Order, Please! Uncertainty in the Ordinal-Level Classification of Chlorophyceae

Background. Chlorophyceae is one of three most species-rich green algal classes and also the only class in core Chlorophyta whose monophyly remains uncontested as gene and taxon sampling improves. However, some key relationships within Chlorophyceae are less clear-cut and warrant further investigation. The present study combined genome-scale chloroplast data and rich sampling in an attempt to resolve the ordinal classification in Chlorophyceae. The traditional division into Sphaeropleales and Volvocales (SV), and a clade containing Oedogoniales, Chaetopeltidales, and Chaetophorales (OCC) was of particular interest with the addition of deeply branching members of these groups, as well as the placement of several incertae sedis taxa. Methods. We sequenced 18 chloroplast genomes across Chlorophyceae to compile a data set of 58 protein-coding genes of a total of 68 chlorophycean taxa. We analyzed the concatenated nucleotide and amino acid datasets in the Bayesian and Maximum Likelihood frameworks, supplemented by analyses to examine potential discordant signal among genes. We also examined gene presence and absence data across Chlorophyceae. Results. Concatenated analyses yielded at least two well-supported phylogenies: nucleotide data supported the traditional classification with the inclusion of the enigmatic Treubarinia into Sphaeropleales sensu lato. However, amino acid data yielded equally strong support for Sphaeropleaceae as sister to Volvocales, with the rest of the taxa traditionally classified in Sphaeropleales in a separate clade, and Treubarinia as sister to all of the above. Single-gene and other supplementary analyses indicated that the data have low phylogenetic signal at these critical nodes. Major clades were supported by genomic structural features such as gene losses and trans-spliced intron insertions in the plastome. Discussion. While the sequence and gene order data support the deep split between the SV and OCC lineages, multiple phylogenetic hypotheses are possible for Sphaeropleales s.l. Given this uncertainty as well as the higher-taxonomic disorder seen in other algal groups, dwelling on well-defined, strongly supported Linnaean orders is not currently practical in Chlorophyceae and a less formal clade system may be more useful in the foreseeable future. For example, we identify two strongly and unequivocally supported clades: Treubarinia and Scenedesminia, as well as other smaller groups that could serve a practical purpose as named clades. This system does not preclude future establishment of new orders, or emendment of the current ordinal classification if new data support such conclusions

Order, Please! Uncertainty in the Ordinal-Level Classification of Chlorophyceae

Background. Chlorophyceae is one of three most species-rich green algal classes and also the only class in core Chlorophyta whose monophyly remains uncontested as gene and taxon sampling improves. However, some key relationships within Chlorophyceae are less clear-cut and warrant further investigation. The present study combined genome-scale chloroplast data and rich sampling in an attempt to resolve the ordinal classification in Chlorophyceae. The traditional division into Sphaeropleales and Volvocales (SV), and a clade containing Oedogoniales, Chaetopeltidales, and Chaetophorales (OCC) was of particular interest with the addition of deeply branching members of these groups, as well as the placement of several incertae sedis taxa. Methods. We sequenced 18 chloroplast genomes across Chlorophyceae to compile a data set of 58 protein-coding genes of a total of 68 chlorophycean taxa. We analyzed the concatenated nucleotide and amino acid datasets in the Bayesian and Maximum Likelihood frameworks, supplemented by analyses to examine potential discordant signal among genes. We also examined gene presence and absence data across Chlorophyceae. Results. Concatenated analyses yielded at least two well-supported phylogenies: nucleotide data supported the traditional classification with the inclusion of the enigmatic Treubarinia into Sphaeropleales sensu lato. However, amino acid data yielded equally strong support for Sphaeropleaceae as sister to Volvocales, with the rest of the taxa traditionally classified in Sphaeropleales in a separate clade, and Treubarinia as sister to all of the above. Single-gene and other supplementary analyses indicated that the data have low phylogenetic signal at these critical nodes. Major clades were supported by genomic structural features such as gene losses and trans-spliced intron insertions in the plastome. Discussion. While the sequence and gene order data support the deep split between the SV and OCC lineages, multiple phylogenetic hypotheses are possible for Sphaeropleales s.l. Given this uncertainty as well as the higher-taxonomic disorder seen in other algal groups, dwelling on well-defined, strongly supported Linnaean orders is not currently practical in Chlorophyceae and a less formal clade system may be more useful in the foreseeable future. For example, we identify two strongly and unequivocally supported clades: Treubarinia and Scenedesminia, as well as other smaller groups that could serve a practical purpose as named clades. This system does not preclude future establishment of new orders, or emendment of the current ordinal classification if new data support such conclusions

Assessing Combinability of Phylogenomic Data Using Bayes Factors

With the rapid reduction in sequencing costs of high-throughput genomic data, it has become commonplace to use hundreds of genes to infer phylogeny of any study system. While sampling a large number of genes has given us a tremendous opportunity to uncover previously unknown relationships and improve phylogenetic resolution, it also presents us with new challenges when the phylogenetic signal is confused by differences in the evolutionary histories of sampled genes. Given the incorporation of accurate marginal likelihood estimation methods into popular Bayesian software programs, it is natural to consider using the Bayes Factor (BF) to compare different partition models in which genes within any given partition subset share both tree topology and edge lengths. We explore using marginal likelihood to assess data subset combinability when data subsets have varying levels of phylogenetic discordance due to deep coalescence events among genes (simulated within a species tree), and compare the results with our recently described phylogenetic informational dissonance index (D) estimated for each data set. BF effectively detects phylogenetic incongruence and provides a way to assess the statistical significance of D values. We use BFs to assess data combinability using an empirical data set comprising 56 plastid genes from the green algal order Volvocales. We also discuss the potential need for calibrating BFs and demonstrate that BFs used in this study are correctly calibrated

