Syst Synth Biol
DOI 10.1007/s11693-008-9020-5

COMMENTARY

Stabilizing synthetic data in the DNA of living organisms
Nozomu Yachie Æ Yoshiaki Ohashi Æ
Masaru Tomita

Received: 19 October 2008 / Revised: 19 November 2008 / Accepted: 25 November 2008
 The Author(s) 2008. This article is published with open access at Springerlink.com

Abstract Data-encoding synthetic DNA, inserted into the
genome of a living organism, is thought to be more robust
than the current media. Because the living genome isduplicated and copied into new generations, one of themerits of using DNA material is long-term data storage
within heritable media. A disadvantage of this approach isthat encoded data can be unexpectedly broken by mutation,
deletion, and insertion of DNA, which occurs naturally
during evolution and prolongation, or laboratory experiments. For this reason, several information theory-based
approaches have been developed as an error check of
broken DNA data in order to achieve data durability. These
approaches cannot efficiently recover badly damaged dataencoding DNA. We recently developed a DNA data-storage approach based on the multiple sequence alignment
method to achieve a high level of data durability. In thispaper, we overview this technology and discuss strategies
for optimal application of this approach.

N. Yachie  Y. Ohashi  M. Tomita
Institute for Advanced Biosciences, Keio University, Tsuruoka
997-0017, Japan
M. Tomitae-mail: mt@sfc.keio.ac.jp
N. Yachie  M. Tomita
Systems Biology Program, Graduate School of Media andGovernance, Keio University, Fujisawa 252-8520, Japane-mail: nzm@sfc.keio.ac.jp
Y. Ohashi (&)  M. Tomita
Biomedical Group, Human Metabolome Technologies, Inc.,
246-2 Mizukami, Kakuganji, Tsuruoka 997-0052, Yamagata,Japane-mail: ohashi@humanmetabolome.com

Keywords DNA data storage  Sequence alignment 
Polymerase chain reaction (PCR)  Error check 
Error correction  Genetically modified organism (GMO)‘‘Increasing performance of CPUs and memories will
be squandered if not matched by a similar performance increase in I/O. While the capacity of Single
Large Expensive Disks (SLED) has grown rapidly,
the performance improvement of SLED has beenmodest. Redundant Arrays of Inexpensive Disks(RAID), based on the magnetic disk technology
developed for personal computers, offers an attractive
alternative to SLED, promising improvements of anorder of magnitude in performance, reliability, power
consumption, and scalability.’’David Patterson, Garth Gibson, and Randy Katz 1988
when they first proposed RAID1Introduction
DNA consists of stable double-stranded long polymers of
only four different nucleotides: adenine (A), cytosine (C),guanine (G) and thymine (T). For living organisms, theprimary role of DNA is long-term and inheritable data
storage of genetic information, which is the set of blueprints to construct cellular components, such as RNA andprotein molecules. The features of a DNA sequence areanalogous to a digital data sequence. For this reason,
recent studies have focused on the behavior of DNA in
1

For quote, see: Patterson et al. (1988)

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N. Yachie et al.

the application of artificial data memory. For example, byinserting a synthetic data-encoding DNA molecule into
the genome of living organisms, the encoded data can be
reproducible and inheritable in the small media vessel ofthe living cell. The data-storage media broadly used
today, including paper, magnetic media, and silicon chips,
are easily damaged by human-caused and spontaneously
occurred accidents, and require constant time-consuming
and laborious maintenance. The properties of DNA provide the potential for realization of long-term data
storage, which can be maintained as archived data for
hundreds to thousands of years (Bancroft et al. 2001; Cox
2001; Smith et al. 2003; Yachie et al. 2007; Wong et al.
2003). Since Clelland et al. (1999) demonstrated theencryption of hidden messages into DNA, the DNA-data
encoding approach has essentially focused on DNA steganography, useful for the identification of geneticallymodified organisms (GMO) by its encoded signature ortrademark in genomic DNA (Arita and Ohashi 2004;
Heider and Barnekow 2007a, b; Heider et al. 2008; Wonget al. 2003). However, the artificial DNA sequences canbe changed or degraded by laboratorial treatment during
the preparation of synthetic data-encoded DNA, and by
genetic mutations, deletions, and insertions in generations
beyond those of the data-stored cells. Furthermore, thereis the possibility of interfusion of sequencing errors whena DNA sequencer retrieves the encoded data. For thesereasons, sophisticated methodology is required to ensure
the robustness and durability of encoded data in order torealize the significant potential for DNA-mediated data
storage for large amounts of important information overan extended period of time.

