Phylogeny of Prokaryotes and Chloroplasts Revealed by a Simple Composition Approach on All Protein Sequences from Complete Genomes Without Sequence Alignment

The complete genomes of living organisms have provided much information on their phylogenetic relationships. Similarly, the complete genomes of chloroplasts have helped to resolve the evolution of this organelle in photosynthetic eukaryotes. In this paper we propose an alternative method of phylogenetic analysis using compositional statistics for all protein sequences from complete genomes. This new method is conceptually simpler than and computationally as fast as the one proposed by Qi et al. (2004b) and Chu et al. (2004). The same data sets used in Qi et al. (2004b) and Chu et al. (2004) are analyzed using the new method. Our distance-based phylogenic tree of the 109 prokaryotes and eukaryotes agrees with the biologists tree of life based on 16S rRNA comparison in a predominant majority of basic branching and most lower taxa. Our phylogenetic analysis also shows that the chloroplast genomes are separated to two major clades corresponding to chlorophytes s.l. and rhodophytes s.l. The interrelationships among the chloroplasts are largely in agreement with the current understanding on chloroplast evolution

Mannose-binding lectin genotypes: lack of association with susceptibility to thoracic empyema

<p>Abstract</p> <p>Background</p> <p>The role of the innate immune protein mannose-binding lectin (MBL) in host defence against severe respiratory infection remains controversial. Thoracic empyema is a suppurative lung infection that arises as a major complication of pneumonia and is associated with a significant mortality. Although the pathogenesis of thoracic empyema is poorly understood, genetic susceptibility loci for this condition have recently been identified. The possible role of MBL genotypic deficiency in susceptibility to thoracic empyema has not previously been reported.</p> <p>Methods</p> <p>To investigate this further we compared the frequencies of the six functional <it>MBL </it>polymorphisms in 170 European individuals with thoracic empyema and 225 healthy control individuals.</p> <p>Results</p> <p>No overall association was observed between MBL genotypic deficiency and susceptibility to thoracic empyema (2 × 2 Chi square = 0.02, <it>P </it>= 0.87). Furthermore, no association was seen between MBL deficiency and susceptibility to the Gram-positive or pneumococcal empyema subgroups. MBL genotypic deficiency did not associate with progression to death or requirement for surgery.</p> <p>Conclusions</p> <p>Our results suggest that MBL genotypic deficiency does not associate with susceptibility to thoracic empyema in humans.</p

Hierarchical information clustering by means of topologically embedded graphs

We introduce a graph-theoretic approach to extract clusters and hierarchies in complex data-sets in an unsupervised and deterministic manner, without the use of any prior information. This is achieved by building topologically embedded networks containing the subset of most significant links and analyzing the network structure. For a planar embedding, this method provides both the intra-cluster hierarchy, which describes the way clusters are composed, and the inter-cluster hierarchy which describes how clusters gather together. We discuss performance, robustness and reliability of this method by first investigating several artificial data-sets, finding that it can outperform significantly other established approaches. Then we show that our method can successfully differentiate meaningful clusters and hierarchies in a variety of real data-sets. In particular, we find that the application to gene expression patterns of lymphoma samples uncovers biologically significant groups of genes which play key-roles in diagnosis, prognosis and treatment of some of the most relevant human lymphoid malignancies.Comment: 33 Pages, 18 Figures, 5 Table

AI-powered transmitted light microscopy for functional analysis of live cells

Transmitted light microscopy can readily visualize the morphology of living cells. Here, we introduce artificial-intelligence-powered transmitted light microscopy (AIM) for subcellular structure identification and labeling-free functional analysis of live cells. AIM provides accurate images of subcellular organelles; allows identification of cellular and functional characteristics (cell type, viability, and maturation stage); and facilitates live cell tracking and multimodality analysis of immune cells in their native form without labeling

Bioinformatics for the human microbiome project

Microbes inhabit virtually all sites of the human body, yet we know very little about the role they play in our health. In recent years, there has been increasing interest in studying human-associated microbial communities, particularly since microbial dysbioses have now been implicated in a number of human diseases [1]–[3]. Dysbiosis, the disruption of the normal microbial community structure, however, is impossible to define without first establishing what “normal microbial community structure” means within the healthy human microbiome. Recent advances in sequencing technologies have made it feasible to perform large-scale studies of microbial communities, providing the tools necessary to begin to address this question [4], [5]. This led to the implementation of the Human Microbiome Project (HMP) in 2007, an initiative funded by the National Institutes of Health Roadmap for Biomedical Research and constructed as a large, genome-scale community research project [6]. Any such project must plan for data analysis, computational methods development, and the public availability of tools and data; here, we provide an overview of the corresponding bioinformatics organization, history, and results from the HMP (Figure 1).National Institutes of Health (U.S.) (NIH U54HG004969)National Institutes of Health (U.S.) (grant R01HG004885)National Institutes of Health (U.S.) (grant R01HG005975)National Institutes of Health (U.S.) (grant R01HG005969

The Tree versus the Forest: The Fungal Tree of Life and the Topological Diversity within the Yeast Phylome

A recurrent topic in phylogenomics is the combination of various sequence alignments to reconstruct a tree that describes the evolutionary relationships within a group of species. However, such approach has been criticized for not being able to properly represent the topological diversity found among gene trees. To evaluate the representativeness of species trees based on concatenated alignments, we reconstruct several fungal species trees and compare them with the complete collection of phylogenies of genes encoded in the Saccharomyces cerevisiae genome. We found that, despite high levels of among-gene topological variation, the species trees do represent widely supported phylogenetic relationships. Most topological discrepancies between gene and species trees are concentrated in certain conflicting nodes. We propose to map such information on the species tree so that it accounts for the levels of congruence across the genome. We identified the lack of sufficient accuracy of current alignment and phylogenetic methods as an important source for the topological diversity encountered among gene trees. Finally, we discuss the implications of the high levels of topological variation for phylogeny-based orthology prediction strategies

Transcriptional Analysis of Arabidopsis thaliana Response to Lima Bean Volatiles

Exposure of plants to herbivore-induced plant volatiles (HIPVs) alters their resistance to herbivores. However, the whole-genome transcriptional responses of treated plants remain unknown, and the signal pathways that produce HIPVs are also unclear.Time course patterns of the gene expression of Arabidopsis thaliana exposed to Lima bean volatiles were examined using Affymetrix ATH1 genome arrays. Results showed that A. thaliana received and responded to leafminer-induced volatiles from Lima beans through up-regulation of genes related to the ethylene (ET) and jasmonic acid pathways. Time course analysis revealed strong and partly qualitative differences in the responses between exposure at 24 and that at 48 h. Further experiments using either A. thaliana ET mutant ein2-1 or A. thaliana jasmonic acid mutant coi1-2 indicated that both pathways are involved in the volatile response process but that the ET pathway is indispensable for detecting volatiles. Moreover, transcriptional comparisons showed that plant responses to larval feeding do not merely magnify the volatile response process. Finally, (Z)-3-hexen-ol, ocimene, (3E)-4,8-dimethyl-1,3,7-nonatriene, and (3E,7E)-4,8,12-trimethyl-1,3,7,11-tridecatetraene triggered responses in A. thaliana similar to those induced by the entire suite of Lima bean volatiles after 24 and 48 h.This study shows that the transcriptional responses of plants to HIPVs become stronger as treatment time increases and that ET signals are critical during this process