How the other half lives: CRISPR-Cas's influence on bacteriophages

CRISPR-Cas is a genetic adaptive immune system unique to prokaryotic cells used to combat phage and plasmid threats. The host cell adapts by incorporating DNA sequences from invading phages or plasmids into its CRISPR locus as spacers. These spacers are expressed as mobile surveillance RNAs that direct CRISPR-associated (Cas) proteins to protect against subsequent attack by the same phages or plasmids. The threat from mobile genetic elements inevitably shapes the CRISPR loci of archaea and bacteria, and simultaneously the CRISPR-Cas immune system drives evolution of these invaders. Here we highlight our recent work, as well as that of others, that seeks to understand phage mechanisms of CRISPR-Cas evasion and conditions for population coexistence of phages with CRISPR-protected prokaryotes.Comment: 24 pages, 8 figure

Western Indian Ocean marine and terrestrial records of climate variability: a review and new concepts on land-ocean interactions since AD 1660

We examine the relationship between three tropical and two subtropical western Indian Ocean coral oxygen isotope time series to surface air temperatures (SAT) and rainfall over India, tropical East Africa and southeast Africa. We review established relationships, provide new concepts with regard to distinct rainfall seasons, and mean annual temperatures. Tropical corals are coherent with SAT over western India and East Africa at interannual and multidecadal periodicities. The subtropical corals correlate with Southeast African SAT at periodicities of 16–30 years. The relationship between the coral records and land rainfall is more complex. Running correlations suggest varying strength of interannual teleconnections between the tropical coral oxygen isotope records and rainfall over equatorial East Africa. The relationship with rainfall over India changed in the 1970s. The subtropical oxygen isotope records are coherent with South African rainfall at interdecadal periodicities. Paleoclimatological reconstructions of land rainfall and SAT reveal that the inferred relationships generally hold during the last 350 years. Thus, the Indian Ocean corals prove invaluable for investigating land–ocean interactions during past centuries

A review of elliptical and disc galaxy structure, and modern scaling laws

A century ago, in 1911 and 1913, Plummer and then Reynolds introduced their models to describe the radial distribution of stars in `nebulae'. This article reviews the progress since then, providing both an historical perspective and a contemporary review of the stellar structure of bulges, discs and elliptical galaxies. The quantification of galaxy nuclei, such as central mass deficits and excess nuclear light, plus the structure of dark matter halos and cD galaxy envelopes, are discussed. Issues pertaining to spiral galaxies including dust, bulge-to-disc ratios, bulgeless galaxies, bars and the identification of pseudobulges are also reviewed. An array of modern scaling relations involving sizes, luminosities, surface brightnesses and stellar concentrations are presented, many of which are shown to be curved. These 'redshift zero' relations not only quantify the behavior and nature of galaxies in the Universe today, but are the modern benchmark for evolutionary studies of galaxies, whether based on observations, N-body-simulations or semi-analytical modelling. For example, it is shown that some of the recently discovered compact elliptical galaxies at 1.5 < z < 2.5 may be the bulges of modern disc galaxies.Comment: Condensed version (due to Contract) of an invited review article to appear in "Planets, Stars and Stellar Systems"(www.springer.com/astronomy/book/978-90-481-8818-5). 500+ references incl. many somewhat forgotten, pioneer papers. Original submission to Springer: 07-June-201

The impact of ENSO on Southern African rainfall in CMIP5 ocean atmosphere coupled climate models