PCR-based readout and error checkable codes
Most of the data-storage methods based on DNA developed
so far depend on the polymerase chain reaction (PCR) for
encoding and readout of information. In the data-storage
procedure of these methods, data sequence initially isconverted into DNA sequence according to a rule, which isusually a set of encryption keys or ‘codons’ and is like thereverse procedure of the translation of RNA sequence into
the amino acid sequence of protein. Two unique template
DNA regions, corresponding to the forward and reverse
primers for DNA amplification, then are added to the dataencoded region, one at each end (Fig. 1a). According to thesequence design of data-encoded DNA, double-stranded
synthetic DNA is prepared and finally inserted into the junk
region of genomic DNA. For readout of encoded data,
within the mixture of the data-inserted genomic DNA andboth primer sequences, the data-encoded DNA region is
amplified by PCR and decoded by a DNA sequencer.

123

Fig. 1 Commonly used structure of data-stored synthetic DNA (a)and possible breakage points (b). ‘F primer’, forward primer region
for DNA amplification; ‘R primer’, reverse primer region; ‘p’, point
DNA breakage (mutation); ‘d’, deletion; ‘i’, insertion

The genomic DNA segment of the data-encoded region isaltered, as diagrammatically represented in Fig. 1b,
according to mechanisms underlying natural selective pressure in a living system. Moreover, in the data encoding anddecoding procedures, data breakage can occur due to humanerror. Therefore, several approaches based on information
theory have been proposed to check for errors in the DNA
and broken DNA data (Arita 2004; Smith et al. 2003).
The comma code and the alternating code provide visible and regular rules for the nucleotide sequences of thedata-encoded region. The comma code of DNA regularly
repeats punctuation by using a single nucleotide within thedata-encoded sequence and creates an automatic DNA
reading frame (Smith et al. 2003). For example, a partial
data-encoded DNA sequence utilizing the comma code isgiven by
G

G

G

G;

ð1Þ

where each G is the punctuation and A, C, and T are in theother spaces. Similarly, the redundant alternate code
comprises a regularly alternating sequence of two divided
groups of nucleotides, likeRYRYRY;ð2Þ

where R = A or G and Y = C or T. For both codes having
regular rules of repetitive features in DNA sequences,
errors are detectable only when the repetitiveness isostensibly broken; the error check and correction is partially satisfied in each code.
A strategy employing a binary comma-free code for
DNA memory has also been proposed; this code utilizes
the binary comma-free and error-correctable data sequencein the DNA letters (Arita 2004). Although this comma-freecode is robust and the error correction works to correctagainst small-scale damage such as DNA point mutations,this system does not have the capacity to recover broken
data when a large DNA segment is deleted from the dataencoded DNA region.
A major disadvantage of these PCR-based methods isthe susceptibility of the template DNA region for theStabilizing synthetic data

introduction of errors. In the case when the forward orreverse primer regions are broken, there is the potential forthe entire data sequence to become unreadable because of
the failure to support PCR amplification. When this occurs,
there is no code that can protect the template regions.

Fig. 2 Conceptual representation of reversible transformation
for data sequence and DNA
sequence. By using an encoding
function, the data sequence istransformed into DNA sequence.
Encoded data is decodable fromthe DNA sequence by f -1

Concept of alignment-based readout
For more simple, flexible and durable data storage using
DNA material, we recently proposed the alignment-based
method (Yachie et al. 2007), which is independent of the
PCR-based readout procedure but based on the sequencealignment method (Altschul et al. 1990). In this data-storage
method, multiple oligonucleotide sequences encoding thesame data are redundantly inserted into the genome of aliving organism. When the encoded data is retrieved, thecomplete genome sequence, including multiple segments
of inserted DNAs, is first read by a DNA sequencer, andthen the multiple regions encoding the same data aresearched for by sequence alignment. Based on the multiplealignments of sequences of data-encoded regions, errorsthat may have occurred within the encoded data can bechecked and corrected.

