The impact of fire on habitat use by the short-snouted elephant shrew ('Elephantulus brachyrhynchus') in North West Province, South Africa

Several studies have investigated the response of small mammal populations to fire, but few have investigated behavioural responses to habitat modification. In this study we investigated the impact of fire on home range, habitat use and activity patterns of the short-snouted elephant shrew (Elephantulus brachyrhynchus) by radio-tracking individuals before and after a fire event. All animals survived the passage of fire in termite mound refugia. Before the fire, grassland was used more than thickets, but habitat utilization shifted to thickets after fire had removed the grass cover. Thickets were an important refuge both pre- and post-fire, but the proportion of thicket within the home range was greater post-fire. We conclude that fire-induced habitat modification resulted in a restriction of E. brachyrhynchus movements to patches of unburned vegetation. This may be a behavioural response to an increase in predation pressure associated with a reduction in cover, rather than a lack of food. This study highlights the importance of considering the landscape mosaic in fire management and allowing sufficient island patches to remain post-fire ensures the persistence of the small mammal fauna

Hot, Sour and Breathless – Ocean under Stress.

ISBN 978-0-9519618-6-

Long-Branch Attraction Bias and Inconsistency in Bayesian Phylogenetics

Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias—which is apparent under both controlled simulation conditions and in analyses of empirical sequence data—also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages—that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis

Optimal data partitioning, multispecies coalescent and Bayesian concordance analyses resolve early divergences of the grape family (Vitaceae)

Evolutionary rate heterogeneity and rapid radiations are common phenomena in organismal evolution and represent major challenges for reconstructing deep-level phylogenies. Here we detected substantial conflicts in and among data sets as well as uncertainty concerning relationships among lineages of Vitaceae from individual gene trees, supernetworks and tree certainty values. Congruent deep-level relationships of Vitaceae were retrieved by comprehensive comparisons of results from optimal partitioning analyses, multispecies coalescent approaches and the Bayesian concordance method. We found that partitioning schemes selected by PartitionFinder were preferred over those by gene or by codon position, and the unpartitioned model usually performed the worst. For a data set with conflicting signals, however, the unpartitioned model outperformed models that included more partitions, demonstrating some limitations to the effectiveness of concatenation for these data. For a transcriptome data set, fast coalescent methods (STAR and MP-EST) and a Bayesian concordance approach yielded congruent topologies with trees from the concatenated analyses and previous studies. Our results highlight that well-resolved gene trees are critical for the effectiveness of coalescent-based methods. Future efforts to improve the accuracy of phylogenomic analyses should emphasize the development of newmethods that can accommodate multiple biological processes and tolerate missing data while remaining computationally tractable. (C) The Willi Hennig Society 2017.National Natural Science Foundation of China [NNSF 31500179, 31590822, 31270268]; National Basic Research Program of China [2014CB954101]; National Science Foundation [DEB0743474]; Smithsonian Scholarly Studies Grant Program and the Endowment Grant Program; CAS/SAFEA International Partnership Program for Creative Research Teams; Laboratory of Analytical Biology of the National Museum of Natural History, Smithsonian Institution; Science and Technology Basic Work [2013FY112100]info:eu-repo/semantics/publishedVersio

DNA double strand breaks as predictor of efficacy of the alpha-particle emitter Ac-225 and the electron emitter Lu-177 for somatostatin receptor targeted radiotherapy

Key biologic effects of the alpha-particle emitter Actinium-225 in comparison to beta-particle emitter Lutetium-177 labeled somatostatin analogue DOTATOC in vitro and in vivo were studied to evaluate the significance of H2AX-foci formation and its downstream effects. To determine relative biological effectiveness (RBE) between the two isotopes somatostatin expressing AR42J cells were incubated with Ac-225-DOTATOC and Lu-177-DOTATOC up to 48 h and viability was analyzed using the MTT assay. DNA double strand breaks were quantified after immunofluorescence staining of H2AX. Cell cycle was analyzed by flow cytometry. In vivo, uptake of both radiolabeled somatostatin-analogues into subcutaneous AR42J tumors and number of cells displaying H2AX-foci were measured. Therapeutic efficacy was assayed by monitoring tumor growth after treatment with activities translated from in vitro cytotoxicity. Ac-225-DOTATOC was synthesized with specific activities between 0.2-0.4 MBq/µg and radiochemical purity of > 90%. ED50 values were 30 kBq/ml after 24 h and 14 kBq/ml after 48 h. Lu-177-DOTATOC displayed radiochemical purity of >95% and ED50 values of 10 MBq/ml after 48 h. Number of DNA double strand breaks increased with increasing concentration of Ac 225 DOTATOC and Lu-177-DOTATOC similarly, if a factor of approximately 700 of Lu-177 activities over Ac-225 activities was applied. Already 24 h after incubation with 2.5, 5, and 10 kBq/ml Ac 225 DOTATOC cell cycle studies showed an increment of the percentage of tumor cells in G2/M phase up to 60%. After 72 h an apoptotic subG1 peak was also detectable. Tumor uptake for both radio peptides at 48 h was identical with 7.5 %ID/g, though overall number of cells with H2AX-foci was higher for tumors treated with 48 kBq Actinium-225-DOTATOC than tumors treated with 30 MBq Lutetium-177-DOTATOC (35% vs. 21%). Tumors with a mean volume of 0.34 ml reached exponential tumor growth after 25 days (44 kBq Ac-225-DOTATOC), after 21 days (34 MBq Lu-177-DOTATOC) and after 5 days (control). Thus H2AX-foci displayed the key parameter after irradiation with similar downstream effects for beta and alpha irradiation.JRC.E.5-Nuclear chemistr

