Horizontal DNA transfer mechanisms of bacteria as weapons of intragenomic conflict

Horizontal DNA transfer (HDT) is a pervasive mechanism of diversification in many microbial species, but its primary evolutionary role remains controversial. Much recent research has emphasised the adaptive benefit of acquiring novel DNA, but here we argue instead that intragenomic conflict provides a coherent framework for understanding the evolutionary origins of HDT. To test this hypothesis, we developed a mathematical model of a clonally descended bacterial population undergoing HDT through transmission of mobile genetic elements (MGEs) and genetic transformation. Including the known bias of transformation toward the acquisition of shorter alleles into the model suggested it could be an effective means of counteracting the spread of MGEs. Both constitutive and transient competence for transformation were found to provide an effective defence against parasitic MGEs; transient competence could also be effective at permitting the selective spread of MGEs conferring a benefit on their host bacterium. The coordination of transient competence with cell-cell killing, observed in multiple species, was found to result in synergistic blocking of MGE transmission through releasing genomic DNA for homologous recombination while simultaneously reducing horizontal MGE spread by lowering the local cell density. To evaluate the feasibility of the functions suggested by the modelling analysis, we analysed genomic data from longitudinal sampling of individuals carrying Streptococcus pneumoniae. This revealed the frequent within-host coexistence of clonally descended cells that differed in their MGE infection status, a necessary condition for the proposed mechanism to operate. Additionally, we found multiple examples of MGEs inhibiting transformation through integrative disruption of genes encoding the competence machinery across many species, providing evidence of an ongoing "arms race." Reduced rates of transformation have also been observed in cells infected by MGEs that reduce the concentration of extracellular DNA through secretion of DNases. Simulations predicted that either mechanism of limiting transformation would benefit individual MGEs, but also that this tactic's effectiveness was limited by competition with other MGEs coinfecting the same cell. A further observed behaviour we hypothesised to reduce elimination by transformation was MGE activation when cells become competent. Our model predicted that this response was effective at counteracting transformation independently of competing MGEs. Therefore, this framework is able to explain both common properties of MGEs, and the seemingly paradoxical bacterial behaviours of transformation and cell-cell killing within clonally related populations, as the consequences of intragenomic conflict between self-replicating chromosomes and parasitic MGEs. The antagonistic nature of the different mechanisms of HDT over short timescales means their contribution to bacterial evolution is likely to be substantially greater than previously appreciated

Forecasting with Big Data: A Review

Big Data is a revolutionary phenomenon which is one of the most frequently discussed topics in the modern age, and is expected to remain so in the foreseeable future. In this paper we present a comprehensive review on the use of Big Data for forecasting by identifying and reviewing the problems, potential, challenges and most importantly the related applications. Skills, hardware and software, algorithm architecture, statistical significance, the signal to noise ratio and the nature of Big Data itself are identified as the major challenges which are hindering the process of obtaining meaningful forecasts from Big Data. The review finds that at present, the fields of Economics, Energy and Population Dynamics have been the major exploiters of Big Data forecasting whilst Factor models, Bayesian models and Neural Networks are the most common tools adopted for forecasting with Big Data

Omics Approaches for Understanding Biogenesis, Composition and Functions of Fungal Extracellular Vesicles

This is the final version. Available on open access from Frontiers Media via the DOI in this recordExtracellular vesicles (EVs) are lipid bilayer structures released by organisms from all kingdoms of life. The diverse biogenesis pathways of EVs result in a wide variety of physical properties and functions across different organisms. Fungal EVs were first described in 2007 and different omics approaches have been fundamental to understand their composition, biogenesis, and function. In this review, we discuss the role of omics in elucidating fungal EVs biology. Transcriptomics, proteomics, metabolomics, and lipidomics have each enabled the molecular characterization of fungal EVs, providing evidence that these structures serve a wide array of functions, ranging from key carriers of cell wall biosynthetic machinery to virulence factors. Omics in combination with genetic approaches have been instrumental in determining both biogenesis and cargo loading into EVs. We also discuss how omics technologies are being employed to elucidate the role of EVs in antifungal resistance, disease biomarkers, and their potential use as vaccines. Finally, we review recent advances in analytical technology and multi-omic integration tools, which will help to address key knowledge gaps in EVs biology and translate basic research information into urgently needed clinical applications such as diagnostics, and immuno- and chemotherapies to fungal infections.NIHPacific Northwest National Laboratory (PNNL)CNPq/Science Without Borders Science Program, BrazilJohns Hopkins Malaria Research InstituteFAPESPCAPESCNPqMedical Research Council (MRC

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Mucosa-associated lymphoid tissue lymphoma and concurrent adenocarcinoma of the prostate

