Patent Publication Number: US-2019194738-A1

Title: Key-value store that harnesses live micro-organisms to store and retrieve digital information

Description:
BACKGROUND 
     1. Field 
     This invention relates to a method of information storage and retrieval that harnesses biological processes in live micro-organisms and genetic engineering to store and retrieve digital data. 
     2. Description of the Related Art 
     Humanity has generated more archived data in the past two years than in all of preceding history, and soon, hard drives may not be able to store it all. DNA sequences can be a potential medium for digital storage. DNA storage methods [1] store digital data in the base sequence of the DNA. To retrieve data, DNA is sequenced to obtain the base sequence, and the base pairs are decoded to yield digital data. DNA storage is significant for several reasons. DNA is the highest-density large-scale data storage scheme ever invented −215 petabytes can be stored in a single gram of DNA [1]. It is remarkably easy to reliably duplicate DNA in large quantities through methods like PCR [1]. DNA can survive in cold, dry, or dark conditions for thousands of years. Arguably most importantly, DNA will not become obsolete as long as there are DNA-based living organisms. 
     There are two radically different types of DNA storage methods: in-vitro DNA storage, and in-vivo DNA storage. 
     In-vitro (i.e. taking place in a test-tube, culture dish or elsewhere outside of any living organism) DNA storage methods use artificial DNA made using commercially available oligonucleotide synthesis machines for storage and DNA sequencing machines for retrieval of base sequence in the artificial DNA. These methods use naked synthetic DNA strands, typically floating within tubes of liquid. Several in-vitro DNA storage methods have been reported recently [2][3][4][5]. However, in-vitro DNA storage is expensive ($7K to store 2 MB, and $2K to read the stored data [3]) but advances in oligonucleotide synthesis and gene sequencing are expected to bring 10,000-fold reduction in cost. Also, almost all known in-vitro DNA storage methods cannot selectively retrieve subsets of stored data, which analytics algorithms require to mine insights from big data. To read even a single byte from the DNA storage, the entire DNA pool of strands must be sequenced and decoded. To address this limitation, researchers at University of Washington reported a method [5] in April 2016 to sequence and decode only a subset of the synthetic DNA to retrieve any data set out of several data sets stored in the DNA storage system. 
     In sharp contrast to in-vitro methods, in-vivo (i.e. taking place inside a living organism) DNA storage methods harness live micro-organisms, and these methods can dramatically lower the costs of storage. Unlike naked synthetic DNA strands in a test tube, live micro-organisms multiply. Therefore, the data in these organisms does not degrade, and the organisms pass on this customized information to the next generation, making this form of biological data storage extremely efficient and powerful. However, storing data in live micro-organisms requires radically different techniques than schemes used by in-vitro stores. This is because the artificial DNA sequences with data may not be stable in-vivo, and such sequences may adversely interfere with the normal genetic and biological mechanisms in live micro-organisms. In July 2017, researchers at Harvard University exploited the CRISPR-based adaptive-immunity mechanism in prokaryotes to store practical amounts of data in genomes of living bacteria [6]. To retrieve data, they extract DNA from different bacteria in the population and sequence their entire genomes. Nucleotide sequence obtained from DNA sequencing are decoded to yield the digital information stored within the genome of living bacteria. 
     Our invention applies to in-vivo storage and retrieval of digital data. 
     Unfortunately, all prior in-vivo DNA storage methods suffer from a serious drawback: they all have the disadvantage that the whole DNA in the population of the living micro-organisms has to be sequenced to retrieve one of several data sets that were previously stored in the population. In other words, none of the prior in-vivo methods provide random-access (i.e. selective access) to just one of the many data sets encoded in the population. A mechanism to directly access and retrieve a select subset of data remarkably improves the data retrieval time in in-vivo methods. 
     Unlike all prior in-vivo DNA storage methods, our DNA digital storage invention discloses a radically new method to store digital data in live micro-organisms, and our unique storage method enables a new retrieval method that selectively retrieves random subsets of the stored data. 