Reproduction and Dispersal of Biological Soil Crust Organisms

Biological soil crusts (BSCs) consist of a diverse and highly integrated community of organisms that effectively colonize and collectively stabilize soil surfaces. BSCs vary in terms of soil chemistry and texture as well as the environmental parameters that combine to support unique combinations of organisms—including cyanobacteria dominated, lichen-dominated, and bryophyte-dominated crusts. The list of organismal groups that make up BSC communities in various and unique combinations include—free living, lichenized, and mycorrhizal fungi, chemoheterotrophic bacteria, cyanobacteria, diazotrophic bacteria and archaea, eukaryotic algae, and bryophytes. The various BSC organismal groups demonstrate several common characteristics including—desiccation and extreme temperature tolerance, production of various soil binding chemistries, a near exclusive dependency on asexual reproduction, a pattern of aerial dispersal over impressive distances, and a universal vulnerability to a wide range of human-related perturbations. With this publication, we provide literature-based insights as to how each organismal group contributes to the formation and maintenance of the structural and functional attributes of BSCs, how they reproduce, and how they are dispersed. We also emphasize the importance of effective application of molecular and microenvironment sampling and assessment tools in order to provide cogent and essential answers that will allow scientists and land managers to better understand and manage the biodiversity and functional relationships of soil crust communities

Candida albicans Hypha Formation and Mannan Masking of β-Glucan Inhibit Macrophage Phagosome Maturation

Received 28 August 2014 Accepted 28 October 2014 Published 2 December 2014 This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported license. ACKNOWLEDGMENTS We thank Janet Willment, Aberdeen Fungal Group, University of Aberdeen, for kindly providing the soluble Dectin-1-Fc reporter. All microscopy was performed with the assistance of the University of Aberdeen Core Microscopy & Histology Facility, and we thank the IFCC for their assistance with flow cytometry. We thank the Wellcome Trust for funding (080088, 086827, 075470, 099215, 097377, and 101873). E.R.B. and A.J.P.B. are funded by the European Research Council (ERC-2009-AdG-249793), and J.L. is funded by a Medical Research Council Clinical Training Fellowship.Peer reviewedPublisher PD

Cyanobacterial ribosomal RNA genes with multiple, endonuclease-encoding group I introns

<p>Abstract</p> <p>Background</p> <p>Group I introns are one of the four major classes of introns as defined by their distinct splicing mechanisms. Because they catalyze their own removal from precursor transcripts, group I introns are referred to as autocatalytic introns. Group I introns are common in fungal and protist nuclear ribosomal RNA genes and in organellar genomes. In contrast, they are rare in all other organisms and genomes, including bacteria.</p> <p>Results</p> <p>Here we report five group I introns, each containing a LAGLIDADG homing endonuclease gene (HEG), in large subunit (LSU) rRNA genes of cyanobacteria. Three of the introns are located in the LSU gene of <it>Synechococcus </it>sp. C9, and the other two are in the LSU gene of <it>Synechococcus lividus </it>strain C1. Phylogenetic analyses show that these introns and their HEGs are closely related to introns and HEGs located at homologous insertion sites in organellar and bacterial rDNA genes. We also present a compilation of group I introns with homing endonuclease genes in bacteria.</p> <p>Conclusion</p> <p>We have discovered multiple HEG-containing group I introns in a single bacterial gene. To our knowledge, these are the first cases of multiple group I introns in the same <it>bacterial </it>gene (multiple group I introns have been reported in at least one phage gene and one prophage gene). The HEGs each contain one copy of the LAGLIDADG motif and presumably function as homodimers. Phylogenetic analysis, in conjunction with their patchy taxonomic distribution, suggests that these intron-HEG elements have been transferred horizontally among organelles and bacteria. However, the mode of transfer and the nature of the biological connections among the intron-containing organisms are unknown.</p

A comparison of course-related stressors in undergraduate problem-based learning (PBL) versus non-PBL medical programmes

Background: Medical students report high levels of stress related to their medical training as well as to other personal and financial factors. The aim of this study is to investigate whether there are differences in course-related stressors reported by medical students on undergraduate problem-based learning (PBL) and non-PBL programmes in the UK. Method: A cross-sectional study of second-year medical students in two UK medical schools (one PBL and one non-PBL programme) was conducted. A 16-question self-report questionnaire, derived from the Perceived Medical Student Stress Scale and the Higher Education Stress Inventory, was used to measure course-related stressors. Following univariate analysis of each stressor between groups, multivariate logistic regression was used to determine which stressors were the best predictors of each course type, while controlling for socio-demographic differences between the groups. Results: A total of 280 students responded. Compared to the non-PBL students (N = 197), the PBL students (N = 83) were significantly more likely to agree that: they did not know what the faculty expected of them (Odds Ratio (OR) = 0.38, p = 0.03); there were too many small group sessions facilitated only by students resulting in an unclear curriculum (OR = 0.04, p < 0.0001); and that there was a lack of opportunity to explore academic subjects of interest (OR = 0.40, p = 0.02). They were significantly more likely to disagree that: there was a lack of encouragement from teachers (OR = 3.11, p = 0.02); and that the medical course fostered a sense of anonymity and feelings of isolation amongst students (OR = 3.42, p = 0.008). Conclusion: There are significant differences in the perceived course-related stressors affecting medical students on PBL and non-PBL programmes. Course designers and student support services should therefore tailor their work to minimise, or help students cope with, the specific stressors on each course type to ensure optimum learning and wellbeing among our future doctors