Gene functionalities and genome structure in Bathycoccus prasinos reflect cellular specializations at the base of the green lineage

ABSTRACT: BACKGROUND: Bathycoccus prasinos is an extremely small cosmopolitan marine green alga whose cells are covered with intricate spider's web patterned scales that develop within the Golgi cisternae before their transport to the cell surface. The objective of this work is to sequence and analyze its genome, and to present a comparative analysis with other known genomes of the green lineage. RESULTS: Its small genome of 15Mb consists of 19 chromosomes and lacks transposons. Although 70% of all B. prasinos genes share similarities with other Viridiplantae genes, up to 428 genes were probably acquired by horizontal gene transfer, mainly from other eukaryotes. Two chromosomes, one big and one small, are atypical, an unusual synapomorphic feature within the Mamiellales. Genes on these atypical outlier chromosomes show lower GC content and a significant fraction of putative horizontal gene transfer genes. Whereas the small outlier chromosome lacks colinearity with other Mamiellales and contains many unknown genes without homologs in other species, the big outlier shows a higher intron content, increased expression levels and a unique clustering pattern of housekeeping functionalities. Four gene families are highly expanded in B. prasinos, including sialyltransferases, sialidases, ankyrin repeats and zinc ion-binding genes, and we hypothesize that these genes are associated with the process of scale biogenesis. CONCLUSION: The minimal genomes of the Mamiellophyceae provide a baseline for evolutionary and functional analyses of metabolic processes in green plants.     

Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers

Background

Accurate outcome prediction in neuroblastoma, which is necessary to enable the optimal choice of risk-related therapy, remains a challenge. To improve neuroblastoma patient stratification, this study aimed to identify prognostic tumor DNA methylation biomarkers.

Results

To identify genes silenced by promoter methylation, we first applied two independent genome-wide methylation screening methodologies to eight neuroblastoma cell lines. Specifically, we used re-expression profiling upon 5-aza-2''-deoxycytidine (DAC) treatment and massively parallel sequencing after capturing with a methyl-CpG-binding domain (MBD-seq). Putative methylation markers were selected from DAC-upregulated genes through a literature search and an upfront methylation-specific PCR on 20 primary neuroblastoma tumors, as well as through MBD- seq in combination with publicly available neuroblastoma tumor gene expression data. This yielded 43 candidate biomarkers that were subsequently tested by high-throughput methylation-specific PCR on an independent cohort of 89 primary neuroblastoma tumors that had been selected for risk classification and survival. Based on this analysis, methylation of KRT19, FAS, PRPH, CNR1, QPCT, HIST1H3C, ACSS3 and GRB10 was found to be associated with at least one of the classical risk factors, namely age, stage or MYCN status. Importantly, HIST1H3C and GNAS methylation was associated with overall and/or event-free survival.

Conclusions

This study combines two genome-wide methylation discovery methodologies and is the most extensive validation study in neuroblastoma performed thus far. We identified several novel prognostic DNA methylation markers and provide a basis for the development of a DNA methylation-based prognostic classifier in neuroblastoma.     

A sensitive and rapid ultra HPLC-MS/MS method for the simultaneous detection of clopidogrel and its derivatized active thiol metabolite in human plasma

A sensitive, selective, and rapid ultra-high performance liquid chromatography-tandem mass spectrometry (uHPLC-MS/MS) was developed for the simultaneous quantification of clopidogrel (Plavix(?)) and its derivatized active metabolite (CAMD) in human plasma. Derivatization of the active metabolite in blood with 2-bromo-3'-methoxy acetophenone (MPB) immediately after collection ensured metabolite stability during sample handling and storage. Following addition of ticlopidine as an internal standard and simple protein precipitation, the analytes were separated on a Waters Acquity UPLC? sub-2 μm-C(18) column via gradient elution before detection on a triple-quadrupole MS with multiple-reaction-monitoring via electrospray ionization. The method was validated across the clinically relevant concentration range of 0.01-50 ng/mL for parent clopidogrel and 0.1-150 ng/mL (r(2)=0.99) for CAMD, with a fast run time of 1.5 min to support pharmacokinetic studies using 75, 150, or 300 mg oral doses of clopidogrel. The analytical method measured concentrations of clopidogrel and CAMD with accuracy (%DEV) <±12% and precision (%CV) of <±6%. The method was successfully applied to measure the plasma concentrations of clopidogrel and CAMD in three subjects administered single oral doses of 75, 150, and 300 mg clopidogrel. It was further demonstrated that the derivatizing agent (MPB) does not affect clopidogrel levels, thus from one aliquot of blood drawn clinically, this method can simultaneously quantify both clopidogrel and CAMD with sensitivity in the picogram per mL range.     

RNA inhibition highlights cyclin d1 as a potential therapeutic target for mantle cell lymphoma

Mantle cell lymphoma is characterized by a genetic translocation results in aberrant overexpression of the CCND1 gene, which encodes cyclin D1. This protein functions as a regulator of the cell cycle progression, hence is considered to play an important role in the pathogenesis of the disease. In this study, we used RNA interference strategies to examine whether cyclin D1 might serve as a therapeutic target for mantle cell lymphoma. Knocking down cyclin D1 resulted in significant growth retardation, cell cycle arrest, and most importantly, induction of apoptosis. These results mark cyclin D1 as a target for mantle cell lymphoma and emphasize the therapeutic potential hidden in its silencing.     

Millimeter‐scale genetic gradients and community‐level molecular convergence in a hypersaline microbial mat

To investigate the extent of genetic stratification in structured microbial communities, we compared the metagenomes of 10 successive layers of a phylogenetically complex hypersaline mat from Guerrero Negro, Mexico. We found pronounced millimeter‐scale genetic gradients that were consistent with the physicochemical profile of the mat. Despite these gradients, all layers displayed near‐identical and acid‐shifted isoelectric point profiles due to a molecular convergence of amino‐acid usage, indicating that hypersalinity enforces an overriding selective pressure on the mat community.     

A molecular study of microbe transfer between distant environments

Background

Environments and their organic content are generally not static and isolated, but in a constant state of exchange and interaction with each other. Through physical or biological processes, organisms, especially microbes, may be transferred between environments whose characteristics may be quite different. The transferred microbes may not survive in their new environment, but their DNA will be deposited. In this study, we compare two environmental sequencing projects to find molecular evidence of transfer of microbes over vast geographical distances.

Methodology

By studying synonymous nucleotide composition, oligomer frequency and orthology between predicted genes in metagenomics data from two environments, terrestrial and aquatic, and by correlating with phylogenetic mappings, we find that both environments are likely to contain trace amounts of microbes which have been far removed from their original habitat. We also suggest a bias in direction from soil to sea, which is consistent with the cycles of planetary wind and water.

Conclusions

Our findings support the Baas-Becking hypothesis formulated in 1934, which states that due to dispersion and population sizes, microbes are likely to be found in widely disparate environments. Furthermore, the availability of genetic material from distant environments is a possible font of novel gene functions for lateral gene transfer.     

Predicting biological networks from genomic data

Continuing improvements in DNA sequencing technologies are providing us with vast amounts of genomic data from an ever-widening range of organisms. The resulting challenge for bioinformatics is to interpret this deluge of data and place it back into its biological context. Biological networks provide a conceptual framework with which we can describe part of this context, namely the different interactions that occur between the molecular components of a cell. Here, we review the computational methods available to predict biological networks from genomic sequence data and discuss how they relate to high-throughput experimental methods.