a 117-amino acid fragment of huntingtin shown previously in mammalian cell lines and transgenic mice, and here in primary cortical neurons, to be non-toxic. Further, we demonstrate that expanded huntingtin shortstop has a reduced ability to form amyloid-like fibrils characteristic of the aggregation pathway for toxic expanded polyglutamine proteins. Taken together, these data provide a possible candidate toxic species in HD. In addition, these studies demonstrate the fundamental differences in early aggregation events between mutant huntingtin exon-1 and shortstop proteins that may underlie the differences in toxicity.     

Benzylideneoxymorphone: A new lead for development of bifunctional mu/delta opioid receptor ligands

Opioid analgesic tolerance remains a considerable drawback to chronic pain management. The finding that concomitant administration of delta opioid receptor (DOR) antagonists attenuates the development of tolerance to mu opioid receptor (MOR) agonists has led to interest in producing bifunctional MOR agonist/DOR antagonist ligands. Herein, we present 7-benzylideneoxymorphone (6, UMB 246) displaying MOR partial agonist/DOR antagonist activity, representing a new lead for designing bifunctional MOR/DOR ligands.     

CC chemokine receptor 7 contributes to Gi-dependent T cell motility in the lymph node

Naive T cells migrate extensively within lymph node (LN) T zones to scan for Ag-bearing dendritic cells. However, the extracellular signals controlling T cell motility in LNs are not well defined. In this study, by real-time imaging of LNs, we show that the inhibition of Gi signaling in T cells severely impairs their migration. The chemokine CCL21, a ligand of CCR7, strongly induces chemokinesis in vitro, and T cell motility in LNs from CCR7 ligand-deficient plt/plt mice was reduced. CCR7-deficient T cells in wild-type LNs showed a similar reduction in motility, and antagonism of CXCR4 function did not further decrease their motility. The effect of CCR7 or CCR7-ligand deficiency could account for approximately 40% of the Gi-dependent motility. These results reveal a role for CCR7 in promoting T cell migration within lymphoid organ T zones, and they suggest the additional involvement of novel Gi-coupled receptors in promoting T cell motility at these sites.