A Novel Bifunctional Alkylphenol Anesthetic Allows Characterization of γ-Aminobutyric Acid,Type A (GABAA), Receptor Subunit Binding Selectivity in Synaptosomes

Propofol, an intravenous anesthetic, is a positive modulator of the GABA_A receptor, but the mechanistic details, including the relevant binding sites and alternative targets, remain disputed. Here we undertook an in-depth study of alkylphenol-based anesthetic binding to synaptic membranes. We designed, synthesized, and characterized a chemically active alkylphenol anesthetic (2-((prop-2-yn-1-yloxy)methyl)-5-(3-(trifluoromethyl)-3H-diazirin-3-yl)phenol, AziPm-click (1)), for affinity-based protein profiling (ABPP) of propofol-binding proteins in their native state within mouse synaptosomes. The ABPP strategy captured ∼4% of the synaptosomal proteome, including the unbiased capture of five α or β GABA_A receptor subunits. Lack of γ2 subunit capture was not due to low abundance. Consistent with this, independent molecular dynamics simulations with alchemical free energy perturbation calculations predicted selective propofol binding to interfacial sites, with higher affinities for α/β than γ-containing interfaces. The simulations indicated hydrogen bonding is a key component leading to propofol-selective binding within GABA_A receptor subunit interfaces, with stable hydrogen bonds observed between propofol and α/β cavity residues but not γ cavity residues. We confirmed this by introducing a hydrogen bond-null propofol analogue as a protecting ligand for targeted-ABPP and observed a lack of GABA_A receptor subunit protection. This investigation demonstrates striking interfacial GABA_A receptor subunit selectivity in the native milieu, suggesting that asymmetric occupancy of heteropentameric ion channels by alkylphenol-based anesthetics is sufficient to induce modulation of activity.     

Activated Memory CD4+ T Helper Cells Repopulate the Intestine Early following Antiretroviral Therapy of Simian Immunodeficiency Virus-Infected Rhesus Macaques but Exhibit a Decreased Potential To Produce Interleukin-2

Using the simian immunodeficiency virus (SIV)-infected rhesus macaque model, we performed a longitudinal study to determine the effect of antiretroviral therapy on the phenotype and functional potential of CD4(+) T cells repopulating intestinal mucosa in human immunodeficiency virus infection. Severe depletion of CD4(+) and CD4(+) CD8(+) T cells occurred in the intestinal mucosa during primary SIV infection. The majority of these cells were of activated memory phenotype. Phosphonate 9-[2-(phosphomethoxypropyl]adenine (PMPA) treatment led to a moderate suppression of intestinal viral loads and repopulation of intestinal mucosa by predominantly activated memory CD4(+) T-helper cells. This repopulation was independent of the level of viral suppression. Compared to preinfection values, the frequency of naive CD4(+) T cells increased following PMPA therapy, suggesting that new CD4(+) T cells were repopulating the intestinal mucosa. Repopulation by CD4(+) CD8(+) T cells was not observed in either jejunum or colon lamina propria. The majority of CD4(+) T cells repopulating the intestinal mucosa following PMPA therapy were CD29(hi) and CD11ahi. A subset of repopulating intestinal CD4(+) T cells expressed Ki-67 antigen, indicating that local proliferation may play a role in the repopulation process. Although the majority of repopulating CD4(+) T cells in the intestinal mucosa were functionally capable of providing B- and T-cell help, as evidenced by their expression of CD28, these CD4(+) T cells were found to have a reduced capacity to produce interleukin-2 (IL-2) compared to the potential of CD4(+) T cells prior to SIV infection. Persistent viral infection may play a role in suppressing the potential of repopulating CD4(+) T cells to produce IL-2. Hence, successful antiretroviral therapy should aim at complete suppression of viral loads in mucosal lymphoid tissues, such as intestinal mucosa.     

