Droplet Tn-Seq combines microfluidics with Tn-Seq for identifying complex single-cell phenotypes.
ABSTRACT: While Tn-Seq is a powerful tool to determine genome-wide bacterial fitness in high-throughput, culturing transposon-mutant libraries in pools can mask community or other complex single-cell phenotypes. Droplet Tn-Seq (dTn-Seq) solves this problem by microfluidics facilitated encapsulation of individual transposon mutants into growth medium-in-oil droplets, thereby enabling isolated growth, free from the influence of the population. Here we describe and validate microfluidic chip design, production, encapsulation, and dTn-Seq sample preparation. We determine that 1-3% of mutants in Streptococcus pneumoniae have a different fitness when grown in isolation and show how dTn-Seq can help identify leads for gene function, including those involved in hyper-competence, processing of alpha-1-acid glycoprotein, sensitivity against the human leukocyte elastase and microcolony formation. Additionally, we show dTn-Seq compatibility with microscopy, FACS and investigations of bacterial cell-to-cell and bacteria-host cell interactions. dTn-Seq reduces costs and retains the advantages of Tn-Seq, while expanding the method's original applicability.
Project description:Tn-Seq is an experimental method for probing the functions of genes through construction of complex random transposon insertion libraries and quantification of each mutant's abundance using next-generation sequencing. An important emerging application of Tn-Seq is for identifying genetic interactions, which involves comparing Tn mutant libraries generated in different genetic backgrounds (e.g. wild-type strain versus knockout strain). Several analytical methods have been proposed for analyzing Tn-Seq data to identify genetic interactions, including estimating relative fitness ratios and fitting a generalized linear model. However, these have limitations which necessitate an improved approach. We present a hierarchical Bayesian method for identifying genetic interactions through quantifying the statistical significance of changes in enrichment. The analysis involves a four-way comparison of insertion counts across datasets to identify transposon mutants that differentially affect bacterial fitness depending on genetic background. Our approach was applied to Tn-Seq libraries made in isogenic strains of Mycobacterium tuberculosis lacking three different genes of unknown function previously shown to be necessary for optimal fitness during infection. By analyzing the libraries subjected to selection in mice, we were able to distinguish several distinct classes of genetic interactions for each target gene that shed light on their functions and roles during infection.
Project description: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 the flanking regions en masse. These changes are used to calculate each mutant's fitness. Using this approach, we determined fitness for each gene of Streptococcus pneumoniae, a causative agent of pneumonia and meningitis. A genome-wide screen for genetic interactions of five query genes identified both alleviating and aggravating interactions that could be divided into seven distinct categories. Owing 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.
Project description:Transposon insertion sequencing (Tn-Seq) is a microbial systems-level tool, that can determine on a genome-wide scale and in high-throughput, whether a gene, or a specific genomic region, is important for fitness under a specific experimental condition.Here, we present MAGenTA, a suite of analysis tools which accurately calculate the growth rate for each disrupted gene in the genome to enable the discovery of: (i) new leads for gene function, (ii) non-coding RNAs; (iii) genes, pathways and ncRNAs that are involved in tolerating drugs or induce disease; (iv) higher order genome organization; and (v) host-factors that affect bacterial host susceptibility. MAGenTA is a complete Tn-Seq analysis pipeline making sensitive genome-wide fitness (i.e. growth rate) analysis available for most transposons and Tn-Seq associated approaches (e.g. TraDis, HiTS, IN-Seq) and includes fitness (growth rate) calculations, sliding window analysis, bottleneck calculations and corrections, statistics to compare experiments and strains and genome-wide fitness visualization.MAGenTA is available at the Galaxy public ToolShed repository and all source code can be found and are freely available at https://vanopijnenlab.github.io/MAGenTA/ .email@example.com.Supplementary data are available at Bioinformatics online.
