Continuous monitoring of intra- and extracellular environments, ranging from open fields and rivers to within a single cell, is often limited by costly equipment, labor intensity, or invasive techniques. It may, however, be possible to avoid these issues by developing a monitoring device on a much smaller scale. By applying novel synthetic biology techniques, it is now possible to engineer organisms with refined biorecording capabilities, using DNA as a recording medium on which a cellular “memory” of past events can be written. Through a variety of mechanisms, using recombinases, CRISPR nucleases, base editing, polymerases, and prime editing, intra- and extracellular events can be recorded along with temporal, spatial, and magnitude information. Here, the mechanisms developed for DNA-based biorecording devices so far are assessed and discussed, within the context of the potential future applications of these devices.
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References
1.
KeckF, BouchezA, FrancA, et al.Linking phylogenetic similarity and pollution sensitivity to develop ecological assessment methods: A test with river diatoms. J Appl Ecol, 2016; 53(3):856–864; doi: 10.1111/1365-2664.12624
2.
CairnsJ, Van Der SchalieWH. Introduction to early warning systems. Elsevier: Netherlands; 1982.
3.
JarqueS, BittnerM, BlahaL, et al.Yeast biosensors for detection of environmental pollutants: Current state and limitations. Trends Biotechnol, 2016; 34(5):408–419; doi: 10.1016/j.tibtech.2016.01.007
4.
OstrovN, JimenezM, BillerbeckS, et al.A modular yeast biosensor for low-cost point-of-care pathogen detection. Sci Adv, 2017; 3(6):e1603221–e1603221; doi: 10.1126/sciadv.1603221
5.
BelkinS, Yagur-KrollS, KabessaY, et al.Remote detection of buried landmines using a bacterial sensor. Nat Biotechnol, 2017; 35(4):308–310; doi: 10.1038/nbt.3791
6.
Ajo-FranklinCM, DrubinDA, EskinJA, et al.Rational design of memory in eukaryotic cells. Genes Dev, 2007; 21(18):2271–2276; doi: 10.1101/gad.1586107
7.
GardnerTS, CantorCR, CollinsJJ. Construction of a genetic toggle switch in Escherichia coli. Nature, 2000; 403(6767):339–342; doi: 10.1038/35002131
8.
KramerBP, VirettaAU, BabaMD-E, et al.An engineered epigenetic transgene switch in mammalian cells. Nat Biotechnol, 2004; 22(7):867–870; doi: 10.1038/nbt980
9.
ErlichY, ZielinskiD. DNA Fountain enables a robust and efficient storage architecture. Science, 2017; 355(6328):950–954; doi: 10.1126/science.aaj2038
10.
KjaerKH, Winther PedersenM, De SanctisB, et al.A 2-million-year-old ecosystem in Greenland uncovered by environmental DNA. Nature, 2022; 612(7939):283–291; doi: 10.1038/s41586-022-05453-y
11.
ChalfieM, TuY, EuskirchenG, et al.Green fluorescent protein as a marker for gene expression. Science, 1994; 263(5148):802–805; doi: 10.1126/science.8303295
JiaoC, ReckstadtC, KönigF, et al.RNA recording in single bacterial cells using reprogrammed tracrRNAs. Nat Biotechnol, 2023; doi: 10.1038/s41587-022-01604-8
14.
LiuY, PintoF, WanX, et al.Reprogrammed tracrRNAs enable repurposing of RNAs as crRNAs and sequence-specific RNA biosensors. Nat Commun, 2022; 13(1):1937; doi: 10.1038/s41467-022-29604-x
15.
LiuL, ChenD, WangJ, et al.Advances of single-cell protein analysis. Cells, 2020; 9(5); doi: 10.3390/cells9051271
16.
LiuD, EvansT, ZhangF. Applications and advances of metabolite biosensors for metabolic engineering. Metabolic Engineering, 2015; 31(35–43; doi: https://doi.org/10.1016/j.ymben.2015.06.008
17.
SorensonAE, SchaefferPM. Real-time temperature sensing using a ratiometric dual fluorescent protein biosensor. Biosensors, 2023; 13(3):338; doi: 10.3390/bios13030338
18.
SerdyukovDS, GoryachkovskayaTN, MescheryakovaIA, et al.Fluorescent bacterial biosensor E. coli/pTdcR-TurboYFP sensitive to terahertz radiation. Biomed Opt Express, 2021; 12(2):705–721; doi: 10.1364/BOE.412074
19.