We study the ability of 24 ocean atmosphere global coupled models from the Coupled Model Intercomparison Project 5 (CMIP5) to reproduce the teleconnections between El Niño Southern Oscillation (ENSO) and Southern African rainfall in austral summer using historical forced simulations, with a focus on the atmospheric dynamic associated with El Niño. Overestimations of summer rainfall occur over Southern Africa in all CMIP5 models. Abnormal westward extensions of ENSO patterns are a common feature of all CMIP5 models, while the warming of the Indian Ocean that happens during El Niño is not correctly reproduced. This could impact the teleconnection between ENSO and Southern African rainfall which is represented with mixed success in CMIP5 models. Large-scale anomalies of suppressed deep-convection over the tropical maritime continent and enhanced convection from the central to eastern Pacific are correctly simulated. However, regional biases occur above Africa and the Indian Ocean, particularly in the position of the deep convection anomalies associated with El Niño, which can lead to the wrong sign in rainfall anomalies in the northwest part of South Africa. From the near-surface to mid-troposphere, CMIP5 models underestimate the observed anomalous pattern of pressure occurring over Southern Africa that leads to dry conditions during El Niño years

Predicting the seasonal evolution of southern African summer precipitation in the DePreSys3 prediction system

We assess the ability of the DePreSys3 prediction system to predict austral summer precipitation (DJF) over southern Africa, defined as the African continent south of 15°S. DePresys3 is a high resolution prediction system (at a horizontal resolution of ~ 60 km in the atmosphere in mid-latitudes and of the quarter degree in the Ocean) and spans the long period 1959–2016. We find skill in predicting interannual precipitation variability, relative to a long-term trend; the anomaly correlation skill score over southern Africa is greater than 0.45 for the first summer (i.e. lead month 2–4), and 0.37 over Mozambique, Zimbabwe and Zambia for the second summer (i.e. lead month 14–16). The skill is related to the successful prediction of the El-Nino Southern Oscillation (ENSO), and the successful simulation of ENSO teleconnections to southern Africa. However, overall skill is sensitive to the inclusion of strong La-Nina events and also appears to change with forecast epoch. For example, the skill in predicting precipitation over Mozambique is significantly larger for the first summer in the 1990–2016 period, compared to the 1959–1985 period. The difference in skill in predicting interannual precipitation variability over southern Africa in different epochs is consistent with a change in the strength of the observed teleconnections of ENSO. After 1990, and consistent with the increased skill, the observed impact of ENSO appears to strengthen over west Mozambique, in association with changes in ENSO related atmospheric convergence anomalies. However, these apparent changes in teleconnections are not captured by the ensemble-mean predictions using DePreSys3. The changes in the ENSO teleconnection are consistent with a warming over the Indian Ocean and modulation of ENSO properties between the different epochs, but may also be associated with unpredictable atmospheric variability

Methods of model reduction for large-scale biological systems: a survey of current methods and trends

Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed

Climate, history, society over the last millennium in southeast Africa

Climate variability has been causally linked to the transformation of society in pre-industrial southeast Africa. A growing critique, however, challenges the simplicity of ideas that identify climate as an agent of past societal change; arguing instead that the value of historical climate–society research lies in understanding human vulnerability and resilience, as well as how past societies framed, responded and adapted to climatic phenomena. We work across this divide to present the first critical analysis of climate–society relationships in southeast Africa over the last millennium. To achieve this, we review the now considerable body of scholarship on the role of climate in regional societal transformation, and bring forward new perspectives on climate–society interactions across three areas and periods using the theoretical frameworks of vulnerability and resilience. We find that recent advances in paleoclimatology and archaeology give weight to the suggestion that responses to climate variability played an important part in early state formation in the Limpopo valley (1000–1300), though evidence remains insufficient to clarify similar debates concerning Great Zimbabwe (1300–1450/1520). Written and oral evidence from the Zambezi-Save (1500–1830) and KwaZulu-Natal areas (1760–1828) nevertheless reveals a plurality of past responses to climate variability. These were underpinned by the organization of food systems, the role of climate-related ritual and political power, social networks, and livelihood assets and capabilities, as well as the nature of climate variability itself. To conclude, we identify new lines of research on climate, history and society, and discuss how these can more directly inform contemporary African climate adaptation challenges

A statistical toolbox for metagenomics: assessing functional diversity in microbial communities