Molecular biodiversity of cassava begomoviruses in Tanzania: evolution of cassava geminiviruses in Africa and evidence for East Africa being a center of diversity of cassava geminiviruses

Cassava is infected by numerous geminiviruses in Africa and India that cause devastating losses to poor farmers. We here describe the molecular diversity of seven representative cassava mosaic geminiviruses (CMGs) infecting cassava from multiple locations in Tanzania. We report for the first time the presence of two isolates in East Africa: (EACMCV-[TZ1] and EACMCV-[TZ7]) of the species East African cassava mosaic Cameroon virus, originally described in West Africa. The complete nucleotide sequence of EACMCV-[TZ1] DNA-A and DNA-B components shared a high overall sequence identity to EACMCV-[CM] components (92% and 84%). The EACMCV-[TZ1] and -[TZ7] genomic components have recombinations in the same genome regions reported in EACMCV-[CM], but they also have additional recombinations in both components. Evidence from sequence analysis suggests that the two strains have the same ancient origin and are not recent introductions. EACMCV-[TZ1] occurred widely in the southern part of the country. Four other CMG isolates were identified: two were close to the EACMV-Kenya strain (named EACMV-[KE/TZT] and EACMV-[KE/TZM] with 96% sequence identity); one isolate, TZ10, had 98% homology to EACMV-UG2Svr and was named EACMV-UG2 [TZ10]; and finally one isolate was 95% identical to EACMV-[TZ] and named EACMV-[TZ/YV]. One isolate of African cassava mosaic virus with 97% sequence identity with other isolates of ACMV was named ACMV-[TZ]. It represents the first ACMV isolate from Tanzania to be sequenced. The molecular variability of CMGs was also evaluated using partial B component nucleotide sequences of 13 EACMV isolates from Tanzania. Using the sequences of all CMGs currently available, we have shown the presence of a number of putative recombination fragments that are more prominent in all components of EACMV than in ACMV. This new knowledge about the molecular CMG diversity in East Africa, and in Tanzania in particular, has led us to hypothesize about the probable importance of this part of Africa as a source of diversity and evolutionary change both during the early stages of the relationship between CMGs and cassava and in more recent times. The existence of multiple CMG isolates with high DNA genome diversity in Tanzania and the molecular forces behind this diversity pose a threat to cassava production throughout the African continent.     

Accuracy of diagnostic registers and management of chronic obstructive pulmonary disease: the Devon primary care audit

Background

Guidelines on COPD diagnosis and management encourage primary care physicians to detect the disease at an early stage and to treat patients according to their condition and needs. Problems in guideline implementation include difficulties in diagnosis, using spirometry and the disputed role of reversibility testing. These lead to inaccurate diagnostic registers and inadequacy of administered treatments. This study represents an audit of COPD diagnosis and management in primary care practices in Devon.

Methods

Six hundred and thirty two patients on COPD registers in primary care practices were seen by a visiting Respiratory Specialist Nurse. Diagnoses were made according to the NICE guidelines. Reversibility testing was carried out either routinely or based on clinical indication in two sub-samples. Dyspnoea was assessed. Data were entered into a novel IT-based software which computed guideline-based treatment recommendations. Current and recommended treatments were compared.

Results

Five hundred and eighty patients had spirometry. Diagnoses of COPD were confirmed in 422 patients (73%). Thirty nine patients were identified as asthma only, 94 had normal spirometry, 23 were restrictive and 2 had a cardiac disorder. Reversibility testing changed diagnosis of 11% of patients with airflow obstruction, and severity grading in 18%. Three quarters of patients with COPD had been offered practical help with smoking cessation. Short and long-acting anticholinergics and long acting beta-2 agonists had been under-prescribed; in 15–18% of patients they were indicated but not received. Inhaled steroids had been over-prescribed (recommended in 17%; taken by 60%), whereas only 4% of patients with a chronic productive cough were receiving mucolytics. Pulmonary rehabilitation was not available in some areas and was under-used in other areas.

Conclusion

Diagnostic registers of COPD in primary care contain mistakes leading to inaccurate prevalence estimates and inappropriate treatment decisions. Use of pre-bronchodilator readings for diagnosis overestimates the prevalence and severity in a significant minority, thus post bronchodilator readings should be used. Management of stable COPD does often not correspond to guidelines. The IT system used in this study has the potential to improve diagnosis and management of COPD in primary care.     