RennickJJ, NowellCJ, PoutonCW, et al.Resolving subcellular pH with a quantitative fluorescent lifetime biosensor. Nat Commun, 2022; 13(1):6023; doi: 10.1038/s41467-022-33348-z
20.
AhmedS, ShaikhN, PathakN, et al. Chapter 3—An Overview of Sensitivity and Selectivity of Biosensors for Environmental Applications. In: Tools, Techniques and Protocols for Monitoring Environmental Contaminants. (Kaur Brar S, Hegde K, Pachapur VL. eds.) Elsevier: Netherlands; 2019; pp. 53–73.
21.
DubendorfJW, StudierFW. Controlling basal expression in an inducible T7 expression system by blocking the target T7 promoter with lac repressor. J Mol Biol, 1991; 219(1):45–59; doi: 10.1016/0022-2836(91)90856-2
22.
OldRW, PrimroseSB. Principles of Gene Manipulation: An Introduction to Genetic Engineering. Blackwell Scientific: United States; 1994.
23.
GruberDF, PieriboneVA, PortonB, et al.Strict regulation of gene expression from a high-copy plasmid utilizing a dual vector system. Protein Expr Purif, 2008; 60(1):53–57; doi: 10.1016/j.pep.2008.03.014
24.
IshiguroS, MoriH, YachieN. DNA event recorders send past information of cells to the time of observation. Curr Opin Chem Biol, 2019; 52:54–62; doi: 10.1016/j.cbpa.2019.05.009
25.
KallunkiT, BarisicM, JäätteläM, et al.How to choose the right inducible gene expression system for mammalian studies?. Cells, 2019; 8(8):796; doi: 10.3390/cells8080796
ToppS, GallivanJP. Emerging applications of riboswitches in chemical biology. ACS Chem Biol, 2010; 5(1):139–148; doi: 10.1021/cb900278x
30.
IsaacsFJ, DwyerDJ, DingC, et al.Engineered riboregulators enable post-transcriptional control of gene expression. Nat Biotechnol, 2004; 22(7):841–847; doi: 10.1038/nbt986
31.
PardeeK, GreenAA, TakahashiMK, et al.Rapid, low-cost detection of Zika virus using programmable biomolecular components. Cell, 2016; 165(5):1255–1266; doi: 10.1016/j.cell.2016.04.059
32.
HongF, MaD, WuK, et al.Precise and programmable detection of mutations using ultraspecific riboregulators. Cell, 2020; 180(5):1018–1032.e16; doi: 10.1016/j.cell.2020.02.011
33.
KaseniitKE, KatzN, KolberNS, et al.Modular, programmable RNA sensing using ADAR editing in living cells. Nat Biotechnol, 2022; 41(4):482–487; doi: 10.1038/s41587-022-01493-x
34.
KlauserB, AtanasovJ, SiewertLK, et al.Ribozyme-based aminoglycoside switches of gene expression engineered by genetic selection in S. cerevisiae. ACS Synth Biol, 2014; 4(5):516–525; doi: 10.1021/sb500062p
35.
DavidsonME, HarbaughSV, ChushakYG, et al.Development of a 2,4-dinitrotoluene-responsive synthetic riboswitch in E. coli cells. ACS Chem Biol, 2012; 8(1):234–241; doi: 10.1021/cb300274g
36.
MaAT, SchmidtCM, GoldenJW. Regulation of gene expression in diverse cyanobacterial species by using theophylline-responsive riboswitches. Appl Environ Microbiol, 2014; 80(21):6704–6713; doi: 10.1128/AEM.01697-14
37.
YangL, NielsenAAK, Fernandez-RodriguezJ, et al.Permanent genetic memory with >1-byte capacity. Nat Methods, 2014; 11(12):1261–1266; doi: 10.1038/nmeth.3147
38.
PerliSD, CuiCH, LuTK. Continuous genetic recording with self-targeting CRISPR-Cas in human cells. Science, 2016; 353(6304); doi: 10.1126/science.aag0511
39.
BhanN, CallistoA, StrutzJ, et al.Recording temporal signals with minutes resolution using enzymatic DNA synthesis. J Am Chem Soc, 2021; 143(40):16630–16640; doi: 10.1021/jacs.1c07331
40.
WangY, YauY-Y, Perkins-BaldingD, et al.Recombinase technology: Applications and possibilities. Plant Cell Rep, 2011; 30(3):267–285; doi: 10.1007/s00299-010-0938-1
41.
