Patent Application
20230258623
The present disclosure relates generally to biotechnology, biochemistry, biophysics, chemistry, bioelectronics and computer sciences. More specifically, the present disclosure relates to the use of biologically inspired cells to perform various operations.
Computers were developed to perform algorithmic and logical functions, such as complex calculations. Computers have electrical switches corresponding to electrical inputs arranged in binary code. The inputs and corresponding code are programmed to receive and process the inputs according to defined algorithms, and to generate a desired output.
Computers have been used to monitor conditions and perform mechanical and electrical functions. Computers can be coupled to sensors to collect data from various sources, such as environmental conditions. In some cases, the sensors may be coupled to chemical matter to sense chemical parameters, such as composition, or biological matter to sense biological parameters. The data collected from the sensors may be stored in memories, and processed by the processing units. The processed data may be used to make decisions, and/or activate equipment to perform functions. Computers may be coupled to mechanical or electrical equipment to activate such equipment to operate according to programmed processes.
Despite advances in computer technology, there remains a need for devices capable of efficiently performing complex operations, such as autonomous functions. The present disclosure seeks to fill such needs.
In at least one aspect, the disclosure relates to a synthetic, cognitive cell for automatically generating an output based on an environmental input. The cognitive cell comprises an operator comprising chemical agents, and a coded chemical comprising polymers. Each of the polymers comprises a sequence of affinity blocks of molecular groups arranged in predetermined patterns to define a multi-layered base code. Each of the affinity blocks comprises a monomer with a sidechain, the sidechains having affinities to each other. At least a portion of the affinity blocks form a gate switch defining a bridge between the environmental inputs and the chemical agent whereby, upon exposure to the environmental inputs, the gate switches trigger the chemical agent to perform an operation. The coded chemical and at least one chemical agent are contained within a natural or synthetic membrane.
In at least one aspect, the disclosure relates to a synthetic, cognitive system for automatically generating an output based on an environmental input. The system includes at least one environmental input and synthetic cognitive cell. Each of the synthetic cognitive cell comprises an operator comprising chemical agents, and a coded chemical comprising polymers. Each of the polymers comprises a sequence of affinity blocks of molecular groups arranged in predetermined patterns to define a multi-layered base code. Each of the affinity blocks comprises a monomer with a sidechain, the sidechains having affinities to each other. At least a portion of the affinity blocks form a gate switch defining a bridge between the environmental inputs and the chemical agent whereby, upon exposure to the environmental inputs, the gate switches trigger the chemical agent to perform an operation. The coded chemical and at least one chemical agent are contained within a natural or synthetic membrane.
Finally, in another aspect, the disclosure relates to a method of making a synthetic cognitive cell for automatically generating an output based on an environmental input. The method comprises providing an operator comprising chemical agents; providing polymers comprising monomers; and forming a coded chemical. The forming involves selectively forming affinity blocks by modifying the monomers with sidechains (the sidechains having an affinity to each other), and arranging a sequence of the affinity blocks of the polymer into predetermined patterns of molecular groups defining a multi-layered base code and into gate switches defining a bridge between the environmental input and the chemical agent such that, on exposure to the environmental input, chemical reactions between the chemical agent and the coded chemical perform an operation. The method further comprises mixing the operator with the coded chemical to form a coded mixture, and applying the coded mixture to a membrane.
So that the above recited features and advantages of the present disclosure can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to the embodiments thereof that are illustrated in the appended drawings. The appended drawings illustrate example embodiments and are, therefore, not to be considered limiting of its scope. The figures are not necessarily to scale and certain features, and certain views of the figures may be shown exaggerated in scale or in schematic in the interest of clarity and conciseness.
Herein incorporated by reference is the sequence listing filed with the USPTO as 1093-218 CONT.xml which was created on Apr. 19, 2023, and the size is 4,852 bytes.
The description that follows includes exemplary apparatus, methods, techniques, and/or instruction sequences that embody techniques of the present subject matter. However, it is understood that the described embodiments may be practiced without these specific details.
The disclosure relates to cognitive techniques (e.g., cognitive cell, system and method) for generating an output based on an environmental input (e.g., sunlight, pH, temperature, etc.). A cognitive cell may be chemically coded to automatically respond to the environmental inputs and to trigger a chemical reaction that generates the desired output. The coded chemical (e.g., plasmid) may comprise affinity blocks arranged in predetermined patterns to define a base code comprising gate switches (e.g., clusters of molecules) capable of storing information in multiple layers to connected the coded chemicals to their environmental factors. These patterns may be pre-defined to store large volumes of information that are automatically triggered to provide an outcome upon receipt of a known environmental input in a multi-layered configuration that provides iterative processing across multiple directions to generate the predetermined, corresponding outcome, thereby reducing processing time.
The cognitive cell provides a cognitive chemistry platform with a molecular structure capable of embedding matrices of information in the chemicals. The information may be transduced by molecules using gate switches that act as molecular logic gates. The platform uses molecular machinery in the form of clusters of engineered coupled chemical reactions. The chemical reactions may be pre-engineered with recognition capacity over its environmental conditions. The cognitive cell may apply molecular sensors and coupling of environmental signals with internal logical operations of the cognitive cell using the logic gate switches.
The cognitive cells may be chemically and/or biologically programmed to correlate the coded chemicals in the cell to respond to the selected environmental inputs and cause reactions which generate the predetermined outputs. Such programming may employ single or multi-layered configurations of the gate switches capable of triggering the chemical agent to perform complex operations, such as generating energy (e.g., power), growing (e.g., regenerating, healing) cells, and/or performing logic (e.g., complex calculations), etc.
The cognitive techniques described herein seek to provide one or more of the following, among others: a renewable energy source, efficient processing, communication between cells and/or subjects, complex (e.g., multi-level) calculations, chemical and/or biological programming capabilities, natural and/or synthetic cell design, a commercially efficient autonomous polymer generator, a mechanism to convert energy (e.g., solar) directly to a desirable form (e.g., polymer or a desired structure with a highly specific geometrical architecture), and/or other capabilities based on needs of the system or in response to special environmental signals/conditions.
As shown by the operation 104 of
Part, or all of, the cognitive cell 102 may be natural or synthetic. The cognitive cell 102 may include a membrane 109 with a buffer 110 therein to support chemicals to perform the chemical reactions. The membrane 109 may be permeable, semipermeable, or impermeable depending on the desired application. For example, the membrane 109 may be made of cellulose to allow fluid flow therethrough. The buffer 110 may be a fluid (e.g., water phosphate buffer with a pH of about 7.4, etc.) housed in the membrane 109 to support the chemicals therein.
The cognitive cell 102 may include a variety of chemicals designed to respond to certain of the inputs 108 and generate the desired output 106. As shown in
The coded chemicals 111 may be a natural or synthetic chemical or material with a predetermined molecular weight and physically observable mass usable for coding. The coded chemical 111, such as a polymer, and may comprise and/or be formed from, for example, deoxyribonucleic acid (DNA), graphene, aptamer, peptide, polysaccharide, protein, enzyme sensitive nanopolymer, synthetic nanopolymer, synthetic polysaccharide, polyethylene glycol, silica, and/or other chemicals.
The coded chemical 111 may comprise any programmable chemical and/or materials such as synthetic or/and natural polymers, made of a sequence of monomelic subunits, that are engineered or modified to store/embed codes (information) in chemical/electrostatic/hydrogen/polar and non-polar bonds between the affinity blocks in their molecular subunits, and/or in the pattern and sequence of their affinity blocks (e.g., as a sequence of alphabetic and digit characters in a language or coding system respectively). The coded chemicals may be engineered to be multifunctional (e.g., may be engineered to function as coding and energy-producing units at the same time), as well as being self-regulating in response to their environmental stimuli by direct connection to a wide range of logic gates which are connected to the environmental factors. For example, a logic gate may be responsive to a wide range of environmental stimuli including chemical, mechanical, physical, optical, electromagnetic, etc.
The coded chemical (or coded material) 111 may comprise monomers modified with sidechains to form affinity blocks 114. Examples of sidechains may include simple chemical groups such as hydroxyl, amino, carboxyl, carbonyl, sulfide, or they may include more complex groups such as natural or synthetic antigens and antibodies. The affinity blocks 114 may be arranged in predetermined patterns defining a base code 116. The affinity blocks 114 may be comprise of chemical groups in coding subunits of a coded chemical (material) that is engineered based on their affinity (e.g., through chemical, electrostatic, polar, hydrostatic interactions, etc.) with the other molecular groups in other coding sub-units and in some parts at least with a chemical agent to make a logic gate.
The molecules of the coded chemical 111 may be selected to act as storage units to provide means for storing information in an information storage matrix. The coded chemical 111 may store information in one or more layers of the molecules and/or portions of its chemical components. The affinity blocks 114 may be applied as chemical barcodes (e.g., representative of numbers/barcodes) for computation purposes in a cognitive chemistry system (e.g., real-time solving of P problems).
Groups of the affinity blocks 114 may be arranged to define gate switches 118 within the base code 116. The gate switches 118 may be configured (i.e. programmed) to correspond to specific environmental inputs 108, and to the operator 112. The gate switches 118 may be optical (e.g., light sensitive switches) chemical (e.g., enzyme sensitive switch), physical (e.g., temperature sensitive switch), electromagnetic (e.g., UV sensitive switch), and/or other logic gates. The coded chemicals 111 may have recognition capacity over its environmental conditions which may enable the cognitive cell 102 to respond to certain environmental inputs 108 through the different affinity blocks 114 and logic gate switches 118 formed by the base code 116.
The configuration of the gate switches 118 may be used to define a bridge between the environmental inputs 108 and the operator 112. The logic gate switches 118 may function as linkers defining the bridge that connects the environmental inputs 108 to the to the internal operation system. For example, the gate switches may be a physical representation used to carry fundamental logical operations, such as NOT, AND, OR, NOR, XOR etc., used to determine when an environmental input 108 is present, which then may be used to trigger the operator 112 to generate its corresponding output 108. One or more of the gate switches 118 may be used to define logic gates (or circuits) used in performing a logic operation (e.g., Boolean function). The operation 104 may be triggered by existence of special environmental factors and/or sequential activation of the affinity blocks 114 and the logic gate switches 118.
The operator 112 may function as a module or a part of the molecular machinery of the cognitive cell 102 used for generating the output 106. The operator 112 may include one or more chemical agents, such as glucose, enzymes, proteins, RNA, lipids, ATP, vitamins, and/or other chemicals, responsive to certain of the gate switches 118. The chemical agents may be capable of generating part or all of the desire output 106 and/or operation 104 by performing a chemical reaction upon triggering by the gate switches 118.