     SUMMARY 
     As our invention, we propose a radically new method to store digital data as DNA in live micro-organisms, and our unique storage method enables a new retrieval method that selectively retrieves random subsets of the data stored in live micro-organisms. Our method can be used to store and retrieve a variety of digital data like text, images, video and audio data. 
     Storing digital data in live micro-organisms, as proposed in our invention, has several advantages. Unlike methods that store digital data as base sequence in naked synthetic DNA strands in a test tube, live micro-organisms multiply. Therefore, the data in these organisms does not degrade, and the organisms pass on this customized information to the next generation, making this form of biological data storage extremely efficient and powerful. These advantages also dramatically lower the costs of storage. 
     Unlike all prior methods that harness live micro-organisms to store data, our invention discloses a new method to selectively retrieve subsets of the data stored in live micro-organisms. This is in sharp contrast to prior methods that require the retrieval of the entire data stored in the population of the live micro-organisms, even if only a subset of the stored data is required. Such selective retrieval of only the desired subset of data not only shortens the retrieval time by orders of magnitude, but it is also a fundamental capability that is necessary for big data analytics to mine valuable insights from the large amounts of data that can be stored in live micro-organisms. 
     We envision the use of our invention by the world&#39;s most wealthy and powerful corporations like Facebook, Apple, Google, and the US government. They are all making astounding investments in magnetic digital storage, but humanity has generated more archived data in the past two years than in all of preceding history, and soon, hard drives may not be able to store it all. Acknowledging this inevitability, these corporations are all now investing in the prospect of storing information in digital DNA stores. 
     These and other features and advantages will become apparent from the following detailed description of illustrative embodiments thereof, which is to be read in connection with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The disclosure will provide details in the following description of preferred embodiments with reference to the following figures wherein: 
         FIG. 1  shows the overall block diagram of the proposed system to store and selectively retrieve digital information in live micro-organisms. 
         FIG. 2  shows the preferred embodiment of a process to store digital information as key-value pairs in a population of live micro-organisms. 
         FIG. 3  shows the preferred embodiment of a process to retrieve the value in a key-value pair, upon presentation of the key. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Key-value store: Digital information is represented as a collection of records, which in turn can have many different fields within them. Each record is a value, and these records are stored and retrieved using a key that uniquely identifies the record. A key-value pair consists of a record and a key that uniquely identifies the record. A key-value store is a data storage scheme for storing and retrieving key-value pairs. Given a key, a key-value store can quickly retrieve the value. This type of data structure is also known as dictionary or hash. 
     Overview of proposed DNA digital store:  FIG. 1  shows an overview of the proposed DNA digital store. Given a key-value pair  110 , the key is mapped to a unique gene that expresses a fluorescent protein (GFP). The mapping of keys to GFPs is maintained in a two-column table  120 . This mapping ensures that every key is mapped to a unique GFP. The combination of GFP, key and value  130  is presented to the GFP-Store  140 , which stores the key-value pair in live micro-organisms. To retrieve information, a key  150  is given as input to the digital store. The key is mapped to its corresponding GFP by using the two-column table  160  that contains the mapping of keys to GFPs. Subsequently, the GFP and the key  170  are used by the GFP-Retrieve method  180  to retrieve the key-value  190  pair from live micro-organisms. 
     Storage method:  FIG. 2  shows the procedure to store a key-value pair. Given a combination of GFP, key and value  210 , the encoding method  220  encodes the GFP, key and value into three separate base-pair sequences. These three base-pair sequences are synthesized  230  into three oligonucleotide chains, or artificial DNA strands, which are subsequently included in the synthesis  240  of a recombinant DNA plasmid. A plurality of recombinant plasmids is incorporated  250  into a population of live micro-organisms that do not have a recombinant DNA plasmid, or any gene that expresses a fluorescent protein. Since only a few of the live micro-organisms typically absorb the recombinant DNA plasmids, such organisms are isolated  260  from the rest of the micro-organisms that have not absorbed the plasmids. Live micro-organisms with the recombinant DNA plasmid in their cells are stored in a common pool  270  with micro-organisms that store other key-value pairs. 