ChowK-HK, BuddeMW, GranadosAA, et al.Imaging cell lineage with a synthetic digital recording system. Science, 2021; 372(6538):eabb3099; doi: 10.1126/science.abb3099
42.
MimeeM, TuckerAC, VoigtCA, et al.Programming a human commensal bacterium, Bacteroides thetaiotaomicron, to sense and respond to stimuli in the murine gut microbiota. Cell Syst, 2015; 1(1):62–71; doi: 10.1016/j.cels.2015.06.001
43.
BonnetJ, SubsoontornP, EndyD. Rewritable digital data storage in live cells via engineered control of recombination directionality. Proc Natl Acad Sci U S A, 2012; 109(23):8884–8889; doi: 10.1073/pnas.1202344109
44.
FriedlandAE, LuTK, WangX, et al.Synthetic gene networks that count. Science, 2009; 324(5931):1199–1202; doi: 10.1126/science.1172005
45.
SubsoontornP, EndyD. Design and analysis of genetically encoded counters. Procedia Comput Sci, 2012; 11:43–54; doi: 10.1016/j.procs.2012.09.006
WeinbergBH, PhamNTH, CaraballoLD, et al.Large-scale design of robust genetic circuits with multiple inputs and outputs for mammalian cells. Nat Biotechnol, 2017; 35(5):453–462; doi: 10.1038/nbt.3805
49.
RoquetN, SoleimanyAP, FerrisAC, et al.Synthetic recombinase-based state machines in living cells. Science, 2016; 353(6297); doi: 10.1126/science.aad8559
50.
DurrantMG, FantonA, TyckoJ, et al.Systematic discovery of recombinases for efficient integration of large DNA sequences into the human genome. Nat Biotechnol, 2023; 41(4):488–499; doi: 10.1038/s41587-022-01494-w
51.
FarzadfardF, LuTK. Synthetic biology. Genomically encoded analog memory with precise in vivo DNA writing in living cell populations. Science, 2014; 346(6211):1256272–1256272; doi: 10.1126/science.1256272
52.
FarzadfardF, GharaeiN, CitorikRJ, et al.Efficient retroelement-mediated DNA writing in bacteria. Cell Syst, 2021; 12(9):860–872.e5; doi: 10.1016/j.cels.2021.07.001
53.
ArdeschDJ, ScholtensLH, van den HeuvelMP. The Human Connectome from an Evolutionary Perspective. Elsevier: Netherlands; 2019.
54.
KlingerE, MottaA, MarrC, et al.Cellular connectomes as arbiters of local circuit models in the cerebral cortex. Nat Commun, 2021; 12(1):2785–2785; doi: 10.1038/s41467-021-22856-z
55.
KomorAC, KimYB, PackerMS, et al.Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature, 2016; 533(7603):420–424; doi: 10.1038/nature17946
56.
TangW, LiuDR. Rewritable multi-event analog recording in bacterial and mammalian cells. Science, 2018; 360(6385):eaap8992; doi: 10.1126/science.aap8992
57.
FarzadfardF, GharaeiN, HigashikuniY, et al.Single-nucleotide-resolution computing and memory in living cells. Mol Cell, 2019; 75(4):769–780.e4; doi: https://doi.org/10.1016/j.molcel.2019.07.011
58.
ZouZ-P, YeB-C. Long-term rewritable report and recording of environmental stimuli in engineered bacterial populations. ACS Synth Biol, 2020; 9(9):2440–2449; doi: 10.1021/acssynbio.0c00193
59.
SlesarenkoYS, LavrovAV, SmirnikhinaSA. Off-target effects of base editors: What we know and how we can reduce it. Curr Genet, 2021; 68(1):39–48; doi: 10.1007/s00294-021-01211-1
60.
McKennaA, FindlayGM, GagnonJA, et al.Whole-organism lineage tracing by combinatorial and cumulative genome editing. Science, 2016; 353(6298):aaf7907-aaf7907; doi: 10.1126/science.aaf7907
61.