The chemical agents may comprises a set of chemicals or molecules that are coupled with each other through chemical reactions and are functioning as modules of a molecular machinery to perform a desired operation/function initiating with one or multiple input(s). The chemical agents may be connected to other chemical agents internal to the cognitive cell(s), and may be connected to the environmental agents (factors) through the logic gates. Combinations of different chemical agents with various logic gates may provide a tight connection of the system to its environment and/or enable the system to indicate complex cognitive-like behaviors in response to various environmental inputs. Examples of chemical agents that may be used include adenosine diphosphate (ADP), ATP, guanosine diphosphate (GDP), GTP (guanosine triphosphate, nicotinamide adenine dinucleotide (NAD), Flavin adenine dinucleotide (FAD), transfer ribonucleic acid (tRNA), Ribulose 1.5 bisphosphate, Cobalaxime, tetracycline, rttA, nucleotides, ligase, amino acids, magnesium chloride, primers, glucose, and/or vitamins.
As also shown by
While
The cognitive cells and systems may be configured as autonomous systems having features that provide cognitive, decision making, self-controlling, self-assembling, self-organizing, self-healing, self-replicating, self-fueling, and/or other capabilities. The cognitive system has capabilities relating to acquisition, perception, understanding, and remembering of information. The decision making may be independent of any outside mediator or operator. The self-controlling may relate to coding, controlling, and running its own processor, and may also have cognitive and decision making capabilities. The self-assembling may relate to assembling its own sub-units together and making a more complex structure or system based on thermodynamic laws (e.g., a self-assembling system would be generation of crystals of ice from H2O at 0° C. or polymerization of self-assembling polymers). The self-organizing system may relate to thermodynamic stability in structure, and provide integrated self-controlling (e.g., able to pass and transfer itself through different scales of complexity) and self-assembling features (e.g., the capability to generate its own sub-units and modules at different levels and scales of complexity). The self-fueling system may have the capability of producing and up-taking its own energy requirements from its environment without the need for any external mediator or operator. The autonomy may relate to independence from an external mediator or operator in the sense of coding, control, operation, structure formation, and assembling, as well as energy production. The self-healing may relate to regenerating its own damaged part by itself, independent of any external mediator or operator. The self-replicating may relate to replicating itself.
Design and generation of cognitive cells, systems, and methods may be based on cognitive chemistry which in addition to energy, information (code) is stored in the chemical bonds and/or electrostatic interactions between molecules. Cognitive chemistry comprises special class of multifunctional materials that are highly flexible in the sense of coding (information) storage capacity, as well as energy and mass (structure) production and/or transformation. Here, this feature of cognitive chemistry is defined as relativity of code, energy and mass versus relativity of energy and mass (in non-cognitive chemicals and materials).
The cognitive cells, systems, and methods may be used to feature one or the following: systems that are function based on the cognitive chemistry (relativity of code, energy and mass); design and creation of cognitive, decision making, self-assembling, self-controlling, self-organizing, self-healing, self-replicating, and/or self-fueling systems; design and creation of artificial intelligence, nano and microprocessors, Solving P problems, Big data analysis, dynamic coding, conditional coding, multi-layer coding, production of renewable energies, solar cells, artificial photosynthesis, biofuels, bioreactors, agriculture and food industry, Synthetic life, symbiotic, integrated systems the embody both hardware and software (e.g., bioware), Cognitive diagnostic/therapeutic biomedical devices, Cognitive self-regenerating systems, Cognitive regeneration-stimulating biomedical products, Anti-aging treatment, Cognitive weight controlling biomedical devices, treatment of coding disorders in human/animals' diseases such as Cancer, Alzheimer, and genetic diseases, etc.
Design and generation of cognitive systems may be based on relativity of code, energy, and mass. The cognitive cells and/or systems may utilize “code” in industrial applications across disciplines including but not limited to energy and environment, biotech and life sciences, tech, agriculture, materials, medical, etc. For example, the cognitive cells and/or systems may be used in the field of biomedical science in designing and generation of cognitive biomedical devices that recognize the physiological and/or pathological conditions in human body. The cognitive cells and/or systems may be applied in treatment of diseases that currently there is no cure for them applying conventional therapeutic methods, such as cancer, HIV, auto immune diseases, Multiple Sclerosis, diabetes, and age related diseases (e.g., Alzheimer). Cognitive chemistry may involve creating systems that embody hardware and software (i.e., “bioware”), where even the smallest hardware building blocks show similar software capability as an overall unit in terms of intelligence. The bioware may have outputs about a first layer that acts as the input of the next layer, thereby providing a path-dependent process like a conditional set of dominoes.
A biologically inspired cognitive cells and systems may define the relativity of code, mass, and energy by virtue of a multi-layer, multi-stage, multi-level (multi-scale) biological coding system. As shown in Table 1 below, a biologically inspired cognitive system may have features comparable to computer systems, or employ features of computer systems, such as storage media, memory capacity, operators, coding subunits, operation, analysis/decision making capacity, hardware/software units, etc.
In addition to computer capabilities, the cognitive cells and/or systems may be provided with layering usable for complex coding and/or storage. Table 2 shows examples of layered coding in a biological cognitive system.
The cognitive cells and/or systems may also be provided with scaled coding for passing information between various aspects of the biological system. Table 3 shows examples of scaled coding in a biological cognitive system.
The cognitive cells and/or systems may be provided with staged, dynamic, multi-stage coding that may occur according to various timing. Table 4 shows examples of stages in a biological cognitive system.
Each of the cognitive cells and/or components of the cognitive system may include various layers, scales and levels of coding and operations applied in a biologically inspired multi-layer, multi-scale, multi-stage/dynamic coding and data processing system.
Generation of the autonomous system, with capabilities of being cognitive, dynamic in coding and data processing and flexible in data processing and physical reactions to various environmental conditions and signals through dynamic structural changes, may involve a special form of real-time de novo coding instructed by environmental conditions (i.e., without the need of intermediates like coding by human for every single reaction to every single environmental condition). In addition, this system may be able to generate its own hardware in a flexible way based on the environmental conditions and signals (e.g., in the form of a physically and structurally real-time self-healing, self-replicating system).
The coding system may be classified in the sense of flexibility and capability to respond to the environmental conditions in categories, such as computer (conserved) coding and cognitive (de novo) coding. Computer coding may refer to current coding systems in silicon based computers in that an output of the system and responses to environmental conditions may be limited to the circumstances that are coded by a programmer, and the machine may not have the capability of self de novo coding based on new environmental conditions.
The cognitive coding may employ aspects of the computer coding, with the added capability of direct contact with the environment to be instructed and programmed directly by environmental condition and without the need of an intermediate programmer to code a predetermined response or boundary to an environmental condition. This may be used to expand the capability of current silicon based computers in response to the environmental conditions and signals to provide real time, self-de novo coding applying its basic coding sub-units. The expanded system may be provided with flexibility to be instructed by the environmental condition for generation of new codes for a particular reaction (output) to the environmental signals as the real-time input referred to as self de novo coding.
The cognitive coding may employ features of biological systems to provide the capability of real-time response to unlimited environmental conditions through de novo coding mechanisms applying basic coding sub-units at different layers and levels of coding. For example, an immune system provides real time de novo coding for synthesis of antibodies. Antibodies are synthesizing in the body just after the antigen presentation to the immune cells through the mechanism of alternative splicing for F-ab arm of Immunoglobulin (IgG) mRNA. After Ag presentation, a specific Ab based on the specific environmental condition (presentation of unlimited number of Ags in the nature) may be synthesized in the body. Therefore, even though a limited number of immunoglobulin G basic genes at the layer of DNA coding system (e.g., in human, mice, rats, etc.), immune system may have the capability of generation of various (unlimited) specific Abs against Ags that have not been in the body before. Just after their presentation to the body, immune system starts the process of de novo coding for the generation and synthesis of an Antibody against every single Ags presented to the body.
The cognitive processes and methods are coded as described herein for generation of a biologically inspired autonomous system by integration of the biologically inspired multilayer, multi-level dynamic cognitive decision maker system in the sense of coding, structure formation and energy utilization.
Multi-level directed self-assembly may be used in the formation of different structures with predefined morphology by applying the basic sub-units of coding and structure based on the environmental conditions through the mechanism of de novo coding. Designing such an autonomous system in coding, data processing and morphogenesis (flexibility in structure for example in a self-healing system) and independent energy production capability, may use a variety of features, such as coding features (e.g., coding media, layered coding), unity of software and hardware for directed self-assembly (e.g., for self-organization), flexibility, autonomy (e.g., self-energizing, self-deciding, self-coding, self-controlling, self-assembling, self-organizing and self-fueling), scaling (e.g., multi-layer, multi-level, multi-scale, conditional, dynamic, de novo coding), artificial photosynthesis, adaptability to environmental conditions, hardware regeneration, machinery for production or degradation of basic molecules into sub-units, and other features.
Various materials may be used in the cognitive system to provide a system capable of operation as a biologically inspired software capable of operating in a self-controlling state, while its hardware forms in a self-assembling, self-fueling, and self-operating state and in a self-organizing manner.
Different coded chemicals (materials) may be used for generation of a cognitive cell/system. Generation of cognitive cells/systems which indicating one or multiple features of autonomy (e.g., self-regeneration, self-fueling and self-regulation) requires the application of coded materials comprising sub-units with high flexibility in coding capacity, energy and mass (structure) production/transformation. For example, DNA, saccharides, proteins, graphene and aptamers are representative of materials that are highly flexible in coding, energy and mass production/transformation and are appropriate materials in generation of such autonomous systems.
For example, proteins are made of 20 amino acid sub units configurable in a large variety of combinations. Thousands of hundreds of proteins with large variety in structure and function can be generated through the assembling of amino acid coding sub units. The coding capability of the amino acids may be used for generation of a multilayer coding system, such as layers of amino acids and protein coding for solving problems, such as the NP or TSP problem of Example 3 (described herein). In addition, amino acids have the oxidation capability which may also be used to convert ATP into energy in biological systems. Therefore, amino acids and proteins can be defined as efficient materials with essential requirements of cognitive materials to be applied in generation of an autonomous system through the relativity in coding capability, mass (structure formation) and energy production/transformation.