     Encoding data as base-pairs: Digital data is represented as a sequence of two symbols 0 and 1. Naturally occurring DNA consists of four types of nucleotides: adenine (A), thymine (T), cytosine (C) and guanine (G). The two symbols 0 and 1 can be mapped to the four symbols A, T, C and G in many ways. As an example, the symbol 0 can be mapped to the combination AT and the symbol 1 can be mapped to the combination GC. Then, a binary sequence like 101 can be represented as a nucleotide sequence GCATGC. A comparison of various encoding methods that have been used by DNA stores is available in [7]. Methods that encode digital data as a sequence of base-pairs typically trade off encoding density for more reliable manufacturing of oligonucleotides. It is also common to use error-correction schemes, and different nucleotide sequences to encode the same data, because such redundancy helps offset errors that are invariably introduced in oligonucleotide synthesis and DNA sequencing. Data could be lost during evolution, and a preferred encoding for storage of data in live micro-organisms is described in [6]. 
     Manufacture of base-pairs as artificial DNA: Rapid advances in solid phase-based synthesis technologies have made automated high-throughput custom oligonucleotide chains possible [8]. Oligonucleotide chains are made by using a DNA synthesizer, which is a computer-controlled reagent delivery system. The first base is attached to a solid support, usually a glass or polystyrene bead, and the first base anchors the growing DNA chain of bases in the reaction column. Appropriate nucleotides are sequentially coupled to the growing oligonucleotide chain in the order required by the base-pair sequence. Two points are worth noting about oligonucleotide synthesis. There is a practical limit on the length of oligonucleotide chain (about 200 nucleotides) because the number of errors in assembling the chain increase with the length of the chain. Coupling efficiency, a measure of how efficiently the DNA synthesizer is adding new bases to the growing DNA chain, is around 99%. This means that DNA synthesizer makes mistakes as often as 1 in every 100 nucleotides. To account for these errors, methods that encode digital data as base-pairs introduce significant amount of redundancy in encoding. 
     Synthesis of recombinant DNA plasmid: Plasmids are small circular double-stranded pieces of DNA that replicate independently from the chromosomal DNA of the host. Natural plasmids are mostly found in prokaryotes, and range in size from a few thousand base pairs to more than 100,000 base pairs. Like the host-cell chromosomal DNA, plasmid DNA is duplicated before every cell division and a copy is segregated to each daughter cell. This assures continued propagation of the plasmid through successive generations of the host cell. 
     Plasmids are also routinely synthesized in the laboratory for DNA cloning [8], where foreign DNA is injected into live micro-organisms for duplication. Artificial plasmids typically include recombinant DNA, which is any DNA molecule formed by joining DNA fragments from different sources. The ease of modifying plasmids and the ability of plasmids to self-replicate within a cell make them attractive tools for biotechnology scientists and genetic engineers. To simplify working with artificial plasmids, their size is typically restricted to 3000 base pairs. In the present invention, we engineer the design of the plasmid to achieve the following objectives, and we illustrate ways to achieve these objectives: 
     a) Duplication: After a plasmid is absorbed into a live micro-organism, replication of the plasmid (along with replication of the host cell) is essential to assure propagation of the key-value pair embedded in the plasmid through successive generations of the host cell. This can be achieved as follows. Every plasmid has an origin of replication (ORI), which is a specific DNA sequence of 50-100 base pairs that must be present in a plasmid for it to replicate. Host-cell enzymes bind to ORI, initiating replication of the circular plasmid. After DNA replication is initiated at ORI, it continues around the circular plasmid regardless of the nucleotide sequence. Therefore, any DNA sequence inserted into such a plasmid is replicated along with the rest of the plasmid DNA, and this property is exploited by the present invention to store and assure continued propagation through successive generations of the host cell. 