FriedaKL, LintonJM, HormozS, et al.Synthetic recording and in situ readout of lineage information in single cells. Nature, 2017; 541(7635):107–111; doi: 10.1038/nature20777
LiangY, XieJ, ZhangQ, et al.AGBE: A dual deaminase-mediated base editor by fusing CGBE with ABE for creating a saturated mutant population with multiple editing patterns. Nucleic Acids Res, 2022; 50(9):5384–5399; doi: 10.1093/nar/gkac353
ShipmanSL, NivalaJ, MacklisJD, et al.Molecular recordings by directed CRISPR spacer acquisition. Science, 2016; 353(6298):aaf1175–aaf1175; doi: 10.1126/science.aaf1175
67.
ShipmanSL, NivalaJ, MacklisJD, et al.CRISPR-Cas encoding of a digital movie into the genomes of a population of living bacteria. Nature, 2017; 547(7663):345–349; doi: 10.1038/nature23017
68.
ShethRU, YimSS, WuFL, et al.Multiplex recording of cellular events over time on CRISPR biological tape. Science, 2017; 358(6369):1457–1461; doi: 10.1126/science.aao0958
69.
Bhattarai-KlineS, LearSK, FishmanCB, et al.Recording gene expression order in DNA by CRISPR addition of retron barcodes. Nature, 2022; 608(7921):217–225; doi: 10.1038/s41586-022-04994-6
70.
LovelessTB, GrottsJH, SchechterMW, et al.Lineage tracing and analog recording in mammalian cells by single-site DNA writing. Nat Chem Biol, 2021; 17(6):739–747; doi: 10.1038/s41589-021-00769-8
71.
AnzaloneAV, RandolphPB, DavisJR, et al.Search-and-replace genome editing without double-strand breaks or donor DNA. Nature, 2019; 576(7785):149–157; doi: 10.1038/s41586-019-1711-4
72.
ChenW, ChoiJ, NathansJF, et al.Multiplex genomic recording of enhancer and signal transduction activity in mammalian cells. bioRxiv, 2021:467434; doi: 10.1101/2021.11.05.467434
73.
LovelessTB, CarlsonCK, HuVJ, et al.Molecular recording of sequential cellular events into DNA. bioRxiv, 2021:467507; doi: 10.1101/2021.11.05.467507
74.
ChoiJ, ChenW, MinkinaA, et al.A time-resolved, multi-symbol molecular recorder via sequential genome editing. Nature, 2022; 608(7921):98–107; doi: 10.1038/s41586-022-04922-8
75.
ShinS, JangS, LimD. Small molecules for enhancing the precision and safety of genome editing. Molecules, 2022; 27(19):6266; doi: 10.3390/molecules27196266
76.
HeatherJM, ChainB. The sequence of sequencers: The history of sequencing DNA. Genomics, 2016; 107(1):1–8; doi: 10.1016/j.ygeno.2015.11.003
77.
AmarasingheSL, SuS, DongX, et al.Opportunities and challenges in long-read sequencing data analysis. Genome Biol, 2020; 21(1):30–30; doi: 10.1186/s13059-020-1935-5
78.
TylerAD, MatasejeL, UrfanoCJ, et al.Evaluation of Oxford Nanopore's MinION sequencing device for microbial whole genome sequencing applications. Sci Rep, 2018; 8(1):10931–10931; doi: 10.1038/s41598-018-29334-5
79.
DickinsonGD, MortuzaGM, ClayW, et al.An alternative approach to nucleic acid memory. Nat Commun, 2021; 12(1):2371–2371; doi: 10.1038/s41467-021-22277-y
80.
GaudetM, FaraA-G, BeritognoloI, et al.Allele-Specific PCR in SNP Genotyping. Humana Press: United States; 2009.
81.
PurvisJE, LahavG. Encoding and decoding cellular information through signaling dynamics. Cell, 2013; 152(5):945–956; doi: 10.1016/j.cell.2013.02.005
82.
JeknićS, KudoT, CovertMW. Techniques for studying decoding of single cell dynamics. Front Immunol, 2019; 10:755–755; doi: 10.3389/fimmu.2019.00755
83.
KordingKP. Of toasters and molecular ticker tapes. PLoS Comput Biol, 2011; 7(12):e1002291–e1002291; doi: 10.1371/journal.pcbi.1002291
YaoM, RenT, PanY, et al.A new generation of lineage tracing dynamically records cell fate choices. Int J Mol Sci, 2022; 23(9):5021; doi: 10.3390/ijms23095021
86.
LiA, LiuB, XuJ, et al.Research progress of cell lineage tracing and single-cell sequencing technology in malignant skin tumors. Front Surg, 2022; 9(934828–934828; doi: 10.3389/fsurg.2022.934828
87.
