Detection of secondary structure elements in proteins by hydrophobic cluster analysis.

Hydrophobic cluster analysis (HCA) is a protein sequence comparison method based on alpha-helical representations of the sequences where the size, shape and orientation of the clusters of hydrophobic residues are primarily compared. The effectiveness of HCA has been suggested to originate from its potential ability to focus on the residues forming the hydrophobic core of globular proteins. We have addressed the robustness of the bidimensional representation used for HCA in its ability to detect the regular secondary structure elements of proteins. Various parameters have been studied such as those governing cluster size and limits, the hydrophobic residues constituting the clusters as well as the potential shift of the cluster positions with respect to the position of the regular secondary structure elements. The following results have been found to support the alpha-helical bidimensional representation used in HCA: (i) there is a positive correlation (clearly above background noise) between the hydrophobic clusters and the regular secondary structure elements in proteins; (ii) the hydrophobic clusters are centred on the regular secondary structure elements; (iii) the pitch of the helical representation which gives the best correspondence is that of an alpha-helix. The correspondence between hydrophobic clusters and regular secondary structure elements suggests a way to implement variable gap penalties during the automatic alignment of protein sequences.     

Assigning strains to bacterial species via the internet

Background  

Methods for assigning strains to bacterial species are cumbersome and no longer fit for purpose. The concatenated sequences of multiple house-keeping genes have been shown to be able to define and circumscribe bacterial species as sequence clusters. The advantage of this approach (multilocus sequence analysis; MLSA) is that, for any group of related species, a strain database can be produced and combined with software that allows query strains to be assigned to species via the internet. As an exemplar of this approach, we have studied a group of species, the viridans streptococci, which are very difficult to assign to species using standard taxonomic procedures, and have developed a website that allows species assignment via the internet.     

Fuzzy species among recombinogenic bacteria

Background  

It is a matter of ongoing debate whether a universal species concept is possible for bacteria. Indeed, it is not clear whether closely related isolates of bacteria typically form discrete genotypic clusters that can be assigned as species. The most challenging test of whether species can be clearly delineated is provided by analysis of large populations of closely-related, highly recombinogenic, bacteria that colonise the same body site. We have used concatenated sequences of seven house-keeping loci from 770 strains of 11 named Neisseria species, and phylogenetic trees, to investigate whether genotypic clusters can be resolved among these recombinogenic bacteria and, if so, the extent to which they correspond to named species.     

Exploratory and inferential analysis of gene cluster neighborhood graphs

Background  

Many different cluster methods are frequently used in gene expression data analysis to find groups of co-expressed genes. However, cluster algorithms with the ability to visualize the resulting clusters are usually preferred. The visualization of gene clusters gives practitioners an understanding of the cluster structure of their data and makes it easier to interpret the cluster results.     

Control of Transdermal Permeation of Hydrocortisone Acetate from Hydrophilic and Lipophilic Formulations

The purpose of this research was the preparation of four formulations containing hydrocortisone acetate (HCA) for topical application, including two aqueous systems (hydrophilic microemulsion and aqueous gel) and two systems with dominant hydrophobicity (hydrophobic microemulsion and ointment). The formulations were tested for the release and permeation of HCA across an animal membrane. The release of HCA was found comparable for the four systems. The two microemulsions promote permeation across an ex-vivo membrane, examined by means of a Franz cell. Hydrophobic microemulsion guarantees the highest solubility (2,370 μg/ml) and flux (133 μg/cm².h) of the drug, since it contains almost 40% Transcutol, a permeation enhancer. Gel and ointment provide lower solubility and flux, being the values, related to the ointment, the lowest ones (562 μg/ml and 0.4 μg/cm².h). Experimental results allow the conclusion that gel and ointment can be suitable when it is desirable to minimize absorption of topically applied HCA as to keep the drug restricted to the diseased area and prevent side effects of the systemic presence of HCA.     

Macrosystem community change in lake phytoplankton and its implications for diversity and function

Aim

We use lake phytoplankton community data to quantify the spatio-temporal and scale-dependent impacts of eutrophication, land-use and climate change on species niches and community assembly processes while accounting for species traits and phylogenetic constraints.

Location

Finland.

Time period

1977–2017.

Major taxa

Phytoplankton.

Methods

We use hierarchical modelling of species communities (HMSC) to model metacommunity trajectories at 853 lakes over four decades of environmental change, including a hierarchical spatial structure to account for scale-dependent processes. Using a “region of common profile” approach, we evaluate compositional changes of species communities and trait profiles and investigate their temporal development.

