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Sentinel cells programmed to respond to environmental DNA including human sequences

Nature Chemical Biology volume 20, pages 211–220 (2024)Cite this article

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Abstract

Monitoring environmental DNA can track the presence of organisms, from viruses to animals, but requires continuous sampling of transient sequences from a complex milieu. Here we designed living sentinels using Bacillus subtilis to report the uptake of a DNA sequence after matching it to a preencoded target. Overexpression of ComK increased DNA uptake 3,000-fold, allowing for femtomolar detection in samples dominated by background DNA. This capability was demonstrated using human sequences containing single-nucleotide polymorphisms (SNPs) associated with facial features. Sequences were recorded with high efficiency and were protected from nucleases for weeks. The SNP could be determined by sequencing or in vivo using CRISPR interference to turn on reporter expression in response to a specific base. Multiple SNPs were recorded by one cell or through a consortium in which each member recorded a different sequence. Sentinel cells could surveil for specific sequences over long periods of time for applications spanning forensics, ecology and epidemiology.

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Fig. 1: Sentinel cell overview.
Fig. 2: Human DNA uptake by super-competent B. subtilis.
Fig. 3: Detection and discrimination of human DNA by sentinel cells.
Fig. 4: Recording of DNA from a human-derived genomic sample.
Fig. 5: Simultaneous recording of multiple human DNAs.

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Data availability

Sequences for strains and plasmids, including accession numbers of target DNA sequences, used in this work are included in the Supplementary Information file. Raw flow cytometry, NGS, qPCR and colony enumeration data can be accessed at https://github.com/VoigtLab/DNA_sentinels. Additional data are available from the corresponding author upon reasonable request.

Code availability

All code for this work, including custom scripts for flow cytometry, NGS and qPCR analysis, is available at https://github.com/VoigtLab/DNA_sentinels.

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Acknowledgements

This work was funded by the US Defense Advanced Research Projects Agency Advanced Plant Technologies (HR0011-18-0049; X.A.N. and C.A.V.) and the Ministry of Defense of Israel (MIT 4441024394; X.A.N. and C.A.V.).

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Authors and Affiliations

  1. Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Xuefei Angelina Nou & Christopher A. Voigt

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  1. Xuefei Angelina Nou
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Contributions

X.A.N. and C.A.V. conceived the study and designed the experiments. X.A.N. performed the experiments. X.A.N. and C.A.V. participated in data analysis and wrote the paper.

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Correspondence to Christopher A. Voigt.

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Extended data

Extended Data Fig. 1 DNA recording frequency for additional human sequences.

DNA recording frequencies for B. subtilis W2 through W5 and B. subtilis S2 through S5. For all strains, SEQ#gfp/kan was added at 950 pM. The DNA recording frequency was calculated as the ratio of GFP+ and kanamycin resistant cells to total cells. The data represent three experiments performed on different days and the bars are the average of these replicates.

Extended Data Fig. 2 Dose response of sentinel strains to target DNA concentration.

Sentinel cells were incubated with plasmid DNA containing the target sequence with either the reference SNP allele (SEQ2, SEQ3, SEQ4, SEQ5) or an alternate SNP allele (SEQ2C, SEQ3G, SEQ4G, SEQ4T, SEQ5A). The recording frequencies were calculated from the flow cytometry data shown in Supplementary Fig. 1 and data were fit to Eq. 1. c0 is unitless and κ has units of pM. The grey data points are for the cells incubated without DNA and the dashed line indicates the average DNA uptake frequency calculated across all –DNA data points. The data show three replicates performed on different days.

Extended Data Fig. 3 Response to homologous animal sequences.

Species-level phylogenetic trees for animals with sequences homologous to SEQ2, SEQ3, and SEQ4. No homologous sequences were identified for SEQ5. Schematics comparing homologous animal sequences to the original show sequence identities (orange – SEQ2 homologs; purple – SEQ3 homologs; green – SEQ4 homologs); mismatches (red), insertions (red ticks above bar), and deletions (gaps in bar). The percent identity of the animal homolog sequence to the original, as determined by the Needleman-Wunsch algorithm, is shown above each sequence. The data show the fraction ON for each sentinel cell incubated with 800 pM of each target DNA, calculated from the data in Supplementary Fig. 1. The data points for 100% sequence identity used human SEQ2/SEQ2C, SEQ3/SEQ3G, and SEQ4/SEQ4G/SEQ4T for B. subtilis SEN2, SEN3, and SEN4, respectively, and were identical to the data shown in Extended Data Fig. 2 at 800pM. The dashed line is identical to the dashed line shown in the DNA recording frequency plots in Extended Data Fig. 2 and shows the mean DNA recording frequency calculated from sentinel cells incubated without DNA. The data show three replicates performed on different days and the solid lines are the mean values.

Extended Data Fig. 4 Design of CRISPRi-based circuit to respond to SNP base identity.