Project description:To perform Tn-seq experiments random distribution of the transposon in the genome of the recipient cells is essential. In case transposon is delivered into the host cell by conjugation, donor may affect the distribution of the transposon in the genome of the recipient cell. Here, we provide two Tn-seq performed with two different donor strains. FX371 corresponds the Tn-seq using E. coli B-2163 as donor strain. FX442 corresponds to the Tn-seq using E. coli MFDpir as donor strain.
Project description:We describe a deep-sequencing procedure for tracking large numbers of transposon mutants of Pseudomonas aeruginosa. The procedure employs a new Tn-seq methodology based on the generation and amplification of single-strand circles carrying transposon junction sequences (the Tn-seq circle method), a method which can be used with virtually any transposon. The procedure reliably identified more than 100,000 transposon insertions in a single experiment, providing near-saturation coverage of the genome. To test the effectiveness of the procedure for mutant identification, we screened for mutations reducing intrinsic resistance to the aminoglycoside antibiotic tobramycin. Intrinsic tobramycin resistance had been previously analyzed at genome scale using mutant-by-mutant screening and thus provided a benchmark for evaluating the new method. The new Tn-seq procedure identified 117 tobramycin resistance genes, the majority of which were then verified with individual mutants. The group of genes with the strongest mutant phenotypes included nearly all (13 of 14) of those with strong mutant phenotypes identified in the previous screening, as well as a nearly equal number of new genes. The results thus show the effectiveness of the Tn-seq method in defining the genetic basis of a complex resistance trait of P. aeruginosa and indicate that it can be used to analyze a variety of growth-related processes.
Project description:The bacterium Pantoea stewartii ssp. stewartii causes Stewart's wilt disease in corn. Pantoea stewartii is transmitted to plants via corn flea beetles, where it first colonizes the apoplast causing water-soaked lesions, and then migrates to the xylem and forms a biofilm that blocks water transport. Bacterial quorum sensing ensures that the exopolysaccharide production necessary for biofilm formation occurs only at high cell density. A genomic-level transposon sequencing (Tn-Seq) analysis was performed to identify additional bacterial genes essential for survival in planta and to provide insights into the plant-microbe interactions occurring during wilt disease. A mariner transposon library of approximately 40 000 mutants was constructed and used to inoculate corn seedlings through a xylem infection model. Cultures of the library grown in Luria-Bertani (LB) broth served as the in vitro pre-inoculation control. Tn-Seq analysis showed that the number of transposon mutations was reduced by more than 10-fold for 486 genes in planta compared with the library that grew in LB, suggesting that they are important for xylem survival. Interestingly, a small set of genes had a higher abundance of mutants in planta versus in vitro conditions, indicating enhanced strain fitness with loss of these genes inside the host. In planta competition assays retested the trends of the Tn-Seq data for several genes, including two outer membrane proteins, Lon protease and two quorum sensing-associated transcription factors, RcsA and LrhA. Virulence assays were performed to check for correlation between growth/colonization and pathogenicity. This study demonstrates the capacity of a Tn-Seq approach to advance our understanding of P. stewartii-corn interactions.
Project description:Tn-seq is a high throughput technique for analysis of transposon mutant libraries. Tn-seq Explorer was developed as a convenient and easy-to-use package of tools for exploration of the Tn-seq data. In a typical application, the user will have obtained a collection of sequence reads adjacent to transposon insertions in a reference genome. The reads are first aligned to the reference genome using one of the tools available for this task. Tn-seq Explorer reads the alignment and the gene annotation, and provides the user with a set of tools to investigate the data and identify possibly essential or advantageous genes as those that contain significantly low counts of transposon insertions. Emphasis is placed on providing flexibility in selecting parameters and methodology most appropriate for each particular dataset. Tn-seq Explorer is written in Java as a menu-driven, stand-alone application. It was tested on Windows, Mac OS, and Linux operating systems. The source code is distributed under the terms of GNU General Public License. The program and the source code are available for download at http://www.cmbl.uga.edu/downloads/programs/Tn_seq_Explorer/ and https://github.com/sina-cb/Tn-seqExplorer.