Results

We demonstrate the emergence of novel and widespread community composition clusters in previously more compositionally homogeneous communities, with cluster-specific community trait profiles, indicating functional differences. A strong phylogenetic signal of species responses to the environment implies similar responses among closely related taxa. Community cluster-specific species prevalence indicates lower taxonomic dispersion within the current dominant clusters compared with the historically dominant cluster and an overall higher prevalence of smaller species sizes within communities. Our findings denote profound spatio-temporal structuring of species co-occurrence patterns and highlight functional differences of lake phytoplankton communities.

Main conclusions

Diverging community trajectories have led to a nationwide reshuffling of lake phytoplankton communities. At regional and national scales, lakes are not single entities but metacommunity hubs in an interconnected waterscape. The assembly mechanisms of phytoplankton communities are strongly structured by spatio-temporal dynamics, which have led to novel community types, but only a minor part of this reshuffling could be linked to temporal environmental change.     

Maternal Serum C-Reactive Protein in Women with Preterm Prelabor Rupture of Membranes

Objective

This study evaluated maternal C-reactive protein (CRP) as a predictor of microbial invasion of the amniotic cavity (MIAC) and histological chorioamnionitis (HCA) in women with preterm prelabor rupture of the membranes (PPROM) before and after 32 weeks of gestation.

Methods

This study was a prospective observational cohort study of 386 women. Maternal serum CRP concentrations were evaluated, and amniotic fluid samples were obtained via transabdominal amniocentesis at the time of admission. Placentas underwent histopathological examination after delivery. MIAC was defined based on a positive PCR for Ureaplasma species, Mycoplasma hominis and Chlamydia trachomatis and/or positive 16S rRNA gene amplification. HCA was defined based on the Salafia classification.

Results

Maternal CRP was significantly higher in women with MIAC and HCA (median 9.0 mg/l) than in women with HCA alone (median 6.9 mg/l), MIAC alone (median 7.4 mg/l) and without MIAC or HCA (median 4.5 mg/l) (p<0.0001). CRP was a weak predictor of the occurrence of MIAC and HCA before and after 32 weeks of gestation. Only the 95^th percentile of CRP and PPROM before 32 weeks exhibited a false-positive rate of 1%, a positive predictive value of 90% and a positive likelihood ratio of 13.2 to predict MIAC and HCA. However, the low sensitivity of 15% limits the clinical utility of this detection.

Conclusion

CRP is a poor predictor of the occurrence of MIAC and HCA, even at early gestational ages.     

Inhibition of protein aggregation: supramolecular assemblies of arginine hold the key

Background

Aggregation of unfolded proteins occurs mainly through the exposed hydrophobic surfaces. Any mechanism of inhibition of this aggregation should explain the prevention of these hydrophobic interactions. Though arginine is prevalently used as an aggregation suppressor, its mechanism of action is not clearly understood. We propose a mechanism based on the hydrophobic interactions of arginine.

Methodology

We have analyzed arginine solution for its hydrotropic effect by pyrene solubility and the presence of hydrophobic environment by 1-anilino-8-naphthalene sulfonic acid fluorescence. Mass spectroscopic analyses show that arginine forms molecular clusters in the gas phase and the cluster composition is dependent on the solution conditions. Light scattering studies indicate that arginine exists as clusters in solution. In the presence of arginine, the reverse phase chromatographic elution profile of Alzheimer''s amyloid beta 1-42 (Aβ_1-42) peptide is modified. Changes in the hydrodynamic volume of Aβ_1-42 in the presence of arginine measured by size exclusion chromatography show that arginine binds to Aβ_1-42. Arginine increases the solubility of Aβ_1-42 peptide in aqueous medium. It decreases the aggregation of Aβ_1-42 as observed by atomic force microscopy.

Conclusions

Based on our experimental results we propose that molecular clusters of arginine in aqueous solutions display a hydrophobic surface by the alignment of its three methylene groups. The hydrophobic surfaces present on the proteins interact with the hydrophobic surface presented by the arginine clusters. The masking of hydrophobic surface inhibits protein-protein aggregation. This mechanism is also responsible for the hydrotropic effect of arginine on various compounds. It is also explained why other amino acids fail to inhibit the protein aggregation.     

Hydrophobic cluster analysis: procedures to derive structural and functional information from 2-D-representation of protein sequences

Hydrophobic cluster analysis (HCA) [15] is a very efficient method to analyse and compare protein sequences. Despite its effectiveness, this method is not widely used because it relies in part on the experience and training of the user. In this article, detailed guidelines as to the use of HCA are presented and include discussions on: the definition of the hydrophobic clusters and their relationships with secondary and tertiary structures; the length of the clusters; the amino acid classification used for HCA; the HCA plot programs; and the working strategies. Various procedures for the analysis of a single sequence are presented: structural segmentation, structural domains and secondary structure evaluation. Like most sequence analysis methods, HCA is more efficient when several homologous sequences are compared. Procedures for the detection and alignment of distantly related proteins by HCA are described through several published examples along with 2 previously unreported cases: the beta-glucosidase from Ruminococcus albus is clearly related to the beta-glucosidases from Clostridum thermocellum and Hansenula anomala although they display a reverse organization of their constitutive domains; the alignment of the sequence of human GTPase activating protein with that of the Crk oncogene is presented. Finally, the pertinence of HCA in the identification of important residues for structure/function as well as in the preparation of homology modelling is discussed.     

DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcription factor binding sites

Background  

A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted with the seemingly arbitrary choice between numerous algorithms to perform cluster analysis.     

Ecological and genetic divergence between two lineages of Middle American túngara frogs <Emphasis Type="Italic">Physalaemus</Emphasis> (= <Emphasis Type="Italic">Engystomops</Emphasis>) <Emphasis Type="Italic">pustulosus</Emphasis>

Background  

Uncovering how populations of a species differ genetically and ecologically is important for understanding evolutionary processes. Here we combine population genetic methods (microsatellites) with phylogenetic information (mtDNA) to define genetic population clusters of the wide-spread Neotropical túngara frog (Physalaemus pustulosus). We measure gene flow and migration within and between population clusters and compare genetic diversity between population clusters. By applying ecological niche modeling we determine whether the two most divergent genetic groups of the túngara frog (1) inhabit different habitats, and (2) are separated geographically by unsuitable habitat across a gap in the distribution.     

Hydrophobic Cluster Analysis of G Protein-Coupled Receptors: A Powerful tool to Derive Structural and Functional Information from 2D-Representation of Protein Sequences

Abstract

Current methods for comparative analyses of protein sequences are 1D-alignments of amino acid sequences based on the maximization of amino acid identity (homology) and the prediction of secondary structure elements. This method has a major drawback once the amino acid identity drops below 20–25 %, since maximization of a homology score does not take into account any structural information. A new technique called Hydrophobic Cluster Analysis (HCA) has been developed by Lemesle-Varloot et al. (Biochimie 72, 555–574), 1990). This consists of comparing several sequences simultaneously and combining homology detection with secondary structure analysis.

HCA is primarily based on the detection and comparison of structural segments constituting the hydrophobic core of globular protein domains, with or without transmembrane domains. We have applied HCA to the analysis of different families of G-protein coupled receptors, such as catecholamine receptors as well as peptide hormone receptors. Utilizing HCA the thrombin receptor, a new and as yet unique member of the family of G-protein coupled receptors, can be clearly classified as being closely related to the family of neuropeptide receptors rather than to the catecholamine receptors for which the shape of the hydrophobic clusters and the length of their third cytoplasmic loop are very different. Furthermore, the potential of HCA to predict relationships between new putative and already characterized members of this family of receptors will be presented.     

Amniotic fluid cathelicidin in PPROM pregnancies: from proteomic discovery to assessing its potential in inflammatory complications diagnosis

Background

Preterm prelabor rupture of membranes (PPROM) complicated by microbial invasion of the amniotic cavity (MIAC) leading to histological chorioamnionitis (HCA) significantly impacts perinatal morbidity. Unfortunately, no well-established tool for identifying PPROM patients threatened by these disorders is available.

Methodology/Principal Findings

We performed an unbiased exploratory analysis of amniotic fluid proteome changes due to MIAC and HCA. From among the top five proteins that showed the most profound and significant change, we sought to confirm results concerning cathelicidin ({"type":"entrez-protein","attrs":{"text":"P49913","term_id":"1706745","term_text":"P49913"}}P49913, CAMP_HUMAN), since an ELISA kit was readily available for this protein. In our exploratory proteomic study, cathelicidin showed a ∼6-fold higher concentration in PPROM patients with confirmed MIAC and HCA. We verified significantly higher levels of cathelicidin in exploratory samples (women without both MIAC and HCA: median 1.4 ng/ml; women with both conditions confirmed: median 3.6 ng/ml; p = 0.0003). A prospective replication cohort was used for independent validation and for assessment of cathelicidin potential to stratify women with MIAC leading to HCA from women in whom at least one of these conditions was ruled out. We confirmed the association of higher amniotic fluid cathelicidin levels with MIAC leading to HCA (the presence of both MIAC and HCA: median 3.1 ng/ml; other women: median 1.4 ng/ml; p<0.0001). A cathelicidin concentration of 4.0 ng/ml was found to be the best cut-off point for identifying PPROM women with both MIAC and HCA. When tested on the validation cohort, a sensitivity of 48%, a specificity of 90%, a likelihood ratio of 5.0, and an area under receiver-operating characteristic curve of 71% were achieved for identification of women with MIAC leading to HCA.

