Reply to Ali & Aitchison's comment on 'Restoration of Cenozoic deformation in Asia, and the size of Greater India'

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Volcanic constraints on the unzipping of Africa from South America: Insights from new geochronological controls along the Angola margin

The breakup of Africa from South America is associated with the emplacement of the Paraná-Etendeka flood basalt province from around 134 Ma and the Tristan da Cunha plume. Yet many additional volcanic events occur that are younger than the main pulse of the Paraná-Etendeka and straddle the rift to drift phases of the main breakup. This contribution reports on new geochronological constraints from the Angolan part of the African Margin. Three coastal and one inland section have been sampled stretching across some 400 Km, with 39Ar/40Ar, U-Pb and Palaeontology used to provide age constraints. Ages from the new data range from ~100 to 81 Ma, with three main events (cr. 100, 91 and 82-81 Ma). Volcanic events are occurring within the Early to Late Cretaceous, along this part of the margin with a general younging towards Namibia. With the constraints of additional age information both onshore and offshore Angola, a clear younging trend at the early stages of rift to drift is recorded in the volcanic events that unzip from North to South. Similar age volcanic events are reported from the Brazilian side of the conjugate margin, and highlight the need to fully incorporate these relatively low volume volcanic pulses into the plate tectonic breakup models of the South Atlantic Margin

The Cerenkov effect revisited: from swimming ducks to zero modes in gravitational analogs

We present an interdisciplinary review of the generalized Cerenkov emission of radiation from uniformly moving sources in the different contexts of classical electromagnetism, superfluid hydrodynamics, and classical hydrodynamics. The details of each specific physical systems enter our theory via the dispersion law of the excitations. A geometrical recipe to obtain the emission patterns in both real and wavevector space from the geometrical shape of the dispersion law is discussed and applied to a number of cases of current experimental interest. Some consequences of these emission processes onto the stability of condensed-matter analogs of gravitational systems are finally illustrated.Comment: Lecture Notes at the IX SIGRAV School on "Analogue Gravity" in Como, Italy from May 16th-21th, 201

Culture-independent molecular analysis of bacterial diversity in uranium-ore/-mine waste-contaminated and non-contaminated sites from uranium mines

Soil, water and sediment samples collected from in and around Jaduguda, Bagjata and Turamdih mines were analyzed for physicochemical parameters and cultured, and yet to be cultured microbial diversity. Culturable fraction of microbial community measured as Colony Forming Unit (CFU) on R2A medium revealed microbes between 104 and 109 CFU/g sample. Community DNA was extracted from all the samples; 16S rRNA gene amplified, cloned and subject to Amplified Ribosomal DNA Restriction Analysis. Clones representing each OTU were selected and sequenced. Sequence analyses revealed that non-contaminated samples were mostly represented by Acidobacteria, Bacteroidetes, Firmicutes and Proteobacteria (β-, γ-, and/or δ-subdivisions) along with less frequent phyla Nitrospira, Deferribacteres, Chloroflexi. In contrast, samples obtained from highly contaminated samples showed distinct abundance of β-,γ- and α-Proteobacteria along with Acidobacteria,Bacteroidetes and members of Firmicutes, Chloroflexi, Candidate division, Planctomycete, Cyanobacteria and Actinobacteria as minor groups. Our data represented the baseline information on bacterial community composition within non-contaminated samples which could potentially be useful for assessing the impact of metal and radionuclides contamination due to uranium mine activities

Constraints on lithosphere net rotation and asthenospheric viscosity from global mantle flow models and seismic anisotropy

Author Posting. © American Geophysical Union, 2010. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 11 (2010): Q05W05, doi:10.1029/2009GC002970.Although an average westward rotation of the Earth's lithosphere is indicated by global analyses of surface features tied to the deep mantle (e.g., hot spot tracks), the rate of lithospheric drift is uncertain despite its importance to global geodynamics. We use a global viscous flow model to predict asthenospheric anisotropy computed from linear combinations of mantle flow fields driven by relative plate motions, mantle density heterogeneity, and westward lithosphere rotation. By comparing predictions of lattice preferred orientation to asthenospheric anisotropy in oceanic regions inferred from SKS splitting observations and surface wave tomography, we constrain absolute upper mantle viscosity (to 0.5–1.0 × 1021 Pa s, consistent with other constraints) simultaneously with net rotation rate and the decrease in the viscosity of the asthenosphere relative to that of the upper mantle. For an asthenosphere 10 times less viscous than the upper mantle, we find that global net rotation must be <0.26°/Myr (<60% of net rotation in the HS3 (Pacific hot spot) reference frame); larger viscosity drops amplify asthenospheric shear associated with net rotation and thus require slower net rotation to fit observed anisotropy. The magnitude of westward net rotation is consistent with lithospheric drift relative to Indo-Atlantic hot spots but is slower than drift in the Pacific hot spot frame (HS3 ≈ 0.44°/Myr). The latter may instead express net rotation relative to the deep mantle beneath the Pacific plate, which is moving rapidly eastward in our models.This research was supported by NSF grants EAR‐0855546 (C.P.C.) and EAR‐0854673 (M.D.B.)

