Single cell transcriptomics of neighboring hyphae of <Emphasis Type="Italic">Aspergillus niger</Emphasis>

Single cell profiling was performed to assess differences in RNA accumulation in neighboring hyphae of the fungus Aspergillus niger. A protocol was developed to isolate and amplify RNA from single hyphae or parts thereof. Microarray analysis resulted in a present call for 4 to 7% of the A. niger genes, of which 12% showed heterogeneous RNA levels. These genes belonged to a wide range of gene categories.     

Living with myotonic dystrophy; what can be learned from couples? a qualitative study

Background  

Myotonic dystrophy type 1 (MD1) is one of the most prevalent neuromuscular diseases, yet very little is known about how MD1 affects the lives of couples and how they themselves manage individually and together. To better match health care to their problems, concerns and needs, it is important to understand their perspective of living with this hereditary, systemic disease.     

Biomolecular characterization of allergenic proteins in snow crab (Chionoecetes opilio) and de novo sequencing of the second allergen arginine kinase using tandem mass spectrometry

Snow crab (Chionoecetes opilio) proteins have been recognized as an important source of both food and occupational allergens. While snow crab causes a significant occupational allergy, only one novel allergen has recently been fully characterized. The muscle proteins from snow crab legs were profiled by SDS-PAGE. Several of these proteins were characterized using tandem mass spectrometry. Five proteins were identified; sarcoplasmic Ca-binding (20kDa), arginine kinase (40), troponin (23kDa) and α-actine (42kDa) and smooth endoplasmic reticulum Ca(2+)ATPase (113kDa). Immunoblotting using serum of sixteen allergic patients resulted in strong reactivity with the 40-kDa protein in seven patients (43%). This protein was purified by chromatography and subsequently de novo sequenced using matrix assisted laser desorption ionization and electrospray tandem mass spectrometry. We identified a second important allergen, arginine kinase, in snow crab, designated Chi o 3. Based on identity and homology analysis, using bioinformatics tools, a signature peptide was identified as a chemical surrogate for arginine kinase. The suitability of this signature peptide was tested for analytically representing the arginine kinase, by performing a multi-reaction monitoring tandem mass spectrometry approach on actual air filter samples collected from a simulated crab processing plant.     

Character displacement in the midst of background evolution in island populations of Anolis lizards: A spatiotemporal perspective

Negative interactions between species can generate divergent selection that causes character displacement. However, other processes cause similar divergence. We use spatial and temporal replication across island populations of Anolis lizards to assess the importance of negative interactions in driving trait shifts. Previous work showed that the establishment of Anolis sagrei on islands drove resident Anolis carolinensis to perch higher and evolve larger toepads. To further test the interaction's causality and predictability, we resurveyed a subset of islands nine years later. Anolis sagrei had established on one island between surveys. We found that A. carolinensis on this island now perch higher and have larger toepads. However, toepad morphology change on this island was not distinct from shifts on six other islands whose Anolis community composition had not changed. Thus, the presence of A. sagrei only partly explains A. carolinensis trait variation across space and time. We also found that A. carolinensis on islands with previously established A. sagrei now perch higher than a decade ago, and that current A. carolinensis perch height is correlated with A. sagrei density. Our results suggest that character displacement likely interacts with other evolutionary processes in this system, and that temporal data are key to detecting such interactions.     

Synthesis and biological evaluation of novel 5(H)-phenanthridin-6-ones, 5(H)-phenanthridin-6-one diketo acid, and polycyclic aromatic diketo acid analogs as new HIV-1 integrase inhibitors

A new series of phenanthridinone derivatives, and diketo acid analogs, as well as related phenanthrene and anthracene diketo acids have been synthesized and evaluated as HIV integrase (IN) inhibitors. Several new beta-diketo acid analogs with the phenanthridinone scaffold replaced by phenanthrene, anthracene or pyrene exhibited the highest IN inhibitory potency. There is a general selectivity against the integrase strand transfer step. The most potent IN was 2,4-dioxo-4-phenanthren-9-yl-butyric acid (27f) with an IC(50) of 0.38microM against integrase strand transfer. The phenanthrene diketo acids 27d-f were more potent (IC(50)=2.7-0.38microM) than the corresponding phenanthridinone diketo acid 16 (IC(50)=65microM), suggesting that the polar amide bridge in the phenanthridinone system decreases inhibitory activity relative to the more lipophilic phenanthrene system. This might have to do with the possible binding of the aryl group of the compounds binding to a lipophilic pocket at the integrase active site as suggested by the docking simulations. Molecular modeling also suggested that effectiveness of chelation of the active site Mg(2+) contributes to IN inhibitory potency. Finally, some of the potent compounds inhibited HIV-1 replication in human peripheral blood mononuclear cells (PBMC) with EC(50) down to 8microM for phenanthrene-3-(2,4-dioxo)butyric acid (27d), with a selectivity index of 10 against PBMCs.     