Carbohydrates (e.g., saccharide) can be applied in generation of an autonomous system by providing the main requirements of the building blocks of an autonomous system through the high level of flexibility in the sense of coding capacity, energy and mass transformation. Carbohydrates may be applied in a cognitive cell/system for coding purpose. Glucose and other mono saccharides (e.g., fructose, galactore, mannose, ribose, etc.) have coding capacity by polymerization and providing specific sequences of glycosides. This may be done, for example, through post translational modification of proteins and formation of highly specific glycoproteins which may function as major mediators of signal transduction in biological systems. Glucose and other saccharides have physically defined structure and measurable molecular mass. Glucose and other saccharides can be oxidized and produce energy. For example in biological systems oxidation of one mole Glucose produces 38 mole ATP (which is defined as the energy currency in cells). See, e.g. Nelson D L, and Cox M M, Principles of Biochemistry, W.H. Free man and Company, New York, USA (2010, 202), the entire contents of which is hereby incorporated by reference herein.
Nucleic acids are another exemplary category of materials that can be applied in generation of an autonomous system by providing the building blocks of an autonomous system through the flexibility in the sense of coding capability, energy and mass (structure) transformation. Nucleic acid molecules (including ATP) are defined as a specialized coding chemical in biological systems. In addition, nucleic acids may be considered a specialized molecule for generation and transformation of energy. For example ATP functions as an energy currency in cells. Therefore, nucleic acids may provide a coding system with a measurable mass and the capability of formation of energy as well as various levels of structural complexities. ATP can be defined as an example of a material with relativity of code, energy and mass.
Structurally, nucleic acids, such as nucleotides and/or nucleosides, can be polymerized through phosphodiester bounds. As a result of polymerization reaction between nucleotides, different forms of nucleic acid polymers including DNA, mRNA, tRNA, rRNA with different levels of structural complexity and for different functional purposes may be formed. For instance, DNA is a specialized molecule for data storage, while mRNA is more specialized for data transportation and tRNA is specialized for translating and conversion of data from one layer of coding to the next one. However, rRNA almost specialized as a structural molecule in the formation of ribosome.
Unlike human made electrical binary coding system which is luck of features of mass for data, nucleic acids may be use for transformation from coding feature to mass. Nucleic acids may be used to provide a unique coding system with a measurable mass (e.g. MW of ATP=504.18 gr/mole) and the capability of formation of different structures. ATP can be defined as an example of materials with relativity in coding capability, energy production and mass formation (relativity in code, mass and energy).
Nucleic acids may be applied as coded chemicals in both forms of polymerized nucleotides (e.g. in the forms of DNA and mRNA) as well as single free nucleotides (such as cAMP as a signal transducer in a cognitive cell). DNA double helix structure may be used as a chemically and physically defined coding media. This structure may be used along with other coding systems, such as the binary coding system in current computers. In addition, novel coding and data processing algorithms may be defined for generation of multi-layer, multi stage dynamic coding system including multiple layers of DNA conserved coding layer, DNA epigenetic conditional and dynamic coding layer, mRNA alternative splicing de novo coding layer, for solving NP-hard problems'
Nucleic acids may also be used to produce energy, in the sense of relativity in energy. Nucleic acids can be oxidized and produce energy. ATP may be defined as an energy currency in cognitive cell.
Based on the multifunctional property of coded chemicals (e.g., ATP molecule), in the sense of coding capacity, energy and mass transformation; a novel equation of relativity may be defined as relativity of code, energy and mass. ATP may be used as a rechargeable molecular battery in a self-fueling solar cell and artificial photosynthesis system as in example 1 (described herein), code-based, self-fueling ATP battery with the capacity of production of energy and mass applying the relativity of code, energy and mass.
The biologically inspired multi-layer, multi-scale, de novo dynamic coding and data processing system may be used as CEMVITA™ Bioware, which is an integrated software and hardware system. CEMVITA™ Bioware may apply a multi-layer coding system, and DNA may function as the first layer of coding. Protein may function as the second layer of coding. In the first layer of coding which is DNA coding layer, 4 coding sub-units (quarters of code) including ATP, GTP, CTP and TTP (adenosine, guanosine, cytidine, and thymidine triphosphate, respectively) are used. CEMVITA™ algorithm may be used to explain the relativity f code, energy and mass for each quarter of ATP code. However similar calculations can be applied for other coding sub units at different layers of DNA, mRNA, protein and other coded chemical systems.
The equation of relativity of code energy and mass considers code as the third dimension of the physicochemical properties of a coded chemical and explains the transformation of code, energy and mass sub units to each other in a cognitive cell/system versus the equation of general relativity of energy, and mass E=mC2 (Albert Einstein, 1995) which explains the transformation of energy and mass in a non-cognitive cell/system. The equation of relativity of code, energy, and mass explains and clarifies complex molecular features of a cognitive cell (including self-organization, self-regulation, self-fueling, self-regenerating and self-replication) that cannot be explain simply by currently defined laws of thermodynamics and/or general relativity of energy and mass.
Based on the General relativity law energy−mass and considering coding property of ATP molecule, as well as applying the molecular weight of ATP (MW: 507.18 gr/mole) and the equal amount of energy (J) stored in each ATP molecule, a novel equation for the relativity of code, energy and mass may be defined. ATP may be used as a rechargeable molecular battery in a cognitive cell.
DNA coding language is made of 4 sub-units of coding (quarters of code) including ATP, GTP, CTP, TTP. Here, ATP has been used for explaining the relativity of code, energy and mass in codded chemicals, but, similar calculations may be done for other coding sub-units at the layers of nucleic acids, amino acids, proteins, and any other coded chemicals which are flexible for energy and information storage in their chemical bonds or electrostatic interactions with other molecules
ATP is a highly specialized molecule of energy transportation and storage in biological systems including the capability for storage of light/solar energy in its chemical bounds (as chemical energy), and can be converted to the electrical, mechanical and other forms of energy. Light energy can be stored in ATP molecules through the natural or synthetic photosynthesis reactions in a cognitive cell/system.
The light used by for photosynthesis reaction in chloroplast has a wave length of about 700 nm. The energy (E) in a single photon is given by the plank equation at a wave length (k) as follows:
An Einstein of light is Avogadro's number (6.022×1023) of photons, the energy of one Einstein of photons at 700 nm is:
(2.84×10−19 J/photon)(6.022×1023 photons/Einstein)=171.1×104 J/Einstein Eq. (IB)
Therefore, a mole of photons of red light has about five times the energy needed to produce a mole of ATP from ADP and Pi.
Based on the coding property of ATP as a nucleic acid sub unit and considering the molecular weight of ATP (MW=507.18 gr/mole), a new equation may be defined which explains the relativity of code, energy and mass in a cognitive (chemical) cell/system.
A Tara quarter of code (for a molecule of ATP) is defined as a coding unit that is relative in the sense of energy and mass. In other words, One (1) Tara quarter of code is defined as a unit of code as follows:
Using this approach, the cognitive system may use biological and/or chemical materials to achieve the desired coding. For example, using the carbohydrates, nucleic acids and amino acids may provide the flexibility in coding properties, energy production and mass formation, (relativity in code, energy and mass). In a cognitive chemistry system, main building blocks of structure, code, and energy are capable of transforming to each other based on the environmental conditions, energy levels and real time structural needs of the system.
In another example, other multifunctional synthetic chemicals such as the graphenes, aptamers, polyethylene glycol (PEG) and/or their modified forms in combination with carbohydrates, amino acids and nucleotides are other materials that can be applied as the appropriate candidate materials in the cognitive system. These and other materials may be combined to provide the cognitive system provide with integration of coding, energy and structural units together as well as designing and application of the materials with the relativity in coding properties, mass formation and energy production.
The coding of the cognitive system may be used for various applications, such as the solar application of Example 1, the growth application of Example 2, and/or the TSP application of Example 3.
In the solar power example depicted in
The coded chemical 111a may be a plasmid 516a made from nucleic acid as shown in
Back bone expression of the plasmid PET-TALEN-HIS contains 6×His tag on C terminal of insert, and recombinant proteins of Spider silk, Insulin, Albumin, Phosphohexose lsomerase for cloning and expression in E. Coli are used. In this example, the plasmid 516a is an expression plasmid PET TALEN-HIS including a Multiple Spidoin-1 (MaSp1) gene, encoding Major ampullated Spidroin I protein (e.g., protein of Spider silk) of the Spider Nephila Clavipes. See, e.g., Xia et al., Native-sized recombinant spider silk protein produced in metabolically engineered Escherichia coli results in a strong fiber. Proc Natl Acad Sci. USA. 2010, 107: 14059-63, the entire contents of which are hereby incorporated by reference herein.
The expression of the MaSp1 gene is linked to a gate switch 518a, triggered by an input of the tetracycline. The plasmid 516 also includes an insulin gene which is linked to a gate switch 518a with IPTG as an input, an Albumin gene under the control of a gate switch with Tamoxifen as an input, and a 4-Phosphohexose isomerase gene which produces an enzyme used as the operator 112a for conversion of fructose to glucose. The 4-phosphohexose isomerase gene expression is triggered by a gate switch which uses light as an input. The DNA sequences of the proteins of the operator 112a are attached to His Tag DNA Sequence, for the protein purification, and uses integration of specific DNA constructs of each gene from multiple cloning site of PET T ALEN HI S (Add gene, Cat No. 40787).
As shown in
The gate switches 618a-d may be binary switches responsive to input 108a by either being in an on or off state. The ON or OFF state of the gate switch may then effect a change in the cognitive cell 202a, by, for example, acting as an input 108 to further gate switches, signaling the production and or activation of an operator 112a, and/or causing the cognitive cell 202a to produce the output 106a. For example, the gate switch 618a is an AND gate, which is in an ON state only when both the first protein 618a1 and the second protein 618a2 are activated by the input 108a. Gate switch 618b is an OR gate, which is in an ON state if either the first protein 618b1 or the second protein 618b2 is activated by the input 108a. Gate switch 618c is a NOR gate, which is in an ON state only if the first protein 618c1 is activated and the second protein 618c2 is not activated by the input. Gate switch 618d is a NOT gate, which is in an on state only if both the first protein 618d1 and the second protein 618d2 are not activated by the input.
The chemical reactions provided by the combination of the coded chemical 111a and the chemical agent 112a may provide both energy and information storage/transformation in molecules. These molecules may be usable as a programmable system to transform energy resources (e.g., solar energy inputs) into desired materials for a wide range of industrial/biomedical applications.
The output 106a generated by the reaction of the coded chemical 111a and the chemical agent 112a may generate chemical components as fuel 106a receivable by the subject 422. These chemicals may be selected for providing power to living organisms without toxic, explosive, flammable, or other damaging risks. Such chemicals may also be selected to operate in even extreme environmental conditions, such as aerospace condition for astronauts, space travelers, survival and rescue groups, etc. In this example, the output is ATP, but other chemicals, such as glucose, capable of generating energy may be used as the chemical output generated from the solar power cognitive cell. Energy production by ATP may not require the breaking of whole chemical bonds of the molecule. ATP may be used to produce energy by transferring of its high-energy phosphate groups when coupled with other chemical reactions. Each molecule of ATP may store about 12 kcal per mole (50 kJ mol″1) from natural to artificial photosynthesis.