Structural biology and phylogenetic estimation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62633/1/388527a0.pd

Selective Constraints on Amino Acids Estimated by a Mechanistic Codon Substitution Model with Multiple Nucleotide Changes

Empirical substitution matrices represent the average tendencies of substitutions over various protein families by sacrificing gene-level resolution. We develop a codon-based model, in which mutational tendencies of codon, a genetic code, and the strength of selective constraints against amino acid replacements can be tailored to a given gene. First, selective constraints averaged over proteins are estimated by maximizing the likelihood of each 1-PAM matrix of empirical amino acid (JTT, WAG, and LG) and codon (KHG) substitution matrices. Then, selective constraints specific to given proteins are approximated as a linear function of those estimated from the empirical substitution matrices. Akaike information criterion (AIC) values indicate that a model allowing multiple nucleotide changes fits the empirical substitution matrices significantly better. Also, the ML estimates of transition-transversion bias obtained from these empirical matrices are not so large as previously estimated. The selective constraints are characteristic of proteins rather than species. However, their relative strengths among amino acid pairs can be approximated not to depend very much on protein families but amino acid pairs, because the present model, in which selective constraints are approximated to be a linear function of those estimated from the JTT/WAG/LG/KHG matrices, can provide a good fit to other empirical substitution matrices including cpREV for chloroplast proteins and mtREV for vertebrate mitochondrial proteins. The present codon-based model with the ML estimates of selective constraints and with adjustable mutation rates of nucleotide would be useful as a simple substitution model in ML and Bayesian inferences of molecular phylogenetic trees, and enables us to obtain biologically meaningful information at both nucleotide and amino acid levels from codon and protein sequences.Comment: Table 9 in this article includes corrections for errata in the Table 9 published in 10.1371/journal.pone.0017244. Supporting information is attached at the end of the article, and a computer-readable dataset of the ML estimates of selective constraints is available from 10.1371/journal.pone.001724

DNA barcoding reveals the coral “laboratory-rat”, Stylophora pistillata encompasses multiple identities

Stylophora pistillata is a widely used coral “lab-rat” species with highly variable morphology and a broad biogeographic range (Red Sea to western central Pacific). Here we show, by analysing Cytochorme Oxidase I sequences, from 241 samples across this range, that this taxon in fact comprises four deeply divergent clades corresponding to the Pacific-Western Australia, Chagos-Madagascar-South Africa, Gulf of Aden-Zanzibar-Madagascar, and Red Sea-Persian/Arabian Gulf-Kenya. On the basis of the fossil record of Stylophora, these four clades diverged from one another 51.5-29.6 Mya, i.e., long before the closure of the Tethyan connection between the tropical Indo-West Pacific and Atlantic in the early Miocene (16–24 Mya) and should be recognised as four distinct species. These findings have implications for comparative ecological and/or physiological studies carried out using Stylophora pistillata as a model species, and highlight the fact that phenotypic plasticity, thought to be common in scleractinian corals, can mask significant genetic variation

Data incongruence and the problem of avian louse phylogeny

Recent studies based on different types of data (i.e. morphological and molecular) have supported conflicting phylogenies for the genera of avian feather lice (Ischnocera: Phthiraptera). We analyse new and published data from morphology and from mitochondrial (12S rRNA and COI) and nuclear (EF1-) genes to explore the sources of this incongruence and explain these conflicts. Character convergence, multiple substitutions at high divergences, and ancient radiation over a short period of time have contributed to the problem of resolving louse phylogeny with the data currently available. We show that apparent incongruence between the molecular datasets is largely attributable to rate variation and nonstationarity of base composition. In contrast, highly significant character incongruence leads to topological incongruence between the molecular and morphological data. We consider ways in which biases in the sequence data could be misleading, using several maximum likelihood models and LogDet corrections. The hierarchical structure of the data is explored using likelihood mapping and SplitsTree methods. Ultimately, we concede there is strong discordance between the molecular and morphological data and apply the conditional combination approach in this case. We conclude that higher level phylogenetic relationships within avian Ischnocera remain extremely problematic. However, consensus between datasets is beginning to converge on a stable phylogeny for avian lice, at and below the familial rank