Storing multiple-copied data
When multiple segments of the same DNA sequence exist
within a single genome, or even within a single cell, thereis the possibility for problems to occur with the storage ofdata. In particular, the existence of two of the same DNA
sequences within a bacterial genome is known to induce
homologous DNA recombination (Kowalczykowski et al.
1994; Kuzminov 1999). Homologous DNA recombination
subsequently can disturb the growth and development of
data-storage cells or the inserted DNA sequences may beremoved from the genome in early cell division in cell
culture. Therefore, in order to safely encode multiplecopied data sequences into genomic DNA, unique DNA
oligomers encoding the same data according to different
data encryption procedures are required.
Moreover, to realize the potential for this alignmentbased method for storing and recovering multiple-copied
data sequences, specific and universal behaviors are necessary for all the encryption transformations that generateunique DNA oligomers encoding the same data and fortheir corresponding decryption transformations. Here, weoverview every set of reversible transformations of data
encoding into and decoding from the DNA sequence. By
the forward transformation function f, a given data
sequence is encoded into the DNA sequence, and theencoded data can be completely read from the DNA

sequence by the reverse transformation function f -1
(Fig. 2). Let L be the data sequence to be encoded, which ispresented as a string of n letters l1l2…ln (n C 1). The dataencoded DNA sequence D, which is encoded from L as astring of w DNA letters d1d2…dw (w C 1), can be given by
D ¼ f ðLÞ:ð3ÞPutting that the encoded data L in D is decodable byf -1:
L ¼ f 1 ðDÞ;the reversibility of functions f and ff

1ðf ðLÞÞ ¼ L:

ð4Þ
-1is represented byð5Þ

Moreover, both f and f -1 satisfy the associative laws
defined asf Li;j ¼ f Li;k f Lkþ1;j ;
ð6Þ



f 1 Dp;q ¼ f 1 Dp;r f 1 Drþ1;q ;ð7Þ
where the partial segment from li to lj in L can be
represented as Li,j = lili?1…lj (1 B i B j B n) and ksatisfies i B k \ j, and the partial segment from dp to dq
in D can be represented as Dp,q = dpdp?1…dq(1 B p B q B w) and r satisfies p B r \ q. Therefore, if
the data-encoded DNA sequences have been partiallyaltered, the sectional data segments can be decoded fromthe unchanged regions of DNA. We demonstrate an
example procedure of sectional data read from a DNA
sequence, which includes the partial segment of dataencoded DNA and two nonsense DNA sequences
sandwiching it, as follows:f 1 N...Nf Li;j N...N ¼ f 1 ðN. ..NÞLi;j f 1 ðN. ..NÞ; ð8Þ
where f(Li,j) is the partial DNA region of data-encoded
sequence derived from Li,j and N = A or C or G or T.
When the DNA sequence N…Nf(Li,j)N…N is totally
decoded by f -1, the decoded sequence includes the sectional data Li,j.
In order to store the data in the genome of a livingorganism, we used multiple different pairs of reversible
transformation functions, with the behaviors describedabove. In the data-storage procedure, by using the multiple
data-encoding functions, the data sequence is transformed
to multiple different sequences of DNA (Fig. 3a). As

123

N. Yachie et al.

three possible reading frames of three-letter DNA codons
in the DNA sequence to encode the amino acid sequence ofthe protein.