     b) Isolation: After plasmids are absorbed into a population of live micro-organisms, it is necessary to separate micro-organisms that have absorbed a plasmid from the rest of the population. This can be achieved as follows. The selectable marker region of a plasmid allows placement of one or more selection markers (they are also specific DNA sequences). These markers enable isolation of plasmid-containing live micro-organisms. As an example, if we add an antibiotic resistance gene [10] in the selectable marker region, then live micro-organisms that have absorbed the plasmid will express this gene and resist antibiotics, while the rest die when exposed to the antibiotic. 
     c) Cell-sortability: After a unique plasmid is created for every key-value pair, micro-organisms that absorb plasmids embedded with key-value pairs co-exist in a common pool. However, during the retrieval method, it is necessary to quickly separate live micro-organisms that contain a specific key-value pair that corresponds to the given retrieval key. To enable cell-sorting, we engineer the plasmid to include a cell-sorting metric that a high-speed fluorescence activated cell sorter can use to classify and separate micro-organisms. As an example of a cell-sorting metric, in the present invention every key is mapped to a unique gene responsible for synthesis of a specific fluorescent protein, and the said gene is inserted into the plasmid. After the said plasmid is absorbed by live micro-organisms, the expression of the said gene results in a fluorescent protein. A fluorescence activated cell sorter detects the said fluorescent protein, and isolates the live micro-organisms that have the said fluorescent protein. Insertion of genes that express proteins into a plasmid requires additional care. A plasmid has multiple sites where new DNA sequences can be inserted. These are the restriction sites, which are also specific DNA sequences, that allow for easy insertion of foreign DNA. Molecular scissors called restriction enzymes are used to cut plasmids open at the restriction sites, and new DNA sequences are inserted into the cut plasmid. The resulting DNA fragments from different sources are joined together by DNA ligase. This allows scientists to cut and paste components of plasmid together. The restriction sites are often downstream from a promoter, which is yet another specific DNA sequence of about 100 to a 1000 base pairs. Promoter [10] is important because it drives the transcription of genes inserted at the restriction sites. The sequence of the promoter region controls the binding of the RNA polymerase and transcription factors, and promoters play a large role in determining where and when a gene of interest will be expressed. Promoter also determines which cell types the gene is expressed in and how much recombinant protein is produced by the gene (host transcription machinery varies across different types of live micro-organisms). As an illustration, to store a key-value pair in a plasmid, the said key&#39;s gene for fluorescent protein can be inserted at a restriction site that is downstream from the promoter, and the gene expression can be controlled by appropriate choice of the promoter sequence. 
     d) Payload insertion: Artificial DNA sequences corresponding to a key and value are also inserted at the restriction sites, but transcription of these sequences into proteins is inhibited through promoter regulation [10]. 
     e) Amplification: After a cell-sorter isolates live micro-organisms that contain a specific key-value pair, DNA sequencing determines the sequence of base-pairs in the recombinant DNA plasmid. Prior to DNA sequencing, PCR is a common technique that is used in the laboratory to make millions of copies of (i.e. amplify) a particular section of DNA, starting from a very small amount of DNA. However, short stretches of DNA called the primers are necessary to initiate the PCR reaction, and two primers have to flank the section of DNA to be amplified on either side. Therefore, during the synthesis of the recombinant DNA plasmid, two primers are added to flank the payload (key-value pair) on either side. 
     Electroporation into live micro-organisms: Transformation process facilitates absorption of recombinant DNA plasmids by live micro-organisms [12, 13]. Transformation of bacteria with plasmids is important because bacteria are used as the means for both storing and replicating plasmids. Therefore, nearly all artificial plasmids routinely carry a bacterial origin of replication. Also, specific treatments have been discovered that make bacteria more susceptible to either chemical or electrical based transformation, and such treatments generate ‘competent cells.’ Many companies sell competent cells, which come frozen and are prepared for optimal transformation efficiencies upon thawing. The two popular methods of bacterial transformation are heat shock of chemically prepared competent cells (chemical transformation), and electroporation of competent cells. Chemically competent cells absorb small plasmids fast and are easy to use, but such cells are less efficient at taking up larger plasmids. To transform large plasmids with key-value pairs, it is better to use electro-competent cells. Instead of relying on the heat-shock to cause the cells to take up the recombinant DNA plasmid, an electro-magnetic field is applied to the cell/DNA mixture to induce membrane permeability [14], and such electroporation is an order of magnitude more efficient than chemical transformation. 