Chemical energy stored in the ATP molecule can be transferred to the biofuel molecules, or converted into the fuel. Considering that each ATP molecule is carrying three high energy phosphate groups and chemical energy in ATP molecule can be converted to the other forms of fuel usable as energy for various applications, such as electricity. ATP can also be applied as an efficient rechargeable power source. The cognitive cell 202a may provide an ATP-Glucose battery which may be integrated to an artificial photosynthesis system, such as a chemical solar cell.
The chemical coding of the cognitive cell may employ features of photosynthesis present in green plants. Natural photosynthesis captures sunlight and converts it into chemical bonds of biomass in green plants. Through the photosynthetic processes and using solar energy, water splits into oxygen and hydrogen equivalents through the electron transfer chain in cytochrome systems of chloroplasts. The oxygen is released into the atmosphere where it is available for living organisms and maintenance of nature. The hydrogen equivalents are used to reduce C02 and for production of biomass in green plants.
During natural photosynthesis, light reactions in chloroplasts (including light absorption, water split and electron proton transfer) may provide the reducing equivalents in the form of reductive H2. Nicotinamide adenine dinucleotide (NAD) is an enzymatic cofactor involved in redox reactions. NAD functions as an electron carrier, cycling between the oxidized (NAD) and reduced (NADH) forms. In the other words, NAD functions as a carrier for the released hydrogen from water splitting reaction. During natural photosynthesis, reduction of NAD to NADH occurs in cytochromes in chloroplast. The hydrogen is then used as a reducing equivalent for fixation of C02 and production of glucose.
Artificial photosynthesis may be performed in vitro by production of synthetic cytochromes. At least some artificial photosynthesis may involve complexity of cytochromes still and may result in lower efficiency than the natural photosynthetic systems. Techniques using photosynthesis are described in Huntley et al., C02 Mitigation And Renewable Oil From Photosynthetic Microbes: A New Appraisal, Mitigat. Adapt. Strat. Global Change, 12:573-608 (2007); Li Y et al., Biofuels from microalgae, Biotechnol Prog, 24:815-20 (2008); Atsumi et al., Direct Photosynthetic Recycling of Carbon Dioxide To Isobutyraldehyde, Nat Biotechnol, 27: 1177-80 (2009); Niederholtmeyer et al., Engineering Cyanobacteria to Synthesize And Export Hydrophilic Products, Appl Environ Microbiol, 2010,76:3462-6; Zhu et al., (2014); Kim D. et al., Artificial photosynthesis for sustainable fuel and chemical production, Angew, Chem. Int. Ed. 54:2-10 (2015); and McConnell I, Li G and Brudvig G W; Kim et al., Photochemical Production of NADH Using Carbaldoxime Catalysts and Visible-Light Energy, Article: Inorganic Chemistry, American Chemical Society (2012); Kim et al., Visible-Light-Driven Photo production of Hydrogen Using Rhodium Catalysts and Platinum Nanoparticles with Formate, Article: American Chemical Society, pp. 25844-52 (2014); Park et al., Phototactic Guidance of a Tissue-Engineered Soft-Robotic Ray, Reports: Science Mag., pp. 158-62, Jul. 8, 2016; Han et al., Synergistic Effect of Pyrroloquinoline Quinone And Graphene Nano-Interface For Facile Fabrication Of Sensitive NADH Biosensor; Biosens Bioelectron, 89:422-429 (2017); Wang et al., Optimization of a Photo-regeneration system for NADH using Pristine Tio as a catalyst; and J Mol Catal. 2017, the entire contents of which are hereby incorporated by reference herein.
As shown by
Chemical materials, such as nucleic acids (e.g., ATP), may be used to form the coded chemicals and chemical agent to enable the cognitive cell to function as a high-energy rechargeable molecular battery. The cognitive cell 202a may be designed as a programmable ATP-battery that converts the solar energy input 108a to other forms of energy that are compatible for instance with electronic devices, a human body and/or other subjects 422. The solar power cognitive cell 202a may also be used to generate a hybrid artificial photosynthesis/ATP-sugar battery/and multi-functional polymer generator system that converts the solar energy input 108a to a wide range of materials, with different biochemical and biomechanical properties. The cognitive cell may be capable of transformation of solar energy to other renewable energy forms, thereby providing a self-generating polymer (material) generator.
The solar cognitive cell 202a may also be used as an alternate renewable energy source to supplement or replace fossil fuels and other non-renewable energy sources. The chemical structure of the cognitive cell may be used to store energy in the form of chemical bonds that may replicate photosynthesis in green plants. The solar cognitive cell 202a seeks to provide a synthetic source capable of providing one or more of the capacities of natural photosynthesis, such as oxygen production, solar energy up-take, energy storage, as well as synthesis of different types of materials by uptake of solar energy and C02 from atmosphere.
In an example, the cognitive cell 202a is synthesized in a configuration that produces a recombinant protein (e.g., spider silk, Insulin, albumin, collagen or each of the enzymes for the desired synthetic pathways such as different units of a solar cell, Glucose-ATP battery, etc.). Gene constructs of each recombinant protein/polymer are designed using the known DNA sequence relevant to each gene construct. The DNA constructs is synthesized by chemical methods, amplified by cloning in E.Coli, and subsequently purified. This is done by applying the Maxiprep method. See, e.g., ThermoFisher Scientific, Cat No, K210004. Each gene construct is inserted to a plasmid. The plasmid may be, for example, a PET TALEN-His plasmid (e.g., Addgene, Cat No. 40787). Each gene construct is inserted into back-bone plasmid through its multiple cloning site by applying the matching restriction enzyme for each gene construct. Expression plasmids containing genes of interest are cloned in E. Coli expression strain BL21 (DE3).E. Coli cells are cultured in 250 mL flasks containing 20 mL of LB medium in shaking incubator at 220 rpm. Cells are induced for 6 hours with the favorite inducible switches including Tetracycline, IPTG, Tamoxifen and light, etc.
When the OD 600 (optical density at 400 nm) reaches 0.4, samples are taken after 6 hours' induction for isolation of recombinant proteins and two-dimensional gel electrophoresis. Recombinant proteins are isolated and purified applying a His-Tag protein purification kit. The kit may be a plasma kit commercially available from www.clonetech.com (Clontech, Cat #635656). Purified proteins are sequenced and analyzed for physiological functionality. Matrix-Assisted Laser Desorption/Ionization on reflection Time-Of-Flight (MALDI-TOF) is used as the amino acid sequencing method.
The environment for formation of the cognitive cell 202a is defined to support the desired chemical reactions. The cognitive cell is formed in an in-vitro environment for production of recombinant proteins (Energy requirements provided by solar cell-ATP Battery). The in-vitro Environment for production of polymers uses a T7 mRNA synthesis kit, and an in vitro protein synthesis kit including free amino acids and expression of each protein under the control of its specific inducible switch. The enzymatic environmental reaction for production of each polymer conducted at pH 7.4, 37° C., and energy of the system is provided by Solar Cell and Fructose, ATP battery. A microbial bioreactor environmental condition (Energy requirements provided by solar cell-ATP Battery) is used. Cloning of Plasmids into E.Coli for production of the enzymes for production of each polymer uses isolation and purification of Recombinant proteins from the bioreactor through His-affinity columns.
The coded chemical is formed by cell free protein production using In vitro RNA Transcription and Protein Translation. This translation is performed by coding DNA sequence related to each gene amplified by PCR (polymerase chain reaction) using specific primers. PCR products are purified and the quality of the generated DNA is determined. Using the in vitro transcription (IVT) process, mRNA is generated from the DNA product. Subsequently, the product is purified and treated with phosphatase to remove 5′-triphosphates. Sequentially, mRNA is purified and applied for in vitro translation. To this end, T-7 RNA Polymerase In-vitro Transcription kit (Thermofisher science) and In-vitro Translation kit (Thermo Scientific 1-step IVT kit are applied.
Analytical assays for measurement of NADH, Glyceraldehyde 3-phosphate, Fructose 6-Phosphate and ATP are performed. To evaluate the amount of NADH production, NADH fluorometric assay kit (APEx Bio) and NAD/NADH Quantification Kit (Sigma-Aldrich, Cat No. MHC037) are applied. Production levels of Glyceraldehyde 3-phosphate, Fructose-6 phosphate, and ATP, are evaluated applying Glyceraldehyde colorimetric assay kit (Sigma-Aldrich, Product No. 1.2.1.12), Fructose 6-phosphate assay kit (Sigma-Aldrich, Cat No. MAK020), and Luminescent ATP detection assay kit (Abeam, ab 113849), respectively.
The enzyme clusters on artificial membranes (e.g., artificial cellulose membrane) are immobilized in the artificial photosynthesis-ATP/Glucose battery cognitive cell 202a. The solar input 108a causes a chemical reaction in the cognitive cell 202a which generates power 106a. The solar input 108a, together with carbon dioxide and water, reacts within the cognitive cell 202a. The coded chemical maps these inputs with the operators. The operators may include chemical agents in the form of clustered enzymes, such as ribulose-1,5, bisphosphate carboxylate/oxygenase, phosphoglycerate kinase, glyceraldehyde-3-phosphate dehydrogenase, ribulose 1,5-bisphosphate, aldolase, fructose 1.6 bisphosphatase, glyceraldehyde dehydrogenase, and phosphoglycerate kinase. In addition, the operator may include cobaloxime, which may be on an cobaloxime-coated cellulose-membrane with intermediate chemicals, such as NAD, ATP, and 02.
The cognitive cell 202a uses synthetic photosynthesis reaction engineering by coupling chemical catalytic reactions with enzymatic reactions. Synthetic chemical pathways designed by coupling a chemical photocatalytic water splitting reaction with a cluster of synthetic enzymatic reaction to convert solar energy to chemical energy as rechargeable solar cell/battery compatible with human body. Inorganic catalysts, such as rhodium, platinum, Ti02 nanoparticles, pyrroloquinoline quinone and graphenes nanoparticles, may be applied to facilitate the oxidoreductive chemical reactions. A catalyst is a substance that increases the rate of a chemical reaction without itself undergoing any permanent chemical change.
