Genome-wide fitness and genetic interactions determined by Tn-seq, a high-throughput massively parallel sequencing method for microorganisms

Abstract

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 antimicrobials and vaccines. Here we present the method Tn-seq, with which it has become 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 in the annotation of genes and untangle complex phenotypes. The method is based on the construction 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. The method has been developed for the Gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis; however, due to the wide activity of the Mariner transposon, Tn-seq can be applied to many different microbial species.

Figure 1E.3.1

A detailed schema of how the primers and adapter combine to result in a 120-bp DNA fragment that can be sequenced on an Illumina GAII. AP-B (AP-B_bc-ACAC) and AP-A (AP-A bc-ACAC) are two oligos that make up the adapter. AP-A has a random two base overhang (NN), which is employed to ligate the adapter onto the genomic DNA (MmeI leaves a random two-base overhang). Note that to prevent self-ligation, AP-B is slightly longer than AP-A. In addition, the adapter contains a 4-base barcode (bc) which enables mixing of different samples in a single flow cell lane. With primers P1-M6-MmeI and Gex PCR Primer 2 a 120-bp fragment is generated that contains Illumina specific sequences (the black tails with asterisk) that are necessary for sequencing. The Gex Sequencing primer is used for sequencing once samples are loaded on the flow cell (also see Tables 1E.3.1 and 1E.3.2 for oligo details).

Figure 1E.3.2

Flowchart depicting Tn-seq, from library construction to massively parallel sequencing of transposon-chromosome junctions. (A) A gene-disruption library is constructed by transposing the mini-transposon magellan6 into bacterial genomic DNA in vitro and subsequently transforming a bacterial population with the transposed DNA. The result is a pool of strains where each bacterium contains a single transposon randomly inserted in its genome. DNA is isolated from a portion of the bacterial pool (t₁); another portion is used to seed a culture on which selection is performed (in vitro or in vivo); after selection, bacteria are recovered and DNA is isolated again (t₂). (B) To accomplish sequencing of only the regions flanking magellan6 insertions, DNA from both time points is digested with MmeI, which binds a sequence in the magellan6 terminal inverted repeats but cuts 20 bp downstream, leaving a two-base overhang to which an adapter is ligated. A PCR is performed with one primer having complementarity to the adapter and the other complementary to the inverted repeat sequence. (C) The resulting PCR product is 120 bp long, with approximately 20 bp of bacterial specific DNA flanked by Illumina specific sequences needed for sequencing. After sequencing, different samples are split based on barcode sequence, and the bacteria-specific reads are mapped to the genome and counted for each insertion, thus allowing fitness to be calculated.

Figure 1E.3.3

Tn-seq fitness details. (A) A gene’s fitness is based on the average effect of multiple independent transposon insertions into a gene. On the x axis, the genomic region for S. pneumoniae TIGR4 is plotted covering genes SP0456 to SP0460. Black data points depict the fitness of a single transposon insertion within the coding region of a gene. A black line depicts the average fitness of a specific gene calculated from the individual insertions into that gene. For instance, the average fitness for genes SP0456, SP0458, and SP0460 is around 1 (same as wild type), while insertions into genes SP0457 and SP0459 are clearly disadvantageous and give average fitness values well below 1. The gray data points depict fitness from insertions into intergenic regions between genes. (B) Reproducibility between independently generated libraries, consisting of 10,000 transposon insertion each is high (R² = 0.92). (C) Fitness for all genes across the S. pneumoniae genome.