Data retrieval by sequence alignment

Fig. 3 Alignment-based DNA data storage and retrieval method. In
this figure, the data storage and retrieval procedures are explainedusing four pairs of reversible encoding and decoding functions. Whendata L (dark gray box) are encoded into the genome of a livingorganism, four different DNA oligomers D1, D2, D3 and D4 aredesigned by querying the data sequence L to the encoding functions
f1, f2, f3 and f4, respectively (a). Then, the double-stranded DNA
oligomers are inserted into the genome g (b). In order to retrieve theencoded data L, the complete sequence of data-stored genome g’ areinitially decoded by a DNA sequencer, and the DNA sequence of g’ istotally transformed to multiple data sequences G1, G2, G3 and G4 by-1-1
and f-1
the decoding functions f-1
1 , f2 , f3
4 , respectively (c).
According to our defined behaviors of the reversible functions, thesame encoded data L must be included within each partial region of
all the four decoded sequences (dark gray box). The encoded data L isthus retrievable by searching for the same data sequences by sequencealignment

described below, at least two different encodings is fundamental to this method, and at least three different
encodings is optimal to ensure data durability. According
to the design of the DNA sequence, double-stranded DNA
oligomers that include the data-encoded sequences on one
strand are synthesized and then inserted into the intracellular genomic DNA (Fig. 3b).
We previously demonstrated one of the simplest procedures to define the multiple and reversible transformations
from a single data sequence to multiple DNA sequences(Yachie et al. 2007). In this procedure, a set of ‘codons’is prepared that indicates the relationships between all
possible patterns of x letters in a data sequence and theirassigned DNA segments of the same size. There are x
possible reading frames of ‘codons’ according to a one-byone frame shifting of data letters in the target data sequence
region, thus x different DNA sequences can be designed
from the data sequence. This process mimics the DNA
codons used for intracellular protein synthesis. There are123

In the data retrieval procedure, the complete genomic
sequence harboring multiple synthetic DNA oligomers isfully sequenced by using a DNA sequencer, and then, thetotal sequence of genomic DNA is decompressed to multiple data sequences by using the decoding functions thatare paired with the respective encoding functions used fordata storage (Fig. 3c). The majority of regions of therespective long sequences decoded at the genomic level arenonsense, and they are mostly different from each other,because the different decoding functions are performed fora single genomic sequence. According to Eq. 8, the data
sequence encoded in each synthetic DNA region of the
genome accurately appears within the partial region ofcertain long data sequence transformed from the genomic
sequence by the decoding function, which is the reverse of
the encoding function used for the design of the respective
region. Therefore, if all the data-encoded regions are notbroken by DNA errors, every long decoded sequence must
include the same unique data sequence in its partial region(Fig. 3c). By progressing through the series of data handling procedures, it is possible to search for and finally readout the same data sequence of encoded data by using thesequence alignment function.

Error check and correction by sequence alignment
At the end of the readout procedure, data durability can befurther enhanced by taking advantage of the sequencealignment method. Because of the associative rules in theencoding and decoding functions defined in Eqs. 6 and 7,
DNA mutations, deletions, and insertions of synthetic DNA
are the causal factors of point breakage of data sequence,
sectional data deletion, and nonsense data insertion,
respectively. The types and positions of DNA errors are
directly related to the errors in the decompressed data
sequence. Therefore, according to this rule, even if someDNA errors are randomly contained in the multiple synthetic
regions of data-stored genomic DNA, we can find the multiple-copied but partially broken data sequences by searchingfor similar data sequences in the respective long data
sequences decoded from the genome, and the mismatches ofaligned data sequences can identify the position of broken
data-encoded sequences. Accordingly, the multiple-copied
data sequences encoded within the different features of DNA
sequences can fulfill an error check function.