The solar operation depicted in solar unit 804a may be performed using an in vitro synthetic photosynthesis process may be used that applies a synthetic (inorganic) catalyst (e.g., cobaloxime) for splitting water molecules into oxygen and hydrogen. The photochemical water splitting reaction is coupled with the NAD reduction. The NADH functions as a reducing agent for the sequential C02 fixation reactions. Another synthetic chemical pathway is provided for C02 fixation. Ribulose 1.5 bisphosphate (Sigma-Aldrich, Product No, R0878) is applied as the initial substrate for initiation of C02 fixation reactions. In the following chemical reactions, Ribulose 1.5 bisphosphate is synthesized as a side product of the system for self-regeneration. Ribulose 1.5 bisphosphate carboxylase/oxidase converts Ribulose 1.5 bisphosphate in two molecules of 3-phosphoglycerate. By addition of one molecule of C02, one molecule of NADH and one molecule of ATP to the next reaction results in the conversion of 3-phosphoglycerate into glyceraldehyde 3-phosphate which is 3-carbon sugar and converts to 6-carbon sugars sequentially as the final product of this pathway.
In this artificial photosynthesis process, molecules of water split in a synthetic photochemical reaction applying an inorganic (synthetic) catalyst (Cobaloxime). 02 is released in to the atmosphere, and hydrogen is used for CO2 fixation. Applying 2 sequential synthetic enzymatic reactions, the captured energy of sunlight which is stored in NADH2 molecule is transferred to the glyceraldehyde 3-phosphate (a three-carbon sugar) (
The light 108a and water interact with cobaloxime to produce NADH. The NADH then interacts with the enzymes and the CO2 to produce glucose. As shown in the ATP Fructose battery compartment 804b, the enzymes may follow alternative pathways to fix the CO2 into alternate metabolic products, such as ethanol and methanol. The synthetic chemical pathways may use an ATP/fructose battery transformation unit 804b to provide storage of power outputs, such as fructose (fruits' saccharide) molecules.
The power outputs may provide energy for human, electrical, and/or other needs for human/animal body use. Both fructose and 3-phosphogly cerate can be applied for production of different forms of biofuels including ethanol and methanol. Examples of the use of biofuels are described in Minteer et al., Enzyme-based Biofuel Cells, Curr Opin Biotechnol, 2007, 18:228-34; Zhu et al., Deep Oxidation Of Glucose In Enzymatic Fuel Cells Through A Synthetic Enzymatic Pathway Containing A Cascade Of Two Thermostable Dehydrogenases, Biosens Bioelectron. 2012, 36: 110-5; and Sarris et al., Biotechnological Production Of Ethanol: Biochemistry, Process And Technologies, Engineering in Life Sciences. 2016, 16(4):307-329, the entire contents of which are hereby incorporated by reference herein.
Both Fructose and ATP are compatible with human/animals' body and can be applied as a power supply for human/animals' body, and for production of electricity in other applications. By conditional coding design and applying chemical switches, the cognitive cell 202a can be switched to be applied as a power supply for human body or as an electronic device.
The lower membrane 803b includes glucose pumps, which allow the glucose 806a to pass out of the cognitive cell 202a, while other components of the cognitive cell 202a, such as the operators 812, remain between the membranes 803a,b. The glucose may then be used to produce a result 810a1-810a3. For example, the glucose 806a may be used to fuel a generator 809 to generate electricity 810al. In another example, the cognitive cell 202a may be coupled to a subject 422 (as in
In a further example, depicted by
Applying a set of molecular switches in the chemicals, the cognitive cell 202a may be programmed for controlled production of various materials. For example, the polymer generator-system may be coupled with an electro-spinning or 3-D printing-system for generation of a wide range of materials with various chemical and mechanical properties and different industrial/biomedical applications. Expression plasmid PET-TALEN-HIS (Add gene, Cat No. 40787) 516 of
As shown by the polymer generation unit 804c of
In the example of
As an example,
The cognitive cells 202b 1, b2 may be similar to the cognitive cell 202a of Example 1 with different chemistry to provide the series of the chemical reactions needed to generate the result 106b. The cognitive cells 202b1 may be, for example, fibroblasts comprising a coded chemical and an operator. The coded chemicals may comprise a plasmid (e.g., similar to the plasmid 516a of
The starfish 922 may have other cells, materials, chemicals, and/or other components, such as pacemaker cells 920 positioned about conductive nodes of the arms 924, purkinjie cells 932 in conductive fibers along the arms 924, and cardiomyocytes 934 positioned within the collagen layer 926.
Materials used in this autonomous system are arranged to provide both energy and information storage in their molecules, thereby providing tools for the generation of autonomous systems (self-responsive to the environmental signal, self-fueling and self-healing) that can transform energy resources (such as solar energy) into desired materials for its own regeneration after damages or producing different materials with a wide range of industrial/or biomedical application. For example, nucleic acids (in both monomeric and polymeric forms), amino acids, peptides, aptamers, carbon nanotubes and graphenes, and proteins are representative of programmable materials in cognitive chemistry by their multi-functional chemical properties for energy and information storage/transformation. Materials are not limited to nucleic acids and proteins, and may involve every synthetic material that is flexible in the sense of information storage/transformation capacity, as well as energy and mass transformation through their molecules.
The various cells and materials of the starfish 922 may be configured to perform one or more operations, such as power using the solar cognitive cell 202a as previously described and/or regeneration using the cognitive cells 202b 1, b2.
In the initial stage W, the synthetic photosynthesis cognitive cell 202a produces cellular energy (in the form of glucose) in response to sunlight (or other solar input) 108a. This glucose acts as a fuel input to power the starfish 922 and its other cognitive cells 202b 1, b2 to carry out the self-healing operation 204b. The glucose may be generated using the solar process 202a as described, for example, with respect to
In damage stage X, when an arm 924 of the starfish 922 is damaged (e.g., cut) by an object (e.g., knife) which acts as an initial input 108e to the process 204b, the collagen layer 926 is opened and the layer of cognitive cells 202b2 are separated to create an opening in the arm 924 of the starfish 922. This opening allows the exterior fluid 927b to mix with the interior fluid 927a. This fluid 927b provides chemical 928 which acts as input 108b1.
In the reaction stage Y, the enzymes 928 in the exterior fluid are exposed to and react with the enzyme sensitive nanoparticles of the cognitive cell 202b 1, causing the nanoparticles 912bl to release the tetracycline 906b2. The output tetracycline 906b2 may then act as a chemical input 108b2 to the cognitive cells 202b2.
In growth stage Z, the tetracycline triggers the production of new collagen 926 and the cardiomyocytes 934. The new collagen 926′ rebuilds the structure of the arm 924 and the growth of new self-healing cells 202b2, sealing the damaged area of the starfish.
During stage W, the FGF 1036b and the COL 1036c are in the OFF state. In the damage stage X, the polymer 101lbl,b2 is exposed to the tetracycline 1012b1, and the polymer 101lbl,b2 is activated to combine rttA 1036e with the tetracycline 1012b1. This also releases cardiomyocytes.
In the reaction stage Y, the rttA 1036e/tetracycline 1012b 1 attaches to the TRE 1036a which releases the growth cardiomyocyte 934. In the repair stage Z, the reactions of stage Y shift the FGF 1036b and the COL 1036c the ON position. In the ON position, the FGF 1036b causes proliferation of the fibroblasts and the COL 1036c causes production of collagen and regeneration of a damage matrix of the collagen along the opening of the arm 924.
In a manner similar to transistor switches in a computer, the gate switches 1118a-d in the logic circuits 1118a,b may act as positive or negative feedback to the logic circuit, in order to regulate the effect of the logic circuit. Each of the logic circuit 1118a,b includes a variety of the gate switches 1118a-e which provide a series of chemical reactions which generate outputs that serve as inputs to the next chemical reaction in the series.
The logic gates in the cognitive chemistry system may be defined as different forms of chemical logic gate switches, such as nanoparticle logic gate switches, DNA promoter inducible switches, protein logic gate switches etc. The gate switches may be different combinations of cognitive-chemical gate-switches. Examples of nano-particle switches include enzyme-sensitive nanoparticle switch, temperature-sensitive nanoparticle switch, hydrolytic nanoparticle switches, pH-sensitive nanoparticle switches, UV/light-sensitive nanoparticle switches, and pressure-sensitive nanoparticles. Examples of DNA (promoter) inducible switches include TET inducible switch, IPTG/galactose inducible switch, estrogen/tamoxifen inducible switch, testosterone inducible switch, heat-shock inducible switch, and light inducible switch.
Each gate switch 1118a-e may act as a positive or negative feedback to either allow or deny generation of the outputs/inputs. Different combinations of cognitive-chemical gate-switches may be applied in the cognitive chemistry coding system with the capacity of performing more complex functions and responses to more complex environmental signals, through designing of multi-layer logical gate processes. Various forms of chemical switches may be applied in the cognitive chemistry computing system to carry the fundamental logical operations at different types of AND, NAND, NOT, OR, NOR, per the rules of Boolean logic.
The corresponding logical gate circuits may be used as a primary element for data processing. Because, as logic gate devices, they are able to adapt and learn. Therefore, various forms of protein logic gate devices can be applied as machine learning units in the cognitive coding system. In addition, different form of nanoparticles (that are programmed to be responsive to their environmental signals), also have been applied in designing the cognitive chemical logic gates.
The cognitive cells may be arranged and use to provide a special form of chemical based computing and data processing system made of cognitive materials to provide hardware and software integrated to each other in a cognitive chemistry system. The cognitive cells have recognition capacity of environmental signals applying various molecular sensors. The cells also provide capacity of both energy and information storage in their molecules (embedding of codes in materials).
The molecular modules and sub-units of the cognitive system are flexible in the sense of information storage/transduction through their chemical bonds as well as transformation of their structural geometry or energy production. The system has the flexibility for transformation of sub-units of coding, structure (mass) and energy to each other. Sub-units of the system are multi-functional and may be relative in the sense of coding capacity, energy and mass production and may shift from one function to another one, based on the environmental signals and for the highest level of flexibility in their autonomous behaviors.
Various environmental signaling factors can be coupled directly with different forms of the chemical logic gates. Direct coupling of an environmental signaling factors with an internal chemical logic gate, the system is empowered the system for direct and real-time response to the relevant environmental signaling factor/environmental condition. Different combinatorial layers of chemical logic gates/switches may be applied for more complex functions, in the cognitive chemistry coding system to empower the capacity of system for the real-time responses and consequently dynamic decision making based on the environmental signals.
