Classes of Multiple Decision Functions Strongly Controlling FWER and FDR

This paper provides two general classes of multiple decision functions where each member of the first class strongly controls the family-wise error rate (FWER), while each member of the second class strongly controls the false discovery rate (FDR). These classes offer the possibility that an optimal multiple decision function with respect to a pre-specified criterion, such as the missed discovery rate (MDR), could be found within these classes. Such multiple decision functions can be utilized in multiple testing, specifically, but not limited to, the analysis of high-dimensional microarray data sets.Comment: 19 page

Towards Alignment Independent Quantitative Assessment of Homology Detection

Identification of homologous proteins provides a basis for protein annotation. Sequence alignment tools reliably identify homologs sharing high sequence similarity. However, identification of homologs that share low sequence similarity remains a challenge. Lowering the cutoff value could enable the identification of diverged homologs, but also introduces numerous false hits. Methods are being continuously developed to minimize this problem. Estimation of the fraction of homologs in a set of protein alignments can help in the assessment and development of such methods, and provides the users with intuitive quantitative assessment of protein alignment results. Herein, we present a computational approach that estimates the amount of homologs in a set of protein pairs. The method requires a prevalent and detectable protein feature that is conserved between homologs. By analyzing the feature prevalence in a set of pairwise protein alignments, the method can estimate the number of homolog pairs in the set independently of the alignments' quality. Using the HomoloGene database as a standard of truth, we implemented this approach in a proteome-wide analysis. The results revealed that this approach, which is independent of the alignments themselves, works well for estimating the number of homologous proteins in a wide range of homology values. In summary, the presented method can accompany homology searches and method development, provides validation to search results, and allows tuning of tools and methods

The fitness of African malaria vectors in the presence and limitation of host behaviour

<p>Background Host responses are important sources of selection upon the host species range of ectoparasites and phytophagous insects. However little is known about the role of host responses in defining the host species range of malaria vectors. This study aimed to estimate the relative importance of host behaviour to the feeding success and fitness of African malaria vectors, and assess its ability to predict their known host species preferences in nature.</p> <p>Methods Paired evaluations of the feeding success and fitness of African vectors Anopheles arabiensis and Anopheles gambiae s.s in the presence and limitation of host behaviour were conducted in a semi-field system (SFS) at Ifakara Health Institute, Tanzania. In one set of trials, mosquitoes were released within the SFS and allowed to forage overnight on a host that was free to exhibit natural behaviour in response to insect biting. In the other, mosquitoes were allowed to feed directly on from the skin surface of immobile hosts. The feeding success and subsequent fitness of vectors under these conditions were investigated on 6 host types (humans, calves, chickens, cows, dogs and goats) to assess whether physical movements of preferred host species (cattle for An. arabiensis, humans for An. gambiae s.s.) were less effective at preventing mosquito bites than those of common alternatives.</p> <p>Results Anopheles arabiensis generally had greater feeding success when applied directly to host skin than when foraging on unrestricted hosts (in five of six host species). However, An. gambiae s.s obtained blood meals from free and restrained hosts with similar success from most host types (four out of six). Overall, the blood meal size, oviposition rate, fecundity and post-feeding survival of mosquito vectors were significantly higher after feeding on hosts free to exhibit behaviour, than those who were immobilized during feeding trials.</p> <p>Conclusions Allowing hosts to move freely during exposure to mosquitoes was associated with moderate reductions in mosquito feeding success, but no detrimental impact to the subsequent fitness of mosquitoes that were able to feed upon them. This suggests that physical defensive behaviours exhibited by common host species including humans do not impose substantial fitness costs on African malaria vectors.</p&gt

Reversible Keap1 inhibitors are preferential pharmacological tools to modulate cellular mitophagy

Mitophagy orchestrates the autophagic degradation of dysfunctional mitochondria preventing their pathological accumulation and contributing to cellular homeostasis. We previously identified a novel chemical tool (hereafter referred to as PMI), which drives mitochondria into autophagy without collapsing their membrane potential (ΔΨm). PMI is an inhibitor of the protein-protein interaction (PPI) between the transcription factor Nrf2 and its negative regulator, Keap1 and is able to up-regulate the expression of autophagy-associated proteins, including p62/SQSTM1. Here we show that PMI promotes mitochondrial respiration, leading to a superoxide-dependent activation of mitophagy. Structurally distinct Keap1-Nrf2 PPI inhibitors promote mitochondrial turnover, while covalent Keap1 modifiers, including sulforaphane (SFN) and dimethyl fumarate (DMF), are unable to induce a similar response. Additionally, we demonstrate that SFN reverses the effects of PMI in co-treated cells by reducing the accumulation of p62 in mitochondria and subsequently limiting their autophagic degradation. This study highlights the unique features of Keap1-Nrf2 PPI inhibitors as inducers of mitophagy and their potential as pharmacological agents for the treatment of pathological conditions characterized by impaired mitochondrial quality control

A grammar-based distance metric enables fast and accurate clustering of large sets of 16S sequences