<p>Abstract</p> <p>Background</p> <p>The 99% of bacteria in the environment that are recalcitrant to culturing have spurred the development of metagenomics, a culture-independent approach to sample and characterize microbial genomes. Massive datasets of metagenomic sequences have been accumulated, but analysis of these sequences has focused primarily on the descriptive comparison of the relative abundance of proteins that belong to specific functional categories. More robust statistical methods are needed to make inferences from metagenomic data. In this study, we developed and applied a suite of tools to describe and compare the richness, membership, and structure of microbial communities using peptide fragment sequences extracted from metagenomic sequence data.</p> <p>Results</p> <p>Application of these tools to acid mine drainage, soil, and whale fall metagenomic sequence collections revealed groups of peptide fragments with a relatively high abundance and no known function. When combined with analysis of 16S rRNA gene fragments from the same communities these tools enabled us to demonstrate that although there was no overlap in the types of 16S rRNA gene sequence observed, there was a core collection of operational protein families that was shared among the three environments.</p> <p>Conclusion</p> <p>The results of comparisons between the three habitats were surprising considering the relatively low overlap of membership and the distinctively different characteristics of the three habitats. These tools will facilitate the use of metagenomics to pursue statistically sound genome-based ecological analyses.</p

Analysis and comparison of very large metagenomes with fast clustering and functional annotation

<p>Abstract</p> <p>Background</p> <p>The remarkable advance of metagenomics presents significant new challenges in data analysis. Metagenomic datasets (metagenomes) are large collections of sequencing reads from anonymous species within particular environments. Computational analyses for very large metagenomes are extremely time-consuming, and there are often many novel sequences in these metagenomes that are not fully utilized. The number of available metagenomes is rapidly increasing, so fast and efficient metagenome comparison methods are in great demand.</p> <p>Results</p> <p>The new metagenomic data analysis method Rapid Analysis of Multiple Metagenomes with a Clustering and Annotation Pipeline (<b>RAMMCAP</b>) was developed using an ultra-fast sequence clustering algorithm, fast protein family annotation tools, and a novel statistical metagenome comparison method that employs a unique graphic interface. RAMMCAP processes extremely large datasets with only moderate computational effort. It identifies raw read clusters and protein clusters that may include novel gene families, and compares metagenomes using clusters or functional annotations calculated by RAMMCAP. In this study, RAMMCAP was applied to the two largest available metagenomic collections, the "Global Ocean Sampling" and the "Metagenomic Profiling of Nine Biomes".</p> <p>Conclusion</p> <p>RAMMCAP is a very fast method that can cluster and annotate one million metagenomic reads in only hundreds of CPU hours. It is available from <url>http://tools.camera.calit2.net/camera/rammcap/</url>.</p

WebCARMA: a web application for the functional and taxonomic classification of unassembled metagenomic reads

Gerlach W, Jünemann S, Tille F, Goesmann A, Stoye J. WebCARMA: a web application for the functional and taxonomic classification of unassembled metagenomic reads. BMC Bioinformatics. 2009;10(1):430.Background Metagenomics is a new field of research on natural microbial communities. High-throughput sequencing techniques like 454 or Solexa-Illumina promise new possibilities as they are able to produce huge amounts of data in much shorter time and with less efforts and costs than the traditional Sanger technique. But the data produced comes in even shorter reads (35-100 basepairs with Illumina, 100-500 basepairs with 454-sequencing). CARMA is a new software pipeline for the characterisation of species composition and the genetic potential of microbial samples using short, unassembled reads. Results In this paper, we introduce WebCARMA, a refined version of CARMA available as a web application for the taxonomic and functional classification of unassembled (ultra-)short reads from metagenomic communities. In addition, we have analysed the applicability of ultra-short reads in metagenomics. Conclusions We show that unassembled reads as short as 35 bp can be used for the taxonomic classification of a metagenome. The web application is freely available at http://webcarma.cebitec.uni-bielefeld.d