Various chemical logic gates and switches may be engineered in various combinatorial forms of stimuli sensitive nanomaterials. Various stimuli sensitive nanomaterials may be applied separately in drug delivery researches. Stimuli sensitive nanomaterials may exhibit reversible or irreversible changes in their chemical structure or physical properties after special changes in environmental conditions such as magnetic fields, pH, ionic strength and enzyme activity. See, e.g., Hu et al., Enzyme Responsive Nomaterials for controlled Drug Delivery, Nanoscale, 6(21): 1227386, Nov. 7, 2014, the entire contents of which are hereby incorporated by reference herein. This approach may use applications of stimuli sensitive nanomaterials limited to very simple reactions based on one or two environmental signals, or more complex structures using various stimuli sensitive nanomaterials as building blocks and modules of logic gates.
Different combinations of stimuli sensitive nanomaterials can be applied as chemical logic gates in soft-robotic systems with the advantage of real-time response to the environmental signals. In addition, in complex logic gates and applying multiple layers of chemical logic gates the system can illustrate more complex cognitive behavior by real time response to multiple environmental signals. In addition, for more complex functions, applying the combinations of DNA coding language and conditional coding system (inducible promoter reporter-conditional expression system) the cognitive chemistry system can be programmed for real time reaction to the unlimited environmental conditions.
As shown by the process 204b as depicted in
The growth/self-healing example of
The starfish 922 may be made by 3D printing of cell suspensions in layers including a layer of cardiomyocytes 934 covered by layers of fibroblasts at the bottom and top. Here, the morphology of system designed as a starfish. A pacemaker node at the central part of the body and pacemaker nodes at on top of each arm 924 are designed. In addition, electrical signals distributes in arms 924 through an array of purkinjie cells 932 at the middle of each arm 924. Pacemaker cells 830 are applied for induction of spontaneous depolarization and induction of contraction in the cardiomyocytes 934 and consequently spontaneous movement of the system.
The cognitive cells 202bl,b2 (e.g., fibroblasts and cardiomyocytes) may be formed by programming materials that respond to different environmental signals including light, chemical and mechanical signals applying. Various inducible promoters may be used for programming of fibroblast and cardiomyocytes for self-healing response to damage (e.g., injuries). Such programming may employ various plasmid techniques.
To program fibroblast and cardiomyocytes for responding to injuries as indicated in
To program fibroblast and cardiomyocytes for responding to lights, cells are transfected with a Lentiviral vector containing GFP and a light inducible promoter-switch. Lentiviral vector system includes packing vector psPAX2 and envelope vector pMDS2.G (addgene). For this purpose, Plasmid PNL-TREPiTT-EGFP delta U3-IRES2-EGFP are applied as a vector plasmid, and 293 FT cells are applied for viral packaging.
To program the fibroblast for responding to the food (e.g., cellulose flavored with IPTG), cells are transfected with a Lentiviral vector containing cellulose gene and a biological IPTG switch. Lentiviral vector system includes packing vector psPAX2 and envelope vector pMDS2.G (addgene). For this purpose, Plasmid PNL-TREPiTT-EGFP delta U3-IRES2-EGFP (e.g.,
To program the fibroblasts and the cardiomyocytes for photosynthesis and production and excretion of energy sources (e.g., glucose, amino acids and ATP), cells are transfected with a Lentiviral vector containing all genes of photosynthesis complex of purple bacteria under the control of a constitutive promoter CMV, applying a Lentiviral vector system including packing vector psPAX2 and envelope vector pMDS2.G (addgene). Plasmid PNL-REPiTT-EGFP delta U3-IRES2-EGFP is applied as a vector plasmid, 293 FT cells are applied for viral packaging.
Viral particle are produced in 293 T cells transfected with psPAX2, pMDS2. G vectors and plasmids containing every single gene of interest (above mentioned). Reprogramming of about 80% confluent ADSCs into proliferative state is accomplished by infection with the viral particles containing each gene of interest. Transfected cells are cultivated in 24 well cell culture plates by DMEM phenol red-free (Invitrogen) supplemented with 10% (vol/vol) Fetal bovine serum (FBS), 0.1 mM non-essential amino acids, 6 mML-glutamate.
To further enhance the cell programming efficiency, this approach is combined with promoter-based Neomycine selection. Administration of Neomycine sequential to Lentiviral transfection, may leads to enrichment of genetically programed cell lineage populations for responding to each environmental signal.
The cardiomyocytes are provided by isolation and cultivation of neonatal rat cardiomyocytes. Freshly dissected whole rat neonatal hearts at day 1 to 3 are minced, incubated with Liberase DH (#05401054001) and Liberase TM (#05401119001) enzyme blends from Roche Diagnostics (Roche Blends) according to the instruction (Invitrogen). Minced heart tissues are incubated with Liberase DH or TM at the recommended concentration for about 35 minutes at about 37° C. The tissues are further disrupted to obtain a single cell suspension by pipetting up and down 25 to 30 times with a pipette fitted with a IOOO μI. tip. Cells are washed twice with Hanks Balanced Salt Solution (HBSS).
After single cell suspensions are obtained from each method, total cell yield is determined using an Invitrogen™ Countess™ Automated Cell Counter and cell viability is determined by trypan blue exclusion assay. DMEM-F12 supplemented with 1% penicillin/streptomycin, 10% horse serum, NaHC03, BSA (bovine serum albumin), Sodium pyruvate, D-Glucose, Ascorbic acid, linoleic acid, transferrin, HEPES (4-92-hydroxy ethyl)-1-piperazineethanesulfonic acid), Sodium selenite). Total number of isolated cells is counted and cell viability estimated via trypan blue staining. Cells are seeded at a density of 125,000 viable cells per cm2 on gelatin-coated multiwell-plates and placed in a humidified incubator at 37° C. and 5% CO2. Cultures are left undisturbed for 24 hours and subsequent media changes are performed every 48 hours.
Pacemaker cells may be generated by isolation and cultivation of embryonic rat pacemaker cells. Undifferentiated Rat Embryonic stem cells (ESCsO) (provided from Lonza. Inc) are cultured in media containing 103 U/mL Leukemia Inhibitory Factor (LIF) (Chemicon) in 10 Cm2 0.1% gelatin coated dishes and passaged every 48 hours. Undifferentiated ESCs are transfected with promoter reporters for two specific pacemaker genes including GATA-6 and HCN-2. Proximal 1.5 Kb (−1.5 kb) region of the rat Gata-6 promoter/enhancer is inserted into the multiple cloning site of promoterless enhancer and red fluorescent protein (ERFP) vector containing hygromycin resistance gene (Clontech). The proximal 1.5 Kb (−1.5 kb region of the rat HCN-2 promoter/enhancer is inserted in to the multiple cloning site of promoterless enhancer and green fluorescent protein (EGFP) vector containing hygromycin resistance gene (Clontech). Undifferentiated ESCs are transfected with lentiviral virus particles containing both constructs as described in virus production and transduction methods earlier.
Once undifferentiated ESCs containing both vectors (promoter reporter GATA-6-ERFP and HCN-EGFP) have been produced, they start their differentiation, using the hanging-drop method. Briefly, 20 μE drop containing 200 ES cells in differentiation medium (growth medium without LIF) are placed on nontreated tissue culture petri dishes (Fiher) which is inverted for 3 days. The embryoid bodies (EBs) in hanging drop are suspended in differentiation medium in the same dishes for an additional 5 days.
At day 7 of differentiation, EBs are plated on to tissue culture dishes coated with 0.1% gelatin where they remained until used for next step detection and selection of conductive pacemaker cells (spontaneous depolarizing cells). On day 7 of differentiation, EBs are dispersed into single cells by incubating the EBs in trypsin for 5 minutes followed by mechanical dissociation using pipette.
After 5 minutes of centrifugation (1000 rpm), cells are suspended and plated into 0.1% gelatin coated dishes containing differentiation medium with 200 g/mL G418 (Invitrogen). Each subsequent day cells are washed multiple times with Calcium magnesium. Free phosphate buffered saline and fresh medium containing 200 μg/ml G418 is added for a total 7 days. After 7 days of selection, cells are cultured for 4-6 days in medium containing no G418. After this time, cells are passaged using trypsin and are plated into 0.1% gelatin coated 35 mm dishes. Conductive cells expressing GATA-6 (RFP+) and HCN-2 (GFP+) cells are identified and sorted by flowcytometry method. mRNA expression and Immunocytochemistry (ICH) analysis for a panel of marker genes of pacemaker cells (including Tbx-3, Tbx-5, Tbx-18, Shox-2 and HCN 1, 2, 3, 4) are performed to confirm the differentiation of pacemaker cells.
Physiological functionality of pacemaker cells is determined through their hyperpolarization activated or funny current (If) which is specific ion current for spontaneously depolarizing pacemaker cells. Funny current (If) is elicited in the whole cell configuration by holding cells at −40 mv for 50 ms followed by 10 mV steps (2s) to −130 mV and returned to −40 mV (50 ms) after each step. See, e.g., White S M, Claycomb W C, Embryonic stem cells form an organized, functional cardiac conduction system in vitro, Am J Physiol Heart Circ Physiol 288:H670-H679 (2005), the entire contents of which is hereby incorporated by reference herein.
In the next step, differentiated pace maker cells are applied in engineering of the spontaneous motile soft-robotic system in combination with hydrogel polymers. The main body of the cognitive chemistry autonomous system is made by a 3D printer applying the combinations of different types of cells suspended in a hydrogel (such as collagen or polyethylene glycol (PEG)).
This logic operation 204c may be used to optimize efficiency of multi-node processes to solve problems, such as Nondeterministic Polynomial time (NP) problems. P problems are a class of mathematical problems which have exponential complexity, for which an efficient solution may not be available. The NP complete problems are categorized as a class of decision problems in computational complexity theory. The travelling salesman problem (TSP) is an example of an NP-hard problem in combinatorial optimization, used in operations research and theoretical computer science. The TSP asks the following question: Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city? See, e.g., Garey et al., Computers and Intractability: A Guide to the theory of NP Completeness, W. H. Freeman & Company (1979) and Afaq et al., On the solutions to the traveling salesman problem using nature inspired computing techniques. IJCSI, 8(4); 21, 326-334 (2011), the entire contents of which is hereby incorporated by reference herein.
The TSP finds a minimum cost (weight) path for a given set of cities (nodes or vertices) and roads (routes or edges). The path must pass each city exactly once and return to the original city. In a TSP with N cities, (N−1)! possible solutions exist. This means that for only 10 cities there are over 180 thousand combinations to try (since the start city is defined, there can be permutations on the remaining nine), resulting in 9!/2=181440 possible solutions.