Primary mucosa-associated lymphoid tissue (MALT) lymphoma of the prostate is a rare disease that characteristically follows an indolent course. It is believed that infection or chronic inflammation may be triggers for malignant transformation in the prostate, but it is of unknown etiology. Reports of MALT lymphomas of the prostate with other concurrent primary prostate cancers are even more limited. We present the unique case of a 67-year-old male with concurrent adenocarcinoma of the prostate and primary MALT lymphoma of the prostate. The patient was treated with standard therapy for prostate adenocarcinoma, which would also treat a primary MALT lymphoma. He has been disease-free for over one year for both his primary malignancies. This case confirms that MALT lymphoma can arise concurrently with adenocarcinoma of the prostate

Fast Identification and Removal of Sequence Contamination from Genomic and Metagenomic Datasets

High-throughput sequencing technologies have strongly impacted microbiology, providing a rapid and cost-effective way of generating draft genomes and exploring microbial diversity. However, sequences obtained from impure nucleic acid preparations may contain DNA from sources other than the sample. Those sequence contaminations are a serious concern to the quality of the data used for downstream analysis, causing misassembly of sequence contigs and erroneous conclusions. Therefore, the removal of sequence contaminants is a necessary and required step for all sequencing projects. We developed DeconSeq, a robust framework for the rapid, automated identification and removal of sequence contamination in longer-read datasets (150 bp mean read length). DeconSeq is publicly available as standalone and web-based versions. The results can be exported for subsequent analysis, and the databases used for the web-based version are automatically updated on a regular basis. DeconSeq categorizes possible contamination sequences, eliminates redundant hits with higher similarity to non-contaminant genomes, and provides graphical visualizations of the alignment results and classifications. Using DeconSeq, we conducted an analysis of possible human DNA contamination in 202 previously published microbial and viral metagenomes and found possible contamination in 145 (72%) metagenomes with as high as 64% contaminating sequences. This new framework allows scientists to automatically detect and efficiently remove unwanted sequence contamination from their datasets while eliminating critical limitations of current methods. DeconSeq's web interface is simple and user-friendly. The standalone version allows offline analysis and integration into existing data processing pipelines. DeconSeq's results reveal whether the sequencing experiment has succeeded, whether the correct sample was sequenced, and whether the sample contains any sequence contamination from DNA preparation or host. In addition, the analysis of 202 metagenomes demonstrated significant contamination of the non-human associated metagenomes, suggesting that this method is appropriate for screening all metagenomes. DeconSeq is available at http://deconseq.sourceforge.net/

Origin and Epidemiological History of HIV-1 CRF14_BG

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Users must also make clear the license terms under which the work was published. CC BY Licence: http://creativecommons.org/licenses/by/4.0/Background: CRF14_BG isolates, originally found in Spain, are characterized by CXCR4 tropism and rapid disease progression. This study aimed to identify the origin of CRF14_BG and reconstruct its epidemiological history based on new isolates from Portugal.Methodology/Principal Findings: C2V3C3 env gene sequences were obtained from 62 samples collected in 1993–1998 from Portuguese HIV-1 patients. Full-length genomic sequences were obtained from three patients. Viral subtypes, diversity, divergence rate and positive selection were investigated by phylogenetic analysis. The molecular structure of the genomes was determined by bootscanning. A relaxed molecular clock model was used to date the origin of CRF14_BG. Geno2pheno was used to predict viral tropism. Subtype B was the most prevalent subtype (45 sequences; 73%) followed by CRF14_BG (8; 13%), G (4; 6%), F1 (2; 3%), C (2; 3%) and CRF02_AG (1; 2%). Three CRF14_BG sequences were derived from 1993 samples. Near full-length genomic sequences were strongly related to the CRF14_BG isolates from Spain. Genetic diversity of the Portuguese isolates was significantly higher than the Spanish isolates (0.044 vs 0.014, P,0.0001). The mean date of origin of the CRF14_BG cluster was estimated to be 1992 (range, 1989 and 1996) based on the subtype G genomic region and 1989 (range, 1984–1993) based on the subtype B genomic region. Most CRF14_BG strains (78.9%) were predicted to be CXCR4. Finally, up to five amino acids were under selective pressure in subtype B V3 loop whereas only one was found in the CRF14_BG cluster.Conclusions: CRF14_BG emerged in Portugal in the early 1990 s soon after the beginning of the HIV-1 epidemics, spread to Spain in late 1990 s as a consequence of IVDUs migration and then to the rest of Europe. CXCR4 tropism is a general characteristic of this CRF that may have been selected for by escape from neutralizing antibody response