NEW YORK (GenomeWeb News) – In PLoS Genetics, researchers from the US and Germany describe findings from their phylogenomic study of seed plants. Using existing sequence data on nearly 23,000 orthologous genes from 150 land plant species in 101 genera, the team not only defined some previously murky plant relationships, but also looked at the timing with which genes with different functional roles appeared throughout the plants' evolution. Together, the analyses illustrate potential roles for certain genes and pathways in shaping plant features and adaptations.
"Having the architecture of this plant tree of life allows us to start to decipher some of the interesting aspects of evolutionary innovations that have occurred in this group," co-corresponding author Rob DeSalle, curator of the American Museum of Natural History's invertebrate zoology division and researcher with AMNH's Sackler Institute for Comparative Genomics, said in a statement.
Researchers from the University of Washington, Harvard University, and the Santa Fe Institute combined metagenomic and metabolic pathway data to get a systems level view of the human gut microbiome — findings they report in the early, online version of the Proceedings of the National Academy of Sciences.
Through metagenomic sequencing of individuals' fecal samples, the team assessed the nature and abundance of microbial species and genes in the guts of 124 unrelated individuals with or without inflammatory bowel disease who were classified as lean, overweight, or obese. They also did metagenomic sequencing on fecal samples from six obese or lean sets of identical twins and their mothers. By developing networks from their data, investigators found clues to the gene-level and network-level shifts in the gut microbiome that accompany obesity or IBD.
"In essence, this study represents an important step in the development of a 'metagenomics systems biology' approach," University of Washington genome sciences researcher Elhanan Borenstein, the study's senior author, and colleagues explain. "Such an approach can potentially advance metagenomics research in the same way that systems biology advanced genomics, appreciating not only the parts list of a system but the complex interactions among parts and the impact of these interactions on function and dynamics."
A Science Translational Medicine study outlines the strategy that scientists from the US and Nicaragua used to explore interactions between dengue virus genetics, infection severity, and variations in human immunity.
By sequencing or genotyping hundreds of dengue viruses from patient samples collected during two clinical studies in Nicaragua and folding in epidemiological, serological, and other data, the researchers illustrated how shifts in viral genetics and host immunity resulted in more severe dengue infections over several seasons. For example, they found that viruses from serotype 2, clade NI-1 viruses caused more serious disease during the 2006-2007 and 2008-2009 dengue seasons, likely due to declining immunity in individuals already exposed to another of the four dengue serotypes, serotype 1. They also saw more severe infections coinciding with the replacement of NI-1 clade viruses by viruses from the NI-2B clade.
"This can explain why it has been so difficult to connect a particular dengue virus and a particular subtype to disease severity," University of California at Berkeley infectious disease and vaccinology researcher Eva Harris, co-corresponding author on the study, said in a statement. "One really needs to take a 'phylodynamic' approach, looking at the phylogenetics — how these viruses evolve over time — and linking it to epidemiology and immunology, which are also changing over time."
A Department of Energy Joint BioEnergy Institute group has come up with a strategy that may eventually allow for the advent of computer-aided design platforms that rely on RNA-based control of gene expression in microbial systems.
As they explain in Science, the researchers first did simulations of mechanistic models and kinetic folding patterns to predict the functions of devices based on ribozyme and aptazyme RNA structures. They then made 28 devices that could orchestrate gene expression levels in Escherichia coli as predicted. Those involved in the project are optimistic that the work may pave the way for CAD tools based on RNA — an approach that may prove useful in everything from biological studies of RNA to microbe-based production systems related to biofuel research and other applications.
"Our work establishes a foundation for developing CAD platforms to engineer complex RNA-based control systems that can process cellular information and program the expression of very large numbers of genes," Joint BioEnergy Institute Director Jay Keasling, senior author on the study, said in a statement. "Perhaps even more importantly, we have provided a framework for studying RNA functions and demonstrated the potential of using biochemical and biophysical modeling to develop rigorous design-driven engineering strategies for biology."
Genomics In The Journals is a weekly feature pointing readers to select, recently published articles involving genomics and related research.