Dramatic down-regulation of oxidoreductases in human hepatocellular carcinoma hepG2 cells: proteomics and gene ontology unveiling new frontiers in cancer enzymology

Background

Oxidoreductases are enzymes that catalyze many redox reactions in normal and neoplastic cells. Their actions include catalysis of the transformation of free, neutral oxygen gas into oxygen free radicals, superoxide, hydroperoxide, singlet oxygen and hydrogen peroxide. These activated forms of oxygen contribute to oxidative stress that modifies lipids, proteins, DNA and carbohydrates. On the other hand, oxidoreductases constitute one of the most important free radical scavenger systems typified by catalase, superoxide dismutase and glutathione peroxidase. In this work, proteomics, Gene Ontology mapping and Directed Acyclic Graphs (DAG) are employed to detect and quantify differential oxidoreductase enzyme expressions between HepG2 cells and normal human liver tissues.

Results

For the set of bioinformatics calculations whose BLAST searches are performed using the BLAST program BLASTP 2.2.13 [Nov-27-2005], DAG of the Gene Ontology's Molecular Function annotations show that oxidoreductase activity parent node of the liver proteome contains 331 annotated protein sequences, 7 child nodes and an annotation score of 188.9, whereas that of HepG2 cells has 188 annotated protein sequences, 3 child nodes and an annotation score of only 91.9. Overwhelming preponderance of oxidoreductases in the liver is additionally supported by the isomerase DAGs: nearly all the reactions described in the normal liver isomerase DAG are oxidoreductase isomerization reactions, whereas only one of the three child nodes in the HepG2 isomerase DAG is oxidoreductase. Upon normalization of the annotation scores to the parent Molecular Function nodes, oxidoreductases are down-regulated in HepG2 cells by 58%. Similarly, for the set of bioinformatics calculations whose BLAST searches are carried out using BLASTP 2.2.15 [Oct-15-2006], oxidoreductases are down-regulated in HepG2 cells by 56%.

Conclusion

Proteomics and Gene Ontology reveal, for the first time, differential enzyme activities between HepG2 cells and normal human liver tissues, which may be a promising new prognostic marker of Hepatocellular carcinoma. Two independent sets of bioinformatics calculations that employ two BLAST program versions, and searched different databases, arrived at essentially the same conclusion: oxidoreductases are down-regulated in HepG2 cells by approximately 57%, when compared to normal human liver tissues. Down-regulation of oxidoreductases in hepatoma is additionally supported by Gene Ontology analysis of isomerises.     

Sample prep for proteomics of breast cancer: proteomics and gene ontology reveal dramatic differences in protein solubilization preferences of radioimmunoprecipitation assay and urea lysis buffers

Background

An important step in the proteomics of solid tumors, including breast cancer, consists of efficiently extracting most of proteins in the tumor specimen. For this purpose, Radio-Immunoprecipitation Assay (RIPA) buffer is widely employed. RIPA buffer's rapid and highly efficient cell lysis and good solubilization of a wide range of proteins is further augmented by its compatibility with protease and phosphatase inhibitors, ability to minimize non-specific protein binding leading to a lower background in immunoprecipitation, and its suitability for protein quantitation.

Results

In this work, the insoluble matter left after RIPA buffer extraction of proteins from breast tumors are subjected to another extraction step, using a urea-based buffer. It is shown that RIPA and urea lysis buffers fractionate breast tissue proteins primarily on the basis of molecular weights. The average molecular weight of proteins that dissolve exclusively in urea buffer is up to 60% higher than in RIPA. Gene Ontology (GO) and Directed Acyclic Graphs (DAG) are used to map the collective biological and biophysical attributes of the RIPA and urea proteomes. The Cellular Component and Molecular Function annotations reveal protein solubilization preferences of the buffers, especially the compartmentalization and functional distributions. It is shown that nearly all extracellular matrix proteins (ECM) in the breast tumors and matched normal tissues are found, nearly exclusively, in the urea fraction, while they are mostly insoluble in RIPA buffer. Additionally, it is demonstrated that cytoskeletal and extracellular region proteins are more soluble in urea than in RIPA, whereas for nuclear, cytoplasmic and mitochondrial proteins, RIPA buffer is preferred. Extracellular matrix proteins are highly implicated in cancer, including their proteinase-mediated degradation and remodelling, tumor development, progression, adhesion and metastasis. Thus, if they are not efficiently extracted by RIPA buffer, important information may be missed in cancer research.