One approach to solving this problem is to generate all possible routes, and then determine which possible route is shortest. To solve the TSP, a non-deterministic machine may be provided to explore each of the routes in parallel and computed in polynomial time, and to consider the possible routes, which may grow exponentially. Current computer operations may be used to process the possible routes sequentially where processing time is acceptable.
Where there are numerous different possible conditions for formation of networks, biological solutions such as, biologically inspired algorithms, genetic algorithms and DNA computing algorithms, may also be used for solving NP hard problems, especially when the number of nodes increases. See, e.g., Adleman L M, Molecular computation of solutions to combinatorial problems, Science, 266: 1021-4 (1994), and Qian et al., Scaling up digital circuit computation with DNA strand displacement cascades, Science, 332: 1196-201 (2011), the entire contents of which are hereby incorporated by reference herein.
Synthetic biological machinery in a logical cognitive cell (as in the logic cognitive cell 202c) may also be used to generate a set of possible solutions. The cognitive system may be used to solve NP hard problems using hundreds of thousands of biological signaling pathways in living cells by a few seconds per operation. The logic cognitive cell 202c define an optimal solution for the TSP by processing one or more of the routes simultaneously.
As shown by
Biological solutions may be generated using techniques based on the physical properties of the DNA molecule including the length or melting temperature of DNA sequences, and/or using biological-inspired algorithms and/or techniques which may be limited to a single layer of coding and data processing and lack the adequate complexity of coding and data processing mechanisms in biological systems. Biological solutions may also be generated using the cognitive cells which use the DNA molecule for its coding properties through triplets of nucleotides to the amino acid codon system, which is involved in 20 codon sub units in a multilayer, multi-stage dynamic biologically-inspired DNA/protein.
In cognitive systems, the multilayer DNA/protein may be encoded and molecular algorithms defined for solving NP problems, including those classified as hard NP problems. The TSP exemplified herein is given a graph consisting of nodes (vertices) linked by edges (binary paths) to find a route/path (concatenation of binary paths) which starts at a given node and ends at another given node, visiting every other node exactly once.
The optimal solution of data clustering can be defined through a NP hard problem such as shortest path. In a genetic pathway, nodes denote different genes, while roads are the correlation between the expression of two genes. The cognitive system may use a multi-layer hybrid DNA/protein algorithm for solving of TSP.
The biological coding and data processing in living systems involve multiple layers of coding, operation and machinery. Each layer of coding in a biological system may involve several coding sub-units (see, e.g., Table 1). Multiple layers of coding in biological systems may include coding languages of DNA, mRNA, amino acids, peptides, protein/enzymatic signaling path ways, systemic signal transduction through endocrine hormones and neurotransmitters and neural networks (see, e.g., Table 2). Biologically inspired computing algorithms with one layer of coding or different biological operations may be used for the coding. See, e.g., Hug H and Schuler R. Strategies for the development of a peptide computer. Bioinformatics. 2001; 17:364-8; Unger R and Moult J. Towards computing with proteins. Proteins. 2006; 63:53-64; De Castro L. N. Fundamentals of natural computing: an overview, Physics of life reviews, 2007, 4, 1-36; Roy S, Bioinspired Ant Algorithms, a review. I. J. Modern Education and computer science, 2013, 4, 25-35; Singh S., Lodhi E. A., Study of variation in TSP using genetic algorithm and its operator comparison, IJSCE, 2013, 3(2), 2231-2307; Chen Y J, Dalchau N, Srinivas N, Phillips A, Cardelli L, Soloveichik D and Seelig G. Programmable chemical controllers made from DNA. Nat Nanotechnol. 2013; 8:755-62; and Yang J, Dung R, Zhang Y, Cong M, Wang F, Tang G, An improved ant colony optimization (I-ACO) method for the quasi traveling salesman problem (Quasi-TSP), International Journal of Geographical information Science, 2015, 29(9), 1534-1551, the entire contents of which are hereby incorporated by reference herein.
Multi-layer biological coding and data processing in biological systems with different levels (scales) of complexity including nano (molecular), micro (or cell-cell interactions) as well as macro (or systematic) levels may be used (see, e.g., Table 3 and
Examples of multi-layer machinery that may be used are provided in Tables 5 and 6 below:
The cognitive biological systems in data analysis and reactions to the environmental signals may be related to the multilayer nature of data processing in these systems (see, e.g.,
The DNA may also be used as a coding molecule in biological system, as a conserved media for data storage during the natural development of various specious. Various biological systems at different levels of development (e.g., from prokaryotes to humans), may be models for the cognitive systems having the capability of responding to the environmental stimuli over time. At the molecular level, cognition may be based on the ability of proteins for data processing according to logical principles.
The level of structural flexibility of proteins and their interactional capability with each other and other biochemical components make them efficient switching elements of data processing networks in biological systems. For example, proteins play various roles in biological systems, including as enzymes, ion channels, receptors, membrane transporters and constructive elements of cells. In a protein-protein signal transduction and data processing net-work, proteins act as switching elements or signal transducers. See, e.g., Mark F, Klingmuller U, Decker K, (2009), Cellular signal processing, an information to the molecular mechanism of signal transduction. USA, Gaelan Science, Tylor and Francis Group; and Nelson D. L. and Cox M, (2012), Lehninger principles of biochemistry, 6th Edition, W.H. Freeman & Company, New York, USA, the entire contents of which are hereby incorporated by reference herein.
Switching capability of proteins is due to a conformational change induced by an in-put signal. Signal transduction can occur by a switching element protein due to the phosphorylation or interactions with cAMP or as a result of intermolecular Allosteric interaction between a regulatory domain (receiving the input signal) and a functional domain (transmitting the output signal). Signal transducing proteins are components of logical gates in biological data processing systems. Switches, can be used to carry out logical operations of the type NOT, AND, OR and NOR according to the rules of Boolean algebra. These operations may be used to process logical information.
The cognitive system may use capabilities of protein networks for data processing and dynamic coding based on environmental conditions, biologically inspired coding and data processing algorithms based on protein signal transduction systems, and/or global coding and operation systems having different levels of complexity including nano (molecular coding systems and operation), micro (cell-cell interaction networks) and macro (systemic signaling in humoral and neural system) in living organisms to provide a multilayer, multi-scale, multi stage biologically inspired algorithm with the capability of dynamic de novo coding based on environmental condition for solving P problems. Different layers of coding may be defined to provide a higher data storage capacity. The coding system of each layer is completely different from the next layer (in the number and forms of sub units), however different layers of coding are highly interconnected to each other and in fact the out-put of each layer is the in-put for the next layer.
The cognitive system may be coded using to provide the problem solving capabilities. The cognitive chemical may use a biologically inspired algorithm which mimics the multi-layer, multi-stage, multi-level (multi-scale) coding systems in biological systems. See, e.g., Tables 1-5 above below which explain and classify different layers, scales and levels of coding and operations that have been applied in the biologically inspired multi-layer, multi-scale, multistage/dynamic coding and data processing system.
The coded chemical 11lc of the cognitive cell 202c (
In a manner similar to how the proteins come together to form signally pathways, the signaling pathways may come together to form signaling networks. As well as representing the information of the original DNA genes as a coding chemical, the signaling networks may also act as gate switches (see, e.g., the gate switches 118 of
Amino Acids may also be clustered based on the PKA of their respective side chains.
As shown in
The coded chemical is designed such that the departure portion 1430b1 binds to the beginning portion 1432a of the first city 1430a and the end portion 1432c binds to the arrival portion 1430a2 of another city 1430b. The portions of the these coded chemicals bind together because the coded chemical is designed such that each of these portions are made of
complementary sequences, such that they bind together through Watson-Crick base pairing. Although only a single pair of cities is shown, further connections may be made through the arrival portion 1430a1 and departure portion 1430b2 of the first and second city 1430a,b.
The middle portion 1432b of the coded chemical represents the ‘length’ (weight) of the path. When the weight of the path 1432 is high, then a DNA sequence is created which codes for amino acids which are more basic (have a high pKa). Once coded chemicals are designed which correspond to each of the cities 1430a,b and paths 1432 between them are designed, them may be inserted into a logical cognitive cell 202c. Through transcription and translation, the information in the DNA coded chemical is then translated to the equivalent information in an amino acid coded chemical. This set of amino acid coded chemicals represents the total number of possible routes through the system. The produced amino acids may then be extracted from the cell, purified, and the weighting (pKa) of the proteins tested (gel electrophoresis) to determine the optimal route through the system. The sequence of the optimal route is then determined by taking the optimal route out of the gel and using MALDI-TOF to determine the sequence of amino acid coding chemicals, which correspond to the cities and paths of the route.
In operation, DNA used as a data storage molecule containing the entire information of an organism may be copied into the next generation of the species. DNA also provides a huge storage capacity because DNA encodes data applying 4 sub units including A, G, C, and T, while current computers apply binary (0, 1) for data storage and processing.
Applying the multilayer data processing and operation model system of hybrid DNA/protein codon system, the optimal solution for TSP problem created and at the final stage the optimal answer of the problem is extracted based on the amino acids' codon as shown in the Hybrid DNA/Protein algorithm of
The DNA sequences can be defined to correspond to each city (node) and road (edge) are referred to herein as TSP genes. The characteristics of each city, road, price, and/or other factors may be identified in the gene. TSP genes carry the information for the sequential data processing and operations. Two clusters of genes are defined, the first being the genes encoding the nucleotide information for nodes, and the second being nucleotide sequences for edges which are defined as amino acid/protein coding systems as shown in Tables 8-10 below:
Every gene encodes the nucleotide information for synthesis of a unique peptide or protein. Since every edge in TSP has a specific weight, the unique genetic sequence of each edge is defined based on their weight (or cost of routes). The weight of each edge is defined by the coding and biochemical properties of corresponding amino acid sequences which have been defined as the second layer of coding (see,
Table 11 depicts a schematic representative of the coding sequences of each edge between different cities.
The coding sequences of edge are made by three parts including initial (A), middle (B) and ending (C) sequences, the initial is designed as the complementary of the ending sequence of the original city (A), the middle part is designed based on the defined weight for each road, the higher weight, the higher frequency of basic amino acids (higher Pka), the ending part is designed as the complementary sequence of the target city (B) (Tables 8-10).
The DNA sequences corresponding to the nodes (or cities) may be designed with equal cost which is coded by nucleotide sequences for nonpolar amino acids. In the example of
Since in TSP the weight of each road is the main factor in the analytical process, the DNA sense strand were designed for coding the road genes (including the cost sequence). Table 10 depicts an example schematic explaining the concept of designing coding sequence of cities and roads based on hybridization mechanism. The schematic indicates an example of coding sequences for the road from city A to city B. Nucleotide hybridization and self-assembling properties of DNA molecule have been applied for parallel formation of all possible TSP solutions. For this purpose, DNA sequences related to each city divided into parts of 1, 2 and the DNA sequences related to each road divided into 3 compartments. The middle part of each road was coded based on the weight of each road. The complementary sequences of the initial and target cities relevant to each road were added to the primary weighted sequences of each road (Table 9).