Stabilizing synthetic data

Moreover, when more than three synthetic DNA oligomers are used for data storage, there is a high potential forcorrection of the identified data breakage points (Fig. 4).
The natural DNA error rate in the genome of a livingorganism or in laboratorial experiments is not as high as theerror rate associated with the insertion of artificial DNA
sequences. Thus, it is extremely rare for the occurrence ofboth sources of errors at the same position within themultiple data-encoded regions. When the letters at a same
position of multiple alignments of decoded data sequences
are different, it is likely that the minority letters have arisen
from data breakages. In this case, the broken data can bealtered according to the majority decision rule. Consequently, for sequence alignment-based DNA data storage,
data breakages can be identified and corrected by comparison with the same positions of other aligned sequencesof decoded data.
When the number of decompressed data sequences fromthe synthetic DNA regions is two, the majority decision
rule cannot be justified, and only the error check can be
performed. At least three synthetic DNAs are necessary forerror correction of broken data, and the cost of higher
redundancy must be paid to achieve more robust durabilityof stored data, leading to a trade-off relationship between
data durability and the copy number of encoded data. Moredurable data storage with stronger error correction can beachieved by the insertion of more synthetic DNA into the
genome. This trade-off appears to favor data durability. By
performing a computational simulation of data retrieval
using this alignment-based method, we previously suggested that when the data storage is conducted by foursynthetic DNAs and when as much as 15% of the data-

Fig. 4 Error correction of decoded sequences by sequence alignment.
Encoded data surrounding regions of G1, G2, G3 and G4 (for detail,see footnote to Fig. 3) are represented with examples of their possible
data breakage points. Dark gray boxes indicate data-encoding regions.
‘p’, point data breakage (or small breakage); ‘d’, sectional datadeletion; ‘i’, sectional data insertion. According to the multiplealignment of decoded data sequences, each data breakage point can be
identified and corrected by comparison with other multiple sequences,and the recovered data sequence L’ can be retrieved

stored genome is randomly mutated or deleted, the recovery rate is over 99% for data rescue (Yachie et al. 2007).
According to combinatorial theory-based logic, the multiplication of synthetic DNA can improve data durability at
an exponential rate.

Cost and practical realization
For data storage into magnetic media, especially hard disks,
redundant arrays of inexpensive disks (RAID) are usedfrequently (Patterson et al. 1988). The concept of RAID is topromote redundantly encoded data within a larger volume of
inexpensive memory storage in order to secure data durability. However, when RAID technology was firstly
proposed in 1988, the cost of memory storage was highwhen compared with the current technology, and the RAID
concept of ‘inexpensive disks’ was considered novel.
The DNA data-storage methods prior to RAID in thecomputational technology field with PCR-based data
retrieval process were associated with restraints including
the high cost of DNA oligomer synthesis and DNA
sequencing and the size limitation of artificial DNA that
can insert into the genome of a living organism. The PCRbased methods store nonredundant data into one shortsynthetic DNA fragment along with the template DNA
regions at each end. The cost of sequencing the partial
data-encoded genomic region amplified by PCR is markedly lower than the cost of complete genome sequencing.
By comparison, the alignment-based method requires theredundant encoding of data into multiple synthetic DNA
molecules and sequencing at the genomic level. However,DNA sequencing is becoming less time-consuming and theassociated cost of DNA synthesis and sequencing isdecreasing.
There are several hundred complete sequences ofchromosomal DNA from eukaryotes, prokaryotes, and archaea currently available via the public databases (Liolios
et al. 2008). This area of research has fuelled a growing
demand for higher speeds of DNA sequencing and lower
cost and has boosted the emergence of new technologies(Church 2006; Hall 2007). For example, the recent development of sequencing technology utilizing emulsion PCR(Margulies et al. 2005; Shendure et al. 2005) has dramatically increased the speed of sequencing. Other new
technologies are in development, and in the near future,
new machines with the capacity to read one million bases
per second at a low cost will be available (Bonetta 2006).
In the alignment-based method, following the design ofmultiple different DNA sequences encoding the same data,
we can add the template DNA regions to each end ofrespective sequences and insert these into the living genome. Complete genome sequencing is unnecessary with123