Conclusion

For proteomics of solid tumors, a two-step extraction process is recommended. First, proteins in the tumor specimen should be extracted with RIPA buffer. Second, the RIPA-insoluble material should be extracted with the urea-based buffer employed in this work.     

A comparison of alternative methods to compute conditional genotype probabilities for genetic evaluation with finite locus models

An increased availability of genotypes at marker loci has prompted the development of models that include the effect of individual genes. Selection based on these models is known as marker-assisted selection (MAS). MAS is known to be efficient especially for traits that have low heritability and non-additive gene action. BLUP methodology under non-additive gene action is not feasible for large inbred or crossbred pedigrees. It is easy to incorporate non-additive gene action in a finite locus model. Under such a model, the unobservable genotypic values can be predicted using the conditional mean of the genotypic values given the data. To compute this conditional mean, conditional genotype probabilities must be computed. In this study these probabilities were computed using iterative peeling, and three Markov chain Monte Carlo (MCMC) methods – scalar Gibbs, blocking Gibbs, and a sampler that combines the Elston Stewart algorithm with iterative peeling (ESIP). The performance of these four methods was assessed using simulated data. For pedigrees with loops, iterative peeling fails to provide accurate genotype probability estimates for some pedigree members. Also, computing time is exponentially related to the number of loci in the model. For MCMC methods, a linear relationship can be maintained by sampling genotypes one locus at a time. Out of the three MCMC methods considered, ESIP, performed the best while scalar Gibbs performed the worst.     

Land Use Implications of Increased Biomass Production Identified by GIS-Based Suitability and Yield Mapping for Miscanthus in England

The need for climate change mitigation and to meet increasing energy demands has led to a rise in the land area under bioenergy crops in many countries. There are concerns that such large-scale land conversion will conflict with food production and impact on the environment. Perennial biomass crops could be grown on more marginal agricultural land. However, for sustainable solutions, biomass yields will need to be sufficient and the wider implications of land-use changes considered. Here, focusing on Miscanthus in England as an example, we combined an empirical model with GIS to produce a yield map and estimated regional energy generation potentials after masking out areas covered by environmental and socio-economic factors which could preclude the planting of energy crops. Agricultural land quality and the distributions of currently grown food crops were then taken into account. Results showed that: (i) regional contrasts occur in the importance of different factors affecting biomass planting; (ii) areas with the highest biomass yields co-locate with food producing areas on high grade land, and; (iii) when such high grade land and unsuitable areas are excluded, a policy-related scenario for increased planting on 350,000 ha utilised 4–28% (depending on the region) of lower grade land and would not necessarily greatly impact on UK food security. We conclude that the GIS-based yield and suitability mapping described here can help identify important issues in bioenergy generation potentials and land use implications at regional or finer spatial scales that would be missed in analyses at the national level.     

Haplotype inference in crossbred populations without pedigree information

Background

Current methods for haplotype inference without pedigree information assume random mating populations. In animal and plant breeding, however, mating is often not random. A particular form of nonrandom mating occurs when parental individuals of opposite sex originate from distinct populations. In animal breeding this is called crossbreeding and hybridization in plant breeding. In these situations, association between marker and putative gene alleles might differ between the founding populations and origin of alleles should be accounted for in studies which estimate breeding values with marker data. The sequence of alleles from one parent constitutes one haplotype of an individual. Haplotypes thus reveal allele origin in data of crossbred individuals.

Results

We introduce a new method for haplotype inference without pedigree that allows nonrandom mating and that can use genotype data of the parental populations and of a crossbred population. The aim of the method is to estimate line origin of alleles. The method has a Bayesian set up with a Dirichlet Process as prior for the haplotypes in the two parental populations. The basic idea is that only a subset of the complete set of possible haplotypes is present in the population.

Conclusion

Line origin of approximately 95% of the alleles at heterozygous sites was assessed correctly in both simulated and real data. Comparing accuracy of haplotype frequencies inferred with the new algorithm to the accuracy of haplotype frequencies inferred with PHASE, an existing algorithm for haplotype inference, showed that the DP algorithm outperformed PHASE in situations of crossbreeding and that PHASE performed better in situations of random mating.