Long read review: redesigning life: how genome editing will transform the world by John Parrington

In Redesigning Life: How Genome Editing Will Transform the World, John Parrington traces a history of genetic engineering, focusing particularly on recent, rapid developments in the capacity to manipulate genomes. This painstakingly researched book acts as an engaging, comprehensive and urgent introduction to the debate over the wider societal impact of these emerging technologies, finds Thomas Christie Williams

Synthetic Virus-Derived Nanosystems (SVNs) for Delivery and Precision Docking of Large Multifunctional DNA Circuitry in Mammalian Cells

DNA delivery is at the forefront of current research efforts in gene therapy and synthetic biology. Viral vectors have traditionally dominated the field; however, nonviral delivery systems are increasingly gaining traction. Baculoviruses are arthropod-specific viruses that can be easily engineered and repurposed to accommodate and deliver large sequences of exogenous DNA into mammalian cells, tissues, or ultimately organisms. These synthetic virus-derived nanosystems (SVNs) are safe, readily customized, and can be manufactured at scale. By implementing clustered regularly interspaced palindromic repeats (CRISPR) associated protein (CRISPR/Cas) modalities into this system, we developed SVNs capable of inserting complex DNAs into genomes, at base pair precision. We anticipate a major role for SVNs as an attractive alternative to viral vectors in accelerating genome engineering and gene therapy applications in the future

Megx.net: integrated database resource for marine ecological genomics

Megx.net is a database and portal that provides integrated access to georeferenced marker genes, environment data and marine genome and metagenome projects for microbial ecological genomics. All data are stored in the Microbial Ecological Genomics DataBase (MegDB), which is subdivided to hold both sequence and habitat data and global environmental data layers. The extended system provides access to several hundreds of genomes and metagenomes from prokaryotes and phages, as well as over a million small and large subunit ribosomal RNA sequences. With the refined Genes Mapserver, all data can be interactively visualized on a world map and statistics describing environmental parameters can be calculated. Sequence entries have been curated to comply with the proposed minimal standards for genomes and metagenomes (MIGS/MIMS) of the Genomic Standards Consortium. Access to data is facilitated by Web Services. The updated megx.net portal offers microbial ecologists greatly enhanced database content, and new features and tools for data analysis, all of which are freely accessible from our webpage http://www.megx.net

The origin of biased sequence depth in sequence-independent nucleic acid amplification and optimization for efficient massive parallel sequencing

Sequence Independent Single Primer Amplification is one of the most widely used random amplification approaches in virology for sequencing template preparation. This technique relies on oligonucleotides consisting of a 39 random part used to prime complementary DNA synthesis and a 59 defined tag sequence for subsequent amplification. Recently, this amplification method was combined with next generation sequencing to obtain viral sequences. However, these studies showed a biased distribution of the resulting sequence reads over the analyzed genomes. The aim of this study was to elucidate the mechanisms that lead to biased sequence depth when using random amplification. Avian paramyxovirus type 8 was used as a model RNA virus to investigate these mechanisms. We showed, based on in silico analysis of the sequence depth in relation to GC-content, predicted RNA secondary structure and sequence complementarity to the 39 part of the tag sequence, that the tag sequence has the main contribution to the observed bias in sequence depth. We confirmed this finding experimentally using both fragmented and non-fragmented viral RNAs as well as primers differing in random oligomer length (6 or 12 nucleotides) and in the sequence of the amplification tag. The observed oligonucleotide annealing bias can be reduced by extending the random oligomer sequence and by in silico combining sequence data from SISPA experiments using different 59 defined tag sequences. These findings contribute to the optimization of random nucleic acid amplification protocols that are currently required for downstream applications such as viral metagenomics and microarray analysis

Putting Synthesis into Biology: A Viral View of Genetic Engineering through De Novo Gene and Genome Synthesis

SummaryThe rapid improvements in DNA synthesis technology hold the potential to revolutionize biosciences in the near future. Traditional genetic engineering methods are template dependent and make extensive but laborious use of site-directed mutagenesis to explore the impact of small variations on an existing sequence “theme.” De novo gene and genome synthesis frees the investigator from the restrictions of the pre-existing template and allows for the rational design of any conceivable new sequence theme.Viruses, being among the simplest replicating entities, have been at the forefront of the advancing biosciences since the dawn of molecular biology. Viral genomes, especially those of RNA viruses, are relatively short, often less than 10,000 bases long, making them amenable to whole genome synthesis with the currently available technology. For this reason viruses are once again poised to lead the way in the budding field of synthetic biology—for better or worse

VIPR: A probabilistic algorithm for analysis of microbial detection microarrays

<p>Abstract</p> <p>Background</p> <p>All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance.</p> <p>Results</p> <p>To specifically address this issue we have developed a novel interpretive algorithm, VIPR (<b>V</b>iral <b>I</b>dentification using a <b>PR</b>obabilistic algorithm), which uses Bayesian inference to capitalize on empirical training data to optimize detection sensitivity. To illustrate this approach, we have focused on the detection of viruses that cause hemorrhagic fever (HF) using a custom HF-virus microarray. VIPR was used to analyze 110 empirical microarray hybridizations generated from 33 distinct virus species. An accuracy of 94% was achieved as measured by leave-one-out cross validation. <it>Conclusions</it></p> <p>VIPR outperformed previously described algorithms for this dataset. The VIPR algorithm has potential to be broadly applicable to clinical diagnostic settings, wherein positive controls are typically readily available for generation of training data.</p

Effects of HBV Genetic Variability on RNAi Strategies

RNAi strategies present promising antiviral strategies against HBV. RNAi strategies require base pairing between short RNAi effectors and targets in the HBV pregenome or other RNAs. Natural variation in HBV genotypes, quasispecies variation, or mutations selected by the RNAi strategy could potentially make these strategies less effective. However, current and proposed antiviral strategies against HBV are being, or could be, designed to avoid this. This would involve simultaneous targeting of multiple regions of the genome, or regions in which variation or mutation is not tolerated. RNAi strategies against single genotypes or against variable regions of the genome would need to have significant other advantages to be part of robust therapies