N. Yachie et al.

this approach, because the partial genomic regions ofrespective synthetic DNA can be amplified by PCR andsequenced, and the multiple alignments of these sequences
can check and correct errors. However, as explained above,
PCR-based data retrieval is associated with the disadvantage of introducing breakage points in the template DNA
region, and the readout procedure depends on appropriate
or error-proof PCR amplification. Therefore, although data
storage durability can be improved to a degree by multiple
PCR amplifications and further by alignment of data
sequences only from the successfully amplified DNAs, ourproposed method fully utilizes the ability of the combinatorial and compositive error supplements by the multiplealignment of all the multiple-copied data, thus the data
durability achieved by sequencing at the whole genomic
level is beyond comparison. One of better strategies is that,with the combination of PCR-based readout, the complete
genome sequencing is performed when the multiple readouts by PCR are failed. Optimal data durability can be
guaranteed only by complete genome sequencing independent of PCR-based readout.
Although the length of synthetic DNA sequences that canbe inserted into the genome of a living organism has been
considered to be limited (Cox 2001), our method expends
multiple and redundant synthetic DNA oligomers to copyand-paste the data for storage. The upper limit of the total
size of synthetic DNAs that can be inserted into the genomeof a living organism has been increased remarkably by thedevelopment of megacloning technologies demonstrated in
the transportation of whole bacterial genomes (Itaya et al.
2005, 2008). Notably, the entire 16.3-Kb mouse mitochondrial genome (Itaya et al. 2008), the 134.5-Kb rice
chloroplast genome (Itaya et al. 2008), and the 3.5-Mb
cyanobacterium genome (Itaya et al. 2005) have been
inserted into the 4.2-Mb genome of Bacillus subtilis
employed as a mother vessel. B. subtilis has the ability toform a tough and protective endospore, which allows thisorganism to survive extreme environmental conditions.
Surprisingly, previous studies isolated strains of Bacillus
species from an extinct bee trapped in 25–30 million-yearold amber (Cano and Borucki 1995) and from a brine
inclusion within a 250 million-year-old salt crystal of thePermian Period (Vreeland et al. 2000). The development of
megacloning technology utilizing B. subtilis has provided
the potential for large-size and long-term DNA data storage.
In this paper, we overviewed the application of reversible transformations for data encoding and decoding for
DNA data storage based on sequence alignment andcomplete genome sequencing. Because the data-encoding
procedure for DNA requires no code and only the application of the associative rule, other codes, including thecomma, alternate, and comma-free codes, can be used with
our method. For example, the Huffman code is an123

economical code, in which is based on the varied frequencies at which English letters are used in the Englishspeaking sphere. The most frequent letter is ‘e’, with afrequency of 12.7%, and the least frequent letters are ‘q’
and ‘z’, both of which have a use frequency of 0.1% (Smithet al. 2003). According to this information, the Huffman
code assigns a shorter ‘codon’ of nucleotide bases for more
frequently used characters, and vice versa. Sophisticatedcodon design is necessary for the Huffman code: once thedecoding procedure has commenced from the beginning of
data-encoded DNA, there must be only one way to
decompress the letters from the sequence of ‘codons’. For
example, if the shortest DNA codon T is defined for the
English letter ‘e’, no other longer codon can start with T(Smith et al. 2003). Similarly, in the alignment-based
method, the encoded data within the synthetic DNAs canbe short and durable, because of the versatile ability to be
combined with previously proposed codes.

Conclusion
Similar to the general concept for magnetic disk drives, thealignment-based DNA data-storage method employs theredundant copy-and-paste-and-paste concept for storingdata to realize the long-term DNA data storage of large
amounts of important information in the small media vesselof the living cell. Although this methodology requires theuse of redundant synthetic DNAs encoding the same data
and whole-genome sequencing of the data-stored cell athigh cost, research demands are promoting the development of new megacloning technology and high-speed DNA
sequencing at a lower cost. For this reason, our proposed
simple and flexible strategy may offer a practical solution
for highly durable data storage in DNA.
Acknowledgments We are grateful to Kazuhide Sekiyama andJunichi Sugahara for helpful discussions and Dr. Kazuharu Arakawa
for useful suggestions in the preparation of the manuscript. This study
was supported by research funds from Yamagata Prefecture andTsuruoka City to Keio University and a grant from the Japan Society
for the Promotion of Science (JSPS) to N. Y.
Open Access This article is distributed under the terms of theCreative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any
medium, provided the original author(s) and source are credited.

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