Conclusions

Our multi-stage study suggests cathelicidin as a candidate marker that should be considered for a panel of amniotic fluid proteins permitting identification of PPROM women with MIAC leading to HCA.     

Transcription profiling of fertilization and early seed development events in a solanaceous species using a 7.7 K cDNA microarray from <Emphasis Type="Italic">Solanum chacoense</Emphasis>ovules

Background  

To provide a broad analysis of gene expression changes in developing embryos from a solanaceous species, we produced amplicon-derived microarrays with 7741 ESTs isolated from Solanum chacoense ovules bearing embryos from all developmental stages. Our aims were to: 1) identify genes expressed in a tissue-specific and temporal-specific manner; 2) define clusters of genes showing similar patterns of spatial and temporal expression; and 3) identify stage-specific or transition-specific candidate genes for further functional genomic analyses.     

Evolutionary sequence analysis of complete eukaryote genomes

Background  

Gene duplication and gene loss during the evolution of eukaryotes have hindered attempts to estimate phylogenies and divergence times of species. Although current methods that identify clusters of orthologous genes in complete genomes have helped to investigate gene function and gene content, they have not been optimized for evolutionary sequence analyses requiring strict orthology and complete gene matrices. Here we adopt a relatively simple and fast genome comparison approach designed to assemble orthologs for evolutionary analysis. Our approach identifies single-copy genes representing only species divergences (panorthologs) in order to minimize potential errors caused by gene duplication. We apply this approach to complete sets of proteins from published eukaryote genomes specifically for phylogeny and time estimation.     

Assessment and improvement of the appropriateness of an LCI data set on a system level – application to textile manufacturing

Purpose

This paper aims at assessing the appropriateness at the system level of different Life Cycle Inventory (LCI) data sets (including default models) selected by the Life Cycle Assessment (LCA) practitioner. This means that the uncertainty measurements are applied on some specific main parameters of the LCI data set instead of measured input values. This approach aims at providing a pragmatic method to approximate and reduce the uncertainties resulting from a lack of information on a specific step.

Methods

The method proposed in this paper to assess the percentage errors on appropriateness includes three main steps. First, different systems including different versions of the same process with technological or geographical changes are assessed. Second, a hierarchical cluster analysis (HCA) or a principal component analysis (PCA) is performed to identify the main variables influencing the results. Third, a multivariate analysis of variances (MANOVA) assesses the significance of the main variables on the results. An appropriate default model can be developed by setting the variables introducing high variations in results.

Results and discussion

When comparing the same spinning process located in different countries, the HCA enabled us to identify the electricity mix as the main variable influencing the results. The “world average default models” has proven inappropriate to represent country specific locations. When comparing spinning technologies, the PCAs identified the electricity and the cotton input required as the main variables influencing the results and explained the variations in results due to technological changes. The HCA performed on different yarn manufacturing procedures identified the location and the yarn thickness as the two main variables influencing the results. The MANOVA assessed the percentage marginal variance (PMV) explained by the variable location between 85 and 92 % for four impact categories. The MANOVA performed on different fabric manufacturing systems assessed the PMV explained by the variables harvest, spinning, and weaving locations above 68 % for all impact categories. The HCA and MANOVA analyses helped design an appropriate “technological average default model.”

Conclusions

From the identification of the main influencing variables (HCA and PCA) to the quantitative appropriateness assessment (MANOVA) and the development of appropriate default models, the method has proven effective in assisting the LCA practitioner in the modeling of textile manufacturing systems, and for other worldwide multi-step manufacturing systems.     

OrthoClusterDB: an online platform for synteny blocks

Background  

The recent availability of an expanding collection of genome sequences driven by technological advances has facilitated comparative genomics and in particular the identification of synteny among multiple genomes. However, the development of effective and easy-to-use methods for identifying such conserved gene clusters among multiple genomes–synteny blocks–as well as databases, which host synteny blocks from various groups of species (especially eukaryotes) and also allow users to run synteny-identification programs, lags behind.     

Organization and evolution of hsp70 clusters strikingly differ in two species of Stratiomyidae (Diptera) inhabiting thermally contrasting environments

Background  

Previously, we described the heat shock response in dipteran species belonging to the family Stratiomyidae that develop in thermally and chemically contrasting habitats including highly aggressive ones. Although all species studied exhibit high constitutive levels of Hsp70 accompanied by exceptionally high thermotolerance, we also detected characteristic interspecies differences in heat shock protein (Hsp) expression and survival after severe heat shock. Here, we analyzed genomic libraries from two Stratiomyidae species from thermally and chemically contrasting habitats and determined the structure and organization of their hsp70 clusters.