Epigenome-wide methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2+): a prospective cohort study in the United States.

BACKGROUND: Methylation levels may be associated with and serve as markers to predict risk of progression of precancerous cervical lesions. We conducted an epigenome-wide association study (EWAS) of CpG methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2 +) following an abnormal screening test. METHODS: A prospective US cohort of 289 colposcopy patients with normal or CIN1 enrollment histology was assessed. Baseline cervical sample DNA was analyzed using Illumina HumanMethylation 450K (n = 76) or EPIC 850K (n = 213) arrays. Participants returned at provider-recommended intervals and were followed up to 5 years via medical records. We assessed continuous CpG M values for 9 cervical cancer-associated genes and time-to-progression to CIN2+. We estimated CpG-specific time-to-event ratios (TTER) and hazard ratios using adjusted, interval-censored Weibull accelerated failure time models. We also conducted an exploratory EWAS to identify novel CpGs with false discovery rate (FDR) < 0.05. RESULTS: At enrollment, median age was 29.2 years; 64.0% were high-risk HPV-positive, and 54.3% were non-white. During follow-up (median 24.4 months), 15 participants progressed to CIN2+. Greater methylation levels were associated with a shorter time-to-CIN2+ for CADM1 cg03505501 (TTER = 0.28; 95%CI 0.12, 0.63; FDR = 0.03) and RARB Cluster 1 (TTER = 0.46; 95% CI 0.29, 0.71; FDR = 0.01). There was evidence of similar trends for DAPK1 cg14286732, PAX1 cg07213060, and PAX1 Cluster 1. The EWAS detected 336 novel progression-associated CpGs, including those located in CpG islands associated with genes FGF22, TOX, COL18A1, GPM6A, XAB2, TIMP2, GSPT1, NR4A2, and APBB1IP. CONCLUSIONS: Using prospective time-to-event data, we detected associations between CADM1-, DAPK1-, PAX1-, and RARB-related CpGs and cervical disease progression, and we identified novel progression-associated CpGs. IMPACT: Methylation levels at novel CpG sites may help identify individuals with ≤CIN1 histology at higher risk of progression to CIN2+ and inform risk-based cervical cancer screening guidelines.

ANASTASIA: An Automated Metagenomic Analysis Pipeline for Novel Enzyme Discovery Exploiting Next Generation Sequencing Data.

Metagenomic analysis of environmental samples provides deep insight into the enzymatic mixture of the corresponding niches, capable of revealing peptide sequences with novel functional properties exploiting the high performance of next-generation sequencing (NGS) technologies. At the same time due to their ever increasing complexity, there is a compelling need for ever larger computational configurations to ensure proper bioinformatic analysis, and fine annotation. With the aiming to address the challenges of such an endeavor, we have developed a novel web-based application named ANASTASIA (automated nucleotide aminoacid sequences translational plAtform for systemic interpretation and analysis). ANASTASIA provides a rich environment of bioinformatic tools, either publicly available or novel, proprietary algorithms, integrated within numerous automated algorithmic workflows, and which enables versatile data processing tasks for (meta)genomic sequence datasets. ANASTASIA was initially developed in the framework of the European FP7 project HotZyme, whose aim was to perform exhaustive analysis of metagenomes derived from thermal springs around the globe and to discover new enzymes of industrial interest. ANASTASIA has evolved to become a stable and extensible environment for diversified, metagenomic, functional analyses for a range of applications overarching industrial biotechnology to biomedicine, within the frames of the ELIXIR-GR project. As a showcase, we report the successful in silico mining of a novel thermostable esterase termed "EstDZ4" from a metagenomic sample collected from a hot spring located in Krisuvik, Iceland.

DNA methylation profiling implicates exposure to PCBs in the pathogenesis of B-cell chronic lymphocytic leukemia.

OBJECTIVES: To characterize the impact of PCB exposure on DNA methylation in peripheral blood leucocytes and to evaluate the corresponding changes in relation to possible health effects, with a focus on B-cell lymphoma. METHODS: We conducted an epigenome-wide association study on 611 adults free of diagnosed disease, living in Italy and Sweden, in whom we also measured plasma concentrations of 6 PCB congeners, DDE and hexachlorobenzene. RESULTS: We identified 650 CpG sites whose methylation correlates strongly (FDR < 0.01) with plasma concentrations of at least one PCB congener. Stronger effects were observed in males and in Sweden. This epigenetic exposure profile shows extensive and highly statistically significant overlaps with published profiles associated with the risk of future B-cell chronic lymphocytic leukemia (CLL) as well as with clinical CLL (38 and 28 CpG sites, respectively). For all these sites, the methylation changes were in the same direction for increasing exposure and for higher disease risk or clinical disease status, suggesting an etiological link between exposure and CLL. Mediation analysis reinforced the suggestion of a causal link between exposure, changes in DNA methylation and disease. Disease connectivity analysis identified multiple additional diseases associated with differentially methylated genes, including melanoma for which an etiological link with PCB exposure is established, as well as developmental and neurological diseases for which there is corresponding epidemiological evidence. Differentially methylated genes include many homeobox genes, suggesting that PCBs target stem cells. Furthermore, numerous polycomb protein target genes were hypermethylated with increasing exposure, an effect known to constitute an early marker of carcinogenesis. CONCLUSIONS: This study provides mechanistic evidence in support of a link between exposure to PCBs and the etiology of CLL and underlines the utility of omic profiling in the evaluation of the potential toxicity of environmental chemicals.

