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SorTn-seq: a high-throughput functional genomics approach to discovering regulators of bacterial gene expression

Abstract

We recently developed a high-throughput functional genomics approach, named ‘SorTn-seq’, to identify factors affecting expression of any gene of interest in bacteria. Our approach facilitates high-throughput screening of complex mutant pools, a task previously hindered by a lack of suitable techniques. SorTn-seq combines high-density, Tn5-like transposon mutagenesis with fluorescence-activated cell sorting of a strain harboring a promoter-fluorescent reporter fusion, to isolate mutants with altered gene expression. The transposon mutant pool is sorted into different bins on the basis of fluorescence, and mutants are deep-sequenced to identify transposon insertions. DNA is prepared for sequencing by using commercial kits augmented with custom primers, enhancing ease of use and reproducibility. Putative regulators are identified by comparing the number of insertions per genomic feature in the different sort bins, by using existing bioinformatic pipelines and software packages. SorTn-seq can be completed in 1–2 weeks and requires general microbiology skills and basic flow cytometry experience.

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Fig. 1: SorTn-seq protocol overview.
Fig. 2: Design of the fluorescent reporter plasmid used during SorTn-seq.
Fig. 3: SorTn-seq TIS workflow.
Fig. 4: SorTn-seq data analysis workflow.
Fig. 5: Transposon mutagenesis workflow.
Fig. 6: Gating strategy used during FACS.
Fig. 7: Binding sites of qPCR primers.
Fig. 8: Summary of input and output files of the SorTn-seq analysis.
Fig. 9: Example plots generated by the SorTnSeq_analysis R script.

Data availability

Sequencing data originally published in ref. 13 are available in the Sequence Read Archive under BioProject number PRJNA601789. The annotated genome of Serratia sp. ATCC 39006-LacA is available through the National Center for Biotechnology Information (reference sequence NZ_CP025085.1). Source data are provided with this paper.

Code availability

R scripts and files required for data processing the Serratia csm dataset are available at Zenodo (https://doi.org/10.5281/zenodo.4554398) and on GitHub (https://github.com/JacksonLab/SorTn-seq)64.

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Acknowledgements

This work was supported by the Marsden Fund from the Royal Society of New Zealand and the School of Biomedical Sciences Bequest Fund from the University of Otago. L.M.S. was supported by a University of Otago Doctoral Scholarship and Postgraduate Publishing Bursary. We thank M. Wilson for help with cell sorting and A. Jeffs of the Otago Genomics Facility for assistance with sequencing. We thank J. Ussher and R. Hannaway for help with flow cytometry. We thank H. Hampton, D. Mayo-Muñoz, N. Birkholz and members of the Fineran laboratory for helpful discussions.

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Contributions

L.M.S. designed all experiments with input from S.A.J. and P.C.F. L.M.S. performed all experiments (except where a specialized facility was used), analyzed all data and prepared all figures. S.A.J. wrote data processing scripts, and P.P.G. provided input into bioinformatic analyses. P.C.F. conceived the project. S.A.J., P.P.G. and P.C.F. supervised the project. L.M.S. and P.C.F. wrote the manuscript. All authors edited the manuscript.

Corresponding author

Correspondence to Peter C. Fineran.

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Key reference using this protocol

Smith, L. et al. Nat. Microbiol. 6, 162–172 (2021): https://doi.org/10.1038/s41564-020-00822-7

Extended data

Extended Data Fig. 1 Gating on a secondary reporter eliminates noise from the primary reporter fluorescence distribution.

The primary reporter (eYFP) fluorescence distribution is shown for without (a) or with (b) gating on a secondary reporter (mCherry). In a and b, events are first gated on SSC and FSC parameters area (A) and height (H) to isolate individual bacteria (‘singlets’ and ‘cells’). a, A characteristic secondary peak is observed centered around zero. Many of the events comprising this secondary peak exhibit negative fluorescence levels and therefore cannot be sorted. This non-fluorescent population is probably comprised of dead/dormant cells, cellular debris, bubbles or electronic noise generated by the instrument. b, The addition of a gate around mCherry-positive (mCherry+) events results in the removal of the secondary peak from the eYFP fluorescence distribution. This improved distribution allows for more accurate placement of gates during cell sorting.

Extended Data Fig. 2 Promoter region and reporter plasmid used during SorTn-seq.

Type III-A CRISPR-Cas expression was measured from an eYFP fusion to 250 nt upstream of the csm operon. Key features in the promoter are indicated (−35 and −10) as are the transcription start site (+1), native RBS and the start codon (ATG, green). An IPTG-inducible 2nd fluorophore (mCherry) is under the control of the T5-lac promoter (PT5-lac). The pBR322 origin of replication facilitates ~15–20 copies of the reporter per cell.

Extended Data Fig. 3 Transposon delivery vector and transposon organization.

a, Organization of the pKRCPN2 transposon delivery vector. b, Schematic of the transposon Tn-DS1028uidAKm, which contains a transcriptional uidA reporter, origin of replication (R6Kγ) and kanamycin resistance gene (KmR).

Supplementary information

Supplementary Information

Supplementary Figs. 1–3, Supplementary Tables 1–8 and Supplementary Protocol

Supplementary Data 1

Results of the SorTn-seq differential enrichment analysis

Source data

Source Data Fig. 6

Number of cells sorted into each bin during replicate library sorting

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Smith, L.M., Jackson, S.A., Gardner, P.P. et al. SorTn-seq: a high-throughput functional genomics approach to discovering regulators of bacterial gene expression. Nat Protoc 16, 4382–4418 (2021). https://doi.org/10.1038/s41596-021-00582-6

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