Blog
About

94
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Tn-seq; high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms

      , ,

      Nature methods

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Biological pathways are structured in complex networks of interacting genes. Solving the architecture of such networks may provide valuable information, such as how microorganisms cause disease. Here we present a method (Tn-seq) for accurately determining quantitative genetic interactions on a genome-wide scale in microorganisms. Tn-seq is based on the assembly of a saturated Mariner transposon insertion library. After library selection, changes in frequency of each insertion mutant are determined by sequencing of the flanking regions en masse. These changes are used to calculate each mutant’s fitness. Fitness was determined for each gene of the gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis. A genome-wide screen for genetic interactions identified both alleviating and aggravating interactions that could be further divided into seven distinct categories. Due to the wide activity of the Mariner transposon, Tn-seq has the potential to contribute to the exploration of complex pathways across many different species.

          Related collections

          Most cited references 29

          • Record: found
          • Abstract: found
          • Article: not found

          Genes required for mycobacterial growth defined by high density mutagenesis.

          Despite over a century of research, tuberculosis remains a leading cause of infectious death worldwide. Faced with increasing rates of drug resistance, the identification of genes that are required for the growth of this organism should provide new targets for the design of antimycobacterial agents. Here, we describe the use of transposon site hybridization (TraSH) to comprehensively identify the genes required by the causative agent, Mycobacterium tuberculosis, for optimal growth. These genes include those that can be assigned to essential pathways as well as many of unknown function. The genes important for the growth of M. tuberculosis are largely conserved in the degenerate genome of the leprosy bacillus, Mycobacterium leprae, indicating that non-essential functions have been selectively lost since this bacterium diverged from other mycobacteria. In contrast, a surprisingly high proportion of these genes lack identifiable orthologues in other bacteria, suggesting that the minimal gene set required for survival varies greatly between organisms with different evolutionary histories.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            STRING 7—recent developments in the integration and prediction of protein interactions

            Information on protein–protein interactions is still mostly limited to a small number of model organisms, and originates from a wide variety of experimental and computational techniques. The database and online resource STRING generalizes access to protein interaction data, by integrating known and predicted interactions from a variety of sources. The underlying infrastructure includes a consistent body of completely sequenced genomes and exhaustive orthology classifications, based on which interaction evidence is transferred between organisms. Although primarily developed for protein interaction analysis, the resource has also been successfully applied to comparative genomics, phylogenetics and network studies, which are all facilitated by programmatic access to the database backend and the availability of compact download files. As of release 7, STRING has almost doubled to 373 distinct organisms, and contains more than 1.5 million proteins for which associations have been pre-computed. Novel features include AJAX-based web-navigation, inclusion of additional resources such as BioGRID, and detailed protein domain annotation. STRING is available at
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A DNA integrity network in the yeast Saccharomyces cerevisiae.

              A network governing DNA integrity was identified in yeast by a global genetic analysis of synthetic fitness or lethality defect (SFL) interactions. Within this network, 16 functional modules or minipathways were defined based on patterns of global SFL interactions. Modules or genes involved in DNA replication, DNA-replication checkpoint (DRC) signaling, and oxidative stress response were identified as the major guardians against lethal spontaneous DNA damage, efficient repair of which requires the functions of the DNA-damage checkpoint signaling and multiple DNA-repair pathways. This genome-wide genetic interaction network also identified novel components (DIA2, NPT1, HST3, HST4, and the CSM1 module) that potentially contribute to mitotic DNA replication and genomic stability and revealed novel functions of well-studied genes (the CTF18 module) in DRC signaling. This network will guide more detailed characterization of mechanisms governing DNA integrity in yeast and other organisms.
                Bookmark

                Author and article information

                Journal
                101215604
                32338
                Nat Methods
                Nature methods
                1548-7091
                1548-7105
                24 September 2009
                20 September 2009
                October 2009
                20 October 2010
                : 6
                : 10
                : 767-772
                Affiliations
                Howard Hughes Medical Institute and Dept. of Molecular Biology & Microbiology, Tufts University School of Medicine, 136 Harrison Avenue, South Cove 510, Boston, MA 02111-1817, Ph: 617-636-2144, Fax: 617-636-2175, Andrew. Camilli@ 123456Tufts.edu
                Article
                hhmipa143284
                10.1038/nmeth.1377
                2957483
                19767758

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                Funding
                Funded by: Howard Hughes Medical Institute
                Award ID: ||HHMI_
                Categories
                Article

                Life sciences

                Comments

                Comment on this article