WangM-Y, ZhouY, LaiG-S, et al.DNA barcode to trace the development and differentiation of cord blood stem cells (review). Mol Med Rep, 2021; 24(6):849; doi: 10.3892/mmr.2021.12489
88.
ZhangY, ZengF, HanX, et al.Lineage tracing: Technology tool for exploring the development, regeneration, and disease of the digestive system. Stem Cell Res Ther, 2020; 11(1):438–438; doi: 10.1186/s13287-020-01941-y
89.
CroneDE.GFP-Based Biosensors. IntechOpen: Sine loco; 2013.
90.
McBrideGB, RutherfordJC. Accurate modeling of river pollutant transport. J Environ Eng, 1984; 110(4):808–827; doi: 10.1061/(asce)0733-9372(1984)110:4(808)
91.
PatelN, KhanM, ShahaneS, et al.Emerging pollutants in aquatic environment: source, effect, and challenges in biomonitoring and bioremediation—A review. Pollut, 2020; 6:99–113; doi: 10.22059/poll.2019.285116.646
92.
DanielsMB, SharpleyA, HarmelRD, et al.The utilization of edge-of-field monitoring of agricultural runoff in addressing nonpoint source pollution. J Soil Water Conserv, 2018; 73(1):1–8; doi: 10.2489/jswc.73.1.1
93.
SlomovicS, PardeeK, CollinsJJ. Synthetic biology devices for in vitro and in vivo diagnostics. Proc Natl Acad Sci U S A, 2015; 112(47):14429–14435; doi: 10.1073/pnas.1508521112
94.
NaydichAD, NangleSN, BuesJJ, et al.Synthetic gene circuits enable systems-level biosensor trigger discovery at the host-microbe interface. mSystems, 2019; 4(4):e00125–19; doi: 10.1128/mSystems.00125-19
95.
ChoJH, OkumaA, SofjanK, et al.Engineering advanced logic and distributed computing in human CAR immune cells. Nat Commun, 2021; 12(1):792–792; doi: 10.1038/s41467-021-21078-7
96.
ChenT, Ali Al-RadhawiM, VoigtCA, et al.A synthetic distributed genetic multi-bit counter. iScience, 2021; 24(12):103526–103526; doi: 10.1016/j.isci.2021.103526
97.
PurcellO, LuTK. Synthetic analog and digital circuits for cellular computation and memory. Curr Opin Biotechnol, 2014; 29:146–155; doi: 10.1016/j.copbio.2014.04.009
98.
HsiaoV, HoriY, RothemundPW, et al.A population-based temporal logic gate for timing and recording chemical events. Mol Syst Biol, 2016; 12(5):869–869; doi: 10.15252/msb.20156663
99.
KalhorR, KalhorK, MejiaL, et al.Developmental barcoding of whole mouse via homing CRISPR. Science, 2018; 361(6405):eaat9804; doi: 10.1126/science.aat9804
100.
NguyenPQ, SoenksenLR, DonghiaNM, et al.Wearable materials with embedded synthetic biology sensors for biomolecule detection. Nat Biotechnol, 2021; 39(11):1366–1374; doi: 10.1038/s41587-021-00950-3
101.
HelerR, WrightAV, VuceljaM, et al.Mutations in Cas9 enhance the rate of acquisition of viral spacer sequences during the CRISPR-Cas immune response. Mol Cell, 2017; 65(1):168–175; doi: 10.1016/j.molcel.2016.11.031
102.
RottinghausAG, FerreiroA, FishbeinSRS, et al.Genetically stable CRISPR-based kill switches for engineered microbes. Nat Commun, 2022; 13(1):672–672; doi: 10.1038/s41467-022-28163-5
103.
LeeJW, ChanCTY, SlomovicS, et al.Next-generation biocontainment systems for engineered organisms. Nat Chem Biol, 2018; 14(6):530–537; doi: 10.1038/s41589-018-0056-x
104.
HoffmannSA, DiggansJ, DensmoreD, et al.Safety by design: Biosafety and biosecurity in the age of synthetic genomics. iScience, 2023; 26(3):106165–106165; doi: 10.1016/j.isci.2023.106165
105.
PanM, NetheryMA, Hidalgo-CantabranaC, et al.Comprehensive mining and characterization of CRISPR-Cas systems in Bifidobacterium. Microorganisms, 2020; 8(5):720; doi: 10.3390/microorganisms8050720