Isolation and Characterization of a Hybrid Respiratory Supercomplex Consisting of Mycobacterium tuberculosis Cytochrome bcc and Mycobacterium smegmatis Cytochrome aa3

Recently, energy production pathways have been shown to be viable antitubercular drug targets to combat multidrug-resistant tuberculosis and eliminate pathogen in the dormant state. One family of drugs currently under development, the imidazo[1,2-a]pyridine derivatives, is believed to target the pathogen''s homolog of the mitochondrial bc₁ complex. This complex, denoted cytochrome bcc, is highly divergent from mitochondrial Complex III both in subunit structure and inhibitor sensitivity, making it a good target for drug development. There is no soluble cytochrome c in mycobacteria to transport electrons from the bcc complex to cytochrome oxidase. Instead, the bcc complex exists in a “supercomplex” with a cytochrome aa₃-type cytochrome oxidase, presumably allowing direct electron transfer. We describe here purification and initial characterization of the mycobacterial cytochrome bcc-aa₃ supercomplex using a strain of M. smegmatis that has been engineered to express the M. tuberculosis cytochrome bcc. The resulting hybrid supercomplex is stable during extraction and purification in the presence of dodecyl maltoside detergent. It is hoped that this purification procedure will potentiate functional studies of the complex as well as crystallographic studies of drug binding and provide structural insight into a third class of the bc complex superfamily.     

Interleukin-10 regulates the inflammasome-driven augmentation of inflammatory arthritis and joint destruction

Introduction

Activation of the inflammasome has been implicated in the pathology of various autoinflammatory and autoimmune diseases. While the NLRP3 inflammasome has been linked to arthritis progression, little is known about its synovial regulation or contribution to joint histopathology. Regulators of inflammation activation, such as interleukin (IL)-10, may have the potential to limit the inflammasome-driven arthritic disease course and associated structural damage. Hence, we used IL-10-deficient (IL-10KO) mice to assess NLRP3 inflammasome-driven arthritic pathology.

Methods

Antigen-induced arthritis (AIA) was established in IL-10KO mice and wild-type controls. Using histological and radiographic approaches together with quantitative real-time PCR of synovial mRNA studies, we explored the regulation of inflammasome components. These were combined with selective blocking agents and ex vivo investigative studies in osteoclast differentiation assays.

Results

In AIA, IL-10KO mice display severe disease with increased histological and radiographic joint scores. Here, focal bone erosions were associated with increased tartrate-resistant acid phosphatase (TRAP)-positive cells and a localized expression of IL-1β. When compared to controls, IL-10KO synovium showed increased expression of Il1b, Il33 and NLRP3 inflammasome components. Synovial Nlrp3 and Casp1 expression further correlated with Acp5 (encoding TRAP), while neutralization of IL-10 receptor signaling in control mice caused increased expression of Nlrp3 and Casp1. In ex vivo osteoclast differentiation assays, addition of exogenous IL-10 or selective blockade of the NLRP3 inflammasome inhibited osteoclastogenesis.

Conclusions

These data provide a link between IL-10, synovial regulation of the NLRP3 inflammasome and the degree of bone erosions observed in inflammatory arthritis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-014-0419-y) contains supplementary material, which is available to authorized users.     

Effective Automated Feature Construction and Selection for Classification of Biological Sequences

Background

Many open problems in bioinformatics involve elucidating underlying functional signals in biological sequences. DNA sequences, in particular, are characterized by rich architectures in which functional signals are increasingly found to combine local and distal interactions at the nucleotide level. Problems of interest include detection of regulatory regions, splice sites, exons, hypersensitive sites, and more. These problems naturally lend themselves to formulation as classification problems in machine learning. When classification is based on features extracted from the sequences under investigation, success is critically dependent on the chosen set of features.

Methodology

We present an algorithmic framework (EFFECT) for automated detection of functional signals in biological sequences. We focus here on classification problems involving DNA sequences which state-of-the-art work in machine learning shows to be challenging and involve complex combinations of local and distal features. EFFECT uses a two-stage process to first construct a set of candidate sequence-based features and then select a most effective subset for the classification task at hand. Both stages make heavy use of evolutionary algorithms to efficiently guide the search towards informative features capable of discriminating between sequences that contain a particular functional signal and those that do not.

Results

To demonstrate its generality, EFFECT is applied to three separate problems of importance in DNA research: the recognition of hypersensitive sites, splice sites, and ALU sites. Comparisons with state-of-the-art algorithms show that the framework is both general and powerful. In addition, a detailed analysis of the constructed features shows that they contain valuable biological information about DNA architecture, allowing biologists and other researchers to directly inspect the features and potentially use the insights obtained to assist wet-laboratory studies on retainment or modification of a specific signal. Code, documentation, and all data for the applications presented here are provided for the community at http://www.cs.gmu.edu/~ashehu/?q=OurTools.