(a) Schematic of the strain used in Fig. 3h,i (B. subtilis SEN2#1-# or B. subtilis SEN2#2-#, where the superscript # indicates the SNP base pair the sgRNA is designed to target, and the -# indicates the SNP base pair on the genome). The SEN2ΔDT construct containing the SNP is inserted at the amyE locus on the genome and a cassette encoding constitutive expression of dCas9 and a single sgRNA is inserted at the sacA locus. (b) Three sgRNA’s targetting the sense strand, each containing a sequence corresponding to a different SNP base. B. subtilis SEN2ΔDT encoding a T at the SNP position was engineered to consitutively express dCas9 and one of these three sgRNA’s targeted to the SNP region, yielding the strains B. subtilis SEN2T1-T, B. subtilis SEN2G1-T, and B. subtilis SEN2A1-T. GFP expression in strains B. subtilis SEN2ΔDT (terminator excised), B. subtilis SEN2 (terminator present), B. subtilis SEN2T1-T, B. subtilis SEN2G1-T, and B. subtilis SEN2A1-T are plotted. Targetting the sense strand leads to high GFP repression (3-fold greater than DT42), irrespective of whether the sgRNA is a perfect match (B. subtilis SEN2T1-T) or contains a single mismatch (B. subtilis SEN2G1-T, B. subtilis SEN2A1-T) with the target sequence. (c) Three sgRNA’s targetting the antisense strand, each corresponding to a different base at the SNP location. dCas9 and these sgRNA’s were constitutively expressed in B. subtilis SEN2ΔDT encoding a T at the SNP position, yielding B. subtilis SEN2T2-T, B. subtilis SEN2A2-T, and B. subtilis SENC2-T. GFP expression is shown in the bar plot. When the sgRNA matched the target sequence (B. subtilis SEN2T2-T), GFP expression was repressed, but not when there was a single mismatch (B. subtilis SEN2A2-T, B. subtilis SEN2C2-T). Experimental details are provided in the Methods. The bars show the average of three replicates (dots) performed on different days.

Extended Data Fig. 5 NGS data analysis for consortium experiments.

Overview of method used to obtain the data in Fig. 5c–f. (a) Bowtie2 was used to align reads to a reference file of sequences corresponding to all recorder constructs in sentinel cells with (recorder sequences SEN1, 2, 3, 4, 5) and without (recorder sequences SEN1ΔDT, 2ΔDT, 3ΔDT, 4ΔDT, 5ΔDT) the terminator present. (b) Unique reads were selected based on bowtie2-assigned MAPQ scores ≥20. Reads 1, 2, and 3 have unique alignments – read 1 aligns to the junction between homology arms after terminator excision (found in recorder sequence SEN1ΔDT only) and reads 2/3 align to the junction between homology arms and the terminator (found in recorder sequence SEN1 only) – so high MAPQ scores (≥20) would be assigned to these reads. Reads 4 and 5 have multiple possible alignments – read 4 aligns internal to a homology arm (found in recorder sequences SEN1ΔDT and SEN1) and read 5 aligns to gfp (found in all recorder sequences) – so low MAPQ scores would be assigned. MAPQ score distributions for all samples are shown in Supplementary Fig. 13. (c) Alignment profiles are generated from all reads with MAPQ scores ≥20. For SEN#ΔDT sequences (no terminator), the number of aligned reads is reported by summing the number of reads aligning to the SNP position (Fig. 5e and Supplementary Fig. 16). For SEN# sequences (with terminator), the number of aligned reads is reported by averaging the number of reads aligned at either end of the terminator (Supplementary Fig. 15,16). Alignment profiles for all samples are shown in Supplementary Fig. 14(d) Reads aligned at the SNP position in SEN#ΔDT sequences can be used to generate a consensus sequence logo, from which the identity of the SNP recorded can be extracted. All SNP sequences extracted are shown in Extended Data Fig. 6.

Extended Data Fig. 6 Recorded SNP sequences extracted from consortium samples by NGS.

Consortium of all five sentinel cells (B. subtilis SEN1/SEN2/SEN3/SEN4/SEN5) were incubated with mixtures of all five target DNA’s (+SEQ1/SEQ2/SEQ3/SEQ4/SEQ5 in replicate 1; +SEQ1G/SEQ2C/SEQ3G/SEQ4T/SEQ5A in replicate 2; +SEQ1/ SEQ2C/SEQ3G/SEQ4G/SEQ5 in replicate 3), as indicated above each row. Sequence logos were generated from the reads aligned at the SNP position of recorder constructs with the terminator excised (recorder sequences SEN1ΔDT, 2ΔDT, 3ΔDT, 4ΔDT, 5ΔDT). The SNP position is highlighted with bold text. In all cases, the SNP extracted from NGS reads matched the SNP present on the target DNA’s added (the SNPs on SEQ1, SEQ2, SEQ3, SEQ4, and SEQ5 are T, T, A, A, G, respectively). The data show three replicates performed on different days.

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Nou, X.A., Voigt, C.A. Sentinel cells programmed to respond to environmental DNA including human sequences. Nat Chem Biol 20, 211–220 (2024). https://doi.org/10.1038/s41589-023-01431-1

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