New Detection Systems of Bacteria Using Highly Selective Media Designed by SMART: Selective Medium-Design Algorithm Restricted by Two Constraints

Culturing is an indispensable technique in microbiological research, and culturing with selective media has played a crucial role in the detection of pathogenic microorganisms and the isolation of commercially useful microorganisms from environmental samples. Although numerous selective media have been developed in empirical studies, unintended microorganisms often grow on such media probably due to the enormous numbers of microorganisms in the environment. Here, we present a novel strategy for designing highly selective media based on two selective agents, a carbon source and antimicrobials. We named our strategy SMART for highly Selective Medium-design Algorithm Restricted by Two constraints. To test whether the SMART method is applicable to a wide range of microorganisms, we developed selective media for Burkholderia glumae, Acidovorax avenae, Pectobacterium carotovorum, Ralstonia solanacearum, and Xanthomonas campestris. The series of media developed by SMART specifically allowed growth of the targeted bacteria. Because these selective media exhibited high specificity for growth of the target bacteria compared to established selective media, we applied three notable detection technologies: paper-based, flow cytometry-based, and color change-based detection systems for target bacteria species. SMART facilitates not only the development of novel techniques for detecting specific bacteria, but also our understanding of the ecology and epidemiology of the targeted bacteria

Structure and Evolution of Streptomyces Interaction Networks in Soil and In Silico

Soil grains harbor an astonishing diversity of Streptomyces strains producing diverse secondary metabolites. However, it is not understood how this genotypic and chemical diversity is ecologically maintained. While secondary metabolites are known to mediate signaling and warfare among strains, no systematic measurement of the resulting interaction networks has been available. We developed a high-throughput platform to measure all pairwise interactions among 64 Streptomyces strains isolated from several individual grains of soil. We acquired more than 10,000 time-lapse movies of colony development of each isolate on media containing compounds produced by each of the other isolates. We observed a rich set of such sender-receiver interactions, including inhibition and promotion of growth and aerial mycelium formation. The probability that two random isolates interact is balanced; it is neither close to zero nor one. The interactions are not random: the distribution of the number of interactions per sender is bimodal and there is enrichment for reciprocity—if strain A inhibits or promotes B, it is likely that B also inhibits or promotes A. Such reciprocity is further enriched in strains derived from the same soil grain, suggesting that it may be a property of coexisting communities. Interactions appear to evolve rapidly: isolates with identical 16S rRNA sequences can have very different interaction patterns. A simple eco-evolutionary model of bacteria interacting through antibiotic production shows how fast evolution of production and resistance can lead to the observed statistical properties of the network. In the model, communities are evolutionarily unstable—they are constantly being invaded by strains with new sets of interactions. This combination of experimental and theoretical observations suggests that diverse Streptomyces communities do not represent a stable ecological state but an intrinsically dynamic eco-evolutionary phenomenon

Evidence from GC-TRFLP that Bacterial Communities in Soil Are Lognormally Distributed

The Species Abundance Distribution (SAD) is a fundamental property of ecological communities and the form and formation of SADs have been examined for a wide range of communities including those of microorganisms. Progress in understanding microbial SADs, however, has been limited by the remarkable diversity and vast size of microbial communities. As a result, few microbial systems have been sampled with sufficient depth to generate reliable estimates of the community SAD. We have used a novel approach to characterize the SAD of bacterial communities by coupling genomic DNA fractionation with analysis of terminal restriction fragment length polymorphisms (GC-TRFLP). Examination of a soil microbial community through GC-TRFLP revealed 731 bacterial operational taxonomic units (OTUs) that followed a lognormal distribution. To recover the same 731 OTUs through analysis of DNA sequence data is estimated to require analysis of 86,264 16S rRNA sequences. The approach is examined and validated through construction and analysis of simulated microbial communities in silico. Additional simulations performed to assess the potential effects of PCR bias show that biased amplification can cause a community whose distribution follows a power-law function to appear lognormally distributed. We also show that TRFLP analysis, in contrast to GC-TRFLP, is not able to effectively distinguish between competing SAD models. Our analysis supports use of the lognormal as the null distribution for studying the SAD of bacterial communities as for plant and animal communities

Gene prediction in metagenomic fragments: A large scale machine learning approach

<p>Abstract</p> <p>Background</p> <p>Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions.</p> <p>Results</p> <p>We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability.</p> <p>Conclusion</p> <p>Large scale machine learning methods are well-suited for gene prediction in metagenomic DNA fragments. In particular, the combination of linear discriminants and neural networks is promising and should be considered for integration into metagenomic analysis pipelines. The data sets can be downloaded from the URL provided (see Availability and requirements section).</p