Background: We propose a sequence clustering algorithm and compare the partition quality and execution time of the proposed algorithm with those of a popular existing algorithm. The proposed clustering algorithm uses a grammar-based distance metric to determine partitioning for a set of biological sequences. The algorithm performs clustering in which new sequences are compared with cluster-representative sequences to determine membership. If comparison fails to identify a suitable cluster, a new cluster is created. Results: The performance of the proposed algorithm is validated via comparison to the popular DNA/RNA sequence clustering approach, CD-HIT-EST, and to the recently developed algorithm, UCLUST, using two different sets of 16S rDNA sequences from 2,255 genera. The proposed algorithm maintains a comparable CPU execution time with that of CD-HIT-EST which is much slower than UCLUST, and has successfully generated clusters with higher statistical accuracy than both CD-HIT-EST and UCLUST. The validation results are especially striking for large datasets. Conclusions: We introduce a fast and accurate clustering algorithm that relies on a grammar-based sequence distance. Its statistical clustering quality is validated by clustering large datasets containing 16S rDNA sequences

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues

Theoretical study of the insulating oxides and nitrides: SiO2, GeO2, Al2O3, Si3N4, and Ge3N4

An extensive theoretical study is performed for wide bandgap crystalline oxides and nitrides, namely, SiO_{2}, GeO_{2}, Al_{2}O_{3}, Si_{3}N_{4}, and Ge_{3}N_{4}. Their important polymorphs are considered which are for SiO_{2}: $\alpha$-quartz, $\alpha$- and $\beta$-cristobalite and stishovite, for GeO_{2}: $\alpha$-quartz, and rutile, for Al_{2}O_{3}: $\alpha$-phase, for Si_{3}N_{4} and Ge_{3}N_{4}: $\alpha$- and $\beta$-phases. This work constitutes a comprehensive account of both electronic structure and the elastic properties of these important insulating oxides and nitrides obtained with high accuracy based on density functional theory within the local density approximation. Two different norm-conserving \textit{ab initio} pseudopotentials have been tested which agree in all respects with the only exception arising for the elastic properties of rutile GeO_{2}. The agreement with experimental values, when available, are seen to be highly satisfactory. The uniformity and the well convergence of this approach enables an unbiased assessment of important physical parameters within each material and among different insulating oxide and nitrides. The computed static electric susceptibilities are observed to display a strong correlation with their mass densities. There is a marked discrepancy between the considered oxides and nitrides with the latter having sudden increase of density of states away from the respective band edges. This is expected to give rise to excessive carrier scattering which can practically preclude bulk impact ionization process in Si_{3}N_{4} and Ge_{3}N_{4}.Comment: Published version, 10 pages, 8 figure

Parallel multiplicity and error discovery rate (EDR) in microarray experiments

<p>Abstract</p> <p>Background</p> <p>In microarray gene expression profiling experiments, differentially expressed genes (DEGs) are detected from among tens of thousands of genes on an array using statistical tests. It is important to control the number of false positives or errors that are present in the resultant DEG list. To date, more than 20 different multiple test methods have been reported that compute overall Type I error rates in microarray experiments. However, these methods share the following dilemma: they have low power in cases where only a small number of DEGs exist among a large number of total genes on the array.</p> <p>Results</p> <p>This study contrasts parallel multiplicity of objectively related tests against the traditional simultaneousness of subjectively related tests and proposes a new assessment called the Error Discovery Rate (EDR) for evaluating multiple test comparisons in microarray experiments. Parallel multiple tests use only the negative genes that parallel the positive genes to control the error rate; while simultaneous multiple tests use the total unchanged gene number for error estimates. Here, we demonstrate that the EDR method exhibits improved performance over other methods in specificity and sensitivity in testing expression data sets with sequence digital expression confirmation, in examining simulation data, as well as for three experimental data sets that vary in the proportion of DEGs. The EDR method overcomes a common problem of previous multiple test procedures, namely that the Type I error rate detection power is low when the total gene number used is large but the DEG number is small.</p> <p>Conclusions</p> <p>Microarrays are extensively used to address many research questions. However, there is potential to improve the sensitivity and specificity of microarray data analysis by developing improved multiple test comparisons. This study proposes a new view of multiplicity in microarray experiments and the EDR provides an alternative multiple test method for Type I error control in microarray experiments.</p

Solution structure of a repeated unit of the ABA-1 nematode polyprotein allergen of ascaris reveals a novel fold and two discrete lipid-binding sites

Parasitic nematode worms cause serious health problems in humans and other animals. They can induce allergic-type immune responses, which can be harmful but may at the same time protect against the infections. Allergens are proteins that trigger allergic reactions and these parasites produce a type that is confined to nematodes, the nematode polyprotein allergens (NPAs). These are synthesized as large precursor proteins comprising repeating units of similar amino acid sequence that are subsequently cleaved into multiple copies of the allergen protein. NPAs bind small lipids such as fatty acids and retinol (Vitamin A) and probably transport these sensitive and insoluble compounds between the tissues of the worms. Nematodes cannot synthesize these lipids, so NPAs may also be crucial for extracting nutrients from their hosts. They may also be involved in altering immune responses by controlling the lipids by which the immune and inflammatory cells communicate. We describe the molecular structure of one unit of an NPA, the well-known ABA-1 allergen of Ascaris and find its structure to be of a type not previously found for lipid-binding proteins, and we describe the unusual sites where lipids bind within this structur