     Isolation of micro-organisms that absorbed the plasmid: Isolation is easily accomplished by adding an antibiotic resistance gene [11] in the selectable marker region of the recombinant DNA plasmid. Then, live micro-organisms that have absorbed the plasmid will express this gene and exhibit resistance to antibiotics, while the rest die when exposed to the antibiotic. 
     Retrieval method:  FIG. 3  shows the procedure  300  to retrieve a key-value pair. Given a combination of the retrieval key and its GFP  310 , a sample is taken  320  from the storage pool that has a population of live micro-organisms with different key-value pairs. A fluorescence activated cell sorter  330  separates live micro-organisms in the sample that have expressed the protein corresponding to the GFP gene. Subsequently, recombinant plasmid DNA is extracted from these micro-organisms, and DNA sequencing  340  determines the base-pair sequence in the recombinant DNA. This base pair sequence is then decoded  350  to yield the value (digital data)  360  that corresponds to the retrieval key. 
     Cell sorting: Micro-organisms that absorbed plasmids embedded with key-value pairs co-exist in a common pool. However, during the retrieval method, it is necessary to quickly separate live micro-organisms that contain a specific key-value pair that corresponds to the given retrieval key. Since the plasmids in the micro-organisms are expressing fluorescent proteins, it is possible to separate the micro-organisms with a desired fluorescent protein by using cell sorters. Fluorescence-activated cell sorting (FACS) [16] is a specialized type of flow cytometry [15]. It provides a fast, objective and quantitative recording of fluorescent signals from individual cells. This enables sorting a heterogeneous mixture of biological cells into two or more containers, one cell at a time, based upon the specific light scattering and fluorescent characteristics of each living cell. Cell sorters can also sort based on one or more (cell-sortability) properties of the cell like cell size, complexity, phenotype or structure, and magnetic or electrical characteristics. This capability can be exploited by designing the recombinant DNA plasmid to include suitable cell-sortability metrics. 
     DNA sequencing of recombinant DNA plasmid: Many methods have been developed to purify plasmid DNA from bacteria [17]. These methods involve three steps: growth of the bacterial culture, harvesting and lysis of the bacteria, and purification of plasmid DNA. DNA sequencing determines the sequence of base-pairs in the purified recombinant DNA plasmid. Prior to DNA sequencing, PCR is a is used in the laboratory to make millions of copies of (i.e. amplify) of the payload section (key-value pair) of the recombinant DNA plasmid, starting from a very small amount of DNA. The primers necessary to initiate the PCR reaction already flank the section of DNA to be amplified on either side (this was done during the synthesis of the recombinant DNA plasmid). After PCR, known methods [18] can be employed to sequence the payload section of the recombinant DNA. 
     Decoding of base-pairs of payload section to reveal value: Decoding of base-pairs depends on the encoding used during the storage method. As an example, if the symbol 0 was mapped to the combination AT and the symbol 1 was mapped to the combination GC during encoding, then a base pair sequence GCATGC is decoded as the binary sequence 101. 
     Having described preferred embodiments of a system and method for an in-vivo digital DNA store that stores data in live micro-organisms, and retrieves selective subsets of stored data (which are intended to be illustrative and not limiting), it is noted that modifications and variations can be made by persons skilled in the art in light of the above teachings. It is therefore to be understood that changes may be made in the particular embodiments disclosed which are within the scope of the invention as outlined by the appended claims. Having thus described aspects of the invention, with the details and particularity required by the patent laws, what is claimed and desired protected by Letters Patent is set forth in the appended claims.