After merging the sequences relevant to different cities and roads, based on the hybridization capacity of nucleotides, complementary DNA base pairs are hybridizing together all possible pathways between different cities will be formed (Table 9).
The present hybrid DNA/protein algorithm includes two layers of operations. Firstly, synthesizing a solution pool and secondly extraction of optimal solution or shortest path from the solution pool. For the first layer, biochemical operations are directly employed on genetic networks by merging the DNA sequences corresponding all edges and nodes together to create a solution pool containing all possible combinations of roads and nodes. For the second part through the translation operation, all nucleotide sequences converted to their relevant amino acids' codons as the second layer of coding and data processing. Finally, a peptide operation approach is employed to select the optimal solution or shortest path for the TSP (Table 9).
Before going through the Hybrid DNA/protein algorithm, two different sets of biochemical operations are explained here, including the synthesis of answer pool by DNA-based operations and then the extraction of optimal solution from the answer pool applying protein-based operations.
The cognitive system uses biochemical operations in a hybrid DNA/Protein algorithm for solving TSP: Synthesis of DNA genes of TSP is based on standard chemical oligonucleotide synthesis. Gene sequences of cities and costs are designed by 18 and 27 per single stranded DNA (ssDNA) respectively (Table 10). Gene sequences of roads and cities ae designed in a way for assembly to provide the possible combinations of cities and roads (costs) based on the hybridization reaction between the overlapping sequences in cities and roads (Table 10). Each road gene has been made of 3 parts which contains the cost information in the middle (Part I) and two linker parts (Part II and III) on the right and left side of cost information part. Linker parts are connecting the cost part of each road to the original and goal city gene sequences through the hybridization reaction. Linker part A is the complement of the second part (pink color) of the original city and the linker part C is the complement of the first part (yellow color) of the goal city (
Merge operation of cities and costs in the hybrid DNA/protein algorithm is based on the sequential hybridization and ligation reactions between the Watson-Crick complimentary DNA sequences. Briefly, all gene sequences of cities and costs are merged together for the hybridization reaction (including denaturation of DNA sequences at 95° C., following with annealing/hybridization reaction at 20° C.). Sequentially, merge operation is completed by providing the appropriate condition for ligation reaction (including 4 μl Ligase reaction buffer, 30 fmole of vector DNA, 90 fmole insert DNA, up to 15 μl of DNAse/RNAse free H2O, 1 μl of T4 DNA Ligase with the total reaction volume 20 μl, 5 min incubation time) applying Thermo Fisher Scientific T4 ligation kit (Thermo Fisher Scientific, Cat No. 15224-017).
Pathways satisfying the requirements of TSP may be solved through solid phase hybridization/ligation reactions, gel electrophoresis, affinity separation and PCR. The satisfying requirements of TSP are achieved by applying sequential biologically inspired operations including solid phase hybridization/ligation reaction, gel electrophoresis, affinity separation and PCR. In order to generate all possible paths starting and ending with a specific city (e.g., city A), Initially the 5′ end of city A gene sequence is conjugated to a magnetic bead for the next step selection by attachment to a solid phase magnetic column. Then gene sequences of all cities exception of city A and all road sequences are added into the reaction solution. The gene sequences of all cities and roads annealed together through the Watson-Crick hybridization reaction as explained above. After the completion of hybridization/ligation reaction, the remaining city and road gene sequences that did not involve in to the reaction, are removed from the reaction medium by washing.
The merge operation of TSP may be completed by adding the gene sequence of city A at the final stage. Paths that satisfying the TSP requirement of covering 4 cities and roads are defined through their length by gel electrophoresis operation. Paths that are visiting each city once were defined by affinity separation operation through several affinity columns, containing the complementary sequences of each city. In order to provide enough template DNA satisfying the TSP requirements, for the next layer of coding which is protein translation, all paths initiating and ending with city A are amplified by PCR operation (applying specific forward primer for the first part of city A and back ward primer for the second part of city A). PCR is defined based on the QIAGEN multiplex PCR kit instruction (QIAGEN, Cat No. 206143), for 34 cycles, 30S at 95° C., 30 S at Tm-5 C, 30S at 72° C. and initial denaturation for 15° C. Briefly, 2 μl of 2× QIAGEN Multiplex PCR master mix, 5 μl of 10× primer mix (2 μM of each primer), 1 μg of template DNA and RNA free water with the final volume of 50 μl.
Protein translation, extraction, analysis operations include transferring of oligonucleotides' answer pool into expression vectors, in vitro translation assays, protein extraction and analysis assays were performed respectively, in order to extract the optimal solution for a defined TSP problem based on the primary definition of DNA sequences relevant to each city and road.
To this end, isoelectric-focusing and 2D-electrophoresis are defined as the final operations for finding the optimal solution based on the weight and pKa of synthesized peptides. Matrix-Assisted Laser Desorption/Ionization on a reflection Time-Of-Flight (MALDI-TOF) (which is a standard amino acid sequencing method) is defined as the read-out operation of the optimal solution based on the amino acid sequences.
Therefore, in the first layer of algorithm through the self-hybridization and self-assembling properties of DNA base pairs, a TSP answer pool is generated. Then, in the following stages the optimal solution (the shortest and most economical pathway) are extracted by translation of synthetized DNA sequences in to the next layer of coding which is defined as protein translation layer. Finally, based on the coding properties of amino acids the optimal solution is extracted from the peptide answer pool according to the solution of Table 8.
The hybrid DNA/Peptide algorithm of
The above description is for the purpose of teaching the person of ordinary skill in the art how to practice the aspects of the present application, and it is not intended to detail all those obvious modifications and variations of it which will become apparent to the skilled worker upon reading the description. It is intended, however, that all such obvious modifications and variations be included within the scope of the present application. The aspects and embodiments are intended to cover the components and steps in any sequence which is effective to meet the objectives there intended, unless the context specifically indicates the contrary.
The cognitive system may be used in a variety of applications, such as for optimizing the efficiency of a multi-node process comprising applying a hybrid DNA/protein algorithm to a nondeterministic polynomial problem (NP) comprising multiple nodes, wherein the NP (e.g., TSP problem) represents the process. The process may involve a logistics process, procurement, package delivery process, wiring of a computer or circuit board, data array clustering, scheduling of multiple tasks with no intermediate storage or down-time, vehicle routing (autonomous, self-driving car or truck, drone aircraft, etc.). The routing may be for package delivery, surveillance, etc. The process may also involve a method of optimizing the efficiency a vehicle routing process for an autonomous vehicle, comprising: applying a hybrid DNA/protein algorithm to a nondeterministic polynomial problem (NP) comprising multiple nodes, wherein each of said multiple nodes represents a point within the vehicle routing process and each point only occurs once, thereby establishing a optimally efficient route for said autonomous vehicle, and programming said optimally efficient route into said autonomous vehicle.
The multilayer biologically inspired coding may include double, triple or multiple layers of biologically inspired coding systems including DNA (genetic coding), epigenetic (Histone acetylation, DNA methylation), Zinc finger's/TALEN's specific DNA recognition coding, ON/OFF promoter inducible systems (applying inducible switches such as TET, IPTG, Light, Steroids) induction systems, mRNA alternative splicing coding, line RNA (Long intergenic noncoding RNAs), guide RNA/CRISPR/CAS-9 codon integration and targeted genome edition system, genetic integration and recombination coding systems, amino acid coding system, enzymatic and protein signal transduction systems, hormonal and neurotransmitters systemic signal transmission and coding systems, electric signal transduction systems through membrane ion channels and receptors as well as intracellular organelles, chemical and electronic signal transductions between different cell types such as cardiac pacemaker cells and neural cells locally or systematic.
The cognitive system may be used for solving NP problems relating to various technical fields (e.g., engineering), technologies (e.g., airlines, planes, ships, trains, trucks, taxis, ride-share services or cars), industries (e.g., shipping or freight services), cryptographic and/or scheduling applications, public space security problems (e.g., efficient number of security guards, hospital spacing), treatment of diseases, pharmaceuticals (e.g., for optimization of recombinant proteins), and/or chemicals (e.g., catalyst functionality of enzymes), industrial scale use, language and string processing, game and puzzle design and layout, drilling of printed circuit boards, mask plotting in printed circuit board production, overhauling gas turbine engines, X-ray crystallography, computer wiring, order-picking of goods, vehicle routing, printing press scheduling, crew scheduling, interview scheduling, hot rolling scheduling, military mission planning, and design of global navigation satellite system surveying networks, wiring of a computer or circuit board, data array clustering, sand scheduling of multiple tasks with no intermediate storage or down-time, data analysis (e.g., high throughput biological data), data storage, etc.
While the embodiments are described with reference to various implementations and exploitations, it will be understood that these embodiments are illustrative and that the scope of the inventive subject matter is not limited to them. Many variations, modifications, additions and improvements are possible. For example, various combinations of one or more of the features provided herein may be used.
Plural instances may be provided for components, operations or structures described herein as a single instance. In general, structures and functionality presented as separate components in the exemplary configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements may fall within the scope of the inventive subject matter.
Insofar as the description above and the accompanying drawings disclose any additional subject matter that is not within the scope of the claim(s) herein, the inventions are not dedicated to the public and the right to file one or more applications to claim such additional invention is reserved. Although a very narrow claim may be presented herein, it should be recognized the scope of this invention is much broader than presented by the claim(s). Broader claims may be submitted in an application claims the benefit of priority from this application.
Plural instances may be provided for components, operations or structures described herein as a single instance. In general, structures and functionality presented as separate components in the exemplary configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements may fall within the scope of the inventive subject matter.
This application is a Continuation of U.S. application Ser. No. 16/312,820, filed Dec. 21, 2018, which is a National Stage Application of PCT application Serial Number PCT/US2017/041058, filed Jul. 7, 2017, which claims the benefit of U.S. Provisional Application No. 62/359,339, filed Jul. 7, 2016, and U.S. Provisional Application No. 62/361,037, filed Jul. 12, 2016, the entire contents of which are hereby incorporated by reference herein.
| Number | Date | Country | |
|---|---|---|---|
| 62359339 | Jul 2016 | US | |
| 62361037 | Jul 2016 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16312820 | Dec 2018 | US |
| Child | 18162627 | US |