Project description:Borrelia burgdorferi maintains a complex life cycle between tick and vertebrate hosts. Although some genes have been identified as contributing to bacterial adaptation in the different hosts, the list is incomplete. In this manuscript, we report the first use of transposon mutagenesis combined with high-throughput sequencing (Tn-seq) in B. burgdorferi. We utilize the technique to investigate mechanisms of carbohydrate utilization in B. burgdorferi and the role of carbohydrate metabolism during mouse infection. We performed genetic fitness analyses to identify genes encoding factors contributing to growth on glucose, maltose, mannose, trehalose and N-acetyl-glucosamine. We obtained insight into the potential functions of proteins predicted to be involved in carbohydrate utilization and identified additional factors previously unrecognized as contributing to the metabolism of the tested carbohydrates. Strong phenotypes were observed for the putative carbohydrate phosphotransferase transporters BB0408 and BBB29 as well as the response regulator Rrp1. We further validated Tn-seq for use in mouse studies and were able to correctly identify known infectivity factors as well as additional transporters and genes on lp54 that may contribute to optimal mouse infection. As such, this study establishes Tn-seq as a powerful method for both in vitro and in vivo studies of B. burgdorferi.
Project description:The lagging annotation of bacterial genomes and the inherent genetic complexity of many phenotypes is hindering the discovery of new drug targets and the development of new antimicrobial agents and vaccines. This unit presents Tn-seq, a method that has made it possible to quantitatively determine fitness for most genes in a microorganism and to screen for quantitative genetic interactions on a genome-wide scale and in a high-throughput fashion. Tn-seq can thus direct studies on the annotation of genes and untangle complex phenotypes. The method is based on the construction of a saturated transposon insertion library. After library selection, changes in the frequency of each insertion mutant are determined by sequencing flanking regions en masse. These changes are used to calculate each mutant's fitness. The method was originally developed for the Gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis, but has now been applied to several different microbial species.
Project description:Respiratory melioidosis is a disease presentation of the biodefense pathogen, Burkholderia pseudomallei, which is frequently associated with a lethal septicemic spread of the bacteria. We have recently developed an improved respiratory melioidosis model to study the pathogenesis of Burkholderia pseudomallei in the lung (intubation-mediated intratracheal [IMIT] inoculation), which more closely models descriptions of human melioidosis, including prominent septicemic spread from the lung and reduced involvement of the upper respiratory tract. We previously demonstrated that the Type 3 Secretion System cluster 3 (T3SS3) is a critical virulence determinant for B. pseudomallei when delivered directly into the lung. We decided to comprehensively identify all virulence determinants required for respiratory melioidosis using the Tn-seq phenotypic screen, as well as to investigate which virulence determinants are required for dissemination to the liver and spleen. While previous studies have used Tn-seq to identify essential genes for in vitro cultured B. pseudomallei, this represents the first study to use Tn-seq to identify genes required for in vivo fitness. Consistent with our previous findings, we identified T3SS3 as the largest genetic cluster required for fitness in the lung. Furthermore, we identified capsular polysaccharide and Type 6 Secretion System cluster 5 (T6SS5) as the two additional major genetic clusters facilitating respiratory melioidosis. Importantly, Tn-seq did not identify additional, novel large genetic systems supporting respiratory melioidosis, although these studies identified additional small gene clusters that may also play crucial roles in lung fitness. Interestingly, other previously identified virulence determinants do not appear to be required for lung fitness, such as lipopolysaccharide. The role of T3SS3, capsule, and T6SS5 in lung fitness was validated by competition studies, but only T3SS3 was found to be important for respiratory melioidosis when delivered as a single strain challenge, suggesting that competition studies may provide a higher resolution analysis of fitness factors in the lung. The use of Tn-seq phenotypic screening also provided key insights into the selective pressure encountered in the liver.