Using Prokaryotes for Carbon Capture Storage.

Geological storage of CO2 is a fast-developing technology that can mitigate rising carbon emissions. However, there are environmental concerns with the long-term storage and implications of a leak from a carbon capture storage (CCS) site. Traditional monitoring lacks clear protocols and relies heavily on physical methods. Here, we discuss the potential of biotechnology, focusing on microbes with a natural ability to utilize and assimilate CO2 through different metabolic pathways. We propose the use of natural microbial communities for CCS monitoring and CO2 utilization, and, with examples, demonstrate how synthetic biology may maximize CO2 uptake within and above storage sites. An integrated physical and biological approach, combined with metagenomics data and biotechnological advances, will enhance CO2 sequestration and prevent large-scale leakages.

Metagenomic mining for thermostable esterolytic enzymes uncovers a new family of bacterial esterases.

Biocatalysts exerting activity against ester bonds have a broad range of applications in modern biotechnology. Here, we have identified a new esterolytic enzyme by screening a metagenomic sample collected from a hot spring in Kamchatka, Russia. Biochemical characterization of the new esterase, termed EstDZ2, revealed that it is highly active against medium chain fatty acid esters at temperatures between 25 and 60 °C and at pH values 7-8. The new enzyme is moderately thermostable with a half-life of more than six hours at 60 °C, but exhibits exquisite stability against high concentrations of organic solvents. Phylogenetic analysis indicated that EstDZ2 is likely an Acetothermia enzyme that belongs to a new family of bacterial esterases, for which we propose the index XV. One distinctive feature of this new family, is the presence of a conserved GHSAG catalytic motif. Multiple sequence alignment, coupled with computational modelling of the three-dimensional structure of EstDZ2, revealed that the enzyme lacks the largest part of the "cap" domain, whose extended structure is characteristic for the closely related Family IV esterases. Thus, EstDZ2 appears to be distinct from known related esterolytic enzymes, both in terms of sequence characteristics, as well as in terms of three-dimensional structure.

Discovery and Characterization of a Thermostable and Highly Halotolerant GH5 Cellulase from an Icelandic Hot Spring Isolate.

With the ultimate goal of identifying robust cellulases for industrial biocatalytic conversions, we have isolated and characterized a new thermostable and very halotolerant GH5 cellulase. This new enzyme, termed CelDZ1, was identified by bioinformatic analysis from the genome of a polysaccharide-enrichment culture isolate, initiated from material collected from an Icelandic hot spring. Biochemical characterization of CelDZ1 revealed that it is a glycoside hydrolase with optimal activity at 70°C and pH 5.0 that exhibits good thermostability, high halotolerance at near-saturating salt concentrations, and resistance towards metal ions and other denaturing agents. X-ray crystallography of the new enzyme showed that CelDZ1 is the first reported cellulase structure that lacks the defined sugar-binding 2 subsite and revealed structural features which provide potential explanations of its biochemical characteristics.

Integrative workflows for metagenomic analysis.

The rapid evolution of all sequencing technologies, described by the term Next Generation Sequencing (NGS), have revolutionized metagenomic analysis. They constitute a combination of high-throughput analytical protocols, coupled to delicate measuring techniques, in order to potentially discover, properly assemble and map allelic sequences to the correct genomes, achieving particularly high yields for only a fraction of the cost of traditional processes (i.e., Sanger). From a bioinformatic perspective, this boils down to many GB of data being generated from each single sequencing experiment, rendering the management or even the storage, critical bottlenecks with respect to the overall analytical endeavor. The enormous complexity is even more aggravated by the versatility of the processing steps available, represented by the numerous bioinformatic tools that are essential, for each analytical task, in order to fully unveil the genetic content of a metagenomic dataset. These disparate tasks range from simple, nonetheless non-trivial, quality control of raw data to exceptionally complex protein annotation procedures, requesting a high level of expertise for their proper application or the neat implementation of the whole workflow. Furthermore, a bioinformatic analysis of such scale, requires grand computational resources, imposing as the sole realistic solution, the utilization of cloud computing infrastructures. In this review article we discuss different, integrative, bioinformatic solutions available, which address the aforementioned issues, by performing a critical assessment of the available automated pipelines for data management, quality control, and annotation of metagenomic data, embracing various, major sequencing technologies and applications.